In search of the actual groundwater recharge. Project plan

In search of the actual groundwater recharge Project plan BTO 2011.039(s) May 2011

In search of the actual groundwater recharge Project plan BTO 2011.039(s) May 2011

© 2011 KWR Alle rechten voorbehouden. Niets uit deze uitgave mag worden verveelvoudigd, opgeslagen in een geautomatiseerd gegevensbestand, of openbaar gemaakt, in enige vorm of op enige wijze, hetzij elektronisch, mechanisch, door fotokopieën, opnamen, of enig andere manier, zonder voorafgaande schriftelijke toestemming van de uitgever.

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Colofon Titel In search of the actual groundwater recharge Projectnummer BTO 2011.039(s) Opdrachtnummers B111698-001, O710023 & S308635-001 Onderzoeksprogramma‘s PBC Bronnen & CARE Projectmanager Dr. ir. Gé van den Eertwegh Opdrachtgevers BTO & Stichting Kennis voor klimaat Kwaliteitsborger Prof. dr. Pieter Stuyfzand Auteurs Dr. ir. Ruud P. Bartholomeus, Bernard R. Voortman Msc & Prof. dr. ir. Jan-Philip M. (Flip) Witte Verzonden aan Dit rapport is verspreid onder BTO-participanten en is openbaar

Foto kaft Medewerkers van team Ecologie onderzoeken in Polen een droog rivierduin langs rivier de Bierbza

List of symbols Symbol

Unit

Description

a

L/T

empirical coefficient for calculation of Pi

b

-

soil cover fraction for calculation of Pi

E0

L/T

Penman open water evaporation

Ea

L/T

actual soil evaporation

Ep

L/T

potential soil evaporation

Ep_bare

L/T

potential evaporation of a wet bare soil

ETa

L/T

actual evapotranspiration

ETp

L/T

potential evapotranspiration = Ep + Tp + I

ETp_dry

L/T

potential evapotranspiration of a crop with a dry canopy (I=0)

ETp_wet

L/T

potential evapotranspiration of a crop with a wet canopy

ETref

L/T

reference evapotranspiration

ETref_Mak

L/T

reference evapotranspiration according to Makkink

ETref_Mak_dry

L/T

reference evapotranspiration of Makkink but valid for a crop with a dry canopy only

ETref_PM

L/T

reference evapotranspiration according to Penman-Monteith, i.e. for a crop with dry canopy

ETref_PM_avg

L/T

ETref_PM under the real climatic conditions, thus including both wet and dry periods

ETref_PM_dry

L/T

ETref_PM

fCO2

-

correction factor for higher water use efficiency due to increased CO2 (Kruijt et al., 2008; Witte et al., 2006a; Witte et al., 2006b)

fKNMI

-

correction factor for altered temperature and wind, given by the KNMI’06-scenarios (Van den Hurk et al., 2006)

G

W/m2

soil heat flux

gI

-

correction factor for the contribution of I in ETref_Mak

gI,c

-

correction factor for the contribution of I in kc

I

L/T

interception evaporation

kc

-

crop factor according to Feddes, i.e. to be applied on ETref_Mak

kc_dry

-

crop factor to be applied on ETref_Mak_dry

LAI

L2/L2

leaf area index

Pi

L/T

intercepted precipitation

Pgross

L/T

gross precipitation

rair

T/L

aerodynamic resistance

rcrop

T/L

crop resistance

Rn

W/m2

net radiation

Rs

W/m2

global (solar) radiation

SC

-

fractional soil cover

Ta

L/T

actual transpiration

Tair

K

air temperature

Tp

L/T

potential transpiration

Tsoil

K

soil temperature

Κgr

-

extinction coefficient for solar radiation

In search of the actual groundwater recharge © KWR

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Voorwoord In dit rapport beschrijven we onze plannen voor onderzoek naar de werkelijke aanvulling van het grondwatersysteem met water dat vanuit de wortelzone naar beneden percoleert. Die grondwateraanvulling is de drijvende kracht achter de stroming van grondwater. Daarom is een nauwkeurige bepaling van deze post van essentieel belang is voor betrouwbare hydrologische berekeningen en voor een juiste schatting van de hoeveelheid grondwater die kan worden gewonnen zonder schade aan landbouw en natuur te veroorzaken. Op hogere zandgronden waar de wortelzone niet capillair wordt aangevuld vanuit het grondwater, kan de vegetatie reageren op variaties in weersgesteldheid door een aantal aanpassingen van zijn verdampingseigenschappen, zoals van het aandeel kale grond. In kwantitatief opzicht is echter nauwelijks iets over deze aanpassingsmechanismen bekend. Wij hopen met dit onderzoek iets aan dit euvel te kunnen doen. De kennis die we ontwikkelen is van belang voor de bepaling van de grondwateraanvulling onder zowel het huidige klimaat, als onder het klimaat van de toekomst, wanneer de zomers misschien veel droger zijn dan nu en de vegetatie er daardoor heel anders uit ziet. Het onderzoek bestaat uit drie projecten: een project van de drinkwaterbedrijven (BTO), een project uit het fundamenteel onderzoeksprogramma van KWR (FOP), en een promotieproject gesubsidieerd door de stichting Kennis voor Klimaat (KvK). De plannen voor de eerste twee projecten werden begeleid door vertegenwoordigers van de waterbedrijven op het gebied van de hydrologie (Bas Baartmans, Harry Boukes, Jeroen Castelijns, Merel Hoogmoed, Vera Lagendijk, Karel de Mey, Nico van der Moot, Philip Nienhuis, Theo Olsthoorn, Birgitta Putters, Sjaak Rijk, Harry Rolf en Dirk de Smet). Behalve uit Ruud Bartholomeus en Flip Witte bestond de begeleiding van het promotieplan uit wetenschappers van enkele universiteiten (Sjoerd van der Zee, Peter van Bodegom, Marc Bierkens). Wij danken al deze begeleiders hartelijk voor hun commentaar en de vruchtbare uitwisseling van ideeën. Ook zijn wij Fred Daniëls en Mirja Henschel van de universiteit van Münster erkentelijk voor het delen van hun expertise op het gebied van droogteminnende vegetaties met ons. Vermeld moet ook worden Nationaal Park de Hoge Veluwe, dat zeer ruimharig medewerking aan ons heeft verleend en waarvan we, onder leiding van boswachter Evert Cock, een excursie met terreinwagen kregen aangeboden. Ten slotte betuigen wij onze dank aan de waterbedrijven en de stichting Kennis voor klimaat voor het vertrouwen dat wij van hen hebben gekregen om dit interessante onderzoek te mogen uitvoeren.

Ruud Bartholomeus, Bernard Voorman, Flip Witte Nieuwegein, maandag 9 mei 2011


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Inhoud List of symbols

vi

Voorwoord

viii

Inhoud

x

Inleiding

1

Part I

9

Redefining crop factors (BTO & FOP)

1

Introduction

11

1.1

Problem definition

11

1.2

Research topics and goals BTO and FOP-fund

11

1.3

Outline and planned deliverables

12

2

Research topics and products

15

2.1

Vegetation cover vs. reference drought stress (step A)

15

2.2

Unravel crop factors (step B)

18

2.3

Water and heat balance as function of soil and vegetation cover (optional, if time allows) (step C)

23

3

Delivered products

25

3.1

2010

25

3.2

2011

25

Part II PhD proposal Bernard Voortman (KvK)

27

1

Introduction

31

1.1

Background and problem definition

31

1.2

Research objectives

31

1.3

Outline

31

2

Vegetation dynamics in coastal and inland sand dunes

33

2.1

Introduction

33

2.2

Natural Succession

37

2.3

Internal vegetation dynamics

37

2.4

Nitrogen deposition

39

3

Research approach and analyses of the available knowledge

41

4

The role of mosses and lichens in the soil-water balance

43


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4.1


43

4.2

Research objectives

45

4.3

Methods

45

4.4

Expected results

48

4.5

Timeline

49

5

Modelling plant available water for dune vegetation: the effects of vegetation structure and topography 51

5.1


51

5.2

Research objectives

54

5.3

Methods

54

5.4

Expected results

54

5.5

Timeline

55

6

A conceptual model to estimate the vegetation coverage of dry grassland vegetation of European sandy soils under changing climatic conditions 57

6.1


57

6.2

Research objectives

58

6.3

Methods

58

7

The response of vegetation to climate change and its effect on evapotranspiration and groundwater recharge in coastal and inland sand dunes of The Netherlands 61

7.1


61

7.2

Research objectives

61

7.3

Methods

61

8

Timetable

63

References

65


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Inleiding Hydrologen hebben in de afgelopen decennia prachtige computermodellen ontwikkeld waarmee men de stroming van water in de bodem en de diepere ondergrond kan simuleren en waarmee men het verloop in ruimte en tijd van grootheden als de grondwaterstand en het bodemvochtgehalte kan nabootsen. Ruwweg zijn er twee typen modellen beschikbaar: mechanistische modellen en tijdreeksmodellen. In het eerste type worden de fysische eigenschappen van de ondergrond ruimtelijk expliciet geschematiseerd. Een voorbeeld is het model Modflow (Harbaugh et al., 2000). In tijdreeksmodellen worden gebiedseigenschappen impliciet verwerkt in een beperkt aantal sterk gelumpte parameters waarop men het model ijkt. Een bekend voorbeeld is Menyanthes (Von Asmuth et al., 2002; Von Asmuth et al., 2006). Beide benaderingen, mechanistisch of gelumpt, hebben hun eigen voor- en nadelen die in algemene literatuur over modelleren uitvoerig is bediscussieerd (zie o.a. Baird, 1999; Guisan and Zimmermann, 2000). In beide benaderingen wordt het model gevoed door gegevens over neerslag en verdamping. Bij een fysisch model gaat het doorgaans om de werkelijke verdamping, berekend met een model voor het vochttransport in de bodemzone, zoals Swap (Van Dam et al., 2008), MetaSwap (Schaap and Dik, 2007) en Onzat (Van Drecht, 1996), bij een tijdreeksmodel meestal om de referentieverdamping, zoals verstrekt door het KNMI, maar in principe kan ook de werkelijke verdamping als invoer dienen. De fout in de berekening van de werkelijke verdamping zal, schatten we, in veel gevallen zeker 10% bedragen (zie bijvoorbeeld Tabel 6.3 in Massop et al. (2005)). Onder het Nederlandse klimaat tikt die fout gemiddeld ongeveer twee tot drie keer zo hard door in de berekende grondwateraanvulling (zonder oppervlakteafvoer: neerslag minus werkelijke verdamping). Zoals bekend is de grondwaterstand ten opzichte van de drainagebasis bij benadering rechtevenredig aan de grondwateraanvulling. Dit betekent, op zijn beurt, dat een fout in de verdamping eveneens dubbel terugkomt in de gesimuleerde grondwaterstanden. In de praktijk zien we die fout echter niet omdat men de hydrologische modellen ijkt aan gemeten stijghoogten: men verhoogt of verlaagt bijvoorbeeld het doorlaatvermogen van het eerste watervoerende pakket zodanig, dat de gesimuleerde waarden overeenstemmen met de waarnemingen. Fouten in de verdamping compenseren met een aangepast doorlaatvermogen, daar komt het op neer (bij tijdreeksmodellen wordt voor fouten in de verdamping standaard ‘gecompenseerd’ via de optimalisering van de modelparameters). De vraag is echter of het model daarmee geschikt is voor extrapolaties, dus voor toepassingen onder andere omstandigheden dan die waarop het model is geijkt (zie kader). Deze vraag klemt des te meer bij klimaatprojecties, omdat de verdampingseigenschappen van de vegetatie door klimaatverandering wel eens zouden kunnen gaan veranderen1, (Nijssen et al., 2011). Dat het klimaat in Nederland in rap tempo verandert, is met metingen aangetoond: de neerslag is de afgelopen eeuw gemiddeld met bijna 20% toegenomen (Witte et al., 2009) en de temperatuur met 1.7 oC (Anonymus, 2009). Neerslag valt steeds meer in de wintermaanden en in de vorm van buien met een hoge neerslagintensiteit. Voor Nederland publiceerde het KNMI in 2006 vier klimaatscenario’s die betrekking hebben op de jaren 2050 en 2100 (Van den Hurk et al., 2006). Deze scenario’s verschillen in de mate van verandering, maar hebben gemeen dat de temperatuur en de potentiële verdamping stijgen, dat de hoeveelheid neerslag in de winter stijgt en dat de intensiteit van de neerslagbuien toeneemt.

Ter overweging: in het onderzoek naar de winning Ter Wisscha werd een achtergrondsverdroging gevonden van ongeveer 1 cm/jr. Waarschijnlijk wordt die geheel of gedeeltelijk veroorzaakt door veranderende verdampingseigenschappen van de vegetatie. Zo is uit luchtfotoanalyse gebleken dat het Aekingerzand tussen 1950 en 2006 deels is dichtgegroeid, wat tot een afname van 35% in areaal kaal zand heeft geleid; daarvoor in de plaats is voornamelijk bos en heide gekomen. 1

In search of the actual groundwater recharge − Inleiding © KWR

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Volgens het KNMI (mondelinge mededeling Janet Bessembinder) zijn thans het W en W+ scenario’s het aannemelijkst, dat wil zeggen de scenario’s waarbij de temperatuur in 2050 wereldwijd met 2 oC is gestegen en waarbij de windrichting onveranderd blijft (W), dan wel in de zomer vaker uit het oosten komt (W+). Recent onderzoek duidt er op dat de intensiteit van de buien nog meer toeneemt met een stijging van de temperatuur dan in 2006, toen de klimaatscenario’s werden uitgegeven, werd aangenomen (Lenderink and Van Meijgaard, 2008). De verandering van klimaat leidt bovendien tot een andere verdamping van de vegetatie. De potentiële verdamping zal door het opwarmen van de aarde stijgen, maar hoe zit het met de werkelijke verdamping?

Kader: hoe het mis kan gaan met een onttrekkingskegel Dat een fout in de grondwateraanvulling substantieel kan doorwerken in de berekende onttrekkingskegel illustreren we hier aan de hand van een analytische formule voor een freatische onttrekking Q (m3/d) midden op een cirkelvormig eiland met straal L (m), grondwateraanvulling R (m/d), doorlatendheid k (m/d) en hoogte drainagebasis ten opzichte van een ondoorlatende basis H (m). Volgens Huisman (1972) geldt voor de hoogte h (m) van de grondwaterspiegel ten opzichte van de ondoorlatende basis:

h2  H 2

R  L2  x 2  2k

Q

ln L x k

Waarin x (m) de afstand tot de winning is. Stel nu dat een hydroloog dit model eerst fit op een situatie zonder winning (Q = 0) met een grondwateraanvulling die een factor f van de werkelijke aanvulling bedraagt (Rfout = fR). Na kalibreren vindt hij dan natuurlijk een doorlatendheid gelijk aan kfout = fk. Eenvoudig is in te zien dat die fout daarna, bij een winning Q >0, alleen doorwerkt in de rechterterm van bovenstaande vergelijking. Voorbeeld: stel een hydroloog wil de onttrekkingskegel op een gebied als de Veluwe uitrekenen, met een oppervlak van 1000 km2 (L = 18000 m), een freatische pakket met een dikte H van 100 m ten opzichte van een ondoorlatende basis en een werkelijke doorlatendheid k van 5 m/d. De werkelijke grondwateraanvulling (1 mm/d) heeft hij 30% onderschat (f = 0.7), zodat hij na ijking op de gemeten grondwaterstanden (zonder winning) een doorlatendheid vindt van kfout = 3.5 m/d. Vervolgens gaat hij de kegel berekenen van een onttrekking van 3000 m3/d (9.1 Mm3/jr). De fout die hij dan maakt is hieronder weergegeven. Op 1.5 km van de winning bedraagt de fout 0.5 m, op 4.1 km afstand 0.3 m en op 7 km is de fout 0.2 m.

fout (m)

1.0 0.8 0.6 0.4 0.2 0.0

-20000

-10000

0

10000

20000

x (m) Dit voorbeeld is natuurlijk wat gechargeerd, want verstandige hydrologen ijken hun model niet alleen aan gemeten stijghoogten, maar ook aan gemeten afvoeren. Bovendien hebben ze andere manieren om informatie over de eigenschappen van de ondergrond in te winnen, zoals pomproeven. Niettemin toont het voorbeeld aan dat het van belang is de grondwateraanvulling nauwkeurig te bepalen.


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Berekening van de werkelijke verdamping gebeurt in hydrologische modellen als MetaSwap door de vegetatie te schematiseren als een laag met vaste verdampingseigenschappen. Het is aannemelijk dat deze berekening tot aanzienlijke fouten kan leiden bij klimaatprojecties, vooral in natuurgebieden op droge zandgronden zoals stuwwallen en duinen: 1.

Verdamping via de huidmondjes (transpiratie) is in de modellen doorgaans een functie van de drukhoogte in de wortelzone en de potentiële transpiratie van de vegetatie (Feddes et al., 1978). Waarschijnlijk kan dit concept overeind blijven staan.

2.

Een deel van de neerslag bereikt niet de bodem maar wordt door bladeren opgevangen waarvan het weer verdampt. Onder het huidige klimaat is deze interceptiepost ongeveer 20% van de neerslag bij een kort groen grasland (Witte et al., 2006a) en kan hij wel 45% bedragen bij donker naaldhout als Douglas en Fijnspar (Dolman et al., 2000). Als de neerslag minder gelijkmatig valt, en steeds meer in de vorm van intensieve buien, zal de interceptieverdamping dalen zodat meer neerslagwater de bodem bereikt. In een hydrologische simulatie komt dit effect van klimaatverandering alleen dan voldoende naar voren, wanneer de interceptie expliciet en betrouwbaar wordt gesimuleerd. Door Alterra is veel onderzoek gedaan naar de interceptie van bossen (Dolman et al., 2000), maar er is vrij weinig tot niets bekend over de interceptie van andersoortige natuurlijke vegetaties, zoals de mosrijke ‘steppe’ op de Veluwe (Figuur 1).

3.

De potentiële verdamping van de vegetatie wordt meestal berekend door de Makkink referentiegewasverdamping van het KNMI te vermenigvuldigen met een gewasfactor (Feddes, 1987). Deze gewasfactor is empirisch bepaald: het is de verhouding tussen de met een lysimeter of meetmast gemeten verdamping en de Makkink-verdamping. In de meting van de verdamping is de interceptieterm inbegrepen. Dat betekent dat de hoogte van de gewasfactor afhangt van het neerslagpatroon ten tijde van de metingen. Dit roept de vraag op hoe houdbaar gewasfactoren zijn bij klimaatprojecties, zeker als de neerslag steeds meer in de vorm van hevige buien gaat vallen.

4.

Gewasfactoren voor natuurlijke vegetaties zijn nauwelijks onderzocht (Spieksma et al., 1997).

5.

Vermenigvuldiging van de Makkink-verdamping met een gewasfactor zou moeten leiden tot de potentiële verdamping van het vegetatietype waarvoor de gewasfactor is bedoeld. De potentiële verdamping is gedefinieerd als de verdamping van een gewas of vegetatietype dat optimaal wordt voorzien van zoet water. Dat is een moeilijk houdbaar concept voor een vegetatie op droge zandgronden. Een dergelijke vegetatie is immers van nature helemaal niet optimaal van water voorzien, terwijl kunstmatige toediening van voldoende water geen oplossing is om de potentiële verdamping te bepalen, want die handeling leidt tot een andere vegetatie, met nieuwe verdampingseigenschappen. Daarom zijn gewasfactoren voor droge vegetaties in de praktijk verhoudingsgetallen tussen de werkelijke verdamping (die bij droogte is gereduceerd) en de Makkink-verdamping. Net als gewasfactoren (punt 3) gelden die verhoudingsgetallen voor de tijdens de meting heersende weersomstandigheden. Bovendien is de veronderstelling achter de hydrologische rekenprocedure dat met die verhoudingsgetallen de potentiële verdamping wordt vastgesteld, onjuist.

6.

Door stijging van de CO2 concentratie gaan planten netto wat zuiniger om met water: ze transpireren minder. Dit effect is waargenomen in historische reeksen van rivierafvoeren (Gedney et al., 2006). Bovendien toont een recente analyse van fossiel bladmateriaal aan dat de dichtheid aan huidmondjes afneemt met een toenemend CO2 gehalte (De Boer et al., 2011). Door die afname stijgt de stomatale weerstand en daalt de transpiratie. Voor Nederland is geraamd dat in 2050 (ΔCO2 = 150 ppm) de potentiële verdamping (evapotranspiratie) gemiddeld met 2-5% zal zijn gedaald, afhankelijk van de vegetatiestructuur (Kruijt et al., 2008; Witte et al., 2006a; Witte et al., 2006b).

7.

Op hogere zandgronden als de duinen en de Veluwe, nemen het aandeel kale grond en het aandeel niet-wortelende planten (mossen en korstmossen) toe naarmate de zomer droger wordt. Omdat kale grond en (korst)mossen veel minder verdampen dan wortelende vaatplanten, zorgt dit voor een daling van de werkelijke verdamping. Indicatieve berekeningen tonen aan dat in een van de klimaatscenario’s (W+), het aandeel kale grond op zuidhellingen van duinen in 2050 kan zijn gestegen van 30% tot meer dan 80% (Witte et al., 2008b). Het samenspel van klimaat, bodem, water


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en vegetatie is echter nauwelijks begrepen, laat staan goed gekwantificeerd. Overigens is het effect van droogte in hogere zandgronden op microschaal al zichtbaar: noordhellingen zijn daar meer bedekt en productiever dan zuidhellingen. Al met hebben we ernstige bedenkingen bij de manier waarop de werkelijke verdamping wordt berekend op de hogere zandgronden en bij klimaatprojecties. Dit betekent dat effecten op waterhuishouding en ecosystemen van natuurlijke variaties in het weer, nog niet goed kunnen worden voorspeld. Dit geldt nog meer voor de effecten van klimaatverandering. Een goede berekeningswijze is nodig voor een betrouwbare schatting van de grondwateraanvulling, nu en onder het toekomstige klimaat. In dit licht vinden wij het verbazingwekkend dat tot nu toe zo weinig onderzoek is gedaan naar de verdamping van natuurlijke vegetaties, terwijl van de andere kant veel geld en menskracht is geïnvesteerd in de ontwikkeling van grondwatermodellen. Het is immers de grondwateraanvulling die het hydrologische systeem aandrijft. Alle aandacht naar de motor, maar de brandstof wordt verwaarloosd. Misschien is deze discrepantie te verklaren uit verschillen in achtergrond van onze academici: Delftenaren die zich graag wiskundig uitleven op het verzadigde grondwatersysteem, en Wageningers die vooral geïnteresseerd zijn in gewasproductie en daarom de verdamping van landbouwgewassen onderzoeken. Vooral voor de drinkwaterbedrijven is een betrouwbare berekening van de grondwateraanvulling van belang. Ongeveer tweederde van het leidingwater dat de drinkwaterbedrijven in Nederland produceren, is immers onttrokken grondwater, water dat door grondwateraanvulling is ontstaan. Onttrekkingen op de stuwwallen (Brabantse wal, Veluwe, Sallandse hevelrug, etc.) zijn volledig afhankelijk van wat er vanuit de hemel uiteindelijk doorsijpelt naar het grondwater. Als we het KNMI mogen geloven zal het jaarlijkse neerslagoverschot (de neerslag minus Makkink verdamping) te De Bilt onder het W+ scenario in 2050 met bijna 30% zijn gedaald (Hermans et al., 2009) en in de Amsterdamse Waterleidingduinen met 42% (Witte et al., 2008b). Vooral de zomers worden veel droger. Wat deze verandering betekent voor de werkelijke grondwateraanvulling, valt met de huidige stand van kennis echter niet te zeggen. Zal de aanvulling, net als het neerslagoverschot, op jaarbasis afnemen of, door een aantal

Figuur 1. Vegetatie op de Hoge Veluwe, vooral bestaand uit mossen en korstmossen. Een dergelijke steppevegetatie komt op de Veluwe in grote oppervlakten voor en is zeer stabiel (volgens prof. Daniëls minstens twee eeuwen oud). Van de mossen is thans niet bekend hoeveel ze verdampen en of ze capillair water uit de zandondergrond kunnen onttrekken. Misschien is het contact met de ondergrond wel zo los, dat de moslaag hydrologisch geschematiseerd kan worden als een interceptiereservoir.


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terugkoppelingsmechanismen van de vegetatie, juist toenemen? We weten het niet. Ook voor de duinbedrijven die water winnen via infiltratie van rivierwater, kan de werkelijke grondwateraanvulling een belangwekkend vraagstuk worden. In de AWD wordt het meeste water gewonnen via infiltratie van rivierwater; slechts ongeveer 15% is afkomstig van de natuurlijke grondwateraanvulling. De verwachting is echter dat door klimaatverandering de afvoer van rivieren in de zomer dramatisch kan gaan dalen. Volgens een onderzoek in opdracht van de Deltacommissie kan de Rijnafvoer in 2050 ’s zomers tot 35% zijn gedaald en in 2100 zelfs tot 60% (Vellinga et al., 2009). Een dergelijk lage afvoer gaat gepaard met een slechtere waterkwaliteit (van Vliet and Zwolsman, 2008) en met een grotere concurrentie om de vraag naar zoet water door verschillende belanghebbenden. Betwijfeld kan worden of er dan voldoende over blijft voor duininfiltratie. Opslag van water in de ondergrond tijdens de natte wintermaanden (ASR) kan de nood lenigen, maar de vraag is of die maatregel voldoende is om de hele zomer door te komen. Ook pompstations in de duinen worden door veranderde rivierafvoeren meer afhankelijk van de natuurlijke grondwateraanvulling. Ten slotte is een nauwkeurige berekening van de grondwateraanvulling van groot belang voor het berekenen van de kwaliteit van het grondwater. De mate van indikking van opgeloste stoffen in het infiltrerende neerslagwater, de snelheid waarmee stoffen in de bodem omzetten en uitspoelen, de mineralisatiesnelheid van organische stof en respiratiesnelheid van de vegetatie: zij hangen allemaal samen met de bodemtemperatuur en de grondwateraanvulling en de daardoor veroorzaakte dynamiek in de grondwaterspiegel. De waterbedrijven (vertegenwoordigd in de PBC Bronnen) hebben eind 2008 een onderzoeksvoorstel naar de grondwateraanvulling op hogere zandgronden goedgekeurd (projectnummer B111698-001). In dat voorstel werd beloofd te proberen een promovendus aan te stellen met subsidie uit het FESprogramma Kennis voor Klimaat. Dat is gelukt: binnen het KvK-programma Climate Adaptation for Rural arEas (CARE; (Anonymus, 2010)) werkt Bernard Voortman sinds 15 juli 2010 als promovendus bij KWR (S308635-001). Bovendien heeft het onderzoek meer body gekregen door subsidie uit het fundamenteel onderzoeksprogramma van KWR, waardoor vanaf november 2009 Ruud Bartholomeus voor twee jaar als postdoc aan het onderwerp kan werken (O710023). In het onderzoek werken we nauw samen met prof. Sjoerd van der Zee (Wageningen universiteit), dr. ir. Peter van Bodegom (Vrije universiteit) en prof. dr. ir. Marc Bierkens (universiteit Utrecht), onder andere voor de begeleiding van Bernard Voortman. Bovendien hebben we onlangs samenwerking gezocht met prof. dr. Fred Daniëls en promovenda Mirja Henschel (universiteit Münster), vegetatiekundigen met grote kennis van droge graslanden. Fred Daniëls doet al sinds 1980 onderzoek op de Veluwe, onder andere via herhaalde vegetatieopnamen op dezelfde locaties (Figuur 2). Alle drie de projecten hebben tot doel de grondwateraanvulling op hogere zandgronden zo nauwkeurig en klimaatrobuust mogelijk te bepalen. Voor een praktische aanpak is het werk in twee delen verdeeld, wat in de opzet van dit rapport is terug te vinden: -

Het BTO-onderzoek en het onderzoek van het fundamenteel onderzoeksprogramma FOP zijn samengevoegd en worden beschreven in het eerste deel. De nadruk van dit onderzoek is het vinden van een in de praktijk eenvoudig toe te passen manier om de verdamping van hogere zandgronden vast te stellen, bijvoorbeeld via correctiefactoren voor de gewasfactoren.

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Het belangrijkste doel van een promotieonderzoek is het afleveren van een goede dissertatie, het liefst in de vorm van ten minste vier artikelen die in peer reviewed tijdschriften zijn of kunnen worden geplaatst. Wetenschappelijke diepgang staat voorop, nieuwe praktische toepassingen zijn zeer gewenst, zullen ook worden nagestreefd, maar zijn geen doel op zich. Bernard Voortman heeft een onderzoeksvoorstel geschreven dat is besproken met en goedgekeurd door zijn begeleidingscommissie (Bartholomeus, Bierkens, Van Bodegom, Witte, Van der Zee). Het onderzoeksvoorstel is hier opgenomen als tweede deel.


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Figuur 2. Op dinsdag 1 maart 2011, een koude dag, leidt prof. Fred Daniëls ons rond door nationaal park de Hoge Veluwe. Op de achtergrond, v.l.n.r., Ruud Bartholomeus, Bernard Voortman en boswachter Evert Cock. De samenhang tussen beide delen is schematisch weergegeven in Figuur 3. We gaan deze figuur hier niet bespreken; we hopen dat hij een houvast biedt bij het vinden van samenhang in het onderzoek dat op de volgende pagina’s wordt beschreven. Het onderzoek dat we doen is ambitieus en het is de vraag of het plan dat we hier presenteren wel volledig kan worden gerealiseerd binnen het gegeven budget en de beperkte tijd. Natuurlijk moeten we ook keuzes maken in de processen waarop we ons richten. In het eerste deel zullen we zo goed mogelijk aangeven wat we waarschijnlijk wel gaan halen, en over welke producten we minder zeker zijn. De komende tijd zullen we verder gaan met pogingen ons onderzoek te versterken. We willen andere partijen ervoor proberen te interesseren, maar we vinden het vooral gewenst de drinkwaterbedrijven meer bij het onderzoek te betrekken dan we tot nu toe hebben gedaan.


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Figuur 3. Samenhang tussen de verschillende onderdelen van het onderzoek. KVK = promotieonderzoek van Bernard Voortman; FOP = postdoc onderzoek van Ruud Bartholomeus, BTO = BTO-onderzoek grondwateraanvulling.


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In search of the actual groundwater recharge Part I (BTO & FOP) © KWR

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Part I Redefining crop factors (BTO & FOP)


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1

Introduction

1.1 Problem definition Climate change is among the most pressing issues of our time. The global temperature rises, the atmospheric CO2-concentration increases and prolonged dry periods are alternated with heavy rainfall events. According to climate scenarios for the Netherlands, the summer temperature may increase with 3°C, summer rainfall may decrease with 19% and reference evapotranspiration may increase with 15%. Although the total amount of summer rainfall decreases, heavy rainfall events will occur more frequently in summer. The winter rainfall will increase (Van den Hurk et al., 2006). As both precipitation and evapotranspiration are included in the water balance, it is evident that these changes would alter the current hydrological system. However, although the reference evapotranspiration is predicted to increase, the future actual evapotranspiration is highly unknown. As precipitation and actual evapotranspiration largely determine groundwater recharge, climate change likely affects both the spatial and temporal availability of groundwater. This will alter the fresh water availability for agriculture, nature conservation and industrial and drinking water supply. Current knowledge, however, is insufficient to estimate reliably the effects of climate change on future freshwater availability. It has been stated already that increased droughts may affect groundwater recharge rates, and herewith the future availability of fresh water (Bates et al., 2008) for e.g. agriculture and drinking water. In order to predict future groundwater recharge, however, we first need to understand possible vegetation responses to climate change, because these determine the future actual evapotranspiration ETa (Stuyfzand and Rambags, 2011; Wegehenkel, 2009). Although the future potential evapotranspiration ETp may increase due to increased temperatures (Solomon et al., 2007), it is the future ETa that affects groundwater recharge (Droogers, 2000). 1.2 Research topics and goals BTO and FOP-fund Currently, groundwater modeling frameworks, both numerical ones like ModFlow-MetaSwap (used for the NHI; www.nhi.nu) and e.g. analytical impulse-response models like Menyanthes (Von Asmuth et al., 2002) include a very simplistic schematization of the vegetation. In hydrological modeling, it is common practice to fit simulated to measured groundwater levels, by adjusting e.g. the soil physical parameters as these are poorly known. Parameters of ETa usually remain untouched. Generally, ETa is calculated for a vegetation layer with fixed properties, for which ETp is derived from the reference ET (ETref) via the crop factor approach (Feddes, 1987). Such approach may be preferred for model simplicity, but the empirical crop factors can only be applied under the environmental conditions in which they were determined. Additionally, the current crop factors implicitly include the interception of crops under the current climate only. Consequently, empirical crop factors may for instance not be applied under a future climate with altered precipitation regime. Our goal is to unravel and redefine current crop factors so that they can be used for climate projections. Recently, we found an important vegetation response to drought conditions that may affect the groundwater recharge. Based on an explorative study in the Dutch dune area we found that the cover of vascular plants might decrease due to increased drought, which could increase future groundwater recharge, as ETa decreases with decreased vegetation cover (Kamps et al., 2008; Witte et al., 2008b). Drought induced differences in vegetation characteristics affecting ETa can be observed on surfaces with different slope and aspect, where received solar radiation determines the spatial variability in vegetation characteristics due to spatially variable drought conditions (Bennie et al., 2008; Nevo et al., 1998; Witte et al., 2008b). Solar radiation is a key determinant of vegetation characteristics, not only at large spatial scales, but also at local scales where slope and aspect may vary (Bennie et al., 2008). Higher solar radiation on equator-facing slopes relative to polar-facing slopes results in a higher evaporative demand, and consequently drier equator-facing slopes (Gutiérrez-Jurado et al., 2006). As a consequence of such


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dry conditions, the vegetation on equator facing surfaces is more xeric (Bennie et al., 2008; GutiérrezJurado et al., 2006), has a lower aboveground biomass and plant cover (Badano et al., 2005; Broza et al., 2004; Holland and Steyn, 1975; Nevo et al., 1998; Reddy et al., 2004; Schimper, 1903; Shoshany, 2002; Witte et al., 2008b), and is more patchy (Kutiel et al., 1998; Shoshany, 2002) than on polar facing surfaces. Our goal is to relate empirically reference drought stress, i.e. a measure of the soil dryness, to vegetation cover. Changes in soil cover will affect the heat balance at the soil-atmosphere interface. Current hydrological models do consider local effects of low soil moisture pressure in the root zone on ETa by using the Feddes-function for relative root water uptake (Feddes et al., 1978). However, besides this water-limiting effect on ETa, also energy plays an important role. So far, the energy balance is only incorporated in ETref, which has only very limited variability across the Netherlands and does not account for small-scale differences in ETa. However, besides the water balance, also the energy balance will be site-specific. A low vegetation cover, for example, will increase the soil heat flux, which will affect evaporation (Monteith and Unsworth, 1990). Our goal is to calculate the feedback of vegetation cover on the soil heat flux and ETa (optional, if time allows). Transpiration is closely correlated to photosynthesis and herewith CO2 uptake. The increase of the atmospheric CO2 concentration potentially affects transpiration; the water use efficiency of plants will increase due to increased CO2. Recent research (Kruijt et al., 2008; Witte et al., 2006a; Witte et al., 2006b) showed that the stomatal aperture of plants will be lower in the future climate due to increased CO2. Kruijt et al. (2008) and Witte et al. (2006a; 2006b) showed that future ETref will still increase, but about 2% (for a grass cover) less than according to the KNMI’06 climate scenarios. So, together with soil moisture, interception and energy availability, [CO2] will affect ETa. Our goal is to take better account of the plant stomatal response on atmospheric [CO2], micro-climatic variability, interception and soil moisture, simultaneously (optional, if time allows). Overall, we intend to estimate optimally the actual evapotranspiration ETa, for current and for future climatic conditions and herewith the simulation of groundwater recharge in groundwater models. We focus on the effects of increased drought on vegetation characteristics and the vegetation feedbacks on evaporation, transpiration and interception. Finally, these factors determine groundwater recharge. The internationally established model for the unsaturated zone ‘SWAP’ (Van Dam et al., 2008) will play a central role in this project. SWAP incorporates in detail the interacting processes in the soil-water-plantatmosphere continuum, and allows in-depth analysis of each of these processes. 1.3 Outline and planned deliverables The processes that determine the interactions between climate, vegetation, soil moisture and groundwater recharge are complex. Although drought stress is the most important stress factor for plant growth (Reddy et al., 2004) and primarily determines vegetation characteristics (Porporato et al., 2001b) other stresses may affect vegetation characteristics as well. Some other stresses however, like heat stress and shear (wind) stress, are often initiated by drought stress, and are therefore of secondary importance. We also recognize that the impact of e.g. salt spray in the coastal zone (Stuyfzand, 1993), and microclimatological conditions like cold stress in dune depressions (Vugts, 2002), may be important for the vegetation. However, given the period of our project and the complexity of each of these processes and their interactions, it will be infeasible to incorporate them all in our research. Therefore, this research is restricted to the analysis of climate change effects on drought stress and the resulting vegetation characteristics. Effects of salt and wind will be minimized by a deliberate selection of field plots, i.e. by investigating inland rather than coastal dunes. Additionally, in dune systems processes like water repellency, preferential flow and surface runoff affect the moisture availability for plants and the groundwater recharge (Dekker, 1998; Dekker et al., 2001; Dekker et al., 2000; Ritsema, 1998; Ritsema and Dekker, 1994). Because of the difficulty to generalize these processes and to schematize them, we do not explicitly incorporate them in our modeling procedures now.


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Overall, within this project we prioritize to get insight in the effects of climate change on reference drought stress, and the response of the vegetation, and their primary feedback on the groundwater recharge by alterations in evaporation, transpiration and interception. The effects of reduced cover on hydrological processes like water repellency could be important, but are unlikely to fit within the current project. We will also only use plot-scale data and do the simulations accordingly. Extrapolation to large areas requires different data (e.g. from remote sensing), which falls outside the scope of this research. We intend to deliver: -

simulations of drought stress on inclined surfaces; empirical relationship between drought stress and vegetation cover; redefined crop factors for ETref, to be used for climate projections with the crop factor approach; simulations of groundwater recharge with SWAP on slopes with different soils and orientations for different climate scenarios; simulations of groundwater levels with Menyanthes for both the current and future climatic conditions based on the redefined crop factor approach.

Optional (depending on time and student projects): -

reliable and non-biased estimations of fractional vegetation cover; integrating water and heat balance; integrating the Penman-Monteith equation for evapotranspiration and the Jarvis model for stomatal aperture in SWAP, which allows a process-based analysis of climate change effects on actual evapotranspiration.


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2

Research topics and products

2.1 Vegetation cover vs. reference drought stress (step A) We will relate reference drought stress, i.e. a measure of the soil dryness, to the fractional vegetation cover. Drought induced differences in vegetation characteristics affecting ETa can be observed on surfaces with different slope and aspect, where received solar radiation determines the spatial variability in vegetation characteristics due to spatially variable drought conditions (Bennie et al., 2008; Nevo et al., 1998; Witte et al., 2008b). Solar radiation is a key determinant of vegetation characteristics, not only at large spatial scales, but also at local scales where slope and aspect may vary (Bennie et al., 2008). Higher solar radiation on equator-facing slopes relative to polar-facing slopes results in a higher evaporative demand, and consequently drier equator-facing slopes (Gutiérrez-Jurado et al., 2006). As a consequence of such dry conditions, the vegetation on equator facing surfaces is more xeric (2008; Gutiérrez-Jurado et al., 2006), has a lower aboveground biomass and plant cover (Badano et al., 2005; Broza et al., 2004; Holland and Steyn, 1975; Nevo et al., 1998; Reddy et al., 2004; Schimper, 1903; Shoshany, 2002), and is more patchy (Kutiel et al., 1998; Shoshany, 2002) than on polar facing surfaces. Not only in arid and semi-arid regions, but also in humid areas, small-scale differences in topography and meteorological conditions cause significant differences in vegetation characteristics (Bennie et al., 2008). Field data from the Netherlands, for instance, show that the fraction of xerophytic plant species within a vegetation plot is higher on south slopes than on north slopes, and the fraction of xerophytes is higher on sandy than on clayey soils. That differences in the fraction of xerophytes are causally connected to drought stress was already indicated by Schimper (1903). Although other stresses may affect vegetation characteristics as well, drought stress is the most important stress factor for plant growth (Reddy et al., 2004) and primarily determines the vegetation characteristics (Porporato et al., 2001b). Other stresses are often initiated by drought stress. Heat stress for example, only occurs when a shortage of water limits transpiration. Hence, cooling of the plant tissue, and nutrient limitation decrease at lower water availability (Porporato et al., 2001b). To get insight in the effect of drought stress on vegetation characteristics (i.e. fraction of xerophytes and fractional vegetation cover) we will (Figure I.1): -

Step A1: define a process-based measure of reference drought stress;

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Step A2: gather field data of fractional vegetation cover based on digital camera survey;

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Step A3: define an empirical relationship between reference drought stress to fractional vegetation cover.

Figure I.1: Relationships between reference drought stress and soil and vegetation cover In search of the actual groundwater recharge Part I (BTO & FOP) © KWR

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2.1.1 Process-based, physiologically relevant measure of drought stress (A1) Various indices exist to characterize drought as experienced by vegetation. Aboveground biomass, for instance, has been related to mean annual precipitation (Huxman et al., 2004), and mean precipitation deficit (Ciais et al., 2005). Such drought indices, however, cannot explain local variations in vegetation characteristics for they do not account for differences in soil texture, groundwater depth and small topographic variations that impact on micro-meteorology (Bennie et al., 2008). These factors together determine the amount of soil water that is available to plants. When soil moisture availability is too low to meet the water demand for transpiration, a plant suffers from drought stress (Reddy et al., 2004; Schimper, 1903). This definition of drought stress, also called physiological drought (Schimper, 1903), implies that not only water availability but also vegetation’s demand has to be considered. Starting from this ecological basis, we will focus on transpiration reduction as the vegetation response to drought stress, thus considering both the supply and demand of water. Outline: -

1D analyses (SWAP (Van Dam et al., 2008)) for a reference vegetation

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adjust SWAP to allow simulations on inclined surfaces, by correcting for solar radiation, precipitation and evaporating surface

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synthetic and field sites (existing data of Jansen and Runhaar (2005) and Jansen et al. (2000))

Timeline: June 2010 – April 2011 Products: -

process-based measure of reference drought stress

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peer reviewed publication ‘Drought stress and vegetation characteristics on sites with different slopes and orientations’; Bartholomeus, Witte, Runhaar; Ecohydrology, 2011

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peer reviewed publication ‘Need of considering vegetation feedbacks to reliably estimate groundwater recharge’; Opinion paper, Witte, Bartholomeus, Voortman; Ecohydrology, 2011

2.1.2 Estimation of fractional vegetation cover based on digital photography (A2) Recently, an important feedback of the vegetation to climate change was identified in dune systems: the fraction of bare soil and non-rooting species (lichens and mosses) in the dune vegetation might increase when, according to the expectations, summers become drier (Van den Hurk et al., 2006). For hydrological modeling of dune areas, the fractions of bare soil and vegetation are important input parameters. Evapotranspiration of bare soil and non-rooting species is much lower than that of vascular plants and thus the vegetation composition and cover largely determine the soil moisture conditions (Stuyfzand, 1993; Stuyfzand and Rambags, 2011). Therefore, robust and accurate estimations of the vegetation cover are required. Traditionally, vegetation cover is estimated visually, but this method introduces large biases and is prone to systematic and random errors. Furthermore, repeated sampling can give varying results. We are interested in a method that is less sensitive and less subjective and can deliver reliable estimates of bare soil, vascular plants and moss fractions. Outline: -

Student project to explore possibilities of using remote sensing to estimate soil cover fractions;

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Optical sensing techniques can be a possible solution, but several possibilities are available with varying spectral and spatial dimensions (e.g. ASD-Fieldspectrometer, Cropscan, Digital camera);

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Practical and accurate instruments and methods should be further developed (student project) and applied to acquire additional field data with accurate cover fractions;

Timeline: -

Student projects: April-May 2010, and May-June 2011


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Acquire additional field data: May/June 2011

Research partners: -

CGI (Wageningen University)

Selection of relevant literature: -

(Corre, 1991; Curr et al., 2000; Hemmleb et al., 2005; Hu et al., 2007; Louhaichi et al., 2010)

2.1.3 Relationships reference drought stress – cover fractions (A3) The results from Step A1 and Step A2 will be combined, which results in an empirical relationship between reference drought stress and fractional vegetation cover (grass, moss, bare soil). To do so, reference drought stress will be simulated for all sites of Step A2, i.e. sites where cover fractions will be estimated. Hitherto, detailed soil physical properties of each site should be estimated. Detailed soil physical properties will improve accurateness of simulated reference drought stress. Together with unbiased fractional vegetation covers, this will result in an empirical relationship between reference drought stress and fractional vegetation cover with minimal noise and high predictive power. Such relationship will provide insight in the effect of drought stress on fractional vegetation cover under field conditions, and allows predicting the potential future fractional vegetation cover under future climatic conditions. Outline: -

empirical relationship, i.e. no dynamic vegetation models, but field data;

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sites at dry sands at Veluwe and Dutch coastal dunes; start with sites of Jansen and Runhaar, add new sites;

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soil samples of organic top layer and subsoil to obtain Van Genuchten soil physical parameters (analysis at VU-lab);

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fractional vegetation cover from Step A2, but also detailed vegetation records.

Timeline: -

May-December 2011

Products: -

empirical relationship between reference drought stress and vegetation cover fractions;

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robust method for estimation of vegetation cover fractions, with low bias compared to traditional methods;

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peer reviewed publication (based on Steps A1, 2 and 3).


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2.2 Unravel crop factors (step B) The reference evapotranspiration ETref is defined as the evapotranspiration of short grassland optimally supplied with water. ETref is used to estimate the potential evapotranspiration ETp of a crop or vegetation, which reduces to the actual evapotranspiration ETa in case of water shortage. Here, we focus on the estimation of ETp from ETref, which is generally done by applying crop factors, kc (Allen et al., 1998; Allen et al., 2005; Feddes, 1987): ETp = kc · ETref. Crop factors have been derived for different crops and vegetation types based on measurements and are available for e.g. grass, maize, deciduous forest and pine forest. In the Netherlands, crop factors according to (Feddes, 1987) are used to transpose ETref_Mak (i.e. ETref for a reference grassland, according to Makkink (1957)) to the ETp of a crop (i.e. evapotranspiration of a crop without water stress). ETref_Mak is supplied by the KNMI. Currently used crop factors for the Netherlands are published by (Feddes, 1987), and by definition they should be used to derive ETp from ETref_Mak:

ETp  kc  ETref_Mak

[1.1]

where kc is the crop factor and ETref_Mak is the potential evapotranspiration of grass according to Makkink (1957). ETref_Mak includes I, Ep and Tp. Consequently, kc accounts for each of these evaporation components, and thus:

ETp  I  Ep  Tp

[1.2]

where ETp is the potential evapotranspiration of a cropped surface, I is the sum of evaporation of intercepted water (Pi), Ep is the potential soil evaporation and Tp the potential transpiration. So, crop factors according to Feddes (1987) implicitly involve I. Additionally, crop factors for the Netherlands have been derived by soil water balance experiments, and especially from sprinkling experiments in the field, where water is applied in quantities that ETp is reached (Feddes, 1987). Sprinkling, however, leads to interception. Feddes (1987) also emphasizes that the presented crop factors “are averages taken over a population of ‘average’, ‘dry’, and ‘wet’ years, that will certainly not be homogeneously distributed”. Crop factors thus correct for the combined effect of Ep, Tp and I. Each of these factors, however, may change differently under changing climatic conditions. This implies that crop factors can only be applied under the conditions in which they were determined. Consequently, these crop factors are inappropriate to be used for extreme weather years such as 1976 (dry) and 1998 (wet) and they cannot be applied under changing climatic conditions. The crop factor approach by Feddes (1987) is different from that of the FAO (Allen et al., 1998), as these are by definition applied to correct for Ep and Tp only. However, Allen et al. (1998) indicate that their crop factors should be multiplied with a factor 1.1-1.3 if interception, due to sprinkling irrigation for example, is involved. This indicates that I could significantly affect evapotranspiration from a vegetated surface. Therefore, it is important to consider the contribution of I on ETp explicitly. The KNMI provides daily values of ETref_Mak. They define ETref_Mak as the evapotranspiration from a dry grass surface, i.e. I=0, optimally supplied by water (Droogers, 2009). This definition does not correspond to the definition of Feddes (1987) which should be used for the crop factor approach. Additionally, ETref_Mak includes empirical constants and it is not a physical quantity (De Bruin, 1987), which makes it inapplicable for climate projections. Makkink (1957) derived his relationship and the empirical constants on field data, i.e. implicitly involving I, at least at wet days. Consequently, ETref_Mak as provided by the KNMI is not valid for dry crops only, as mentioned by Droogers (2009), but for the mean meteorological conditions that Makkink used for his equation. All in all, some remarks can be made to the applicability of the current crop factor approach in climate projections. Therefore, we intend to improve the current calculations of ETp and I, by detailed simulations using the Penman-Monteith approach, from which correction factors for Makkink will be derived.


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This includes the following steps (Figure I.2): -

Step B1: Simulation of ETp and I using Penman-Monteith: derive ETref_Mak_dry

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Step B2: Derive ETref_mak_dry with Makkink only

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Step B3: Improvement of calculation scheme in SWAP

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Step B4: Simulation of ETp and I using Penman-Monteith and ETref_Mak_dry for KNMI’06 scenarios

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Step B5: Sensitivity analysis using SWAP and Menyanthes

2.2.1 Simulation of ETp and I (B1) SWAP (Van Dam et al., 2008), divides ETp (obtained from ETref through crop factors) in Pi (intercepted precipitation, which will (partly) evaporate (=I)), Ep (potential evaporation under standing crop, with no soil heat flux) and Tp (potential transpiration). Calculation of Tp, however, requires both Pi and Ep as input. Additionally, going from ETref to ETp via kc implicitly includes Pi. Using these kc-values for climate projections of Tp will be fundamentally wrong, as the interception that is involved in kc will differ from the simulated interception that is input for the calculation of Tp (Kroes and Van Dam, 2003). Therefore, we will redefine the crop factors of Feddes (1987), so that they are applicable on a dry crop only. Contrary to Makkink, the Penman-Monteith equation does not include empirical constants. PenmanMonteith may thus outcompete Makkink for climate projections. In fact, the KNMI also used PenmanMonteith for the KNMI’06 scenarios (Van den Hurk et al., 2006); the effects of climate change on ETref were first calculated with Penman-Monteith and thereafter applied on ETref according to Makkink. This is unnecessarily elaborative, as we can use ETref according to Penman-Monteith directly. Additionally, De Bruin (1987) writes that Penman-Monteith “successfully describes the transpiration as well as the interceptive loss from different kinds of vegetation such as tall forests, arable crops, heathland and grass”. This provides more confidence in the validity of Penman-Monteith than of Makkink. First, we will use the Penman-Monteith equation to simulate Ep, Tp and I for the current climatic conditions (1971-2000), which together give the evapotranspiration for a reference grass under the prevailing, actual meteorological conditions. Ideally, (Ep + Tp + I), i.e. ETref_PM_avg, equals ETref_Mak, but slight differences are to be expected (see Droogers, 2009). Then, we will calculate ETref_Mak for a dry crop only, by correcting for the effect of I on ETp, given by gI:

gI 

ETref_PM_dry

[1.3]

ETref_PM_avg

ETref_Mak_dry  gI  ETref_Mak

[1.4]

Figure I.2: Unravel crop factors; split ETref into Ep, Tp and I In search of the actual groundwater recharge Part I (BTO & FOP) © KWR

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where gI is a factor that corrects the contribution of I in ETref_Mak. ETref_Mak_dry is the reference evapotranspiration of Makkink for a dry crop (I = 0). This ETref_Mak_dry should replace ETref_Mak in SWAP. Only then, Tp can be simulated correctly. The reference evapotranspiration of a wet crop should be equal to the Penman evaporation of open water. NB: gI = (Ep + Tp) / (Ep + Tp + I) = (Ep + Tp) / ETref_PM_avg will not give the correct factor, as the reduced Tp when the crop is wet will not be considered then Consequently, also the crop factors should be redefined in order to get ETp_dry. Therefore, for each crop we need to derive gI, which gives gIc. We will do so with SWAP, using the same method as for a reference grass, but with specific crop characteristics (LAI, rcrop, rair). Finally this will give:

kc_dry  gI,c  kc

[1.5]

2.2.2 Derive ETref_mak_dry with Makkink only (B2) As an alternative approach, we will run two SWAP-simulations based on ETref_Mak: one with Pi=0 combined with optimal soil moisture availability (which gives ETp,Pi=0), and one with the real meteorological conditions i.e. real Pgross and Pi (which gives ETp). Ideally, ETp,Pi=0/ETp gives gI. First, we will do these simulations for grass only, and compare gI to that of equation [1.3]. If the results are comparable then we could use this approach for all other crops. However, as ETref_Mak is valid for the average meteorological conditions only, the current SWAP-schematization for the use of ETref_Mak is arranged accordingly. This schematization may not hold for conditions with Pi=0, which may cause differences in the obtained gI’s. Therefore, the usability of this approach is quite uncertain. Nevertheless, if gI for a grass from Step B2 is comparable to that of B1, we will run SWAP with ETref_Mak for different LAI’s and kc’s. This allows deriving a relationship between LAI, kc and gI,c, which could be used to derive kc_dry for a variety of crops. 2.2.3 Improvement of calculation scheme in SWAP (B3) Using ETref_Mak_dry and kc_dry allows an alternative calculation of the evapotranspiration of a wet surface compared to the one that is currently incorporated in SWAP (with ETref_Mak as input). By using ETref_Mak_dry we can account better for different evaporative fluxes under either wet or dry conditions. When ETref_Mak_dry will be input, we can directly calculate ETp_dry. ETp_wet should be taken equal to the Penman open water evaporation E0. Additionally, kc will be replaced by kc_dry. This allows discriminating better between wet and dry conditions. So we need (see also ‘List of Symbols’:

  1 Pi  a  LAI   1  b  Pgross  1  a  LAI 

     

[1.6]

ETp_dry  kc_dry  ETref_Mak_dry

[1.7]

ETp_wet  E0

[1.8]

Then:

Ep  Ep_bare  e

 gr LAI

[1.9]

or


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 Pi  Ep  Ep_bare   1     1  SC    ET p_wet  

[1.10]

and finally:

 Pi Tp   1   ETp_wet 

   ETp_dry  Ep  

[1.11]

Implementation of ETref_Mak_dry in SWAP, as described above, allows continuing using Makkink as supplied by the KNMI. However, I and its effect on Tp will be handled differently compared to the current approach. By adjusting SWAP, Makkink can be used in climate scenarios, as it explicitly separates dry from wet canopy conditions. We will explore this further in step B4. 2.2.4 Simulation of ETp and I using Penman-Monteith and ETref_mak_dry for KNMI’06 scenarios (B4) In this analysis, we will show the application of our improved schematization of ETp and I in groundwater models for the KNMI’06 scenarios. Current hydrological models assume fixed evaporation characteristics of the vegetation, and the effect of interception on the groundwater recharge is not considered explicitly. With climate change, however, vegetation characteristics and interception will change. Here, we will show how evaporation, transpiration and interception should be handled in groundwater models in climate projections, and how each of these factors will change due to climate change. We will use the correction factors of Kruijt et al. (2008) and Witte et al. (2006a; 2006b) (fCO2) to correct ETref_Mak_dry for a higher water use efficiency due to increased atmospheric CO2-concentration under future climatic conditions. For each KNMI’06 scenario (which includes fKNMI), we will run SWAP and simulate ETp based on the adjusted SWAP schematization. ETp will be based on the adjusted SWAP version, with ETp_dry_cc as input. For a specific crop and climate scenario the following holds:

ETp_dry_cc  ETref_Mak_dry  kc_dry  f KNMI  f CO 2

[1.12]

ETp_cc  Ep_cc  Tp_cc  I _cc

[1.13]

(output of SWAP)

Outline step B1-B4: -

vegetation of dry sands: grass, heather, deciduous forest and evergreen forest

-

calculating interception of forests and of short vegetation requires different approaches (Gash vs. Von Hoyningen-Hüne for forests and agricultural vegetation resp.). In contrast to Von Hoyningen-Hüne, Gash accounts for the effect of rain duration and evaporation during the rain event.

-

no measurements, only use existing data (e.g. the Castricum lysimeter data; see Van der Hoeven (2010), www.climatexchange.nl/projects/lysimeter/lysimeter.htm) and general equations for E, T and I, as used in SWAP. Only then, we are able to compare our redefined crop factors to current ones, using SWAP. Both in the Netherlands and internationally, SWAP can be considered the standard to estimate the actual evapotranspiration as function of meteorological conditions combined with crop and soil conditions.

Timeline step B1-B4: -

April 2011-February 2012

Products:


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-

Correction factors kc_dry for grass, heather, deciduous and evergreen forest, to be applied on ETref_Mak_dry to get ETp for each crop/vegetation type.

2.2.5 Sensitivity analysis using SWAP and Menyanthes (B5) We will perform a sensitivity analysis on the effect of using our redefined crop factors (kc_dry) or the current ones (kc) in soil moisture and groundwater simulations. First, we will simulate groundwater levels and soil moisture conditions with SWAP with the traditional crop factors as input, for both the current and future climatic conditions (with fKNMI and fCO2). We will compare climate-induced changes in groundwater levels with SWAP simulations based on kc_dry, fKNMI and fCO2. This will show us whether redefined crop factors significantly alter simulated groundwater levels. Then, we will analyze the effect of using either ETref_Mak (i.e. valid for average conditions), or I, Ep and Tp explicitly (i.e. accounting for temporal deviations from the average conditions) in groundwater level simulations. This will show us the need of considering the effects of temporal dry or wet conditions on interception and on groundwater recharge. Currently, Menyanthes uses Pgross and ETref_Mak, together considered as measure of groundwater recharge, as explaining variables of the groundwater level. Temporal variability in both I, Ep and Tp is thus not considered. We argue that using ETref_Mak as input of groundwater simulations, without explicitly accounting for the contribution of interception, will cause systematically too low or too high groundwater levels in periods of low and high precipitation, respectively. We argue that taking account of the temporal effect of I on ETp and herewith for the minimum groundwater recharge (Pgross – Ep - Tp – I), will improve the accurateness of groundwater level simulations. To show this, we will simulate Ep, Tp and I with SWAP and use this as input for Menyanthes. We will compare model predictions to those based on ETref_Mak of the KNMI. We will compare simulated groundwater levels to measured ones for Ep, Tp and I from SWAP, and ETref_Mak. Outline: -

only SWAP and Menyanthes;

-

sites with groundwater independent vegetation, for which both groundwater levels and drainage functions are available;

-

simulation of Ep, Tp and I according to current SWAP model; no feedbacks of altered soil heat flux due to drought-induced low vegetation cover.

Timeline: -

January-July 2012

Products: -

paper on the sensitivity of simulated groundwater levels to evaporation, interception and transpiration


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2.3

Water and heat balance as function of soil and vegetation cover (optional, if time allows) (step C) In the calculation of ETref the effect of the soil heat flux is considered to be of minor importance as the vegetation is fully covering the soil (Allen et al., 1998). Changes in soil cover (see A), however, will affect the heat balance at the soil-atmosphere interface. A low vegetation cover, for example, will increase the soil heat flux, which will increase ETp (Monteith and Unsworth, 1990). Climate change may alter both the fractional vegetation cover (see A), and the interception of the vegetated surface (see B). A low vegetation cover will affect the soil heat flux and herewith ETp. We will analyze the effect of droughtinduced changes in fractional vegetation cover (A) on Ep, Tp and I for different fractional vegetation covers. In the end this will show us how low vegetation cover affects the groundwater recharge through alteration of the local heat and water balance. If time allows, the following steps will be followed: -

Step C1: simulate soil heat flux for partly covered surfaces with SWAP and its feedback on ETp according to Penman-Monteith

-

Step C2: Effect of bare soil on water balance components, through its feedback on transpiration: combine heat and water balance

2.3.1 Soil heat flux and temperature for partly covered surfaces (C1) A general assumption in the application of the reference evapotranspiration is that it holds for a large uniform surface, so that advection can be ignored. Advection, or the transfer of heat and/or water vapor from the surroundings, provides an extra source of energy and may play a role in partly covered soils. Heat generated at a dry soil surface, for example, can be consumed through increased transpiration by the plants adjacent to the dry soil (Rosenberg et al., 1983) (p. 230). Also within a single dune surface, an open or patchy vegetation layer affects the soil heat flux, as shown by Kustas et al. (2000). The difference between net radiation Rn and the soil heat flux G determines the available energy for transpiration. If the heat loss from the soil to the atmosphere is high (i.e. G is directed upward and thus G<0) there is more energy available for transpiration. This available energy will be affected by the lateral transport of heat, which especially occurs in a patchy vegetation. Therefore, we need to consider the effect of partly covered soils on the soil temperature (Tsoil) and air temperature near the soil surface (Tair) and G. SWAP includes these variables, but improvements may be needed. Especially the feedback of G on Tair just above the vegetation layer is not included yet. We will execute SWAP simulations on north and south facing surfaces, i.e. surfaces with differences in solar radiation Rs. We will investigate the effect of different soil cover fractions on Tsoil, Tair, G, and ETp. A sensitivity analysis will provide insight in the importance of considering both the water and heat balance to estimate ETp and ETa. We hypothesize that a low vegetation cover increases the available energy for the sparse vegetation that is present. This will increase the demand of water, i.e. Tp. If the water availability does not increase proportionally, drought stress will increase. We will investigate the effect of low soil cover on Tp, Ta and actual drought stress, using the SWAP simulations on north and south facing surfaces. This means that we use ETref_PM, and the reduction functions for root water uptake of Feddes et al. (1978) or of Metselaar and de Jong van Lier (2007) to describe the difference between Tp and Ta. Outline: -

SWAP simulations on north and south surfaces in both coastal and inland dune areas in the Netherlands

-

adjust SWAP to account for feedback of soil heat flux on air temperature and on ETp

Timeline: -

2012, possibly student project of 5 months


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May 2011

Products: -

Insight in the effect of low soil cover and altered heat balance on ETp and its feedback on drought stress

-

Note or student report on effect fluxes on water balance

Relevant literature: -

(Kustas et al., 2000; Yang et al., 1999)

2.3.2 Effect of bare soil on water balance components, through its feedback on transpiration: combine heat and water balance (C2) Our ultimate step could be a fully process-based simulation of the plant stomatal response on atmospheric [CO2], micro-climatic variability in heat, and soil moisture, simultaneously. Hereto, we will simulate the plant stomatal aperture explicitly with the Jarvis equation (e.g. Jarvis et al., 1999), and use this as input for the Penman-Monteith equation. We intend to implement this approach in SWAP, and simulate groundwater recharge under both the current and future climatic conditions with a fully process-based approach, without the interference of a reference crop and crop factors. Ideally, this gives insight in the possibility to calculate directly the actual evapotranspiration in groundwater models. This subject could possibly be executed by a student in collaboration with Prof. dr. ir. M. Bierkens of Utrecht University and Prof. dr. ir. S. vd Zee of Wageningen University.


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3

Delivered products

3.1 2010 - student project CGI: insight in methods, field work and report: o -

publications o

-

-

SOIL & VEGETATION FRACTIONS IN DUNE ECOSYSTEMS; Estimation of soil and vegetation fractions from reflectance measurements in dune ecosystems Bartholomeus, R.P., Voortman, B. and Witte, J.P.M., 2010. De toekomstige grondwateraanvulling. H2O, 17: 35-37.

presentations: o

AGU Fall Meeting, 2010. Climate change effects on vegetation characteristics and groundwater recharge. San Francisco, Calif., 16-12-2010, oral presentation.

o

Deltas in times of climate change, 2010. Climate change effects on vegetation characteristics and groundwater recharge. Rotterdam, The Netherlands, 29-9-2010, oral presentation.

o

EGU General Assembly, 2010. Climate change effects on vegetation characteristics and groundwater recharge. Vienna, Austria, 7-5-2010, poster presentation.

o

Latsis 2010 International Symposium on Ecohydrology, 2010. Climate change effects on vegetation characteristics and groundwater recharge. Lausanne, Switserland, 19-10-2010, poster presentation

proceedings: o

Bartholomeus, R.P., Voortman, B., Witte, J.P.M., 2010. Climate change effects on vegetation characteristics and groundwater recharge. Abstract H43J-04 presented at 2010 Fall Meeting, AGU, San Francisco, Calif., 13-17 Dec.

o

Bartholomeus, R.P. and Witte, J.P.M., 2010. Climate change effects on vegetation characteristics and groundwater recharge. Deltas in times of climate change. Abstracts scientific programme deltas in depth. Rotterdam, pp. 61-62.

o

Witte, J.P.M., Bartholomeus, R.P. and Cirkel, D.G., 2010. Climate change effects on vegetation characteristics and groundwater recharge. Latsis 2010 International Symposium on Ecohydrology. Abstract book Latsis 2010, Lausanne, Switserland, pp. 72.

o

Witte, J.P.M., Bartholomeus, R.P. and Cirkel, D.G., 2010. Climate change effects on vegetation characteristics and groundwater recharge, EGU General Assembly 2010. Geophysical Research Abstracts, Abstract EGU2010-3401, Vienna, Austria.

3.2 2011 - student project CGI: insight in methods, field work and report: AHN-2 combined with 4-band air pictures, both 25*25cm scale. Couple with drought stress on inclined surfaces. -

student at KWR: insight in 1D (SWAP) vs 3D (Hydrus-3D) modeling of the unsaturated zone at inclined surfaces and partly covered soils.

-

student at CGI: Automated estimation of fractional cover of plant functional types using digital near infrared photography

-

publications:


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May 2011

-

o

Bartholomeus, R.P., Witte, J.P.M., Runhaar, H. 2011. Drought stress and vegetation characteristics on sites with different slopes and orientations, Ecohydrology.

o

Witte, J.P.M., Bartholomeus, R.P., Voortman, B., 2011. Need of considering vegetation feedbacks to reliably estimate groundwater recharge, Ecohydrology.

presentations: o

-

EGU General Assembly, 2011. Drought stress and vegetation characteristics on sites with different slopes and orientations. Vienna, Austria, 8-4-2011, poster presentation.

proceedings: o

Bartholomeus, R.P. and Witte, J.P.M., 2011. Drought stress and vegetation characteristics on sites with different slopes and orientations, EGU General Assembly 2011. Geophysical Research Abstracts, Abstract EGU2011-2184, Vienna, Austria.


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Part II PhD proposal Bernard Voortman (KvK)

In search of the actual groundwater recharge − Part II (KvK) © KWR

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The future groundwater recharge in coastal and inland sand dunes: evapotranspiration response of natural vegetation to climate change

Research proposal February 2011 B.R. Voortman Supervisors: Prof. Dr. ir. S.E.A.T.M. van der Zee Prof. Dr. ir. M.F.P. Bierkens Prof. Dr. ir. J.P.M. Witte Dr. ir. P.M. van Bodegom Dr. ir. R.P. Bartholomeus


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1

Introduction

1.1 Background and problem definition Global temperatures are expected to increase in the coming century. Higher temperatures will lead to a larger water-holding capacity of the atmosphere which favours increased climate variability, with more intense precipitation events and more droughts (Trenberth et al., 2003). The timing and amount of rainfall events may shift throughout the year (Meehl et al., 2007). These changes will alter the amount of water that percolates to the saturated zone, i.e. the groundwater recharge, as well as the size and dynamics of fresh groundwater bodies. Changes in the supply of fresh groundwater will affect ecosystems, agricultural productivity and the supply of drinking water. Current knowledge, however, is insufficient to reliably estimate the amount of groundwater recharge under changing climatic conditions (Wegehenkel, 2009). The major drawback of current methods to estimate groundwater recharge is the use of static predefined vegetation characteristics in simulation models. It is likely that vegetation characteristics such as the species abundance and composition will adjust to future weather conditions (Kreyling, 2008; Miller et al., 2010) which will affect the energy and water balance. The potential of climate change to affect vegetation characteristic is especially large in water limited ecosystems where soil moisture availability is a constraining factor for plant survival (Porporato et al., 2001a). For these regions the response of vegetation should be included in predictions of the future groundwater recharge. Coastal and inland sand dunes are often considered systems where strong relationships between soil moisture conditions and vegetation characteristics are present (Maun, 1994; Park, 1990; Tazaki, 1960). Even in temperate regions with a large annual precipitation amount, soil moisture conditions affect vegetation characteristics in sand dune systems (Park, 1990). These regions are of interest in this study. In an exploratory study Witte et al. (2008a) showed that increased summer drought might lead to a dieback of vascular plants and an increase in the cover fraction of non-rooting species (mosses and lichens) and barren surfaces in coastal dunes of The Netherlands. Because the evapotranspiration of mosses, lichens and barren soil is much less than that of vascular plants this vegetation response will lead to a lower evapotranspiration and to an increase in groundwater recharge. This interaction between climate, vegetation and evapotranspiration needs further attention as it has a major effect on estimates of the future groundwater recharge. 1.2 Research objectives The primary aim of this research is to improve simulations of evapotranspiration and groundwater recharge in hydrological models in the context of climate change by considering vegetation as a dynamic component. Modelling vegetation dynamics can be achieved on different spatial scales and different levels of complexity. In this study species will be categorised in plant functional types such as bare soil, mosses and lichens, grasses and shrubs. Key interest of this study will lie in quantifying the cover percentage of these plant functional types under changing climatic conditions on groundwater independent sandy soils. This study aims to give answer to the following research questions: 

How are soil moisture conditions related to the cover fractions of plant functional types such as bare soil, mosses, lichens, grasses and shrubs?



How do changes in cover fractions of plant functional types affect soil evaporation, transpiration, interception water loss and groundwater recharge?



What is the effect of changing meteorological conditions on the distribution of plant functional types and how does this affect the future groundwater recharge?

1.3 Outline This research proposal consists of four topics which should lead to four scientific publications. Before these are introduced, a brief review of the vegetation distribution and dynamics in coastal and inland

In search of the actual groundwater recharge − Part II (PhD) © KWR

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May 2011

sand dunes is given in chapter 2. After this chapter, an analysis of the available data and the research approach will be given (chapter 3). The first topic about the effects of mosses and lichens on the soil water balance will be discussed in chapter 4. The second topic is about modelling plant available water in one and three spatial dimensions (chapter 5). This chapter mainly deals with unsaturated flow processes and the effects of the vegetation structure and topography on the water balance. The third topic is about the relationship between soil moisture conditions and the coverage of dry grassland vegetation. A database of 3000 relevés of Corynephorus canescens grassland vegetation following a WestEast gradient from The Netherlands to Slovakia will be used to relate soil moisture conditions to the cover percentage of dry grassland vegetation (chapter 6). The last topic will be about the succession of dune vegetation under changing climatic conditions and its effect on the water balance (chapter 7). This research proposal ends with a timetable summarizing the amount of time needed to perform this research per topic.


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2

Vegetation dynamics in coastal and inland sand dunes

2.1 Introduction An analysis of historical data on active drift sand areas may reveal which processes affect vegetation development. Pollen analyses revealed that the first phase of aeolian reformation of coastal dunes started between the 10th and 12th century and ended in the 13th century (Jelgersma et al., 1970). During the same period inland drift-sands were formed which represent reactivated deposits of Youger Cover Sands (Koster, 1978; Koster et al., 1993). Land cultivation and deforestation are frequently mentioned as the primary cause of increased aeolian activity at the end of the first millennium (Berendsen, 2005; Oostra, 2006). Increased human activity during medieval times coincided with a relatively warm and dry period, the so-called climate optimum (ca. 950 until 1250 AD) (Figure II.3). The climate of this period was continental with warm summers and cold winters. Geological reconstruction of dried-out fen deposits on the ‘Veluwe’ indicate that annual precipitation amounts decreased during this period with 60 to 180 mm with respect to the preceding climate (Heidinga, 2006). We believe that the shift from an oceanic to a more continental climate during the climate optimum might have promoted aeolian activity, namely through a drought induced vegetation dieback. It is, however, difficult to unravel the effects of climate change from anthropogenic effects, because both have a potential to reduce the vegetation coverage and promote aeolian activity.

Figure II.3. Past 1.3 ka northern hemisphere temperature variation reconstructed using different climate proxies (source Jansen et al. (2007)) Aerial photographs and historical maps show a decrease of barren surfaces in Dutch drift-sand areas in the past century (Figure II.4, Figure II.5, Figure II.6). The colonization of barren surfaces may be the result of natural succession. Some authors suggest that the speed of succession is accelerated by atmospheric nitrogen deposition (Bakker et al., 2003; Nijssen et al., 2010). Most natural vegetation in The Netherlands is maintained or affected by management practices which also altered the vegetation development in the past century. The purpose of this study is partly to asses the impact of climate change on cover fractions and the distribution of plant functional types such as bare soil, mosses, lichens, grasses and shrubs. This assessment can only be carried out successfully if the effect of meteorological conditions on observed changes in vegetation coverage and species composition in time and space can be separated from alterations caused by anthropogenic influence and other factors such as game


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tramping, grazing and sand burial. Natural succession and ageing of vegetation can also lead to changes in coverage and species composition, which blurs the effect of weather conditions. This review will point out the significance of different factors affecting the spatial distribution and dynamics of vegetation in coastal and inland sand dunes.

1911

1963

1984

2003

Figure II.4. Vegetation development at the “Kootwijkerzand”, The Netherlands. in the period 1911-2003. (Source upper photo: staatsbosbeheer, source lower photographs: Topografische Dients Emmen;© Eurosense, 2003 vide Oostra (2006))


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May 2011

Figure II.5. Vegetation development at the Hulshorsterzand between 1900 and 1971 (after Van Ree (1993) vide Berendsen (2005))


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Figure II.6. The areal distribution of active and stabilized drift sands of the Veluwe (source: Koster (1978))


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2.2 Natural Succession Natural succession causes barren surfaces to become vegetated. This colonisation process follows different succession stages. In the first succession stage barren surfaces will be either covered with a thin film of algae or colonised by grass species such as Corynephorus canescens (NL: Buntgras, UK: Grey HairGrass) and Carex arenaria (NL: Zandzegge, UK: Sand Sedge). The pioneer grass species can survive in active drift sand while algae are found in more steady areas which are not disturbed by aeolian activity (Pluis, 1993) (Figure II.7 a and b). When aeolian activity is halted mosses, lichen and other grass species such as Agrostis vinealis (NL: Zandstruisgras, UK: Brown Bent) and Festuca filiformis (NL: Fijn Schapengras, UK: Fine leaved Sheep’s-fescue) will invade (Figure II.7 c and d). In the second stage small shrubs (Heath, Calluna) will take over and will compete with grass species such as Molinia (Heil and Bruggink, 1987). Individual pine trees can invade open grass vegetation or heath. A deciduous or pine forest is the potential succession end stage of the inland drift sand areas of The Netherlands.

Figure II.7. First stages of barren soil colonization. Barren soil colonized by Cornyphorus canescens (a), algae film in a sheltered area (b), mosses together with grass species (c), the soil fully covered by a thick moss layer with tussocks of grass in between.

2.3 Internal vegetation dynamics Detailed studies about the response of vegetation to habitat changes are scarce and primarily of a descriptive character. Quantitative correlations between vegetation dynamics and driving forces are fairly absent. Hasse and Daniëls (2006) described the response of a Corynephorus grassland after several experimentally induced habitat changes in national park ‘de Hoge Veluwe’, The Netherlands. They applied different treatments (sand deposition, litter deposition, nitrogen input and mechanical


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disturbance) in permanent plots. These plots were recorded in the subsequent two years that included the exceptionally dry summer of 2003, which enabled the assessment of drought. Only minor changes occurred in species composition in both treated and untreated plots. So, the experiments showed that on a short timescale Corynephorus grassland is a stable plant community. Grasses and therophytes proved to be more susceptible to drought than to any of the treatments. Bryophytes were less susceptible to drought and most lichens did not respond at all. On a larger timescale Daniëls et al. (2008) studied a large permanent plot (26m x 36m) of corynephorus grassland from 1981 till 2004 in the same national park ‘de Hoge Veluwe’. The plot was situated in the ‘Oud Reemster Zand’. The plot was recorded in August in the years 1981, 1984, 1987, 1991, 1994, 1997, 1999, 2002 and 2004. During the 24 years of recording there were now signs of succession towards a heath- or woodland but internal dynamics of the Corynephorus grassland was high. A strong increase in non-vegetated surfaces was recorded in 1991. In this year subplot (1m x 1m) dominance (more than 50% coverage) by vascular plants decreased from 100% in preceding years to 51%. Mainly the dominance of the grass Festuca filiformis decreased in 1991 which the authors related to cold and dry winter months in the preceding years (1985, 1986, 1987) and to an increase in game population. We have, however, an alternative explanation. The year 1991 was the driest year recorded by the author and the preceding two years were dry as well (Figure II.8). The dieback might have been caused by a water deficit for rooting plants. After the year 1991 the open spaces were rapidly colonized by the moss Campylopus introflexus (NL: grijs kronkelsteeltje). This moss covered nearly the whole plot in 1994. The last ten years of this survey can be interpreted as a series of micro succession where lichens recolonize moss carpets and the abundance of Festuca filiformis increases again.

Estimates of precipitation excess

precipitation excess (mm)

700

recorded

600

not recorded

500 400 300 200 100 0 '09-'10

'07-'08

'05-'06

'03-'04

'01-'02

'99-'00

'97-'98

'95-'96

'93-'94

'91-'92

'89-'90

'87-'88

'85-'86

'83-'84

'81-'82

'79-'80

'77-'78

'75-'76

'73-'74

'71-'72

-100

Figure II.8. Estimates of annual precipitation excess of national park “de Hoge Veluwe”. Precipitation excess is estimated by extracting the Makking Reference crop evaporation (climate station de Bilt) from precipitation (climate station Deelen). Estimates are summed for the months September till August which represents the precipitation excess preceding the recording in August. Vegetation dynamics of a poorly vegetated south facing coastal dune was recorded by Ten Harkel (1992). He recorded a highly dynamic seasonal vegetation cover between 1989 and 1990. In general the coverage of mosses and lichens was highest during the winter period. When temperatures increased during spring, the coverage was rapidly reduced and remained low during summer. Occasionally the moss and lichen coverage increased temporary as a result of relative more precipitation. Frost after a moist period resulted in a dieback of mosses and lichen. Ten Harkel (1992) observed a comparable seasonal cycle for vascular plants. In autumn they germinated and in May they died as a result of drought stress. Only a few developed into a mature status in the harsh habitat of south facing dunes. The observed high internal dynamics of dune vegetation as a response to changing weather conditions is consistent with the current perspective of some ecologist which prove that plant populations track within year variation in weather conditions rather than buffer climate fluctuations (Jongejans et al., 2010).


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2.4 Nitrogen deposition The nutrient poor habitats of inland dunes receive an anthropogenic input of nitrogen through atmospheric nitrogen deposition. Ammonia emission from factory farming causes increased atmospheric nitrogen loads (Bleeker and Erisman, 1996). The Veluwe area is more exposed to anthropogenic nitrogen deposition than other drift sand areas in The Netherlands due to nearby agricultural activity situated upwind of the Veluwe. The extra nitrogen input can be used by lichens, mosses and grasses to increase their biomass production. This may lead to accelerated succession, but there is no indisputable evidence for this. Nitrogen deposition can lead to acidification of the soil and higher nitrogen availability. One would expect higher nitrate and ammonia concentrations in areas with higher nitrogen deposition. Data analyses of 165 samples from 20 drift sand areas under 8 different vegetation types revealed that this was not the case (Nijssen et al., 2010). The organic matter content of the soil was the most important factor determining the ammonia nitrate ratio. There was only a significant effect of nitrogen deposition on the total amount of available inorganic nitrogen. Experiments with extra nitrogen input in coastal and inland dunes had a minor effect on vegetation. Ten Harkel and Van Der Meulen (1996) observed no change in species composition in five years of fertilizing with 2.5 g Nm–2a–1 in grazed as well as ungrazed plots of coastal dune grassland in The Netherlands. In the study of Hasse and Daniëls (2006) nitrogen fertilization with 4.2 g Nm-2a-1 only marginally effected mosses, lichens and grasses. This suggests that succession models based on nutrient cycling and nitrogen deposition scenario’s (e.g. NUCOM, (Van Oene et al., 1999)) might be based on secondary driving forces which poorly represent the operational processes, in particular drought.


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3

Research approach and analyses of the available knowledge

Vegetation dynamics in coastal and inland sand dunes is a difficult process to study as a whole range of factors has the potential to affect the species composition and the vitality of species. Previous work in The Netherlands on vegetation dynamics in coastal and inland sand dunes has primarily focused on nutrient availability and soil formation. While sand dune systems are nutrient poor habitats, another vital resource for plants may limit growth: soil moisture. Although the climate of the Netherlands is regarded temperate, soil moisture can be a limiting factor in dune systems due to the poor water holding capacity of sandy soils. Field observations of the vegetation coverage on north and south facing slopes show a close relationship between climatological factors and vegetation. This close relationship was already noticed by numerous authors (De Jong and Klinkhamer, 1988; Marshall, 1968; Oosting and Billings, 1942; Stoutjesdijk, 1959; Stoutjesdijk, 1977; Stoutjesdijk and Barkman, 1992) but none of them was able to transfer climatological forcings to meaningful quantitative measures which correlate well with the recorded vegetation coverage. The knowledge developed in agro-hydrology might form an outcome for quantitatively describing the relationship between vegetation and climatic forcings in natural systems. Drought stress expressed by the soil moisture deficit might pose a great measure to derive a direct relationship between vegetation and climate. Furthermore the development of several soil-vegetation-atmosphere transfer (SVAT) schemes to simulate crop growth (Arora, 2002), could be of great use in this study. These models explicitly simulate the interaction between plant physiological properties and the energy and water balance. This research combines the knowledge from ecology and hydrology to get a better understanding of the relationship between vegetation and soil moisture conditions in coastal and inland sand dunes. This knowledge will be used to integrate vegetation dynamics in hydrological models to be able to simulate vegetation growth under changing climatic conditions and to get a reliable estimate of the future evapotranspiration and groundwater recharge. Simply coupling a vegetation growth model with a hydrological model is not the purpose of this study. Most SVAT schemes were not developed to simulate a vegetation dieback caused by drought and poorly represent the effect of the vegetation structure on hydrological processes. The first priority of this study is to get an understanding of how the water balance will be affected by changes in the vegetation structure. When the vegetation coverage decreases due to drought, gaps in the canopy will allow more sunlight to reach the ground surface which enables mosses and lichens to invade. Great uncertainty about the functional role of mosses and lichens commits us to go in detail about their effects on the soil water balance. Do mosses and lichens deprive the soil of water during rain showers of short duration or does a moss or lichen layer prevent rapid loss of water? Because mosses and lichens are desiccation tolerant, their role in a drier climate may become more prominent. Another uncertainty is the application of well established one dimensional (agro)hydrological models in sloping terrain with an open vegetation coverage. The homogeneous vegetation coverage of agricultural fields is not comparable with the heterogeneous vegetation coverage of dune systems. The heterogeneous surface boundary conditions in dune systems together with a sloping terrain might induce significant lateral unsaturated flow which affects soil moisture contents and drought stress. After the effects of mosses, lichens and the vegetation structure on the water balance are clear, this study will focus on the development of vegetation growth models which are able to simulate a vegetation dieback caused by drought.


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4

The role of mosses and lichens in the soil-water balance

4.1 Background and problem definition The water exchange of mosses with the atmosphere is fundamentally different than that of vascular plants. Mosses do not have roots that extract water from the soil. Instead they take up water directly through their plant tissue. Furthermore they lack leaf stomata and are able to fully desiccate and evaporate water as long as external or internal water is available. Mosses have two paths of water movement: internal through a central cylinder (endohydric, represented by the Polytrichaceae and Mniaceae family) and external along the surface of their plant tissue (ectohydric) (almost all mosses, see Glime (2007)). External water is held between shoots and leaves by capillary forces (Figure II.9). As long as any extracellular water remains in contact with the moss, cells remain fully turgid. When the evaporative demand is high external water quickly evaporates and the moss becomes in a desiccated state. During this dry period one of the most remarkable features of mosses becomes apparent: their ability to dry up without dying. Some mosses are tolerant of water contents below 10 % dry weight and quickly revive on rehydration. A typical moss cell exists for most of the time in one or the other of two stable states, either fully turgid or desiccated, with relatively brief transitions in between (Proctor et al., 2007). The speed at which moss cells lose their cellular water depends on the osmotic potential of the cells and the water potential of the air. As the osmotic potential of moss cells is seldom more negative than -2 MPa (Proctor, 2000) moss cells can only remain full turgid when the air is at a high relative humidity and water potential (Table 1).

Table 1. Air water potential at high relative humidity at an air temperature of 20 ºC. Relative humidity (%)

air water potential (MPa)

100

0

99

-1.36

98

-2.73

95

-6.92


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Figure II.9. Capillary water (arrow) held among the leaves of Bryum. Photo by John Hribljan. Since mosses cannot control their water use by stomata, the rate of evaporation is more or less controlled by the morphology of the moss species. The morphology can be expressed by a surface roughness, which affects air turbulence and the effective area for evaporation. Nakatsubo (1994) found that the evaporation rate of tall turfs and smooth mats of a mesophytic alpine moss species tended to increase with dry weight per basal area (Wa) while the evaporation rate of a xerophytic species with a growth form of tight cushions and dense moss mats remained constant with increasing Wa. Large shoot densities with short shoots reduce the surface area that is in direct contact with solar radiation and enhances the entrapment of moist air between moss shoots. This explains the lower evaporation rate of mosses with a high moss mat density and exemplifies the morphological control on evaporation. Water use mechanisms of mosses and their ability to fully desiccate during drought enables mosses to occupy certain niches in ecological systems. Their ability to take up water through their plant tissue implies that mosses are able to use dew or interception water that would never become available for vascular plants. Several studies demonstrated that mosses and lichens play an important role in the water balance as they may contribute significantly to the total amount of evaporation (Beringer et al., 2001; Bond-Lamberty et al., 2010; Heijmans et al., 2004; Moul and Buell, 1955; Suzuki et al., 2007). These studies are mainly focused on boreal forest understory and arctic moss species. Xerophytic species in temperate zones received less attention, especially the interaction between mosses and the mineral soil. This is expressed by the following quote of Glime (2007) which sums up questions still to answer in bryophyte ecology: “What quantities do the various mosses move from moss mat to atmosphere and how much is moved from the soil to the moss mat? Do the mosses provide an overall net gain to the soil by preventing rapid loss to the atmosphere following rainfall? Do they retain water that would otherwise be lost as runoff, contributing it slowly to the soil and plant roots beneath? Or is their major contribution that of depriving the soil of water during showers of short duration? There is no mass balance equation that includes the role of bryophytes in the overall water budget in any ecosystem.” The previous questions are especially important in water limited ecosystems where mosses may promote or hamper growth of vascular plants by affecting the soil-water balance in the root zone. The functional


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role off mosses is especially important in light of climate change where increased summer drought may lead to an increase in the coverage off desiccation tolerant mosses. This hypothesis is based on field observations in coastal and inland sand dunes of The Netherlands where the cover fraction of mosses and barren soil is larger on south facing slopes and vascular plants primarily cover north facing slopes. More knowledge about the effects of mosses and lichens on the soil water balance is needed to make a reliable estimate of the effects of climate change on the cover fraction of plant functional types and its feedback on evapotranspiration and groundwater recharge in water limited ecosystems. 4.2 Research objectives The aim of this study is to quantify the effects of mosses and lichens on the soil-water balance in water limited ecosystems. The main interest lies in the water interaction of the moss mat with the underlying mineral soil. We would like to know whether the moss mat receives water from the soil beneath and how the total evaporation amount of a moss mat compares to the evaporation amount of a barren soil. This would give insight into the functional role of mosses and would show whether or not vascular plants receive less water when the surrounding soil is covered with mosses. This study aims to answer the following research questions: 

Is there a flux of water form the soil towards the moss mat during drying?



Is there a relationship between the specific surface area of mosses and the water storage capacity?



Can the moss carpet be simulated as an interception reservoir or must the moss carpet be modelled using a different concept (e.g. as a soil layer) because it exerts a capillary force on soil water?

4.3 Methods Lab experiments will be performed to measure the effects of mosses and lichens on the soil-water balance. These experiments will be carried out for the most dominant moss and lichen species with a different morphological structure found in coastal and inland sand dunes of the Netherlands (Figure II.13). Mosses and lichens have different spaces to store water. The total amount of water stored externally by a moss or lichen layer after a rain event is partly stored in spaces which do not participate in unsaturated flow. This immobile volume of water can be considered interception water. The remaining volume of external water has the potential to interact with the mineral soil (referred to as pore water in the following text). Internal water is stored as apoplast water (held in cell-wall capillary spaces) and osmotic (symplast) water (Proctor et al., 1998). In the first lab experiment the volume of external water will be determined and the drying characteristic curve (a relation between suction (pF) and water content (θ)). In the second and third experiment the speed at which different storage terms will empty by evaporation will be determined. For this study 10 samples per moss or lichen species will be taken from the field including a layer of mineral soil (1-5 cm). These samples will be used multiple times during the experiments. Experiment 1. External water storage and drying characteristic curve In this experiment the volume of external water will be determined and separated in mobile (pore water) and immobile water (interception water). At the end of this experiment a pF (θ) drying curve of the whole sample (moss including sand) will be derived. Figure II.10 shows a schematic overview of the different measurements which will be performed during this experiment. The following numbered section refers to the different numbers in Figure II.10. After every step the weight of the whole sample will be determined to measure changes in water content. 1.

All the external water will be extracted from the moss or lichen layer by evaporation and a negative pressure head at the base of the sample.


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2.

In the next step the pore volume of the moss or lichen layer will be determined. When a water table is situated at the base of a moss layer about all pores which participate in unsaturated flow will fill with water due to capillary rise. Most xerophytic moss or lichen species have a thickness of 5 cm or less. This thickness is probably in range of the capillary fringe. The change in weight after step 2 minus the saturated weight of the underlying soil layer is the weight of water stored in the moss layer. The weight of the saturated underlying soil layer will be determined at the end of all experiments.

3.

In this step the volume of the interception store will be determined. This will be done by saturating the moss layer with a sprinkler from above while the underlying soil is still saturated. The change in weight between step 2 and 3 is the weight of water stored as interception water. During this experiment care will be taken to prevent ponding at the soil surface which would lead to overestimation of the interception volume. Whenever ponding occurs this water will be removed with a pipette.

4.

In step 4 the drying curve of the whole sample will be determined with a ceramic plate. This drying curve can be used to derive the drying curve of the moss or lichen layer. This will be done by subtracting the weight of the soil and its water content at different suction levels from the weight of the whole sample. To perform this correction the drying curve of the soil should be known. This drying curve will be derived in experiment 4.

1

2

3

4 -hx7

-h

Figure II.10. Schematic overview of the first experiment. Green is the moss or lichen layer and yellow the underlying soil. Blue is a ceramic plate. Experiment 2. Evaporation of a moss or lichen layer including mineral soil This experiment will be used to measure the evaporation rate of a moss or lichen layer attached to a soil layer. The evaporation rate will be measured at three different levels of intensity and at three different levels of soil suction at the base of the soil layer. The same samples of experiment 1 will be used. When the evaporation rate is independent on the soil suction there is probably a minor interaction with the mineral soil. The outcome of these experiments will be compared to the outcome of experiment 3. During these experiments the relative humidity, temperature, radiation, moss surface temperature and soil temperature will be measured. Additionally the evaporation rate of open water will be determined by measuring changes in weight of a pan filled with water.

5º C

1

-h x 3

15º C

2

1

-h x 3

25º C

2

1

-h x 3

2

Figure II.11. Schematic overview of the second experiment. Green is the moss or lichen layer and yellow the underlying soil. Blue is a ceramic plate.


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Experiment 3. Evaporation of a moss or lichen layer This experiment will be used to measure the evaporation rate of a moss or lichen layer. This experiment can only be carried out successfully for moss or lichen layers which can be separated from the soil without damaging the moss or lichen structure. The moss or lichen layers will be saturated until field capacity (until the moss or lichen layer stops dripping water). The moss layers will be placed in a bucket which is as high as the moss or lichen layer to prevent evaporation to take place from the sides. The evaporation rate will be measured at the same three lab climatic conditions as in experiment 2. The same moss layer will be used at different lab climatic conditions, which means that the experiments must stop when external water is removed to prevent damaging the moss structure by desiccation. At the end of these experiments a subsample of every moss layer will be taken to place in a known volume of water and measure the moss volume of the subsample by the change in water level. Moss or lichen material which is not removed by the subsample will be left to desiccate to measure the volume of internal water. At the end of the experiment all moss material will be oven dried at 70 º C to remove all the remaining water and measure the dry weight of the moss and lichen samples. The volume of the total moss layer can be derived by multiplying the volume per dry weight of the subsample by the dry weight of the whole sample.

1

2

3

4

Figure II.12. Schematic overview of the second experiment. Green is the moss or lichen layer and yellow the underlying soil. Blue is a ceramic plate.

Experiment 4. Soil characteristics The drying curve of the soil layers will be measured at the end of the experiments. These curves are needed to correct the drying curve of the whole sample including the moss or lichen layer, derived during the first experiment. The drying curve will be determined with a ceramic plate for a total of 50 soil layers. The organic matter content will be determined after derivation of the drying curve by weighing and oven drying, at 105 ºC.

1

2 -hx7

Modelling concept The results from the lab experiments will be used to properly schematize a moss or lichen layer for simulations of evaporation with a model for soil water flow, such as SWAP. The moss layer will be schematized as a reservoir with three different storage terms, interception water, pore water and internal


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water. The interception storage will fill up first during a rain event. Secondly the pore volume will fill. External water will enter the internal storage whenever the moss layer is not at full turgor. The modelling concept which will be used to simulate evaporation (i.e. emptying of the storage terms) will be dependent on the outcome of the experiments. Basically there are two options: liquid flow of water from the soil into moss or lichen layer is impossible which means that evaporation will be halted when different storage terms in the moss layer are empty or there is a flow of water into the moss layer which means that evaporation from the moss mat can continue during drying.

Figure II.13. Mosses which will be studied: A Polytrichum piliferum (ruig haarmos), B Syntrichia ruralis (Duinsterretje), C Campylopus introflexus (Grijs kronkelsteeltje), D Hypnum jutlandicum (Heide klauwtjesmos), E Cladonia portentosa (Open rendiermos)

4.4 Expected results This research will rule out if mosses exert a capillary force on soil water and will lead to a relationship between moss volume per basal area and the interception capacity. Soil characteristic curves will be derived for mosses which are able to extract soil water from the mineral soil. This knowledge will be implemented into a modelling concept. This model will be used to simulate the effects of climate change


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on the soil-water balance of moss-covered soils, which will lead to a relationship between precipitation pattern and functional role of mosses. 4.5 Timeline This study will be performed at the start of 2011. Table II.2 shows the amount of time needed to perform this research.

Table II.2.Timeline to perform the research about the effects of mosses on the soil-water balance. weeks

1

2

3

experimental setup

X

x

x

collecting samples

4

5

x

x

performing measurements

6

7

8

9

10

11

12

x

x

x

x

x

x

x

statistical analyses

13

14

15

x

x

x

swap simulations

writing an article

18

19

20

21

22

23

24

25

26

27

28

X

x

x

X

x

x

X

x

x

x

x

16

17

x

x


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5

Modelling plant available water for dune vegetation: the effects of vegetation structure and topography

5.1 Background and problem definition Dune vegetation is characterized by its patchy open vegetation structure. Sharp gradients in vegetation coverage exist between vegetated and barren surfaces (Figure II.14). This vegetation structure leads to a heterogeneous pattern of evapotranspiration characteristics and a large spatial variation in soil temperature (Figure II.15). Proper understanding of flow processes in the root zone and its surrounding area is required to asses which models can be used to simulate soil moisture dynamics and its effect on vegetation stress. A common simplification used in ecohydrological studies is to neglect lateral unsaturated flow processes. This simplification enables the use of one dimensional models, which reduces calculation times and is often favoured because of its simplicity. Assuming water to flow only in the vertical direction implies a homogeneous water content in the horizontal direction. Consequently, an instantaneous flow of water in the horizontal direction is needed to meet this constraint whenever lateral moisture gradients develop in the field situation. So, while lateral flow is not explicitly simulated in one dimensional models it is most often exaggerated implicitly by assuming an evenly distributed soil moisture content in the horizontal direction. For a homogeneous vegetation coverage this assumption may be appropriate but for a partly vegetated surface the heterogeneity in surface boundary conditions could result in lateral head gradients and interacting processes between vegetated areas and barren surfaces. The significance of these processes depends on the spatial scale at which flow is considered. One dimensional models might be sufficient when modelling at the scale of a point, but when a column is considered covered with an open vegetation cover erroneous model results could arise when lateral unsaturated flow is not explicitly simulated. The difference between a 1D and 2D schematization of the unsaturated zone for a partly vegetated column is illustrated in Figure II.16.

Figure II.14. Patchy dune vegetation (Anholt, Denmark, Photo L.B. Sparrius)


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Figure II.15. Surface temperatures (ºC) along a transect perpendicular to a woodland edge with adjoining heathland and juniper scrub in The Netherlands. Soil temperature at 4 cm and 9 cm depth. Air temperature at 1m height is 11.8 ºC. Figures indicate the intensity of solar radiation (W/m2) on three planes with different inclinations. A clear sky on 3 March 1976 at midday (After Stoutjesdijk (1977) vide Stoutjesdijk and Barkman (1992))

Figure II.16. The difference between a one dimensional schematization (left figure) and a two dimensional schematization (right figure) (Source: Witte et al. (2008a)). Besides a patchy vegetation coverage dunes are characterized by a gentle sloping topography. The shape and angle of hillslopes may affect the distribution of water during and after a rain event. Sinai and Dirksen (2006) proved that lateral unsaturated flow occurs on hillslopes as a result of changing surface boundary conditions. They observed an uphill (uphill of the vertical) lateral flow of water during the start of a rain event and a downhill lateral flow component when the precipitation intensity decreased or during drainage. A description of unsaturated flow processes in sandy hillslopes is given by Jackson (1992). He showed that homogeneous isotropic soils will not exhibit lateral downslope flow during wetting, as described by Philip (1991), but is primarily a drainage phenomena. After a rain event the


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supply of vertical infiltrating recharge water near the surface is soon exhausted while soils further into the slope at the same elevation still receive water. Consequently lateral moisture and head gradients develop. So, after rainfall stops, head gradients shift from a vertical to a downslope direction. Whether shallow lateral flow becomes a significant redistribution mechanism for water in the root zone depends on the rate at which the soil conductivity decreases during drying. Anisotropy caused by the horizontal layering of aeolian deposits might further promote lateral flow. Above mentioned processes affect the volume of water available for vegetation and will subsequently affect vegetation stress. When lateral unsaturated flow is a significant redistribution mechanism for water in the shallow unsaturated zone this would imply that soil water outside the range of a root profile might contribute to the plant available water and barren surfaces might function as a source zone of soil moisture. Consequently, vegetation nearest to a barren surface will probably benefit the most from subsurface lateral flow. When this hypothesis is correct more vigorous vegetation would be present downhill of a barren surface. Marshall (1965) observed this pattern (Figure II.17) but related it to more sedimentation of sand in the upperslope area which is in favour of Corynephorus canescens. Simultaneously Marshall (1965) showed that drought would hamper growth of Corynephorus canescens. When the above mentioned mechanisms for water redistribution along a hillslope were taken into account, the author might have drawn a different conclusion. When barren surfaces contribute to the available water for neighbouring plants, a reduction in vegetation coverage would lead to an increased source zone of soil moisture for plants. This means that reducing the vegetation coverage as a response to drought does not only lead to a reduced water consumption but also enlarges the source zone of water for the remaining vegetation. In this way reducing the vegetation coverage as a response to drought may be interpreted as an adaption strategy to drier conditions. A trade off exist between reducing the coverage and creating ecological niches for more drought adapted species. Mosses and lichens, for instance, can fill up gaps between grass tussocks which in turn might reduce water availability for rooting plants. Until now it is unclear to which extent lateral flow processes in the unsaturated zone affect vegetation stress and to which extend flow processes may be simplified for soils covered with patchy vegetation. To be able to relate soil moisture conditions to cover fractions of plant functional types it is essential to know which flow processes will affect vegetation stress.

Figure II.17. Section of a blowout showing the size difference of plants along the slope. (source: Marshall (1965))


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5.2 Research objectives The aim of this study is to asses to which extend lateral flow processes affect plant available water and drought stress. This knowledge can be used to get a better relationship between soil moisture conditions and the vegetation distribution in water limited ecosystems. This study aims to give answer to the following research questions: 

How is the source zone of soil moisture for plants affected by lateral flow outside the range of the root profile?



How is the soil moisture content in the root zone affected by the hillslope topography?

5.3 Methods In this study a 3D model will be used to simulate the soil moisture content in the root zone of patchy vegetation. At first the benefit of a 3D model will be investigated by showing the difference between a 1D and 3D model for patchy vegetation on flat and sloping terrain. This will be done by simulating the transpiration of grass tussocks in a 1D and 3D model (e.g. HYDRUS 3D). A couple of simulations will be performed with varying distance between grass tussocks. For these simulations the soil volume acting as a source zone of water for the individual grass tussocks will be compared between the 1D and 3D simulations. Basically, differences between a 1D and 3D model with patchy vegetation will arise for two reasons. Either lateral flow is not significant, which leads to moist barren areas in comparison with vegetated patches, and thus to concentrated groundwater recharge where vegetation is absent, or lateral flow is significant which leads to a larger source zone (i.e. barren soil) of water for vegetation in the 3D model than prescribed by the root profile in a 1D model. This first numerical analysis forms the basis for continuing in a multidimensional environment. The next step is to show the consequences of lateral flow processes for the state and distribution of vegetation in dune systems. The vegetation distribution of several transects over dunes will be recorded (as shown in Figure II.17). For these transects a 2D model will be used to simulate plant available water. For these simulations a relationship between the cover percentage of plant functional types and plant available water will be developed, which might give an indication of water controls on the vegetation structure. 5.4 Expected results In this study model simulations will provide insight into flow processes which affect the available water for plants. The implications of these flow processes will be shown for several transects by relating vegetation characteristics to soil moisture conditions. The field data and the modelling studies could be published in one article.


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5.5

Timeline

weeks

1

2

getting used to the Hydrus Code

x

x

modify the input of surface boundary conditions

3

4

5

6

X

x

x

x

7

simulate the effects of lateral flow 1D 3D

8

9

10

11

12

x

x

x

x

x

14

15

x

x

x

x

Field work, recording transects Simulate transects (Hydrus 3D)

writing an article

13

16

17

18

19

20

21

22

23

24

25

x

x

x

x

x

x

x

x

x

x


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6

A conceptual model to estimate the vegetation coverage of dry grassland vegetation of European sandy soils under changing climatic conditions

6.1 Background and problem definition Vegetation characteristics will adjust to future weather conditions. The potential of climate change to affect vegetation characteristics is especially large in water limited ecosystems where soil moisture availability is a constraining factor for plant survival. A strong relationship between the vegetation coverage and microclimate is observed in coastal and inland sand dunes. On south facing slopes in coastal dunes the coverage of barren soil and desiccation tolerant mosses and lichens is much larger than on north facing slopes (Figure II.18). This close relationship between slope exposition and vegetation coverage is quantified in Figure II.19 for a coastal dune area of The Netherlands. These observations show that drought, as experienced on south facing slopes, may lead to a lower coverage of rooting species. In an exploratory study Witte et al. (2008a) showed that increased summer drought might lead to a dieback of vascular plants and an increase in the cover fraction of non-rooting species (mosses and lichens) and barren surfaces in coastal dunes of The Netherlands. Because the evapotranspiration of mosses, lichens and barren soil is much less than of vascular plants, this vegetation response leads to a lower evapotranspiration and an increase in groundwater recharge. Therefore the response of vegetation to climate change should be included in simulations of the future groundwater recharge. Modelling vegetation dynamics can be achieved on different spatial scales and levels of complexity. In the past decades several soil-vegetation-atmosphere transfer (SVAT) schemes have been developed which are able to simulate vegetation growth (Arora, 2002). These models explicitly simulate the interaction between plant physiological properties and the energy and water balance. While the growth of vegetation is reasonably well included in these process-based models, the dieback of vegetation remains a difficult process to simulate as lethal levels of stress are fairly unknown. Furthermore, the survival of plants is dependent on successful reproduction and the ability of a plant to adapt to changing meteorological conditions. Current knowledge is insufficient to include these processes in vegetation growth models. The difficulty to model vegetation growth as physically based as possible asks for a different approach. In this study we will develop a conceptual model and combine it with empirical relationships to estimate the coverage of vegetation under changing climatic conditions.


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Figure II.18. The vegetation coverage on north facing slopes (left) and south facing slopes (right) in a dune area in The Netherlands.

Figure II.19. Relationship between vegetation coverage and slope exposition based on 324 vegetation plots (all records yellow, 158 short vegetation plots orange) from the Amsterdam Water Supply Dunes (source: Witte et al. (2008a)).

6.2 Research objectives The aim of this study is to develop a conceptual model able to estimate the coverage of tussock forming grass vegetation under changing climatic conditions. This model can be used in simulations of the future groundwater recharge as vegetation characteristics have a major effect on evapotranspiration and subsequently on groundwater recharge. 6.3 Methods We pursue an optimization technique which is based on two trivial assumptions; vegetation will die at a certain level of drought stress and vegetation will try to use all the available water. In this study we define the coverage to be dependent on the distance between grass tussocks and assume grass tussocks to have a stable allometry throughout the year. We will perform hypothetical simulations for 238 relevés


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spread from The Netherlands till Slovakia to test whether the vegetation distribution of the recorded relevés uses optimally the available water and whether the vegetation distribution can be predicted based on soil and climate data. This will be done by virtually decreasing the vegetation coverage of the recorded relevés by increasing the distance between grass tussocks (hereafter named individuals) from 100% till 5% in a multidimensional unsaturated zone model (e.g. HYDRUS 3D). With an increasing percentage of barren surfaces actual drought stress and transpiration per individual will become constant as individuals won’t interfere with each other at a large mutual distance. At this point it is unlikely that individuals in the field are at a larger mutual distance, as this would not agree with the assumption that ecosystems tend to optimally use the available water. At a small mutual distance drought stress per individual will increase as source areas for soil water will overlap. The optimal distance between individuals would range between the point at which the individuals won’t interfere and the maximum allowable drought stress (Figure II.20). Prior to this optimization a decision scheme will be used to determine whether a moss or lichen layer is present. Mosses and lichens will die when frost comes in after a wet period. Whether a moss or lichen layer is present will be based on the temperature and precipitation pattern. This conceptual model will be validated against the recorded vegetation coverage of the 238 relevés.

Figure II.20. Hypothetical effect of vegetation structure (in terms of distance between tussocks) on drought stress (ζ) and transpiration (Et) for individual grass tussocks for a relatively wet (a) and dry (b) site.


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7

The response of vegetation to climate change and its effect on evapotranspiration and groundwater recharge in coastal and inland sand dunes of The Netherlands

7.1 Background and problem definition Natural succession causes barren surfaces to become vegetated. This colonisation process follows different succession stages (paragraph 2.2). The micro climate has a profound effect on the speed of succession. In Denmark (Molslaboratoriet at Femmøller) north slopes were rapidly covered with well developed heath vegetation after 12 years from cultivation abandonment, while south slopes were still covered with a semi permanent open herb community with lichen and Corynephorus canescens (Marshall, 1968). Most research on vegetation succession in coastal and inland sand dunes of Western Europe has focussed on the effects of nutrients and soil formation while soil moisture conditions received less attention. In this study we focus on the effects of water availability on the succession from barren soil to heath vegetation. In this study the modelling concept of the previous study will be expanded to include changes in soil physical properties, year by year simulation of the vegetation coverage and simulation of heath vegetation. This succession model can be used to asses how climate change will affect the vegetation coverage and subsequently evapotranspiration and groundwater recharge. 7.2 Research objectives The aim of this study is to develop a vegetation succession model for coastal and inland sand dunes which can be used to asses how the vegetation coverage will alter as a result of changing weather conditions. This model can be used to asses how the water balance will be affected by climate change through changes in vegetation characteristics. 7.3 Methods In this study a succession model will be developed. Vegetation will be categorized in plant functional types such as bare soil, mosses and lichens, grasses and shrubs. The conceptual model of the previous study (chapter 4) will be used to estimate the abundance of plant functional types. The abundance of a plant functional type remains in a stable state from the start of the growing season until the end of summer after which a new optimal vegetation distribution will be estimated based on the stress level experienced in the previous summer. The newly estimated vegetation coverage must be interpreted as a measure of the abundance of a certain vegetation type, not as the amount of biomass. The growth of vegetation during the year can be modelled with a crop growth model (e.g. WOFOST). The build up of organic matter has a large effect on the water holding capacity of sandy soils (Figure II.21). This effect of soil formation can be included in the succession model by adding different components of the CENTURY model. The vegetation growth model used in this study can be separated into a plant functional type estimator and a growth model, where the plant functional type estimator runs on a yearly timescale and the growth model on a daily timescale.


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Figure II.21. The relationship between soil organic matter content and the water holding capacity of drift sand (source: Schelling (1955) vide Koster (1978))


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8

Timetable

This research will be performed from the beginning of February 2011 until July 2014 (41 months). The first two topics will start in February 2011. The study about mosses and lichens will be finished at the end of September 2011. In the meanwhile the study about lateral unsaturated flow will be set up and finished in April 2012. From May 2012 more than two years remain to develop a conceptual model and a succession model for coastal and inland sand dunes. The tables below shows the time needed in months to finish this research. Mosses and lichens setting up 1D vs. 3D 1D vs. 3D Conceptual model Succession model Unforeseen Thesis

2011

1

2

3

4

5

6

7

8

9

10

11

12

2012

1

2

3

4

5

6

7

8

9

10

11

12

2013

1

2

3

4

5

6

7

8

9

10

11

12

2014

1

2

3

4

5

6


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References Allen, R.G., Pereira, L.S., Raes, D. and Smith, M., 1998. Crop evapotranspiration - Guidelines for computing crop water requirements FAO Irrigation and drainage paper, 56. FAO - Food and Agriculture Organization of the United Nations, Rome. Allen, R.G., Pereira, L.S., Smith, M., Raes, D. and Wright, J.L., 2005. FAO-56 Dual crop coefficient method for estimating evaporation from soil and application extensions. Journal of Irrigation and Drainage Engineering, 1(2): 2-13. Anonymus, 2009. Wegen naar een klimaatbestendig Nederland., Planbureau voor de Leefomgeving. Anonymus, 2010. Climate Adaptation for Rural arEas (CARE). Final proposal. Arora, V.K., 2002. Modeling vegetation as a dynamic component in soil-vegetation-atmosphere transfer schemes and hydrological models. Reviews of Geophysics, 40(2): 3-1. Badano, E.I., Cavieres, L.A., Molina-Montenegro, M.A. and Quiroz, C.L., 2005. Slope aspect influences plant association patterns in the Mediterranean matorral of central Chile. Journal of Arid Environments, 62(1): 93-108. Baird, A.J., 1999. Modelling. In: A.J. Baird and R.L. Wilby (Editors), Eco-hydrology. Plants and water in terrestrial and aquatic environments. Routlegde, London & New York, pp. 300-345. Bakker, T. et al., 2003. Preadvies Stuifzanden. LNV Rapport nr. 2003/228-O, Wageningen. Bates, B.C., Kundzewicz, Z.W., Wu, S. and Palutikof, J.P. (Editors), 2008. Climate change and water. Technical paper of the intergovernmental panel on climate change. IPCC Secretariat, Geneva, 210 pp. Bennie, J., Huntley, B., Wiltshire, A., Hill, M.O. and Baxter, R., 2008. Slope, aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland. Ecological Modelling, 216(1): 47-59. Berendsen, H.J.A., 2005. Landschappelijk Nederland. De fysisch-geografische regio's. Assen: Van Gorcum: 247. Beringer, J., Lynch, A.H., Chapin, F.S., III, Mack, M. and Bonan, G.B., 2001. The representation of arctic soils in the land surface model: The importance of mosses. Journal of Climate, 14(15): 3324-3335. Bleeker, A. and Erisman, J.W., 1996. Depositie van verzurende componenten in Nederland in de periode 1980-1995, RIVM Bond-Lamberty, B., Gower, S.T., Amiro, B. and Ewers, B.E., 2010. Measurement and modelling of bryophyte evaporation in a boreal forest chronosequence. Ecohydrology. Broza, M., Poliakov, D., Gruia, M. and Bretfeld, G., 2004. Soil collembolan communities on north- and south-facing slopes of an eastern Mediterranean valley. Pedobiologia, 48(5-6): 537-543. Ciais, P. et al., 2005. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature, 437(7058): 529-533. Corre, J.-J., 1991. The sand dunes and their vegetation along the Mediterranean coast of France. Their likely response to climatic change. Landscape Ecology, 6(1): 65-75. Curr, R., Koh, A., Edwards, E., Williams, A. and Davies, P., 2000. Assessing anthropogenic impact on Mediterranean sand dunes from aerial digital photography. Journal of Coastal Conservation, 6(1): 15-22. Daniëls, F.J.A., Minarski, A. and Lepping, O., 2008. Dominance pattern changes of a lichen-rich corynephorus grassland in the inland of The Netherlands. Annali di Botanica n.s., VIII: 9-19. De Boer, H.J. et al., 2011. Climate forcing due to optimization of maximal leaf conductance in subtropical vegetation under rising CO2. PNAS. De Bruin, H.A.R., 1987. From Penman to Makkink. In: C. Hooghart (Editor), Evaporation and weather. Proceedings and Information. Comm. Hydrological Research TNO, The Hague, pp. 5-32. De Jong, T.J. and Klinkhamer, P.G., 1988. Seedling establishment of the biennials Cirsium vulgare and Cynoglossum officinale in a sand-dune area: the importance of water for differential survival and growth. Journal of Ecology, 76(2): 393-402. Dekker, L.W., 1998. Moisture variablility resulting from water repellency in Dutch soils, Wageningen Agricultural University, The Netherlands, 240 pp.


- 65 -

May 2011

Dekker, L.W., Doerr, S.H., Oostindie, K., Ziogas, A.K. and Ritsema, C.J., 2001. Water repellency and critical soil water content in a dune sand. Soil Science Society of America Journal, 65(6): 16671674. Dekker, L.W., Ritsema, C.J. and Oostindie, K., 2000. Extent and significance of water repellency in dunes along the Dutch coast. Journal of Hydrology, 231-232: 112-125. Dolman, H., Moors, E., Elbers, J., Snijders, W. and Hamaker, P., 2000. Het waterverbruik van bossen in Nederland., Alterra, Wageningen. Droogers, P., 2000. Estimating actual evapotranspiration using a detailed agro-hydrological model. Journal of Hydrology, 229(1-2): 50-58. Droogers, P., 2009. Verbetering bepaling actuele verdamping voor het strategisch waterbeheer; Definitiestudie. STOWA 2009-11, STOWA, Utrecht. Feddes, R.A., 1987. Crop factors in relation to Makkink reference-crop evapotranspiration. In: C. Hooghart (Editor), Evaporation and weather. Proceedings and Information. Comm. Hydrological Research TNO, The Hague, pp. 33-47. Feddes, R.A., Kowalik, P.J. and Zaradny, H., 1978. Simulation of field water use and crop yield. Simulation Monographs. Pudoc, Wageningen, 189 pp. Gedney, N. et al., 2006. Detection of a direct carbon dioxide effect in continental river runoff records. Nature, 439(7078): 835-838. Glime, J.M., 2007. Bryophyte Ecology, 1. Pysiological Ecology Ebook sponsored by Michigan Technological University and the International Association of Bryologists. Guisan, A. and Zimmermann, N.E., 2000. Predictive habitat distribution models in ecology. Ecological Modelling, 135: 147-186. Gutiérrez-Jurado, H.A., Vivoni, E.R.H., J.B.J. and Guan, H., 2006. Ecohydrology of root zone water fluxes and soil development in complex semiarid rangelands. Hydrological Processes, 20(15): 32893316. Harbaugh, A.W., Banta, E.R., Hill, M.C. and McDonald, M.G., 2000. MODFLOW 2000, The U.S. geological survey modular ground water model user guide to modularization concepts and the ground water flow process, US Geological Survey. Hasse, T. and Daniëls, F.J.A., 2006. Species responses to experimentally induced habitat changes in a Corynephorus grassland. Journal of Vegetation Science, 17(2): 135-146. Heidinga, A., 2006. Mens en klimaat in de droge tiende eeuw. Leidschrift, 21(1): 45-56. Heijmans, M.M.P.D., Arp, W.J. and Chapin Iii, F.S., 2004. Controls on moss evaporation in a boreal black spruce forest. Global Biogeochemical Cycles, 18(2): GB2004 1-8. Heil, G.W. and Bruggink, M., 1987. Competition for nutrients between Calluna vulgaris (L.) Hull and Molinia caerulea (L.) Moench. Oecologia, 73(1): 105-107. Hemmleb, M., Weritz, F. and Maierhofer, C., 2005. Damage detection on building surfaces with multispectral techniques, CIPA 2005 XX International Symposium, Torino, Italy. Hermans, F., Ott, J. and Van Bakel, J., 2009. Regionale hydrologische modellering ter onderbouwing van klimaateffecten. H2O, 4: 28-32. Holland, P.G. and Steyn, D.G., 1975. Vegetational Responses to Latitudinal Variations in Slope Angle and Aspect. Journal of Biogeography, 2(3): 179-183. Hu, Z.-q. et al., 2007. Estimation of Fractional Vegetation Cover Based on Digital Camera Survey Data and a Remote Sensing Model. Journal of China University of Mining and Technology, 17(1): 116120. Huisman, L., 1972. Groundwater recovery. MacMillan, London and 336 pp. Huxman, T.E. et al., 2004. Convergence across biomes to a common rain-use efficiency. Nature, 429(6992): 651-654. Jackson, C.R., 1992. Hillslope infiltration and lateral downslope unsaturated flow. Water Resources Research, 28(9): 2533-2539. Jansen, E.J. et al., 2007. Palaeoclimate. Report of the Intergovernmental Panel on Climate Change, Cambridge. Jansen, P.C. and Runhaar, J., 2005. Toetsing van het verband tussen het aandeel xerofyten en de droogtestress onder verschillende omstandigheden [Testing of the relationship between the


- 66 -

May 2011

covering of xerophytes and drought stress under different conditions]. Alterra, Wageningen, 31 pp. Jansen, P.C., Runhaar, J., Witte, J.P.M. and van Dam, J.C., 2000. Vochtindicatie van grasvegetaties in relatie tot de vochttoestand van de bodem [Moisture indication of grass vegetations in relation to the moisture conditions of the soil]. Alterra, Wageningen, 65 pp. Jarvis, A.J., Mansfield, T.A. and Davies, W.J., 1999. Stomatal behaviour, photosynthesis and transpiration under rising CO2. Plant, Cell & Environment, 22(6): 639-648. Jelgersma, S.J., de Jong, J., Zagwijn, W.H. and van Regteren Altena, J.F., 1970. The coastal dunes of the western Netherlands, geology, vegetational history and archaeology. Mededelingen Rijks Geologische Dienst, Nieuwe Series, 21: 93-167. Jongejans, E., De Kroon, H., Tuljapurkar, S. and Shea, K., 2010. Plant populations track rather than buffer climate fluctuations. Ecology Letters, 13(6): 736-743. Kamps, P., Nienhuis, P. and Witte, J.P.M., 2008. Effects of climate change on the water table in the coastal dunes of the Amsterdam Water Supply, Modflow 2008. Koster, E.A., 1978. De stuifzanden van de Veluwe: een fysisch-geografische studie. Ph.D Thesis, Universiteit van Amsterdam, 195 pp. Koster, E.A., Castel, I.I.Y. and Nap, R.L., 1993. Genesis and sedimentary structures of late Holocene aeolian drift sands in northwest Europe. The dynamics and environmental context of aeolian sedimentary systems: 247-267. Kreyling, J., 2008. Response of vegetation to extreme weather events. PhD Thesis, Universität Bayreuth, 1-182 pp. Kroes, J.G. and Van Dam, J.C., 2003. Reference Manual SWAP version 3.0.3, Alterra, Green World Research, Wageningen. Kruijt, B., Witte, J.P.M., Jacobs, C.M.J. and Kroon, T., 2008. Effects of rising atmospheric CO2 on evapotranspiration and soil moisture: A practical approach for the Netherlands. Journal of Hydrology, 349(3-4): 257-267. Kustas, W.P., Prueger, J.H., Hatfield, J.L., Ramalingam, K. and Hipps, L.E., 2000. Variability in soil heat flux from a mesquite dune site. Agricultural and Forest Meteorology, 103(3): 249-264. Kutiel, P., Lavee, H. and Ackermann, O., 1998. Spatial distribution of soil surface coverage on north and south facing hillslopes along a Mediterranean to extreme arid climatic gradient. Geomorphology, 23(2-4): 245-256. Lenderink, G. and Van Meijgaard, E., 2008. Increase in hourly precipitation extremes beyond expectations from temperature changes. Nature Geoscience, 1: 511-514. Louhaichi, M., Johnson, M.D., Woerz, A.L., Jasra, A.W. and Johnson, D.E., 2010. Digital charting technique for monitoring rangeland vegetation cover at local scale. International Journal of Agriculture & Biology, 12: 406-410. Makkink, G.F., 1957. Testing the Penman formula by means of lysimeters. Journal of the Institution of Water Engineers, 11: 277-288. Marshall, J.K., 1965. Corynephorus Canescens (L.) P. Beauv. as a Model for the Ammophila Problem. Journal of Ecology, 53(2): 447-463. Marshall, J.K., 1968. Factors Limiting the Survival of Corynephorus canescens (L.) Beauv. in Great Britain at the Northern Edge of Its Distribution. Oikos, 19(2): 206-216. Massop, H.T.L. et al., 2005. Op zoek naar de "ware" neerslag en verdamping; toetsing van de met het STONE 2.1-instrumentarium berekende verdamping aan literatuurgegevens en aan regionale waterbalansen, en de gevoeligheid van het neerslagoverschot op de uitspoeling van nutriënten, Alterra, Wageningen. Maun, M.A., 1994. Adaptations enhancing survival and establishment of seedlings on coastal dune systems. Vegetatio, 111(1): 59-70. Meehl, G.A., Stocker, T.F. and Co-authors, a., 2007. Global climate projections. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge. Metselaar, K. and de Jong van Lier, Q., 2007. The Shape of the Transpiration Reduction under Plant Water Stress. Vadose Zone J, 6: 124-139.


- 67 -

May 2011

Miller, T.E., Gornish, E.S. and Buckley, H.L., 2010. Climate and coastal dune vegetation: disturbance, recovery, and succession. Plant Ecology, 206(1): 97-104. Monteith, J.L. and Unsworth, M.H., 1990. Principles of Environmental Physics, 2nd edition. Edward Arnold, London, 291 pp. Moul, E.T. and Buell, M.F., 1955. Moss Cover and Rainfall Interception in Frequently Burned Sites in the New Jersey Pine Barrens. Bulletin of the Torrey Botanical Club, 82(3): 155-162. Nakatsubo, T., 1994. The effect of growth form on the evaporation in some subalpine mosses. Ecological Research, 9(3): 245-250. Nevo, E. et al., 1998. Edaphic interslope and valley bottom differences at "Evolution Canyon", Lower Nahal Oren, Mount Carmel, Israel. CATENA, 33(3-4): 241-254. Nijssen, M., Riksen, M.J.M., Sparrius, L. and others, a., 2010. Onderzoek naar effectgerichte maatregelen voor het herstel en beheer van stuifzanden, LNV. Nijssen, N. et al., 2011. Effectgerichte maatregelen voor het herstel en beheer van stuifzanden. OBN stuifzandonderzoek 2006-2010, Directie Kennis en Innovatie, Ministerie van Economische Zaken, Landbouw en Innovatie, Den-Haag. Oosting, H.J. and Billings, W.D., 1942. Factors Effecting Vegetational Zonation on Coastal Dunes. Ecology, 23(2): 131-142. Oostra, H.G.M., 2006. Lichen-rich coastal and inland sand dunes (Corynephorion) in the Netherlands: vegetation dynamics and nature management. PhD Thesis, Wageningen University and Research Centre, 202 pp. Park, Y.M., 1990. Effects of drought on two grass species with different distribution around coastal sanddunes. Functional Ecology, 4(6): 735-741. Philip, J.R., 1991. Hillslope infiltration: Planar Slopes. Water Resour. Res., 27(1): 109-117. Pluis, J.L.A., 1993. The role of algae in the spontaneous stabilization of blowouts. PhD Thesis, University of Amsterdam, Amsterdam. Porporato, A., Laio, F., Ridolfi, L. and Rodriguez-Iturbe, I., 2001a. Plants in water-controlled ecosystems: Active role in hydrologic processes and response to water stress III. Vegetation water stress. Advances in Water Resources, 24(7): 725-744. Porporato, A., Laio, F., Ridolfi, L. and Rodriguez-Iturbe, I., 2001b. Plants in water-controlled ecosystems: active role in hydrologic processes and response to water stress: III. Vegetation water stress. Advances in Water Resources, 24(7): 725-744. Proctor, M.C.F., 2000. The bryophyte paradox: Tolerance of desiccation, evasion of drought. Plant Ecology, 151(1): 41-49. Proctor, M.C.F., Nagy, Z., Csintalan, Z. and TakÃ¡cs, Z., 1998. Water-content components in bryophytes: Analysis of pressure-volume relationships. Journal of Experimental Botany, 49(328): 1845-1854. Proctor, M.C.F. et al., 2007. Desiccation-tolerance in bryophytes: A review. Bryologist, 110(4): 595-621. Reddy, A.R., Chaitanya, K.V. and Vivekanandan, M., 2004. Drought-induced responses of photosynthesis and antioxidant metabolism in higher plants. Journal of Plant Physiology, 161(11): 1189-1202. Ritsema, C.J., 1998. Flow and transport in water repellent sandy soils, Wageningen Agricultural University, the Netherlands, 215 pp. Ritsema, C.J. and Dekker, L.W., 1994. Soil moisture and dry bulk density patterns in bare dune sands. Journal of Hydrology, 154(1-4): 107-131. Rosenberg, N.J., Blad, B.L. and Verma, S.B., 1983. Microclimate, the biological environment; second edition. John Wiley & Sons, New York, 495 pp. Schaap, J. and Dik, P., 2007. MetsSWAP meet zich met SWAP. Simulatie van de onverzadigde zone voor regionale en nationale modellen. Stromingen, 13(3): 15-25. Schelling, J., 1955. Stuifzandgronden. Uitvoerige Verslagen van het Bosbouwproefstation T.N.O., 2(1). Schimper, A.F.W., 1903. Plant-geography upon a physiological basis. Clarendon Press, Oxford, 839 pp. Shoshany, M., 2002. Landscape fragmentation and soil cover changes on south- and north-facing slopes during ecosystems recovery: an analysis from multi-date air photographs. Geomorphology, 45(12): 3-20. Sinai, G. and Dirksen, C., 2006. Experimental evidence of lateral flow in unsaturated homogeneous isotropic sloping soil due to rainfall. Water Resources Research, 42(12).


- 68 -

May 2011

Solomon, S. et al., 2007. Technical Summary. In: S. Solomon et al. (Editors), Climate Change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Spieksma, J.F.M., Dolman, A.J. and Schouwenaars, J.M., 1997. De verdamping van natuurterreinen. Stromingen, 3(1): 5-16. Stoutjesdijk, P., 1959. Heaths and inland dunes of the Veluwe. PhD Thesis, Rijksuniversiteit Utrecht, 96 pp. Stoutjesdijk, P., 1977. On the range of micrometeorological differentiation in the vegetation. In: H. Dierschke (Editor), Vegetation und Klima. Cramer, Vaduz, pp. 21-34. Stoutjesdijk, P. and Barkman, J.J., 1992. Microclimate vegetation and fauna. Opulus Press AB, Uppsala 216 pp. Stuyfzand, P.J., 1993. Hydrochemistry and hydrology of the coastal dune are of the Western Netherlands. KIWA, afd. Onderzoek & Advies, Nieuwegein. Stuyfzand, P.J. and Rambags, F., 2011. Hydrologie en hydrochemie van de vier lysimeters te Castricum; Overzicht van resultaten met uitzicht op haalbaarheid van reanimatie van het lysimeterstation; BTO 2011.020(s), KWR Watercycle Research Institute, Nieuwegein. Suzuki, K., Kubota, J., Yabuki, H., Ohata, T. and Vuglinsky, V., 2007. Moss beneath a leafless larch canopy: Influence on water and energy balances in the southern mountainous taiga of eastern Siberia. Hydrological Processes, 21(15): 1982-1991. Tazaki, T., 1960. On the growth of pine yearlings in coastal dune regions with special reference to their drought resistance. Japenese Journal of Botany, 17: 239-277. Ten Harkel, M.J., 1992. De ecohydrologische meetopstelling: Studie naar chemische, fysische en biologische processen op een zuidhelling in de binnenduinen van Meijendel, Universiteit van Amsterdam. Ten Harkel, M.J. and Van Der Meulen, F., 1996. Impact of grazing and atmospheric nitrogen deposition on the vegetation of dry coastal dune grasslands. Journal of Vegetation Science, 7(3): 445-452. Trenberth, K.E., Dai, A., Rasmussen, R.M. and Parsons, D.B., 2003. The changing character of precipitation. Bulletin of the American Meteorological Society, 84(9): 1205-1217+1161. Van Dam, J.C., Groenendijk, P., Hendriks, R.F.A. and Kroes, J.G., 2008. Advances of modeling water flow in variably saturated soils with SWAP. Vadose Zone Journal, 7(2): 640-653. Van den Hurk, B. et al., 2006. KNMI Climate change scenarios 2006 for the Netherlands. KNMI, De Bilt, 82 pp. Van der Hoeven, P.C.T., 2010. Lysimeters Castricum; meetproject en datafiles. Van Drecht, G., 1996. User manual Onzat, input and output description, RIVM, Bilthoven. Van Oene, H., Berendse, F. and De Kovel, C.G.F., 1999. Model analysis of the effects of historic CO2 levels and nitrogen inputs on vegetation succession. Ecological Applications, 9(3): 920-935. Van Ree, M.H.M., 1993. Wandelingen door het stuifzandlandschap van de Noordwest-Veluwe. Toelichting bij de geomorfologische kaart van Leuvenhorst/Leuvenumse Bos. Vereniging Natuurmonumenten 27. van Vliet, M.T.H. and Zwolsman, J.J.G., 2008. Impact of summer droughts on the water quality of the Meuse river. Journal of Hydrology, 353(1-2): 1-17. Vellinga, P., Katsman, C.A., Sterl, A. and Beersma, J.J., 2009. Exploring high-end climate change scenarios for flood protection of the Netherlands. International Scientific Assessment carried out at the request of the Delta Committee., KNMI, De Bilt. Von Asmuth, J.R., Bierkens, M.F.P. and Maas, C., 2002. Transfer function noise modeling in continuous time using predefined impulse response functions. Water Resources Research, 38: 2301-2312. Von Asmuth, J.R., Maas, C. and Knotters, M., 2006. Menyanthes manual, version 1.6. Kiwa Water Research, Nieuwegein. Vugts, H.F., 2002. Weerzien op de Wadden. Pirola. Wegehenkel, M., 2009. Modeling of vegetation dynamics in hydrological models for the assessment of the effects of climate change on evapotranspiration and groundwater recharge. Advances in Geosciences, 21: 109-115.


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Witte, J.P.M., Bartholomeus, R.P., Cirkel, D.G. and Kamps, P.W.J.T., 2008a. Ecologische gevolgen van klimaatverandering voor de kustduinen van Nederland, KIWA Water Research, Nieuwegein. Witte, J.P.M., Bartholomeus, R.P., Cirkel, D.G. and Kamps, P.W.T.J., 2008b. Ecohydrologische gevolgen van klimaatverandering voor de kustduinen van Nederland, Kiwa rapport KWR 08.006, Nieuwegein. Witte, J.P.M., Kruijt, B., Kroon, T. and Maas, C., 2006a. Verdamping planten daalt door toename atmosferische kooldioxyde. H2O, 5: 29-31. Witte, J.P.M., Kruijt, B. and Maas, C., 2006b. The effects of rising CO2 levels on evapotranspiration, Kiwa rapport KWR 06.004, Nieuwegein. Witte, J.P.M., Runhaar, J., Van Ek, R. and Van der Hoek, D.J., 2009. Eerste landelijke schets van de ecohydrologische effecten van een warmer en grilliger klimaat. H2O, 16/17: 37-40. Yang, Z.L., Dai, Y., Dickinson, R.E. and Shuttleworth, W.J., 1999. Sensitivity of ground heat flux to vegetation cover fraction and leaf area index. J. Geophys. Res., 104(D16): 19505-19514.


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