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Effect of different vegetation type cover on the soil water balance in semi-arid areas of South Eastern Spain
Phys. Chcm. Earth (B), Vol. 24, No. 4, pp. 353-357, 1999
8 1999 Elsevier Science Ltd Ali rights mwwd 1464-1909/99/s - see #&It mattw PII: s1464-1909(99)ooo13-1
Vegetabtion Type Cover on the Soil Water Areas of South Eastern Spain t
Erfwd
in Std-Arid
e
J. Bcllot, J. R. Sabchez, E. Chirino, N. Hernandez, F. Abdelli and J. M. Martinez Department
of Ecology, Fat. Sciences, University of Alicante, Apdo.99. 03080 Alicante, Spain
Received 24 April 1998; revised 23 October 1998; accepted 2 December 1998 TheQpeofplantcommunitywnstitutesabmUbrtothe kineticenagyofrainMlbefbrethewMfcaaktk!aoil (Brandt and Thonws, 1987; Thomalk 19!w. Phmta
Abdrrt. The shnuNed soil waterbahnces underfive H of anmmi r&WI (SS3 mm), in dq grasses and pine withgnwazupactivelY.~isthemainoutfIowfknnthc ooil;kingmacthuriM)Kafnetpncigiotioniapineplus shNbw#&tioatypaThebaresoiIsallddrygTaBshow the &&$a# aclcp d@nage v4)uea (208 and 142 mm, xzqw&W~h howwjr, is diicult to e&mate what portion ofthisi~water~tminaquifbr~harge.Dming the studki Year olle hwge rainfall event (X34.6 mm) prodwed the main ~nfiluation flow under all vegetation Qpeq with a dgni&nt obaewed chattge in the aquifer piwaqic IeveI. A’second simulation without this event ShWStbRtt&MmrPldraiMgeifidltypeod~WaS tedwad. Tha soil Water amtent evolunipn qnder each veget&mtype,shoWsthatthebareaoilsanddrygrasscs prraat the highest klues. The most complex wgetation type, with high shtub biomass and pinus presentsthe highestammunptiofl. Caeflicientsof determination for the regm&on ofprediv daily soil water content on observed vaI_ wue 0.65, ‘0.m. 0.90 and 0.93 for the pine nfolarortion with sbrob undcntory; pine refbrestation with dry grase understory; shrubland and dry grassland, respcaivcly 0 1999 Elsevier Science LA. All rights rtstrvtd.
evaporation (E& and vapour pnwrr
de&it (V?&.
Inrecentyears,forestcovefrestorationhas~oneof the main object&s in dry, semi&d an&uiQ rw)r wkn special silvicultural practices have been &wIope& The positive effect on soil protection and m hwebeencriti&ed#brtkirnegatiwc&daon*watcr balanceandsolnepossiiIx!dwtiond fibdriba withtheaimof chui@ngthiscontmvsr)lant& positiveoraegativeei@ctofvegauoncavainrumiaridregion,thisstudya+mptstodewmiactbswater baIancesind8fefentqpesofcanopY8tmctmW(fknn moltilaytrstrpEatosiagkgra8scovcrandb@reMls~in ordeftoprovideabasistoimprovkthestcau@aa#land restoration. The calculated soil water b8Bke mirc*tlne eachveget&ontypeamIdbeextmpWMtoaI-&areas with the same v&&ion cow, soiI t~pa_ and environmental amditionr, that CavQ the aquiw aRa.
1 IntNubetion 2 Studyarea and experimentsIdes@ Thedyarwiaofaoilwatercontentisoneofthemain the chrnlpr and ewkttion of plant Md8u~suffbmlonger peIio&~wB&Id&cit,thatcolwrthevegetation strwtuma&waq+itY,anditsroieonaoilpmtaUionand wanrcoslcruJiai.Msrpreciliwrrion,#omewateris bywwdbYtNcptrntcavu,~a~~ dlwibuMofrai~lltakesplsceduetothethmu~ll and demflow pathwaYs (Rapp and Ibrahim, 197% Bellot and &cam. 199g1,
Thtuudy isbcingcarriedoutinthama&arid hwitermtwlareaof~(~%dn)with
mixcdwithrt5fomwpin~urb.dtylalJrtev (leaf am index LAI=l.S-2). Ml8 am dmMp#d ovcz marlsandcalcwlwbedm&andskQe8vuybahusaa2530%.TbesoildepthisonlY30cm,ductothapMnceof animpermabk@erofmarlqwhichrpntatbatopsoil fromtheaquiferlocatodat65mde#h.M&soil characteristicsaresumm&cdina#xaueof34.47% 45.46 % and 20.07 % of sand, silt and day nrpeftively,
Comqtwndencc fo: Juan Bellot
353
354
J.
Bcllot et 01.: Effect of Different Vegetation Type Cover on Soil Water Balance
0.98 g ad of bulk density,5.4 % of organic matter, and 58.33 41 d porosity. These values may explain the high
permeabilityofthe soil, which has a hydraulicconductivity (KJ of 3.37 cm d, a field capacityof 0.4223cc cc”, and a permanentwiltingpoint of 0.0833cc cc-’at - 6000kPa In themain mpresentativevegetationtypes of the area, the waterbalancewas studiedin 18 hydrologicalplots (8 x 2 m), with 3 replicatesin each vegetationtype. Five types ofvegetationcover were analysed:pine reforestationwith shrub understory; pine reforestation with dry grass understory;shrubland,dry grassland;and, bare soil. Gross and net precipitationwere measmedin each plot, together with surface runoff and erosion after each rai~l event. Wo completeautomaticweatherstations(cambell CRlO) located at the north and south oriented slopes, registered climatic data every 15 minutes. Soil water content was measuredweekly during the entire period, and the day atler rainfall even& using time domain mtlectometry (TDR) probes at three depths (O-IOcm, 20 cm, and 30 cm), with four replicatesper depth, in each experimental plot. In order to evaluatethe importanceof differentwater pathways through the canopy, rainthh simulationswere made in the laboratory on one tree specie (Pinus ha&~&)), three shrub species (Q. cocclfera, Pistucia lentiscus, and Erica mult~~oraa) and one dry grass species (Bruchyptxiium nhwm). Data series for the year 1997 wereusedthmughout.
wmRsoissoilwatcrcon~ttbedayT-l.pI~~ rainWlonsoil,Risruno@andTistimefiomthelast rainthll event. The k is an empiricalpammemrintegrating pammeter of vegetation chamcmristicsat the community level, ditferent for each vegetation type and calii through simulations.This k pammeW summar& all the structuraland emphysiologicalchamcmristicsinvolvedin
3 Eydrxuoglcalmodel Our hydrologicalmodel with a lday me resolutionfor the estimation of the soil water content, the water evapotmnspiration @J, and the aquifer recharge is continuing development. The mode1 is based on the previous works of N&ski and Saugier (1989). and Samper (1997). A general scheme for this model is presented in figure 1, with the main components and processes considered. The model’s inputs am: daily precipitation,some parametersof the soil (field capacity, wiltingpoint and initial watercontent),and somefrom the vegetation(type ofplant community,soil coverby the main species, overlapping canopy layers percentage, em). It calculatesthe total evaporation(E& throughthe MontheiFAO method (Sanchez-Tortbio,1992), as well as daily raintX1water distriiution (interception,net precipitation, runoff and infiltration),for each vegetationtype, and the soil water balance using equations suitable for the field data series,and Sampers’approach(Samper,1997)for the direct rechargein transit. The model applies a negative exponential approach (Tmvor et al., 1994; Rickti and &l&eon, 1982). to estimate actual evaporation &) as a function of k and total evaporation(I&J.The tImctionused is: R. = RSO??Cl&= ) + (Ps-R)+(1-e-7 )
the transpirationprocessesfrom the individualplant to the communitydetailedin other models(Niinski et at., 1989; Chassagneuxand Choisnel,1986). From these calculations,the model performsa soil water balanceto estimatethe daily soil water content (O-30cm), and predicts deep drainage from the soil to the unsatumtedoraquif&levels.Thesimulatalvaluesobminal from the model are teated with di&rent measur& techniques.Intemeption,net precipitationand runoff am ChCdCCdWiththC
-tSEskenOllthChydrologic
plots after each rain&l1event. Actual evapomgon @J is testedbycomparingthosimulatedvaluesfbr&cteddays with the measurements recorded by an in&red gas
J. Bellot et al.: Effect of Different Vegetation Type Cover on Soil Water Balance
GqNCityOftBamodrl. TlIwDdrDI~~tiththesoilwataamtcnt mantFalbytb6TDRpFobes. ~rrlh~lS#?*
Fine*shnb
Pino+Hwbs
lkblCl,showe the prccipitatitnl cxtrcmcstormcvclltof1OOmm(luwerpmt).Tbcalmual Stmh
Herba
Swed
553.5
553.5
653.5
553.5
142.3
195.4
132.2
125.9
16.6
411.3
356.1
421.3
427.6
536.9
2.7
10.3
3.0
5.6
26.4
Z-
331.9 90.0
270.6 79.5
102.6 525.1
2S5.6 142.4
206.5 262.1
Sanmlrrcadaf6ahmp
-13.3
-11.2
a.3
13.6
20.0
N@m Rmon
mrdhoutalargamlnfanavantef
Pim*SW
Pino+Hwbs
355
ShNbr
553.5
HO&S
S8mldl
1WlWl 453.5
453.5
453.5
453.5
121.9
164.6
117.1
107.3
331.7
266.9
336.4
346.2
439.0
2.0
9.3
2.1
5.3
6.6
Z-
331.9 11.0
279.6 6.2
325.1 16.6
265.6 61.5
262.1 125.3
Solmcconcntc!mno
-13.2
-6.3
-9.3
13.6
20.0
ww RUMR
453.5 ,
14.5
T*l.&UUlw(r mdb)fcdmmmaym
b&mcecaWatedwiththcscdamshowsthatduringthis wet year (553 mm of ammal precipitation) interception by thcplantcoverrcp+nts22Kto35%oflainhrll,indry grasseSaadpinckithgmsscsreSpaxivcly.TheThe rqeseWthcmainflowfromthesoil,morethan8O%of netp&pihtkiatbcpine-pl~vcgcWontype.In rclatkmtothedcepdminagc,thebarcsoilanddrygrasses types shows the hiqhcst percolation values (208 and 142 mm, nrpsctively, 38 and 26 % respect to precipitation). However, it is dif&ult to estimate what portion of this
pacolatal waterrepresents an quifcz rcchaqc. The analysis ofthe simulati soil water amtent evolution under each vegetation type (figme 2), shows that the bare soils andlowbiomassorsinglestrataofgt&spfcsc&tthehigher values. Conversely,the most complex veg&&on type, that with high shrub biomass, presents the highest consumpti0~. Asbasbccnmntionedbcfore, 1997wasawuyaqwith a large storm cvenf (134.6 mm), that pmduccd in the simulation the main deep drainage flow supp&ng 8Il
356
J. Bellot et al.: Effect of Different Vegetation Type Cover on Soil Water Balance
vegetation types (figure 3). with a significant change in the measumd aquifer piezometric level (figure 4). To highlight the importance of this kind of big storm (nlatively fkquent in the Mediterranean region) to the aquifer rechatge, a second simulation without this particular event was applied. Table 1 (lower part) shows that simulated ammal deep percolation was reduced in all types of cover. Inthissimulatsdcase,annualE,isthesameasthatinthe previous one, proving that higher precipitation only has signiEcant effects on the aquifer mcharge, but not on the top soil -, due to its limited field capacity and high infiltration of the soil in study area (see section 2). Finally, to test the model estimations of&, we extrapolate the IRGA-poromcter measurem ents of the main shrub
species to integrate the daily transpiration during two particuhu days (one in summer, andtheotherinwinter). The obtained vahles of 1.04 and 0.17 mm day-’ mspectively, wete half the estimatexl vahles by the model for winter, and 4 times those estimated for summer. The orientation effect on irationincmaseatheval~in winter to 0.78 mm uansf day‘, which is twice that of the estimated values from the model. Pinus ha/epensi~ shows significant difBerencesfrom the orientation in winter, being 0.4 mm day-’ in the southern slopes, twice the vahte of those in the north. In this case, the northern value is closer to the model’s estimation. In general the daily soil water content predictions over the study period were accepmblle, coefficients of determination for the regression of pmdkted
Fig 4. Daily piametric levelrecoded on the Vent& aquifer(doacdIii) and daily pwcipilatian(bus).
1. Bellot et al.: Effect of Different Vegetation Type Cover on Soil Water Balance daily soil water content on obsewal values were 0.65, 0.87, 0.90 and 0.93 fat the pine &&station with shrub undcrsmv, pine rcfWstation with dry grass undemwry; ShNblaml amI dry g&slam& lSpcctiwly (figure 5). The calibrated k paramcw in these cases were 0.054 for the pine &orWation with shrub undcmtory; 0.010 for pine reforestation with dry grass understo~, 0.0095 for the shrubland, and 0.008 for the dry grassland vegetation typcsThcbafcsoilvahicshavcnotyctbcencalibratcdin thi!Sway.Inspiteofthcnlativcladcofmcaswcmcnts wor&d until now, and the preliminary state of dcAopmentofthc*l,avua8eobscrwdvaluessccms not to be so f&rfrom the model estimation.
357
hi8hcst values of Eta and the lowest on deep draiaq(p;. at thesametimethatbansoilanddrygru&5~praent lower Eta values and the highest deep flows. Ar a consequence, soil water content is normally highcat in soils with rahxed vegetation cover. In elation to the aquifer recha%e, the positive effect of the big __. storm event _. __has been appru&ed on this type of highly permeable soil, in contrast to 8cnwal opinion. In spite of this high penncability, water mowmcnt throughunsanuatedsoilscemsnattok:the~rruoato explain the obsclnd aquifer recharge. P&ably, during the large rainfall events, preferential flow pathways in karstic areas over the aquifer could explain the obsuwd increase of the $xometic level (figure 4).
References
Fig.5. Dailywater~fdictcdbytbmodelvawsmaawd ddyW&?-dIUi@gthsVdiipliOd.~drtrWCNured loalinntaulemofdetamiNtiialdregreai~ s Conclusionr
The main concluions from this pmliminar work are the r&vanceofthcvegetationtypeinthecstimatedEta,deep drainage and soil water content. The simulations and the field data show that pine-phwshrob vegetation have the
BmndtJ.~ThomwJ,Emhulenct@iaIn:K.L.Orqq@d) Enu@cs qfphyakal mvtnmmmtt5 l-S7,19S7. BeilotJ.andEwr6A.-udthrou#&llde&dwbin~ tqtoukd hohnork fad. Ann. Set. For. 53; 1998. NiJ.d&u&tB.,Amoddoftrrrrpk*ionmd~blaoa fat 8 W o8k faca .4@dtwal and Fomt Afetwmbgy, 47~1.17, 1989. k4anaseaitmwphdar Rqq hf. uxl Itdim Id.. E~dtana& . . . ~pvunpacp1anad&pinurpina.L~poorrr.13:321. 330.1978. Ridcelt K.O. and McKcm O.M.. soil wtu bolrma mod& WAlsEP. ~ofAurtnliSocietyofAnirntRahftiaq1~19S.~l9S2. SunperF.J..M(loQIdanniuri6ndoI~ncrrlL.porh~prUvro de rSux utilii6n. cdilwacih y CJTU%%In:CUUOdbH,LlaM.Ry SqnrJ.(l5k).Lowktctdndslorecquaknaat@vwa& proclipcocra, hidmlbgica. btii Temol~ Gaminma & plpdr: 41-Sl.1997. Shck-Totiio, M.I.. Mtodos para d ?? mdfo k la mqwmd& y Thic~sdohSEO.N*3.r\ppohcuupirocldn. cuuicma Edicha. Locmao, 36 pp., 1992. Thoron, J 0, Ve@atton and rrorion: Pmcmsw and Etwttunmunt~ 518 pR 1990. Tlsvor,J.H..ArblyD.S.radJos,J.L,Amodcldrdt~bJaDIud hchqe#rowlhinlbeuidruq+haf~-Javncrl#Arld Envi. 28~281.298.1994.
8 1999 Elsevier Science Ltd Ali rights mwwd 1464-1909/99/s - see #&It mattw PII: s1464-1909(99)ooo13-1
Vegetabtion Type Cover on the Soil Water Areas of South Eastern Spain t
Erfwd
in Std-Arid
e
J. Bcllot, J. R. Sabchez, E. Chirino, N. Hernandez, F. Abdelli and J. M. Martinez Department
of Ecology, Fat. Sciences, University of Alicante, Apdo.99. 03080 Alicante, Spain
Received 24 April 1998; revised 23 October 1998; accepted 2 December 1998 TheQpeofplantcommunitywnstitutesabmUbrtothe kineticenagyofrainMlbefbrethewMfcaaktk!aoil (Brandt and Thonws, 1987; Thomalk 19!w. Phmta
Abdrrt. The shnuNed soil waterbahnces underfive H of anmmi r&WI (SS3 mm), in dq grasses and pine withgnwazupactivelY.~isthemainoutfIowfknnthc ooil;kingmacthuriM)Kafnetpncigiotioniapineplus shNbw#&tioatypaThebaresoiIsallddrygTaBshow the &&$a# aclcp d@nage v4)uea (208 and 142 mm, xzqw&W~h howwjr, is diicult to e&mate what portion ofthisi~water~tminaquifbr~harge.Dming the studki Year olle hwge rainfall event (X34.6 mm) prodwed the main ~nfiluation flow under all vegetation Qpeq with a dgni&nt obaewed chattge in the aquifer piwaqic IeveI. A’second simulation without this event ShWStbRtt&MmrPldraiMgeifidltypeod~WaS tedwad. Tha soil Water amtent evolunipn qnder each veget&mtype,shoWsthatthebareaoilsanddrygrasscs prraat the highest klues. The most complex wgetation type, with high shtub biomass and pinus presentsthe highestammunptiofl. Caeflicientsof determination for the regm&on ofprediv daily soil water content on observed vaI_ wue 0.65, ‘0.m. 0.90 and 0.93 for the pine nfolarortion with sbrob undcntory; pine refbrestation with dry grase understory; shrubland and dry grassland, respcaivcly 0 1999 Elsevier Science LA. All rights rtstrvtd.
evaporation (E& and vapour pnwrr
de&it (V?&.
Inrecentyears,forestcovefrestorationhas~oneof the main object&s in dry, semi&d an&uiQ rw)r wkn special silvicultural practices have been &wIope& The positive effect on soil protection and m hwebeencriti&ed#brtkirnegatiwc&daon*watcr balanceandsolnepossiiIx!dwtiond fibdriba withtheaimof chui@ngthiscontmvsr)lant& positiveoraegativeei@ctofvegauoncavainrumiaridregion,thisstudya+mptstodewmiactbswater baIancesind8fefentqpesofcanopY8tmctmW(fknn moltilaytrstrpEatosiagkgra8scovcrandb@reMls~in ordeftoprovideabasistoimprovkthestcau@aa#land restoration. The calculated soil water b8Bke mirc*tlne eachveget&ontypeamIdbeextmpWMtoaI-&areas with the same v&&ion cow, soiI t~pa_ and environmental amditionr, that CavQ the aquiw aRa.
1 IntNubetion 2 Studyarea and experimentsIdes@ Thedyarwiaofaoilwatercontentisoneofthemain the chrnlpr and ewkttion of plant Md8u~suffbmlonger peIio&~wB&Id&cit,thatcolwrthevegetation strwtuma&waq+itY,anditsroieonaoilpmtaUionand wanrcoslcruJiai.Msrpreciliwrrion,#omewateris bywwdbYtNcptrntcavu,~a~~ dlwibuMofrai~lltakesplsceduetothethmu~ll and demflow pathwaYs (Rapp and Ibrahim, 197% Bellot and &cam. 199g1,
Thtuudy isbcingcarriedoutinthama&arid hwitermtwlareaof~(~%dn)with
mixcdwithrt5fomwpin~urb.dtylalJrtev (leaf am index LAI=l.S-2). Ml8 am dmMp#d ovcz marlsandcalcwlwbedm&andskQe8vuybahusaa2530%.TbesoildepthisonlY30cm,ductothapMnceof animpermabk@erofmarlqwhichrpntatbatopsoil fromtheaquiferlocatodat65mde#h.M&soil characteristicsaresumm&cdina#xaueof34.47% 45.46 % and 20.07 % of sand, silt and day nrpeftively,
Comqtwndencc fo: Juan Bellot
353
354
J.
Bcllot et 01.: Effect of Different Vegetation Type Cover on Soil Water Balance
0.98 g ad of bulk density,5.4 % of organic matter, and 58.33 41 d porosity. These values may explain the high
permeabilityofthe soil, which has a hydraulicconductivity (KJ of 3.37 cm d, a field capacityof 0.4223cc cc”, and a permanentwiltingpoint of 0.0833cc cc-’at - 6000kPa In themain mpresentativevegetationtypes of the area, the waterbalancewas studiedin 18 hydrologicalplots (8 x 2 m), with 3 replicatesin each vegetationtype. Five types ofvegetationcover were analysed:pine reforestationwith shrub understory; pine reforestation with dry grass understory;shrubland,dry grassland;and, bare soil. Gross and net precipitationwere measmedin each plot, together with surface runoff and erosion after each rai~l event. Wo completeautomaticweatherstations(cambell CRlO) located at the north and south oriented slopes, registered climatic data every 15 minutes. Soil water content was measuredweekly during the entire period, and the day atler rainfall even& using time domain mtlectometry (TDR) probes at three depths (O-IOcm, 20 cm, and 30 cm), with four replicatesper depth, in each experimental plot. In order to evaluatethe importanceof differentwater pathways through the canopy, rainthh simulationswere made in the laboratory on one tree specie (Pinus ha&~&)), three shrub species (Q. cocclfera, Pistucia lentiscus, and Erica mult~~oraa) and one dry grass species (Bruchyptxiium nhwm). Data series for the year 1997 wereusedthmughout.
wmRsoissoilwatcrcon~ttbedayT-l.pI~~ rainWlonsoil,Risruno@andTistimefiomthelast rainthll event. The k is an empiricalpammemrintegrating pammeter of vegetation chamcmristicsat the community level, ditferent for each vegetation type and calii through simulations.This k pammeW summar& all the structuraland emphysiologicalchamcmristicsinvolvedin
3 Eydrxuoglcalmodel Our hydrologicalmodel with a lday me resolutionfor the estimation of the soil water content, the water evapotmnspiration @J, and the aquifer recharge is continuing development. The mode1 is based on the previous works of N&ski and Saugier (1989). and Samper (1997). A general scheme for this model is presented in figure 1, with the main components and processes considered. The model’s inputs am: daily precipitation,some parametersof the soil (field capacity, wiltingpoint and initial watercontent),and somefrom the vegetation(type ofplant community,soil coverby the main species, overlapping canopy layers percentage, em). It calculatesthe total evaporation(E& throughthe MontheiFAO method (Sanchez-Tortbio,1992), as well as daily raintX1water distriiution (interception,net precipitation, runoff and infiltration),for each vegetationtype, and the soil water balance using equations suitable for the field data series,and Sampers’approach(Samper,1997)for the direct rechargein transit. The model applies a negative exponential approach (Tmvor et al., 1994; Rickti and &l&eon, 1982). to estimate actual evaporation &) as a function of k and total evaporation(I&J.The tImctionused is: R. = RSO??Cl&= ) + (Ps-R)+(1-e-7 )
the transpirationprocessesfrom the individualplant to the communitydetailedin other models(Niinski et at., 1989; Chassagneuxand Choisnel,1986). From these calculations,the model performsa soil water balanceto estimatethe daily soil water content (O-30cm), and predicts deep drainage from the soil to the unsatumtedoraquif&levels.Thesimulatalvaluesobminal from the model are teated with di&rent measur& techniques.Intemeption,net precipitationand runoff am ChCdCCdWiththC
-tSEskenOllthChydrologic
plots after each rain&l1event. Actual evapomgon @J is testedbycomparingthosimulatedvaluesfbr&cteddays with the measurements recorded by an in&red gas
J. Bellot et al.: Effect of Different Vegetation Type Cover on Soil Water Balance
GqNCityOftBamodrl. TlIwDdrDI~~tiththesoilwataamtcnt mantFalbytb6TDRpFobes. ~rrlh~lS#?*
Fine*shnb
Pino+Hwbs
lkblCl,showe the prccipitatitnl cxtrcmcstormcvclltof1OOmm(luwerpmt).Tbcalmual Stmh
Herba
Swed
553.5
553.5
653.5
553.5
142.3
195.4
132.2
125.9
16.6
411.3
356.1
421.3
427.6
536.9
2.7
10.3
3.0
5.6
26.4
Z-
331.9 90.0
270.6 79.5
102.6 525.1
2S5.6 142.4
206.5 262.1
Sanmlrrcadaf6ahmp
-13.3
-11.2
a.3
13.6
20.0
N@m Rmon
mrdhoutalargamlnfanavantef
Pim*SW
Pino+Hwbs
355
ShNbr
553.5
HO&S
S8mldl
1WlWl 453.5
453.5
453.5
453.5
121.9
164.6
117.1
107.3
331.7
266.9
336.4
346.2
439.0
2.0
9.3
2.1
5.3
6.6
Z-
331.9 11.0
279.6 6.2
325.1 16.6
265.6 61.5
262.1 125.3
Solmcconcntc!mno
-13.2
-6.3
-9.3
13.6
20.0
ww RUMR
453.5 ,
14.5
T*l.&UUlw(r mdb)fcdmmmaym
b&mcecaWatedwiththcscdamshowsthatduringthis wet year (553 mm of ammal precipitation) interception by thcplantcoverrcp+nts22Kto35%oflainhrll,indry grasseSaadpinckithgmsscsreSpaxivcly.TheThe rqeseWthcmainflowfromthesoil,morethan8O%of netp&pihtkiatbcpine-pl~vcgcWontype.In rclatkmtothedcepdminagc,thebarcsoilanddrygrasses types shows the hiqhcst percolation values (208 and 142 mm, nrpsctively, 38 and 26 % respect to precipitation). However, it is dif&ult to estimate what portion of this
pacolatal waterrepresents an quifcz rcchaqc. The analysis ofthe simulati soil water amtent evolution under each vegetation type (figme 2), shows that the bare soils andlowbiomassorsinglestrataofgt&spfcsc&tthehigher values. Conversely,the most complex veg&&on type, that with high shrub biomass, presents the highest consumpti0~. Asbasbccnmntionedbcfore, 1997wasawuyaqwith a large storm cvenf (134.6 mm), that pmduccd in the simulation the main deep drainage flow supp&ng 8Il
356
J. Bellot et al.: Effect of Different Vegetation Type Cover on Soil Water Balance
vegetation types (figure 3). with a significant change in the measumd aquifer piezometric level (figure 4). To highlight the importance of this kind of big storm (nlatively fkquent in the Mediterranean region) to the aquifer rechatge, a second simulation without this particular event was applied. Table 1 (lower part) shows that simulated ammal deep percolation was reduced in all types of cover. Inthissimulatsdcase,annualE,isthesameasthatinthe previous one, proving that higher precipitation only has signiEcant effects on the aquifer mcharge, but not on the top soil -, due to its limited field capacity and high infiltration of the soil in study area (see section 2). Finally, to test the model estimations of&, we extrapolate the IRGA-poromcter measurem ents of the main shrub
species to integrate the daily transpiration during two particuhu days (one in summer, andtheotherinwinter). The obtained vahles of 1.04 and 0.17 mm day-’ mspectively, wete half the estimatexl vahles by the model for winter, and 4 times those estimated for summer. The orientation effect on irationincmaseatheval~in winter to 0.78 mm uansf day‘, which is twice that of the estimated values from the model. Pinus ha/epensi~ shows significant difBerencesfrom the orientation in winter, being 0.4 mm day-’ in the southern slopes, twice the vahte of those in the north. In this case, the northern value is closer to the model’s estimation. In general the daily soil water content predictions over the study period were accepmblle, coefficients of determination for the regression of pmdkted
Fig 4. Daily piametric levelrecoded on the Vent& aquifer(doacdIii) and daily pwcipilatian(bus).
1. Bellot et al.: Effect of Different Vegetation Type Cover on Soil Water Balance daily soil water content on obsewal values were 0.65, 0.87, 0.90 and 0.93 fat the pine &&station with shrub undcrsmv, pine rcfWstation with dry grass undemwry; ShNblaml amI dry g&slam& lSpcctiwly (figure 5). The calibrated k paramcw in these cases were 0.054 for the pine &orWation with shrub undcmtory; 0.010 for pine reforestation with dry grass understo~, 0.0095 for the shrubland, and 0.008 for the dry grassland vegetation typcsThcbafcsoilvahicshavcnotyctbcencalibratcdin thi!Sway.Inspiteofthcnlativcladcofmcaswcmcnts wor&d until now, and the preliminary state of dcAopmentofthc*l,avua8eobscrwdvaluessccms not to be so f&rfrom the model estimation.
357
hi8hcst values of Eta and the lowest on deep draiaq(p;. at thesametimethatbansoilanddrygru&5~praent lower Eta values and the highest deep flows. Ar a consequence, soil water content is normally highcat in soils with rahxed vegetation cover. In elation to the aquifer recha%e, the positive effect of the big __. storm event _. __has been appru&ed on this type of highly permeable soil, in contrast to 8cnwal opinion. In spite of this high penncability, water mowmcnt throughunsanuatedsoilscemsnattok:the~rruoato explain the obsclnd aquifer recharge. P&ably, during the large rainfall events, preferential flow pathways in karstic areas over the aquifer could explain the obsuwd increase of the $xometic level (figure 4).
References
Fig.5. Dailywater~fdictcdbytbmodelvawsmaawd ddyW&?-dIUi@gthsVdiipliOd.~drtrWCNured loalinntaulemofdetamiNtiialdregreai~ s Conclusionr
The main concluions from this pmliminar work are the r&vanceofthcvegetationtypeinthecstimatedEta,deep drainage and soil water content. The simulations and the field data show that pine-phwshrob vegetation have the
BmndtJ.~ThomwJ,Emhulenct@iaIn:K.L.Orqq@d) Enu@cs qfphyakal mvtnmmmtt5 l-S7,19S7. BeilotJ.andEwr6A.-udthrou#&llde&dwbin~ tqtoukd hohnork fad. Ann. Set. For. 53; 1998. NiJ.d&u&tB.,Amoddoftrrrrpk*ionmd~blaoa fat 8 W o8k faca .4@dtwal and Fomt Afetwmbgy, 47~1.17, 1989. k4anaseaitmwphdar Rqq hf. uxl Itdim Id.. E~dtana& . . . ~pvunpacp1anad&pinurpina.L~poorrr.13:321. 330.1978. Ridcelt K.O. and McKcm O.M.. soil wtu bolrma mod& WAlsEP. ~ofAurtnliSocietyofAnirntRahftiaq1~19S.~l9S2. SunperF.J..M(loQIdanniuri6ndoI~ncrrlL.porh~prUvro de rSux utilii6n. cdilwacih y CJTU%%In:CUUOdbH,LlaM.Ry SqnrJ.(l5k).Lowktctdndslorecquaknaat@vwa& proclipcocra, hidmlbgica. btii Temol~ Gaminma & plpdr: 41-Sl.1997. Shck-Totiio, M.I.. Mtodos para d ?? mdfo k la mqwmd& y Thic~sdohSEO.N*3.r\ppohcuupirocldn. cuuicma Edicha. Locmao, 36 pp., 1992. Thoron, J 0, Ve@atton and rrorion: Pmcmsw and Etwttunmunt~ 518 pR 1990. Tlsvor,J.H..ArblyD.S.radJos,J.L,Amodcldrdt~bJaDIud hchqe#rowlhinlbeuidruq+haf~-Javncrl#Arld Envi. 28~281.298.1994.