technical report of the project: climate change and human...

Technical Report of the Project: Climate Change and Human Impacts on

the Sustainability of Groundwater Resources: Quantity and Quality Issues,

Mitigation and Adaptation Strategies in the Toledo River Basin (Brazil)

Alice Cusi, Marcello Fiorentini, Giovanni Moretti, Stefano Orlandini,

Cicero Jr. Bley, Rafael González Hernando de Aguiar, Salvatore D'Angelo

December 2012

Published in 2013 by the United Nations Educational, Scientific and Cultural Organization7, place de Fontenoy, 75352 Paris 07 SP, France © UNESCO 2013All rights reserved ISBN 978-92-3-001176-5 Published in 2013 by the United Nations Educational, Scientific and Cultural OrganizationThe designations employed and the presentation of material throughout this publication do not imply the expression of any opinion whatsoever on the part of UNESCO concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The ideas and opinions expressed in this publication are those of the authors; they are notnecessarily those of UNESCO and do not commit the Organization.Cover design and illustrations: Salvatore D’Angelo

Technical Report of the project “Climate change and human impacts on the sustainability of groundwater resources: Quantity and quality issues, mitigation and adaptation strategies in the Toledo River basin, Brazil”

Alice Cusi1, Marcello Fiorentini1, Giovanni Moretti1, Stefano Orlandini1,

Cicero Jr. Bley2, Rafael González Hernando de Aguiar2, Salvatore D'Angelo3

1Dipartimento di Ingegneria Meccanica e Civile, Università degli Studi di Modena e Reggio Emilia,

Via Vignolese 905, I-41125 Modena, Italy, Phone: +39 059 2056105, Fax: +39 059 2056126,

Mobile: +39 331 6213086, E-mail: [email protected], http://www.idrologia.unimore.it

2Itaipu Technological Park (PTI) - Hydroinformatics International Center (CIH), Avenida Tancredo

Neves, 6.731, 85856-970, Foz do Iguaçu, Paraná, Brasil, Phone: +55-45-3576-7455,

http://www.hidroinformatica.org

3UNESCO -Hydrological Programme, Division of Water Sciences, 1, rue Miollis, 75732 Paris

Cedex 15, France, Phone: +33 1 45684139, Fax: +33 1 45685811, Email: [email protected],

http://www.unesco.org

mailto:[email protected]

http://www.idrologia.unimore.it

http://www.hidroinformatica.org

mailto:[email protected]

http://www.unesco.org

ABSTRACT

A distributed physically-based hydrological model named CATHY (CATchment HYdrology) is used

to perform a detailed analysis of the Toledo River basin response to climate projections. CATHY

couples a subsurface module, described by a three-dimensional Richards equation, with a surface

module, led by a one-dimensional diffusion wave equation. Dynamical coupling is achieved by

means of a switching in boundary conditions, from a Dirichlet to a Neumann condition and vice

versa. Future climate scenarios are determined from historical time series of daily rainfall and

temperature in the study area by applying changes compatible with predictions made by the

Intergovernmental Panel on Climate Change (IPCC). A twenty-year simulation is run under four

future scenarios and the results are compared with those obtained under an unaltered scenario. It is

found that the rise or the lowering of water table level is generally not uniform across the basin,

being more significant in the uppermost areas. This suggests that measures of adaptation to climate

change effects could be practiced by selecting suitable cultures across drainage basins, especially

in the areas where the impact of climate change are most significant.

CONTENT

1. INTRODUCTION ...................................................................................................................... 1

2. CASE STUDY: THE TOLEDO RIVER CATCHMENT ........................................................... 3

3. HYDROLOGICAL MODEL ..................................................................................................... 4

3.1 THE CATHY MODEL ......................................................................................................................................... 4

3.2 DISCRETIZATION AND PARAMETRIZATION ............................................................................................. 7

3.3 INITIAL CONDITIONS AND NUMERICAL ISSUES ................................................................................... 12

3.4 SENSITIVITY ANALYSIS................................................................................................................................ 14

3.5 MODEL CALIBRATION .................................................................................................................................. 20

4. ATMOSPHERIC INPUT .......................................................................................................... 23

4.1 METEOROLOGICAL DATA............................................................................................................................ 23

4.2 FUTURE CLIMATE SCENARIOS................................................................................................................... 23

5. SIMULATION RESULTS ........................................................................................................ 25

5.1 RIVER DISCHARGE ........................................................................................................................................ 25

5.2 GROUNDWATER RECHARGE ....................................................................................................................... 29

5.3 WATER TABLE DEPTH.................................................................................................................................... 37

6. DISCUSSION ........................................................................................................................... 39

7. CONCLUSIONS ...................................................................................................................... 40

8. REFERENCES ......................................................................................................................... 41

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1. INTTRODUCTTION

Though Brrazil has pllenty of watter resourcees, they aree unevenly distributed across the country. Inn

this contexxt, groundwwater plays an impo rtant role, supplying cities, inddustries andd irrigationn

networks. HHowever, cclimate vari ability and change andd human acttivities coulld significanntly impactt

groundwatter resource s in the couuntry. Thereefore, the evvaluation off those imp acts and thee definitionn

of approprriate mitigattion and addaptation mmeasures aree required. In the casee of climatee variabilityy

and changee, the IPCC scenarios ffor temperatture for the next 20-50 years in Brrazil indicatte that theree

would be aa significan t warming aacross the ccountry. Addditionally, tthere are rissks of overeexploitationn

and contammination of groundwateer resourcess in vulnerabble agricultuural areas.

The WPA II project aaims to understand the hydrologicc relationshiips betweenn control annd responsee

variables inn groundwaater systemms under thee impact of climate chaange and huuman activ ities and too

identify miitigation andd adaptationn measures for groundwwater manaagement undder those immpacts.

In this studdy, the CATTHY (CATchment HYddrology) moodel is usedd to performm a detailed analysis off

the Toledo River basinn under pre dicted clim ate scenarioos. This worrk is part off a strong deevelopmentt

frameworkk of distribbuted hydr ological mmodels, havving the ai m to test and underrstand neww

methodoloogies for invvestigation and managgement of wwater basinss to obtain a tool for tthe forecastt

and predic tion of the hydrologic al response to the occuurring of sppecific condditions or sccenarios. Inn

view of thee magnitudee and ubiquuity of the hhydroclimattic change aand variabillity, stationaarity shouldd

no longer sserve as cenntral, defaullt assumptioon in water-rresource rissk assessmeent and plannning [MIllyy

et al., 20088], therefore it is requiired to revieew all wateer managemment policiess. Couplingg physicallyy

based distrributed hydrrological mmodels with climatic mmodels and ppredicted sccenarios is aa key focuss

to deal wiith non-stattionarity annd variabiliity. At this time as nnever, it is necessary to analyzee

watershedss through mmodels that cconsider thee main pathwways of waater throughh space and time with aa

distributedd approach. While, by one hand, tthese modells, like CATTHY, offer the chance to obtain aa

detailed ddescription of potentiaal and effefective flowws and patthways witth a physi cally-basedd

approach, oon the otherr hand theyy have manyy parameterrs to be calibbrated with in the modeel. Whereass

the amounnt of availabble data is nnever sufficciently commplete and llarge as thee model neeeds, severall

simulation s are perforrmed to sett up these pparameter aand obtain a good desscription of the basin'ss

behavior. The main limitations of succes sful hydrollogical moddeling are related to theoreticall

assumptionns, data scaarcity, inadeequate compputer capaciity, and limmitations of calibration proceduress

[Freeze, 19978]. Howeever, some iissues, e. g. computer ccapacity, haave been ressolved in reecent times..

FINAL REPORTRT: CLIMATE CHHANGE AND HUUMAN IMPACT S ON THE SUSTTAINABILITY OOF GROUNDWAATER RESOURCCES: QUANTITY ANND QUALITY ISSSUES, MITIGATATION AND ADAAPTATION STRAATEGIES IN TWWO CASE STUDIIES IN BRAZIL. 1

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Geographi c informatiion systemms (GIS), remote senssing and ggeophysical techniquess offer thee

potential too incorporaate distributted spatial ddata, thus eexploiting thhe great pottential of hydrologicah ll

models [KaKampf and BBurges, 200 7] as tools for applicattions such aas the invesstigation of hydrologicc

responses tto climate cchanges. Dyynamically coupled hy drological mmodeling off real catch ments havee

gained signnificant atteention and oone of next steps in thiis research ffield is the aapplication and testingg

of such phhysically-based modelss, like CATHHY, to real and compl ex cases off study, as ddone in thiss

work.

Figure 1: GGeographical llocation of thee Toledo Rive r catchment.

FINNAL REPORT: CLLIMATE CHANGGE AND HUMAAN IMPACTS ONN THE SUSTAINNABILITY OF GRROUNDWATERR RESOURCES: QQUANTITY AN D QUALITY ISSSUES, MITIGATTION AND ADAPPTATION STRATATEGIES IN TWOO CASE STUDIEES IN BRAZIL. 2

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2. CAASE STUDYY: THE TOOLEDO RIIVER CATTCHMENTT

The catchmment is loc ated in the district of Toledo, Paaranà, Brasiil and has an area of 111.5 km2,,

centered aat 24°44'18'''S and 53°°41'24''W (FFigure 1). The study area is loccated over the basaltss

outcrop off Serra Geraal Aquifer System (SAASG), whosse thicknesss varies froom 632 to 9920 m, andd

also underllain by the Guarani ba salt aquifer.. The storagge of grounddwater in S GAS is funndamentallyy

related to ggeological ddiscontinuitties, like fauulting and ffracturing; wwater can allso circulatee in contactt

with each flow of lavva, which iss about 25 m thick. S oil thicknesss varies fr om 0 to 3 meters; thee

types of sooil are summmarized in FFigure 2, ac cording to tthe FAO (F ood and Aggriculture OOrganizationn

of the Unitted Nationss) classificaation. Most of the basinn area is coovered by FFerralsol, w hile Nitisoll

(upland) annd Gleysol (in the vall ey) surrounnd the river bed; near thhe basin ouutlet, also Leeptosol andd

generic sannd take placce over the basalt aquiffer. The bassin has a veery high pottential for g roundwaterr

use; howevver, this areea faces a laarge hog prooduction, wwhose sewagge is used tto fertirrigatte the soils,,

with little or no treatmment. Addit ionally, the lower reacch of the Tooledo River crosses thee urban areaa

of the city of Toledo, which is exxperiencing a fast popuulation growwth. The cummulative appplication off

untreated ssewage in tthe basin sooils and thee urban spraawl could llead to an i mportant g roundwaterr

pollution iissue in thee near futurre. In this ccontext, det ailed hydroological moodeling und er differentt

climate sceenarios is aa powerful tool to evaaluate the eeffects of cllimate channge on suchh a delicatee

resource.

Figurre 2: Soil typees in the Toleddo River catchhment.


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3. HYYDROLOGGICAL MOODEL

3.1 THE CCATHY MODDEL

CATHY iis a couplled, physiccally-based, spatially distributedd model for surface--subsurfacee

simulation s [Camporeese et al., 22010]. The model is baased on thee resolutionn of a one-ddimensionall

diffusion wwave approxximation of the Saint-VVenant equaation for oveerland and cchannel rouuting nestedd

within a soolver for thee three-dimmensional eqquation for subsurface flow in varriably saturaated porouss

media. Thee routing sccheme derivves from a discretizatioon of the kiinematic waave equatioon based onn

the Muskiingum-Cungge, or mattched artifiicial disperrsivity (MAAD), methood. Surfacee runoff iss

propagatedd through a 1-D drainaage networkk of rivuletts and channnels automaatically extrracted by aa

digital elevvation moddel (DEM)--based prepprocessor aand characteerized usinng hydraulicc geometryy

scaling rellationships. The distincction betweeen overlannd and channnel flow rregimes is mmade usingg

threshold-ttype relationnships baseed on, for innstance, upsstream drainnage area crriteria. The subsurfacee

solver is baased on Ga lerkin finitee elements iin space, a wweighted finnite differennce in schemme in time,,

and lineariization via Newton orr Picard iteeration. Thee governingg equationss of the maathematicall

model, i.e. the 3-D Riichard's equuation for thhe sub-surfaace [Paniconni and Wood, 1993; Paaniconi andd

Putti, 19944] and the 11-D kinemaatic wave e quation [Orrlandini and Rosso, 19996, 1998] for surfacee

flow, are thhe followingg:

ߪ ሻ డట ሾ ∙ൌడ௧௪௪ሺ ܭ௦ܭ ܭ ሻሿ ߟ ሻሺ௦ݍ ݍ௭ߟ ψሺ (1)

(2)ሻ ,ሺሺݍ ொమడ௦మడܦൌడொడ௦డொడ௧ where

σ : generall storage ter m [1/L]: σ = Sw Ss+ ΦΦ(dSw/dψ)

Sw: water ssaturation == ϑ/ϑs [/]

ϑ: volumettric moisturee content [LL3/ L3]


t

ϑs: saturateed moisture content [LL3/ L3]

Ss: specificc storage [11/L]

Φ: porosityy ( = ϑs if noo swelling/sshrinking)

ψ: pressuree head [L]

t: time [T]]

Ks: saturateed conductiivity tensor [L/T]

Kr: relativee hydraulic conductivitty [/]

ηz: zero in x and y andd 1 in z direcction

z: vertical coordinate ++ve upwardd [L]

qs: subsurfface equation coupling term (moree generally, source/sinkk term) [L3// L3 T]

h: pondingg head (deptth of water oon surface oof each cell)) [L]

s: hillslopee/channel linnk coordinaate [L]

Q: dischargge along s [L3/T]

ck: kinemattic wave ce lerity [L/T]]

Dh: hydrauulic diffusiv ity [L2/T]

qL: surfacee equation cooupling termm (overlandd flow rate) [L3/L T]

Coupling bbetween thee two moduules is achieeved by meaans of a thrreshold-baseed boundaryy conditionn

switching that represeents the intteractions bbetween surrface and suubsurface wwaters (Figuure 3). Thee

boundary condition ffor any giveen surface node can sswitch betwween a Diriichlet cond ition and aa

Neumann condition, ddepending on the satuuration (or ppressure) state of that node. A Neeumann (orr

specified fflux) boundaary conditioon correspoonds to atmoosphere-conntrolled infiiltration or eexfiltration,,

with the fluux equal to the rainfalll or potentiaal evaporatiion rate givven by the aatmospheric input data..

When, durring prolongged or intennse periodss of rainfalll or evaporaation, the s urface nodee reaches aa

threshold llevel of satuuration or mmoisture deeficit, the booundary conndition is sswitched to a Dirichlett

(specified head) conddition, and the infiltraation or exffiltration prrocess becoomes soil liimited. Thee

switching procedure distinguishees in fact ffour possib le states foor a given ssurface nodde: ponded,,

saturated, uunsaturatedd, air-dry. AA ponded noode has a prressure headd value thatt is positivee but minorr

than the thhreshold vallue (pondingg head) thaat a surface node must attain beforre water cann be routedd

by the surfface flow mmodule. Suchh ponding hhead thresh old is an innput parameeter and it caan account,,


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for examp le, for the amount off water thatt remains trrapped in mmicrotopog raphic featuures of thee

surface. Foor instance, in the casee of rainfalll, unsaturateed surface nnodes that hhave becomme saturatedd

or ponded are assigneed a fixed h ead (Dirichhlet) boundaary conditioon, and in thhe subsequeent iterationn

or time sttep of the subsurface flow moduule the soiil-limited innfiltration oor return flflow rate iss

calculated by the codee after obta ining the prressure headd solution. IIn the case of rainfall, a saturatedd

or ponded Dirichlet suurface node is switchedd to Neumannn mode whhenever thee model-commputed fluxx

exceeds thhe input pottential rate,, a signal ffor examplee that the rrainfall ratee has fallenn below thee

infiltrationn capacity o f the soil. HHaving deteermined thee updated saaturation or pressure sttate of eachh

surface noode, and kn owing for each of theese nodes wwhether the potential aatmosphericc forcing iss

positive (rrainfall) or negative (eevaporationn) and, in tthe case of a Dirichleet boundaryy condition,,

whether thhe actual, mmodel compuuted flux reepresents innfiltration orr exfiltrationn and also iits absolutee

value relattive to the potential fllux, the inflow terms qs to be paassed to thee surface fllow routingg

module foor the nextt time stepp are estabblished. Thee boundaryy conditionn switching proceduree

partitions potential (aatmosphericc) fluxes innto actual ffluxes acrooss the landd surface ((infiltration,,

exfiltrationn as evaporaation, and eexfiltration aas return floow) and chaanges in surrface storagge (pondingg

heads) [Caamporese et al., 2010].

FFigure 3: Scheeme of surfacee-subsurface iinteraction in CCATHY modeel.


3.2 DISCRRETIZATIONN AND PARRAMETRIZZATION

The SRTMM (Shuttle Radar Toppography MMission) immages of thhe area inccluding thee basin aree

projected iin the WGSS 1984 Trannsverse Merrcator coorddinate systemm and the ddigital elevaation modell

(DEM) at a cell resollution of 1000 m × 1000 m is derivved. A sub--area contaiining the caatchment iss

retailed froom the DEMM and a rivver network is extractedd using the D8-LTD a lgorithm [OOrlandini ett

al., 2003; Orlandini aand Morettii, 2009a, 20009b], incluuded in CATTHY pre-prrocessing mmodule. Thee

method us ed here to iidentify chaannel headss is a threshhold in termms of Strahller order ω** of surfacee

flow paths [Orlandinii et al., 20100]: a surfacce flow pathh order ω* iis assigned tto each linkk between aa

source andd a junction or betweenn junctions; in the seco nd step, surrface flow ppaths havingg order lesss

than or equual to a giv en thresholdd ω*t are prruned. The rremaining ssurface floww paths are assumed too

provide thhe predictedd channel nnetwork. Chhannel ordeers ω in thhe obtainedd channel nnetwork aree

computed as ൌ ∗ െ ௧∗ . Thhe chosen ωω*t is here equal to 3.. During thhe first run of the pre-

processor, a boundaryy channel iss created byy means off a depittingg algorithmm. Then, thee catchmentt

delimitatioon applicatiion of CATTHY pre-prrocessing mmodule is rrun after chhoosing an outlet celll

within the DEM withh the aid off the surveyyed digital maps repreesenting bassin limits aand channell

network. TThe river nnetwork of the Toledoo is then exxtracted aggain by proocessing thee delimitedd

catchment (Figure 4).. The extraccted featurees are then verified byy a compari son with thhe surveyedd

maps of chhannel netwwork and conntour lines ((Figure 5).

FFigure 4: Toleedo River catcchment DEM and extractedd river networkk.


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Figure 5: TToledo River ccatchment: exttracted and suurveyed river nnetwork, compparison. sso == Strahler streaam order ω*.

Hydraulic geometry iis also giveen as an innput to the terrain anaalysis moduule and is distinct forr

channel neetwork andd hillslope areas (desscribed by rivulet floow). Some input paraameters aree

associated to a selectt the networkk and of thee hillslope: upstream ddrainage ar ea As, flowwed site of t

discharge Qf of selected frequeency (f) annd correspoonding wateer surface width W(AAs, Qf) andd

Gauckler-SStrickler (GGS) coefficcient kS(As, Qf), and spacing beetween eachh rivulet wwithin eachh

hillslope ccell of the DDEM. The other inpuut parameterrs, i.e. expoonents y’, yy’’, b’, b’’ and w, aree

instead ch aracteristicss of the ril l/stream chhannel netwwork as a wwhole and ccharacterizee the “at-a-

station” annd “downstrream” relatiionships of Leopold annd Maddocck [1953], combined too obtain thee

following eexpressionss for W(A, 11) [Orlandinni and Rossso, 1998] annd kS(A, 1) [Orlandini, 2002]:

ሺ ሻ ሺᇲᇲሻ௦ܣሺ ,ܣ,ܣ1 ሺൌൌ ሻܣ ௪⁄ ሻܣ ܣ

௪⁄ ሻܣ ܣ൫ᇲᇲᇲ൯௦ ௦ (3)

ሺ ሻ ሺᇲᇲ௬ሻ௦ܣሺ௦ 1 ሺܣ௦ൌൌ, , ሻሻ ൫௬௬ᇲᇲ௬ᇲ൯௦ ௦ (4)

W(A, 1) annd kS(A, 1) are variabble scaling ccoefficientss for water-surface widdth and GS coefficientt

depending on locationn in the riverr network aand denotingg W and kS aat a site draaining area AA for a floww

discharge eequal to uniity. Surfacee routing moodule takes account of hydraulic ggeometry byy includingg

such scalinng coefficieents in the eexpressions used to callculate of kiinematic ceelerity ck and hydraulicc

diffusivity Dh (equaa paaragraph 3. field mea are not vvailable tootion 1, 1). When surements a

characterizze rill flow dynamics, geometry aand roughneess parametters can be empiricallyy evaluatedd

from literaature studiess [e.g., Parrsons et al, 1994; Abraahams et all, 1996]. Thhe chosen innput valuess


f

t

R

for surfacee hydraulic geometry aare summariized in Tablle 1. Channnel network GS coefficcient kS wass

been initiallly set equaal to 20 m1/3//s, but calibbration trialss led to use kS = 10 m1/3/s.

Table 11: Surface hyddraulic geomeetry input paraameters.

RIVUULET NETWWORK CHANNELL NETWORK

rivulet spaacing (m) 2.00 -

As (mm2) 4 × 105 6 ×× 107

Qf (mm3/s) 1.00 11.00

ww 1.00 11.00

W(As, QQf) (m) 2.00 30.00

b ’ 0.33 00.26

b’’ 0.50 00.50

kS(As, Qf) ( m1/3/s) 2.00 10.00

y’’ 0.20 00.20

y’’ 0.30 00.30

For the subbsurface, a total depthh of 60 m iss selected aand divided in 10 layerrs, each parrallel to thee

surface; a 3D grid of 106370 noodes with 5 57640 tetraahedral elemments is creeated startinng from thee

superficial nodes assoociated to thhe cells of thhe DEM. Thhe hydraulicc properties of the soil domain aree

found by mmeans of ccalibration ttrials and aanalysis of the sensitivvity to the variation oof the mainn

parameterss. An isotroope Ks is seet and each subsurface layer is suupposed to bbe homoge neous. Vann

Genuchtenn and Nielssen [1985] relationshipps are usedd to describbe the retenntion properrties in thee

unsaturatedd zone. Suuch relationnships defiine the mooisture curvves of the unsaturateed domain,,

describing the variation of effeective saturration Se, wwater satur ation Sw, aand relativee hydraulicc

conductivitty Kr as a fuunction of ppressure ψ, aas followingg:

ሻ ሺ1 ,ሻߚ ൏ 0 (5) 01,൜൜ൌሺ

1⁄ߠሻሺሻߠߠ⁄ߠ(6) െ ሺൌሻሺ௪ߠ ௦ ௦ (7)ଶሿሿሻ1 െ Ωሺെെ1ሾඥൌ൯ሻሺ൫ܭܭൌሻሺܭ


r

where: ఏఏఏఏೞೞఏൌeffective satuurationൌሻሺn = fitting ൌ 1 െ ߚ1 ≡ ሺ

Ω ≡ ⁄⁄ଵ 1

exponent, a ⁄௦ሻ approximateely in the raange 1.25 ൏൏ ൏ 6

and the othher paramet ers are definned in paraggraph 3.1.

The resultiing domain is constitutted by two ddifferent materials, whhose propertties are summmarized inn

Table 2.

TTable 2: Subssurface hydrauulic parameterrs of the hydroological modeel.

layer numm. thicknness (m) KKs (m s-1) ϑs (-) Ss (m-1)

material type

1 0..30 10-4 0.50 10-2 a

2 0..48 10-4 0.50 10-2 a

3 0..72 10-4 0.50 10-2 a

4 1..20 10-4 0.50 10-2 a

5 1..98 10-4 0.50 10-2 a

6 4..32 10-5 0.30 10-3 b

7 7..98 10-5 0.30 10-3 b

8 133.02 10-5 0.30 10-3 b

9 155.00 10-5 0.30 10-3 b

10 155.00 10-5 0.30 10-3 b

The remai ining input parameterss were set as followinng: n = 1.55, Ψs = -0.660 m, ϑr == 0.04. Thee

obtained mmoisture curves are showwn in Figurre 6, 7 and 88.


Figure 6: Soil moistture curves (VVan Genuchtenn and Nielsen)): effective satturation.

Figure 7 : Soil moisturre curve (Van Genuchten annd Nielsen): hyydraulic condductivity in maaterial types (aa) and (b).


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Figure 8: Sooil moisture cuurves (Van Geenuchten and NNielsen): voluumetric moistuure content inn material typees (a) and (b).

3.3 INITIAAL CONDITTIONS ANDD NUMERICCAL ISSUESS

The initial conditions, in terms oof pressure head for eaach node, arre determinned before eeach run byy

simulating the drainagge of the basin, with a nnull atmosppheric input , from total ly saturatedd conditionss

to the obsserved floww conditionss at the beeginning of the simulaation periodd, in orderr to set thee

dynamical equilibriumm of the systtem.

Very impo rtant aspectts for the immplementatiion of the mmodel are reelated to thee choice of parameterss

regulating the time sstep, whichh can influuence the cconvergencee of CATHHY subsurfface solver..

Besides, itt is the suubsurface s olver that controls thhe time evvolution of the simulaation usingg

adaptation and “back--stepping” [[Camporesee et al., 20110]. To conttrol the speeed of the c onvergencee

in terms off necessary number of iiterations too reach it, tiime step widdth is adaptted in order to keep thee

iterations nnumber in aa specified rrange. Whenn, at a certa in time stepp, this numbber is out off that range,,

time step wwidth is reduuced or ampplified for nnext time steep. A back-stepping occcurs insteadd, when thee

maximum number off iterations is reached:: the time sstep width is reduced and the soolutions forr


current timme step are bback-calcullated. The tiime step esttablished wwith this straategy, Δtss, iis generallyy

larger thann that requirred by the aaccuracy criiterion in thhe surface rrouting moddule Δts [Cuunge, 1969;;

Ponce, 19886; Syriopooulou and KKoussis, 19991]. Thus foor each sub surface timme level, ns == Δtss / Δtss

surface timme steps are executed (nnested timee stepping). The experi ence acquirred so far suuggests thatt

ns > 30÷550 time steeps may leaad to poor mass balaances, whil e the theorretical aspeects of thiss

constraint need to bee further invvestigated. Because o f these issuues, the runnning of seeveral trialss

before the actual sennsitivity anaalysis and ccalibration is necessarry for the iimplementaation of thee

model. Thee specific paarameters aand their finnal values ussed for simuulations undder predicteed scenarioss

are summaarized in Tabble 3.

Table 3: CAATHY numericcal input parammeters as usedd in Toledo Riiver catchmennt application.

PARAM NA

METER AME

DEEFINITION VALUUE

DTMMIN minimumm time step wwidth 1 s

DTMMAX maximumm time step wwidth 2.88 × 1104 s

ITUUNS maximum nnumber of iteerations 12

ITUUNS1 min

b nimum numb before ampli

ber of iteratio fying time st

ons to reach tep width

4

ITUUNS2 maxximum numb

before reduc ber of iteratio cing time ste

ons to reach ep width

7

DTREEDM multiplicati

time ive factor to e step width

reduce 0.5

DTMAMAGM multiplicativ

time ve factor to i e step width

increase 1.044

TOLLUNS convvergence tol erance on prressure head 0.01 mm


K

r

t

meters

3.4 SENSITTIVITY ANAALYSIS

In order too calibrate thhe hydrologgical modell, a sensitivvity analysiss is first carrried out to understandd

the respon nse of the mmodel to thee variation of each sinngle parameeter among those repreesenting thee

soil hydrauulic and reteention propperties: diffeerent valuess of Ks, ϑs, SSs, fitting exxponent n aand Ψs weree

investigateed. A base-ccase parameeter set (BCCPS) is fixedd, then seveeral simulattions are runn, in whichh

one parammeter at timee changes, iin comparisson to the ffixed set, inn the upper 4 layers (ssoil layers)..

The simulaation periodd is the whoole year 20008 and the aatmosphericc input conssists in meaasured dailyy

rainfall andd estimatedd monthly ppotential evaapotranspiraation. The ccomputed hhydrographss at a givenn

section aree also comp ared to the daily obserrved discharrge at the obbservation sstation (the only in thee

catchment area) locatted in the mmiddle of thhe basin (244º44'17"S, 553º41'20"WW), where thhe drainagee

area is 65.224 km2. Tabble 4 summaarizes the vaalues used iin this analyysis.

Table 4: Subsurface hydraulicc parameters uused in the sennsitivity anali sys.

base-c s case param set (BCPS) paraameter variaations

θr 0.04

θs 0.30 0.40

n 1.5 2.0 2.5

ψs (m) -0.60 --0.40 -0.80

Ks (m s-1) 3 × 10-4 2 × 10-4 10-4 4 × 10-4 5 ×× 10-4

Ss (m-1) 10-2 10-3

As shown in Figure 99, the decreaase of Ks geenerally cauuses the peaaks of the hhydrograph tto increase,,

while the bbaseflow deecreases. Onn the other hand, both the hydroggraphs, in wwhich Ks is hhigher thann

in BCPS, have smalller peaks aand higher recession ccurves: whhat seems uunexpected is that thee

hydrographh undergoess higher varriations with the small er increase of Ks (fromm 3 × 10-4 too 4 × 10-4)..


f

f

Ψ

Compared to the obsserved dischharge, Ks == 4 × 10-4 mmight be thhe best valuue in reprooducing thee

surface, whhile, the hyddrograph aggrees more wwith the subbsurface witth Ks = 5 × 10-4 (Figuree 10).

The increaase of ϑs atttenuates thhe peaks annd causes thhe basefloww to lift, g lobally impproving thee

comparisonn with the oobserved disscharge (Figgure 11 andd Figure 12).

As shown in Figure 113 and Figuure 14, wheen decreasinng the speccific storagee Ss, a globbally higherr

hydrographh is obtaine d, thus imprroving the rreproducingg of subsurface at the exxpense of thhe surface.

The increaase of van GGenuchten fitting exponnent n causees a small gglobal incre ase of the hhydrograph,,

thus improoving the coomparison wwith the subbsurface (Fiigure 15 annd Figure 166). It has too be noticedd

that for n == 2 and n = 2.5, very siimilar, almoost coincideent, hydrogrraphs result..

Compared to the otheer subsurfacce parameteers, the variiation of Ψss is not veryy relevant iin this casee

study: howwever, its in crease (in aabsolute vallue) causes a general loowering of the hydrog raph, whilee

its decreasse has an aattenuating effect on discharge ppeaks, reprroducing beetter the suurface floww

(Figure 17 and Figuree 18).

Figure 9: Sensitivity annalysis, Ks.


Figure 10: SSensitivity anaalysis, Ks; dailyy averaged hyydrographs an d daily observved discharge..

Figure 11 : Sensitivity aanalysis, ϑs.


Figure 12: SSensitivity anaalysis, ϑs; dailyy averaged hyydrographs andd daily observved discharge..

: Sensitivity aanalysis, Ss.Figure 13


Figure 14: SSensitivity anaalysis, Ss; dailyy averaged hyydrographs andd daily observved discharge..

Figure 15 analysis, n.5: Sensitivity a


Figure 16: SSensitivity anaalysis, n; dailyy averaged hy drographs andd daily observved discharge.

Figure 17:: Sensitivity aanalysis, Ψs.


Figure 18: Sensitivity anaalysis, Ψs; dailyy averaged hyydrographs annd daily observved discharge .

3.5 MODEEL CALIBRAATION

The CATHHY model iis calibratedd for subsuurface Ks, ϑϑs, Ss, n, ΨΨs and also for surfacee Gauckler--

Strickler c onductancee coefficientt kS. Severaal trials are carried outt with diffeerent configgurations off

such hydraaulic propeerties of thee domain, in order too reproducee the dischharge measuured at thee

observationn station. TThe observved data ussed is dailly discharg e for the wwhole yearr 2005. Ass

atmospheriic input to calibration simulationns, observedd rainfall att the same station is uused, whilee

estimated monthly avverages are available ffor potentiaal evapotrannspiration. CCalibration results aree

shown in FFigure 19 ass a graphicaal comparisoon betweenn the observ ed hydrograaph and thaat computedd

with the chhosen soil coonfigurationn, illustratedd in paragraaph 3.2.


r

Figure 19: CATTHY model caalibration resuults.

Though thhe two curvves are not perfectly ccoincident, ssuch resultss are accepptable consiidering thatt

subsurfacee properties are calibraated on the basis of suurface obse rvations, beecause no ppiezometricc

data are avvailable. In a coupled mmodel, duriing such kinnd of calibrration, imprroving the bbehavior off

subsurfacee module coould lead too a less connsistent reprresentation of the surfface and vicce versa: too

obtain globbally better results, a mmore comp lete set of ffield data wwould be neecessary. Hoowever, thee

calibrationn of CATHYY in this ccase study iis satisfactoory also coonsidering tthe state off the art off

dynamicallly coupled hhydrologicaal modelingg of real catchments. Tt oo perform aa good desccription of aa

basin behaavior, CATHHY needs mmany physiical parameeters of thee spatial doomain that are usuallyy

unknown oor not fullyy defined, thhus it's morre difficult to obtain g ood results . This kind of studies,,

combined wwith improvved data sett availabilityy (in qualityy and quanttity), are a cchallenge foor the futuree


managemeent of waterssheds as a wwhole.

To verify the calibrattion resultss and validaate the moddel, the simmulation annd the compparison aree

extended tto the seconnd half of year 2004 (accordingg to availabble observattions). Resuults for thee

whole yearrs 2004 andd 2005 are shhown in Figgure 20.

Figure 200: CATHY moodel calibratioon and validatiion results.


f

n

4. ATTMOSPHERRIC INPU T

4.1 METEOOROLOGICCAL DATA

The atmosspheric inpput for the simulationns with CAATHY is thhe net atmoospheric fluux, i.e. thee

difference between prrecipitation and potenttial evapotrranspiration, and is preepared on tthe basis off

meteorologgical observved and esttimated dat a. For rainffall, an obsserved seriees of daily data in thee

period 19779-2009 is aavailable. F or temperatture, observved monthlyy means forr years 20044 and 20055

and downsscaled historrical series (period 19885-2005) of daily minimmum and mmaximum, cooming fromm

the NCEP /NCAR Reeanalysis prroject, are available. TThe NCEP//NCAR Reeanalysis daata set is aa

continuallyy updating ggridded dataa set repres enting the sstate of the Earth's atmmosphere, inccorporatingg

observationns and nummerical weaather predic tion (NWP) model ouutput datingg back to 19948. It is aa

joint produuct from thhe National Centers foor Environmmental Preddiction (NCCEP) and thhe Nationall

Center forr Atmospherric Researcch (NCAR) . Monthly potential evvapotranspiiration is avvailable forr

years 20044 and 20055. In the fiirst sensitivvity analysiis of the mmodel, simuulating the year 2008,,

potential eevapotranspiiration is esstimated staarting from that of yeaar 2005, byy multiplyinng the 20055

values for a scaling ffactor calcu lated by coomparing thhe annual wwater balancce of both yyears in thee

basin and assuming tthat potentiial evapotraanspiration has the samme trend duuring both of the twoo

years. In aabsence of detailed daata, we assuume this hyypothesis reasonable iin account of climaticc

similitude as a whole between thhe two yearss. In calibraation trials, carried out for the yeaar 2005, thee

available mmonthly datta are first uused. Then, daily valuees are estimmated, startinng from NCCEP/NCARR

historical series of temperaturee, with Duuffie and BBeckman [[1991] formmula. Dailyy potentiall

evapotransspiration immproves the response oof the hydrrological m odel duringg calibrationn and suchh

daily valuues of poteential evapootranspiratioon are alsoo used in the simulaations underr predictedd

scenarios. River dischharge is avaiilable as daiily averagess during thee time periodd from Junee 8, 2004 too

May 28, 20009.

4.2 FUTURRE CLIMATTE SCENARRIOS

The buildiing of futurre scenarioss is based, in combinaation with present avaailable dataa, on recentt

studies succh as Marr AAmbrizzi, [[ nnez et al., [2006], Ammbrizzi et al. [2007],engo and 2006], Nu

Marengo eet al. [20077], Solman et al. [20007], Marenggo et al. [22009], prediicting the vvariation off


f

temperaturre and rainnfall in Soouthern Braazil, duringg the time period froom 2071 too 2100, inn

comparisonn with the tthirty years 1961-19900, under diffferent emisssion scenar ios [IPCC, 2007]. Thee

consideredd scenarios are IPCC SSRES A2 aand B2, thee latter morre optimisti c than the former. Ann

increase off both tempperature andd rainfall iss expected aacross the sstudy area uunder thosee scenarios..

Such variaations are: aa temperaturre increase of 2-4°C annd rainfall iincrease of 5-10% undder scenarioo

A2, and a ttemperaturee increase oof 1-3°C andd a rainfall iincrease up to 5% und er scenario B2. On thee

basis of thiis informatiion, five sceenarios are bbuilt also inn order to sttudy the effects of the vvariation off

single tempperature or rainfall. Thhe first scennario repressents that acctually obseerved and itt is denotedd

here as sceenario 0. Thhe other fouur scenarios , obtained ffrom climat e projectionns, are denooted here ass

scenarios AA, B, C annd D. The pattern of the scenariio 0 is use d and one or both vaariables aree

amplified bby differentt factors fo r each future scenario : temperatuure was addded 0, 2 or 4 °C whilee

rainfall inteensity is inccreased of 00, 5 or 10% (Table 5).

Table 5: Fuuture scenarioos for simulatiions with CATTHY model.

SCENNARIO TEEMPERATUURE RAINF INTEN

FALL NSITY

SCENNARIO 0 refereence period 1985-2005

SCENNARIO A + 4°C + 100%

SCENNARIO B + 2°C + 5%

SCENNARIO C - + 5%

SCENNARIO D + 2°C -


5. SIMMULATIOON RESULTTS

For each oof the five sscenarios, aa twenty-ye ar simulatioon is run wwith CATHYY. The resullts are thenn

compared and analyzzed in termss of river ddischarge, rrecharge fluux to the aqquifer and water tablee

level. Riveer discharge is computeed at the outtlet cell of the basin, t wwhile the anaalyzed rechaarge flow iss

that totallyy produced at all node s immediattely above tthe water taable. Nodall recharge fflow is alsoo

analyzed aat the final time of thee simulationn, to see hoow rechargge is distribbuted acrosss the basin..

Water tablee level is allso considerred at the ennd of the simmulation peeriod. Resullts are first plot for thee

unaltered sscenario 0, then the diifferences bbetween sceenario 0 andd the prediccted scenariios A, B, CC

and D are ppresented foor each variiable.

5.1 RIVERR DISCHAR GE

Fiigure 21: Simmulation underr scenario 0: riiver dischargee at outlet cell and atmosphheric input (p--e).


f

Figure 21 shows the ccomputed ddischarge at the outlet oof the basinn for scenarrio 0, togethher with thee

atmospheriic input. Thhe model ooutput is inn agreemennt with the expected rresponse too the givenn

atmospheriic input andd also with the averageely observedd values of discharge iin the basinn at present..

The hydroggraphs resuulting from tthe simulatiions under ppredicted sccenarios A, B, C and DD are shownn

in Figure 222, in compaarison with that of scennario 0.

Figuure 22: Riverr discharge at ooutlet cell, simmulation undeer future scenaarios.

An importaant increasee in peaks iss evident in scenarios AA and C, whhere rainfalll increases tthe most. Inn

scenario B , a smaller iincrease of peaks is nooticeable. Ass expected, discharge ppeaks underggo a visiblee

lowering inn scenario DD, where onnly the tempperature incrreases.


The basefll ndergoes somme variatio ns. While uunder scenaa B these vaaow also un rios A and riations aree

very slightt and withoout a generral effect, thhe increasee of the basseflow undeer scenario C, and itss

lowering uunder scenarrio D, are nooticeable byy zooming tthe hydrogr aphs (Figurre 23).

Figure 23: River disccharge (zoom)) at outlet celll, simulation uunder future sccenarios.


f

Figure 24 shows monnthly meanss for river ddischarge ovver the twennty-year perriod: the effects of thee

temperaturre increase (scenario DD) and of tthe rainfall intensity inncrease (sceenario C) aare evident,,

respectivelly. On the oother hand, tthe total inccrease of rivver dischargge under sceenarios A annd B showss

that the efffect of the inncreased raiinfall intenssity overcommes the effeect of the hi gher temperrature. Thiss

could be reelated to a ssort of comppensation beetween the ssingle effeccts of the higgher temperrature and aa

more intennse rainfall.

FFigure 24: Riiver dischargee, monthly me ans over simuulations periodd.


5.2 GROUUNDWATERR RECHARGGE

Figure 25 shows the total recharrge flow caalculated accross the baasin under sscenario 0. The modell

output is inn agreementt with the exxpected respponse to thee given atmmospheric innput. The tottal rechargee

flow in timme resultingg from the ssimulations under preddicted scenaarios A, B, CC and D, arre shown inn

Figure 26, in comparisson with thaat of scenarrio 0.

Figure 255: Total recharrge flux, simuulation under sscenario 0.


Figure 26: TTotal recharge flux, simulatiions under futuure scenarios..

The most eevident variiation of thee flow is inn peaks: theyy face an immportant inccrease undeer scenarioss

A and C, wwhere rainfaall increasess the most; a smaller inncrease cann be seen unnder scenariio B, wheree

temperaturre and rainffall seem too have a mmutual comppensating efffect, whilee under scennario D, ass

expected, ppeaks undeergo a very slight decrrease (Figuure 26). Thee recession curve alsoo undergoess

some variaations. Undder scenarioos A and BB, where booth temper ature and rrainfall incrrease, suchh

variations are very sli ght and witthout a globbal effect. OOn the contraary, in the zzoomed grapphs (Figuree

27), the ri se of the r ecession cuurve under scenario CC, because oof the increeased rainfaall, and thee

lowering oof the curve under scen ario D, as aan effect of the increaseed temperatture and, coonsequently,,

of a higherr evapotransspiration de mand, are vvisible.


Figgure 27: Totall recharge fluxx (zoom), simuulations underr future scenarrios.

Figure 28 shows monnthly meanss for recharrge flow ovver the twennty-year perriod: the effffects of thee

temperaturre increase ((scenario DD) and of thee rainfall inntensity incrrease (scenaario C) are eevident. Onn

the other hhand, the tottal increase of rechargee flow undeer scenarioss A and B shhows that thhe effect off

the increassed rainfall iintensity coompensates and overcommes the effeect of the hiigher tempeerature.


d

FFigure 28: Tottal recharge fluux, monthly mmeans over simmulation periood.

The next fifigures showw the instanntaneous varriation in noodal rechargge flux at thhe final momment of thee

simulation s under prredicted sceenarios. Suuch variatioon is calcuulated as thhe differencce betweenn

recharge flflux at that instant undder scenarioo A, B, C oor D and reecharge fluxx at that innstant underr

scenario 00. For eachh scenario, other two maps reprresent separrately the nnodes wherre the fluxx

increases aand the nodes where thhe flux decrreases, and tthe increasee or decreasse, in compparison withh

scenario 0,, is expresseed in percennt. The effeects of altereed scenarioss on nodal iinstantaneouus rechargee

to the aquiifer, calculaated by CAATHY, are inn agreemennt to the othher results such as tottal rechargee

flux.


Figure 29: Nodal variation of innstantaneous rrecharge flux at the end of tthe simulationn period, scenaario A.

Under scennario A (Figgure 29), a slight increease of the recharge iss noticeable in most off the nodes..

However, tthe distributtion of rechharge flow iss generally very heteroogeneous. Inn some nodees scatteredd

around thee river, a deccrease largeer than 100%% is visiblee, while the other decreeasing pointts face onlyy

a loweringg close to zzero. On thee other hannd, in the mmost of the increasing points the flux is nott

higher thann 20% with respect to tthat calculatted in the unnaltered casse.


Figurre 30: Nodal vvariation of innstantaneous rrecharge flux aat the end of t he simulationn period, scenaario B.

The distribbution of thhe differennce in nodaal recharge flux in sc enario B iss more hetterogeneouss

(Figure 300). The evaapotranspiraation demaand seems to concentrrate aroundd the river,, while thee

recharge teents to increease preferaably in uplaand areas. TThe calculatted differen ces are alsoo smaller inn

absolute vvalue than that calcullated underr scenario AA, in agreeement withh the moree optimisticc

atmospheriic input.


d

Figurre 31: Nodal vvariation of innstantaneous rrecharge flux aat the end of t he simulationn period, scenaario C.

The increaase of the onnly rainfall, occurring uunder scenaario C (Figuure 31), cauuses the noddal rechargee

flux to gloobally increease, with leess heteroggeneity thann in the firsst two scenaarios. In thiis case, thee

decreasingg points are also more sscattered accross the bassin, instead of being cooncentrated around thee

river. The differences , both increeases and d ecreases, arre generallyy higher in absolute vaalue than inn

the previouus cases, esppecially in uupland areaa ee increase pprevails. s, where th


Figurre 32: Nodal vvariation of innstantaneous rrecharge flux aat the end of thhe simulationn period, scenaario D.

The increaase of the oonly temperrature, occuurring undeer scenario D (Figure 32), causess the nodall

recharge fllux to globaally decreasse, because of the respponse of thee basin to thhe higher teemperature:

more intennsive evaporration fluxees occur andd infiltrationn water decrreases. The lowering off the flux iss

relatively hhomogeneoous. Howev er, the diffeerences in aabsolute va lue are aveeragely smaaller than inn

the other sccenarios. Thhe larger vaariations aree concentratted, as in thee previous ccase, in uplaand areas.


5.3 WATERR TABLE DDEPTH

Figgure 33: Waterr table depth aat the end of thhe simulation under scenariio 0.

Figure 33 represents water tablee depth at thhe end of thhe twenty-yyear simulaation under scenario 0..

This resultt is in agreemment to the average waater table leevel currentlly observedd across the basin. Thiss

map is theen used to make a comparison bbetween thee present siituation andd that prediicted underr

altered sce narios. The difference between suuch referencce water tab le depth andd the water table depthh

calculated at the samee time underr scenarios AA, B, C andd D is repressented in thee next mapss.

Figure 34: Variation of wwater table deppth at the endd of simulationn period underr scenario A.


At the endd of the tweenty-year simmulation unnder scenarrio A (Figurre 34), wateer table leveel is higherr

than underr unaltered sscenario, annd this is notticeable in tthe uppermoost part of thhe basin. Inn agreementt

with the mmore optimisstic atmosphheric input, under scennario B (Figgure 35) difffferences in water tablee

level respeect to scenaario 0 are ssmaller, andd also in thhis case moore visible on the hillsslopes thann

around thee river. As ffor the othe r analyzed variables, wwhen tempeerature increease is commbined withh

rainfall inccrease, the laatter has a sstrongest effffect on the hhydrologicaal response of the basinn.

Under scen

the most ev

Figure 35:

nario C (Fig

vident and,

Variation of w

gure 36), in

as in the pr

water table dep

which no te

revious case

pth at the end

emperature

es, it is large

d of simulation

increase is

er in upland

n period under

applied, the

d areas.

r scenario B.

e rise of watter table is

Figure 36: Variation of wwater table deppth at the endd of simulationn period underr scenario C.


As the onlyy temperatuure increasees under sceenario D (Fiigure 37), wwater table iis found to ddrop acrosss

the whole basin at thee end of thee simulationn, in agreemment with thhe smaller aamount of g roundwaterr

recharge aalso calculatted by CATTHY. Such lowering iis more eviident in thee basin areaas with thee

highest eleevation, as iin the previ ous cases. UUnder all thhe simulate d scenarios , while in ssome pointss

recharge fllux is foundd to have a ccontrasting bbehavior respect to thee whole basiin globally considered,,

the responsse in terms of water tabble level is mmore systemmatic, thouggh not unifoorm.

Figure 37: Variation of wwater table deppth at the endd of simulationn period underr scenario D.

6. DISSCUSSIONN

The obtainned simulatiion results indicate thaat groundwwater rechargge and watter table levvel increasee

when warmming is commbined witth a precipiitation increease (scenaarios A, B, and C), whhereas theyy

decrease iff warming iis not combbined with aan increase of precipitaation (scenaario D). Th e latter is aa

plausible sscenario in light of thee recent studdies on climmate variabbility and chhange. It is commonlyy

recognizedd that the iincrease in temperaturre will havee effect onn extremes more than on overalll

quantities of precipitaation [Mareengo et al., 2009]. In scenario DD, the obtainned simulattion resultss

indicate a ssignificant cchange in ggroundwaterr recharge oon water tabble depth (FFigure 33). TThe changee

of water taable depth, with respeect to the cconfiguratio n displayedd at presentt, is found to be non-

uniform accross the drrainage bassin. The immpact of climmate warmming is signiificantly hi gher in thee

upland parrt of the dr ainage basiin than in tthe valleys. This suggeests an adaaptation of aagriculturall


practices aaddressing tthe change in water taable depth. Cultures haaving deep roots are llikely to bee

very suitabble in the future to aallow waterr uptake unnder conditiions of watter scarcityy. It is alsoo

remarked hhere that goood conditioons of the veegetation coover in the uupper parts of the drainnage basinss

is not onlyy important for vegetattion yields, but also too preserve ssoil and ladd stability inn a climatee

displaying unaltered aannual valuees of precip itation but eenhanced exxtreme evennts.

7. COONCLUSIOONS

The hydroological respponse of thhe Toledo RRiver catchhment to cllimate channge, in termms of riverr

discharge, aquifer reccharge and wwater table depth, wass investigateed. Discharrge and rechharge flowss

are found, under the sselected sceenarios, to hhave a paral lel behaviorr, undergoinng rather thhe effects off

rainfall inc rresponding to an inccrease of thhe flow, thhan the efffects of thee increaseddcrease, cor

temperaturre, which sinngly leads tto a lowerinng of the floow that coulld be visibl e in scenariio D, wheree

temperaturre is the oonly alteredd control vvariable. Vaariations off the waterr table leveel are alsoo

noticeable under alterred scenarioos and they are more evvident in thhe upland arreas than inn the valley..

Measures of adaptati on to climaate change effects couuld be founnd by meanns of a moore detailedd

investigatioon of the role of veggetation in altered waater cycles,, which caan be repreesented, forr

instance, bby the vege tation uptakke in differrent drainagge basin areeas. Selectioon of suitabble culturess

across draainage basinns, especiallly in the aareas wherre the impaacts of climmate chang e are mostt

significant , would be aa challenginng choice inn territorial managemennt.


d

d

8. REEFERENCEES

Abrahams,, A. D., G. Li, and A. JJ. Parsons ((1996), Rilll hydraulics on a semiaarid hillsloppe, southernn Arizonaa, Earth Surrf. Processees Landformms, 21, 35 – 47.

Ambrizzi TT., R. Roch a, J. Marenggo, A. I. Pissnitchenko, L. Alves (22007), Cenaarios regionnalizados dee clima nno Brasil ppara o Sécuulo XXI: PProjeções dee Clima U sando Treis Modelos Regionais.. Ministéério do Mei o Ambientee-Mma, Seccretaria de BBiodiversidaade e Floresstas – Sbf, DDiretoria dee Conserrvação da BBiodiversiddade – DCBBio Mudannças Climááticas Globaais e Efeit os sobre aa Biodiveersidade SSub-projeto: Caracteriização do clima atuual e definnição das alteraçõess climáticcaspara o teerritório braasileiro ao loongo do Sécculo XXI. BBrasilia, Fevvereiro 20077.

Camporesee M., C. Paaniconi, M. Putti, and SS. Orlandinni (2010), S urface–subssurface floww modelingg with ppath-based runoff rouuting, bounndary conddition-based coupling, and assimmilation off multisoource observvation data. Water Res our. Res., 446, W025122, doi:10.10229/2008WRR007536.

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