Evapotranspiration in the Mekong and Yellow river basins / Evapotranspiration dans les bassins du Mekong et du Fleuve Jaune

Transcription

1 Hydrologial Siene Journal ISSN: (Print) (Online) Journal homepage: Evapotranpiration in the Mekong and Yellow river bain / Evapotranpiration dan le bain du Mekong et du Fleuve Jaune MAICHUN ZHOU, HIROSHI ISHIDAIRA, KUNIYOSHI TAKEUCHI & YONGTONG GAO To ite thi artile: MAICHUN ZHOU, HIROSHI ISHIDAIRA, KUNIYOSHI TAKEUCHI & YONGTONG GAO (2009) Evapotranpiration in the Mekong and Yellow river bain / Evapotranpiration dan le bain du Mekong et du Fleuve Jaune, Hydrologial Siene Journal, 54:3, , DOI: /hyj To link to thi artile: Publihed online: 19 De Submit your artile to thi journal Artile view: 416 View related artile Citing artile: 5 View iting artile Full Term & Condition of ae and ue an be found at Download by: [ ] Date: 29 November 2017, At: 10:27

2 Hydrologial Siene Journal de Siene Hydrologique, 54(3) June Evapotranpiration in the Mekong and Yellow river bain MAICHUN ZHOU 1, HIROSHI ISHIDAIRA 2, KUNIYOSHI TAKEUCHI 3 & YONGTONG GAO 4 1 College of Water Conervany and Civil Engineering, South China Agriultural Univerity, Guangzhou , China mzhou@au.edu.n 2 Interdiiplinary Graduate Shool of Mediine and Engineering, Univerity of Yamanahi, Takeda , Kofu , Japan 3 International Centre for Water Hazard and Rik Management (ICHARM) under the aupie of UNESCO, Publi Work Reearh Intitute (PWRI), Minamihara 1-6, Tukuba , Japan 4 Library, South China Agriultural Univerity, Guangzhou , China Abtrat Etimate of potential evapotranpiration (PET) and referene evapotranpiration (RET) were ompared over the Mekong and Yellow river bain, repreenting humid and emi-arid Aian monoon region. Multiple regreion relationhip between monthly RET, PET, LAI (leaf area index) and limati variable were explored for different vegetation type. Over the Mekong River bain, the patial average of RET i only 1.7% lower than PET; however, RET i 140% higher than PET over part of the Tibetan Plateau, due to the hort and pare graland, and 30% lower than PET in part of the lower bain due to the tall and well-developed foret. Over the Yellow River bain, RET i etimated to be higher than PET, on average about 50% higher aro the whole bain, due to the generally pare vegetation. A loe linear relationhip between annual RET and PET allow the etablihment of a regional regreion to predit monthly PET from monthly RET, limati variable and/or vegetation LAI. However, the large predition error indiate that the Shuttleworth-Wallae (S-W) model, although it i more omplex, hould be reommended due to it more robut phyial bai and beaue it uefully aount for the effet of hanging land urfae ondition on PET. The limited available field data ugget that the S-W etimate may be more realiti. It wa alo found that vegetation ondition in ummer are primarily ontrolled by the regional anteedent preipitation in the old and dry eaon over the Loe Plateau in the middle reahe of the Yellow River. Key word potential evapotranpiration; referene evapotranpiration; Penman-Monteith equation; FAO-56; Shuttleworth-Wallae model; Mekong River; Yellow River; humid area; emi-arid area Evapotranpiration dan le bain du Mekong et du Fleuve Jaune Réumé De etimation de l évapotranpiration potentielle (ETP) et de l évapotranpiration de référene (ETR) pour le bain verant du Mekong et du Fleuve Jaune, repréentant de région humide et emiaride de l Aie de mouon, ont été omparée. De relation de régreion multiple entre l ETR et l ETP menuelle, le LAI (indie de urfae foliaire) et de variable limatique ont été explorée pour différent type de végétation. Dan le bain du Mekong, la moyenne patiale de l ETR et inférieure à elle de l ETP de eulement 1.7%; tandi qu elle et upérieure de 140% dan le zone du Plateau Tibétain en raion de prairie rare et rae, et inférieure de 30% dan le zone aval en lien ave le forêt de grande taille et bien développée. Dan le bain du Fleuve Jaune, le etimation montrent que l ETR et upérieure à l ETP dan preque tout le bain ar la végétation et dan l enemble aez rare, à hauteur de 50% en moyenne dan le bain. Une étroite relation linéaire entre l ETR et l ETP annuelle enouragent à établir une régreion régionale pour prévoir l ETP menuelle à partir de l ETR menuelle, de variable limatique et/ou du LAI. Cependant, le importante erreur de préviion indiquent que l utiliation du modèle de Shuttleworth-Wallae (S-W), bien que plu omplexe, et reommandée pour e bae phyique plu robute et pour a prie en ompte effiae de effet de hangement d état de urfae ur l ETP. Le manque de donnée de terrain diponible uggère que le etimation du modèle S-W ont plu réalite. Il apparaît que le ondition de végétation en été ont avant tout ontrôlée par le préipitation antérieure régionale lor de aion froide et èhe ur le Plateau Loeique orrepondant aux affluent intermédiaire du Fleuve Jaune. Mot lef évapotranpiration potentielle; évapotranpiration de référene; équation de Penman-Monteith; FAO-56; modèle de Shuttleworth-Wallae; Fleuve Mekong; Fleuve Jaune; zone humide; zone emi-aride INTRODUCTION Potential evapotranpiration (PET) i generally onidered to be the maximum rate of evaporation from vegetation-overed land urfae when water i freely available, and i primarily determined Thi paper i a revied and updated verion of that preented at the Conferene Hydrologial Siene for Managing Water Reoure in the Aian Developing World, organized by the Center for Water Reoure and Environment, Sun Yat-Sen Univerity and Department of Geography and Reoure Management, The Chinee Univerity of Hong Kong, and held in Guangzhou, China, 8 10 June Open for diuion until 1 Deember 2009

3 624 Maihun Zhou et al. by meteorologial ontrol (Granger, 1989; Lhomme, 1997; MViar et al., 2007b). It i a key input to hydrologial model, impoible to meaure when the environment i water-limited; therefore, it i uually etimated a an area-average. If the environment i energy-limited, then the meaurement of atual evapotranpiration provide a meaure of PET (Donohue et al., 2007). Among the many evaporation model available, the Penman approah i preferred, with two extenion being widely employed: (a) the Penman-Monteith (P-M); and (b) the Shuttleworth- Wallae (S-W) equation. In ontrat to many empirial PET formulation of uni- or bimeteorologial variable (e.g. air temperature only, inluding Thornthwaite, 1948; air temperature and olar radiation, uh a Prietley & Taylor, 1972), the above two extenion of the Penman equation are phyially baed. They ue air temperature, olar radiation, humidity, wind peed and vegetation dynami, and impliitly onider the influene of feedbak among foring meteorologial variable, vegetation and evaporation (MViar et al., 2007b). Thi paper ompare ue of the P-M and S-W equation over the Mekong and Yellow river bain, a humid and a emi-arid region, repetively, at a monthly time-tep for the period METHOD The FAO-56 Penman-Monteith equation The P-M equation treat the vegetation anopy a a ingle uniform over, or big-leaf. Here, the tandard P-M equation wa applied to etimate evaporation of a hypothetial rop uing the form reommended in FAO-56 (Allen et al., 1998), referred to herein a referene evapotranpiration (RET, mm d -1, equation (1)). A hypothetial rop i aumed whih loely reemble an extenive urfae of green gra of uniform height (0.12 m), atively growing (anopy reitane of 70 m -1 ), ompletely hading the ground (albedo of 0.23) and with adequate water: 0.408Δ RET = ( Rn G) + 900γ u2 ( e ea ) ( T ) Δ + γ ( u ) 2 where R n and G are the net radiation above vegetation and the oil heat flux, repetively (MJ m -2 d -1 ); e and e a are the aturation and atual vapour preure, repetively (kpa); T i the mean air temperature ( C); u 2 i the wind peed at 2 m height (m -1 ); Δ i the urve lope of the relationhip between aturation vapour preure and air temperature (kpa C -1 ); and γ i the pyhrometri ontant (kpa C -1 ). The alulation of eah term in equation (1) i given by Allen et al. (1998). Shuttleworth-Wallae equation A an extenion of the P-M equation, the S-W model onider dual oure, namely tranpiration from vegetation and evaporation from underlying oil (Shuttleworth & Wallae, 1985): λ ET = C ET + C ET (2) where ET i the total evapotranpiration (mm d -1 ); λ i the latent heat of water vaporization (MJ kg -1 ); ET and ET are equivalent to tranpiration and evaporation by applying the P-M model to a loed anopy and bare ubtrate, repetively (MJ m -2 d -1 ); and C and C are weighting oeffiient a funtion of reitane. The formulation of all term in equation (2) i given a: ET ET Δ = Δ = a ( Rn G) + [( ) ρ p ( e ea ) Δra ( Rn G) ] ( ra + ra ) a Δ + γ [ 1 + r ( )] ra + ra a ( Rn G) + [( ) ρ p ( e ea ) Δra ( Rn Rn )] ( ra + ra ) a Δ + γ [ 1 + r ( r + r )] a a (1) (3) (4)

4 Evapotranpiration in the Mekong and Yellow river bain 625 C C R R R 1 = 1 + ( R R ) [ R ( R + R )] = a ( R R ) [ R ( R + R )] a ( Δ + γ ) a a r a a a = (7) ( Δ + γ ) r + γ r = (8) ( Δ + γ ) r + γ r a a = (9) where R n i the net radiation over the oil urfae (MJ m -2 d -1 ); ρ i the mean air denity (kg m -3 ); p i the peifi heat of moit air (MJ kg -1 o C -1 ); r and r a are the bulk tomatal and boundary layer reitane of the anopy, repetively; r a and r a a are the aerodynami reitane between the oil and anopy and between the anopy and referene height, repetively; and r i the urfae reitane of oil; all reitane are in m -1. Detailed parameterization of the S-W model i preented in Zhou et al. (2006, 2007). Vegetation leaf area index The vegetation leaf area index (LAI) i ued intenively in S-W parameterization. The LAI for eah vegetation la an be derived from NOAA-AVHRR NDVI through FPAR (Myneni & William, 1994; Seller et al., 1994; Anderen et al., 2002). Here the SiB2 method i ued (Seller et al., 1996): 1 + NDVI SR = (10) 1 NDVI min ( SR SR min ) ( FPAR max FPAR min ) ( SR max SR min ) ln( 1 FPAR) FPAR FlLAImax ln( 1 FPAR max ) FPAR max FPAR = FPAR + (11) ( 1 ) LAI = F l LAI + (12) max where SR i the imple ratio of hemipheri refletane for the NIR (near-infrared) light to that for the viible light; FPAR i the fration of photo-ynthetially ative radiation; F l i the fration of lumped vegetation; SR min and SR max are SR with 5% and 98% of NDVI population. The value of F l, NDVI at 5% and 98% population are adopted from SiB2 for all vegetation type (NDVI at 5% etting to globally, F l and NDVI at 98%); FPAR min = and FPAR max = refer to the atellite-ened NDVI aturation (Seller et al., 1996). LAI max i the maximum LAI when the vegetation develop fully, preribed for eah vegetation (f. Zhou et al., 2006). (5) (6) STUDY REGION DESCRIPTION The Mekong River (Fig. 1) i the longet river in Southeat Aia and the 12th longet river in the world, with a length of 4800 km, a drainage area of km 2 (WRI et al., 2003), and annual runoff of m 3. It originate on the Tibetan Plateau and flow outhward through China, Myanmar, Lao, Thailand, Cambodia and Vietnam, before it diharge into the South China Sea. The Upper Mekong River (1600 km, from the Tibetan Plateau to the Thailand Myanmar border), alled the Lanang River in China, drop rapidly by about 4500 m through a erie of large mountain range. After exiting China and entering the Golden Triangle (an area of around km 2 extending over four ountrie: Myanmar, Lao, Vietnam and Thailand), it i alled the Lower Mekong River, having a gentler lope. The limate of the upper Mekong River bain i

5 626 Maihun Zhou et al. Fig. 1 The Mekong and Yellow river bain: main tream, IGBP land over (1-km reolution), and eleted point.

6 Evapotranpiration in the Mekong and Yellow river bain 627 high-mountain old with mean annual preipitation from about 300 mm at it oure on the Tibetan Plateau to 1600 mm before it enter the Golden Triangle (Xi, 1988; Li et al., 2002). The lower Mekong River i ituated in the tropi and i dominated by two ditint monoon: the outhwet monoon from the Indian Oean from mid-may to mid-otober with frequent rainfall, and the northeat monoon from China from mid-otober to April, with a dry pell. The mean annual rainfall in the lower Mekong River range from 1000 mm in northeat Thailand to more than 3200 mm in the mountainou region in Lao (Kite, 2001), and around 85 90% of the rain fall during the rainy eaon. The Yellow River (Fig. 1) i the eond longet river in China, with a length of 5464 km, draining an area of km 2, and with an annual runoff of m 3 (Li, 2003). The Yellow River i divided into upper (2119 km, from the oure to Lanzhou), middle (2571 km, from Lanzhou to Zhengzhou) and lower (774 km, from Zhengzhou to the Bo Hai Sea) reahe. The upper reah wind around a erie of large mountain range on the eatern Tibetan Plateau with a bain-average elevation of about 4000 m, falling more than 3300 m. Downtream of Lanzhou, the river make a large northern loop through the alluvial plain and the Loe Plateau to Tongguan, piking up more than 90% of it ilt load (3 kg m -3 at Lanzhou inreaing to 35 kg m -3 at Tongguan). The lower reah i narrow and flow within levee and dike whih have been ontruted over the pat 2000 year. Sediment depoition from the highly eroive Loe Plateau ha ontinuouly inreaed the height of the river bed. In plae, the river bed i 20 m above the urrounding land urfae (MViar et al., 2007a). The Yellow River bain ha an arid and emiarid ontinental monoon limate. In the upper bain, the temperature i low throughout the year and depend on the elevation in a ompliated way. In the middle bain, the temperature dereae from outh to north and from eat to wet, and i affeted by loal mountain and deert. In the lower bain, the limate i dry and windy in pring, hot and wet in ummer, dry in autumn, and moderately old and dry in winter. The annual preipitation i between 200 and 650 mm over the bain, being greater in the lower bain and in the outhern portion of the upper and middle bain. DATA SOURCES In order to apply the P-M and S-W model, topographi data, harateriti of land over and meteorologial data are required. Topographi data The P-M and S-W equation ue a digital elevation model (DEM) to alulate the value of atmopheri preure, mean air denity and pyhrometri ontant. The Hydro1K DEM wa downloaded ( and lipped to the bain defined by manual digitization from the DCW (Digital Chart of the World) ( edu/dw; Danko, 1992). It i a DEM developed at the US Geologial Survey (Earth Reoure Obervation Sytem, EROS) (Verdin & Greenlee, 1996). Original topography at 1-km reolution wa averaged to a 8-km 8-km grid, i.e. the ame reolution a the normalized differene vegetation index (NDVI). Land over The International Geophere-Biophere Programme (IGBP) land over data et i ued ( (ee Fig. 1). It wa derived from 1-km AVHRR (Advaned Very High Reolution Radiometer) data panning April 1992 to Marh 1993 (Loveland et al., 2000). The IGBP ategorize the global land over into 17 lae. To how the prevailing type, ome minor land over type are lutered into imilar type in Fig. 1. The original 1-km patial reolution wa aggregated to an 8-km grid aording to the mot ommon land over, keeping the general patial ditribution.

7 628 Maihun Zhou et al. NDVI data Monthly NOAA-AVHRR maximum NDVI ompoite data at 8-km grid reolution (ftp://daa. gf.naa.gov/data/avhrr/global_8km/; Tuker et al., 2005) wa obtained from 13 July 1981 to 21 September 2001, exept for a period with miing data from September to Deember The NDVI data for the bain were tranferred into Lambert Azimuthal Equal Area projetion. The monthly NDVI data are aumed to repreent the value for the middle day of the month. The average monthly NDVI data from 1981 to 2000 are ued during the period when data were miing. Meteorologial data The required meteorologial data inlude air temperature, relative humidity, radiation and wind peed. The CRU (Climate Reearh Unit, Univerity of Eat Anglia, UK) TS 2.0 data et provide monthly time erie of mean air temperature, diurnal air temperature range, loud over, and atual vapour preure on a degree grid (New et al., 1999, 2000). The wind peed wa mainly meaured at 10 m height (New et al., 1999). It hould be emphaized that meteorologial variable are topographially dependent. In etimation of RET and PET, the influene of topography hould be taken into aount (MViar et al., 2007b). In fat, the CRU TS 2.0 data et wa interpolated a a funtion of latitude, longitude and elevation (TBASE 5-min lat long global DEM at from tation data uing thin-plate pline (Huthinon, 1995) for the limati normal and angular ditane-weighted for the monthly anomalie relative to the mean in whih the influene of elevation wa ignored. The primary data variable ued inlude mean air temperature and the diurnal air temperature range, whih were ontruted diretly from tation obervation. The eondary variable ued inlude loud over and vapour preure, whih were ontruted by merging tation obervation (where available) with yntheti data derived from the gridded primary variable. In the yntheti data, loud over wa related to the diurnal air temperature range, and the atual vapour preure to the daily minimum air temperature (New et al., 2000). Thi way of deriving the eondary variable wa alo propoed by MViar & Jupp (1999). The monthly mean wind peed data are ued for the whole imulation period, we aknowledge that hange in RET and PET due to reently reported dereae in terretrial tropial and mid-latitude near-urfae wind peed (MViar et al., 2008) need to be aounted for when onidering longer temporal extent. The wind peed at the referene height (2 m height above the ground in FAO-56 and 2 m height above the vegetation anopy in S-W equation) i onverted uing a logarithmi profile over the weather tation ground and anopy urfae in that the internal boundary layer height of both urfae are mathed and a tep hange in urfae roughne i aumed (Brutaert, 1982, pp. 59 and 167; Federer et al., 1996). All the limati variable hange ignifiantly throughout the year and are non-uniformly ditributed aro the bain (figure not hown here). The CRU data et were extrated for the bain and tranferred into Lambert Azimuthal Equal Area projetion at 8-km reolution without interpolation. RESULTS AND DISCUSSION Comparion of patial ditribution and interrelationhip The bain-average RET and PET, hown in Fig. 2 for the period , reflet a imilar variability and trend in limate. About 70 80% of the inter-annual variability in bain-average PET an be explained by variation in limate (Fig. 3), the remaining 20 30% being determined by vegetation diverity and dynami whih are inorporated in the S-W model but not in the FAO-56 P-M method. However, the patial ditribution of RET and PET are trikingly different (Fig. 4). The RET reflet the three limati pattern over the individual bain: upper, middle and

8 Evapotranpiration in the Mekong and Yellow river bain 629 (a) (b) Fig. 2 Year-to-year hange of annual RET (left) and PET (right) over the whole bain and at three eleted point for : (a) Mekong River bain; and (b) Yellow River bain. lower. On the other hand, thee limati pattern are not o learly diplayed in the PET ditribution, but the effet of vegetation i more obviou. Over the Tibetan Plateau of the Mekong River bain, where the atual vegetation of graland ha a lower LAI than the hypothetial referene rop, RET i higher than PET beaue a lower LAI mean more unovered oil urfae and the oil urfae reitane ued in PET i muh higher than the referene rop reitane (500 m -1 v 70 m -1, Zhou et al., 2006). Over the Lower Mekong River bain where the large foret area ha a higher LAI than the hypothetial referene rop, RET i lower than PET beaue a high LAI mean that oil urfae i overed well and the ombined reitane of the foret and oil urfae i mall (high LAI reduing the bulk tomatal reitane of foret anopy ignifiantly, f. Zhou et al., 2006). The vegetation phenology and LAI alo affet the land urfae albedo, hene R net. The etimate of RET i lower by 120 mm/year (or only 1.7%) than bain-averaged PET. Over the Yellow River bain, with few foret (Fig. 1) and hort vegetation with lower LAI (due to water hortage), RET i muh higher than PET, by 300 mm/year (or about 50%). Three peifi loation repreenting typial vegetation type were invetigated in greater detail, namely, gra (Point 1), foret (Point 2) and rop (Point 3) (ee Fig. 1). The year-to-year

9 630 Maihun Zhou et al. (a) (b) Fig. 3 Relationhip between annual RET and PET over the whole bain and at three eleted point for : (a) Mekong River bain; and (b) Yellow River bain. hange in both RET and PET are imilar at the gra and foret point in the Mekong, and at all three point in the Yellow, i.e. when RET inreae, in mot ae PET alo inreae, and vie vera (ee Fig. 2). But at the rop point over the Mekong, the variation of amplitude in annual PET i not o large a in annual RET during , probably beaue the gra and foret are natural wherea the rop i alo affeted by irrigation, ultivation and human maintenane, with a heavy weight in the Mekong but a lower weight in the Yellow ompared with the limate ontrol. However, the inter-annual hange are larger in PET than in RET at the three point in the Mekong, and at the gra and foret point in the Yellow. Poible explanation are that: (a) vegetation type amplified or diminihed the limati effet on PET (e.g. foret v rop, or gra in the Tibetan Plateau v rop); and (b) vegetation dynami ating a a feedbak foring meteorologial ontrol hanged the limati effet on PET (ee the following etion). Impliation of ylial S-W etimate over Yellow River bain The value of PET at the foret and rop point in the Yellow River bain hange ylially, driven by the eaonal preipitation effet on the vegetation development. To how thi, the relationhip between eaonal vegetation LAI and eaonal preipitation i analyed over a large area (i.e. the whole Loe Plateau in the middle reahe of Yellow River (Fig. 5) in order to avoid the fat that the point vegetation i eaily affeted by loal and urrounding fator (e.g. runoff from neighbouring grid)). The foret point i loated on the Loe Plateau and the rop point i loe to the Loe Plateau. The vegetation LAI over the Loe Plateau in the middle Yellow River i etimated from NDVI data in equation (10) (12). The regional average preipitation i alulated from the weather tation obervation (blak point, Fig. 5) uing the Thieen polygon method. A hown in Fig. 6(), the point vegetation LAI in warm and wet eaon (LAI wet ) hange imilarly to the Loe Plateau vegetation LAI wet but not exatly ine the point are loated in the outh of the Plateau (more preipitation). Comparing LAI wet of the Loe Plateau in Fig. 6() with the preipitation in Fig. 6(d) (f), the vegetation LAI i not muh related to the preipitation in the ame period (P wet ) but i well related to the anteedent preipitation in old and dry eaon (P dry ). The old and dry eaon refer to Otober April while the warm and wet eaon i May September. The regreion R 2 i for LAI wet v P dry (Fig. 6(a)), but for LAI wet v P wet (Fig. 6(b)). Comparing Fig. 6() with Fig. 6(d), LAI wet and P dry have imilar hange trend, but LAI wet and P wet (or P wet + P dry ) do not have thi loe relationhip (Fig. 6() v Fig. 6(e), or Fig. 6() v Fig. 6(f)). Suh a relationhip an only be explained a follow: due to low potential evapo-

10 Evapotranpiration in the Mekong and Yellow river bain 631 (a) (b) Fig. 4 Spatial ditribution of annual (a) RET and (b) PET averaged over for the Mekong (left) and Yellow (right) river bain. tranpiration in the dry and old eaon, mot of preipitation infiltrate in favour of eed germination and new bud development in pring; wherea in the warm and rainy eaon, with intene rainfall and the ruted loe oil, mot of the preipitation load fluhe into the river and the little infiltration i onumed quikly by the trong potential evapotranpiration. Table 1 how that: average value of LAI wet for 1980 and 1990 were imilar beaue P dry wa almot the ame although P wet wa different. Figure 6() and (d) and Table 1 how peifi year with dry or wet

11 632 Maihun Zhou et al. Fig. 5 The Loe Plateau in the middle reahe of the Yellow River bain (haded) and raingauge (blak point). winter. In 1982, 1985, 1999 and 2000, with a dry anteedent winter, P dry wa below 80 mm and LAI wet wa very low; wherea in the year 1984, 1990, 1994 and 1998, with a wet anteedent winter, P dry wa larger than 110 mm and LAI wet wa high. Preipitation in winter (P dry ) primarily ontrol vegetation ondition in ummer. Preipitation in ummer (P wet ) i a eondary ontrolling fator, e.g. in 1985 LAI wet wa a little higher due to high P wet depite low P dry in thi dry-winter year, and in 1994 LAI wet wa a little lower due to low P wet depite high P dry in thi wet-winter year. High LAI tranlate into high PET. Over the middle Yellow River bain, vegetation LAI i higher only in ummer, while in winter, it i very low. Empirial relationhip between FAO-56 P-M and S-W The ue of the FAO-56 method i impler, and the relation between annual RET and PET i linear over the bain and at the eleted point. Thi enourage a earh for a relationhip between monthly RET and PET uing a more robut tatitial analyi. In addition to the vegetation type, the LAI i the only fator ued in the S-W model but not ued in the FAO-56 method. A multiple regreion analyi (SPSS oftware) wa made by ategorizing the vegetation type. Beaue the power funtion wa found to have good R 2 for all land over and it atifie PET = 0 when RET = 0, the dependent variable wa ued a ln(pet) and the independent variable were: IGBP land over, ln(ret), LAI and CRU limati variable. In order to redue the amount of data but not loe their tatitial attribute, not all ell data of thee variable were ued but were randomly ampled for regreion analyi over the individual bain. Of all the limati variable, only ue of monthly preipitation and daily mean temperature in the Mekong River bain, and ue of daily mean temperature in the Yellow River bain notieably improved the value of R 2 in the regreion. Other variable gave only marginal improvement. A linear relationhip deribe the trend between LAI and ln(pet) in the Mekong River bain, e.g. in the ae of vegetation Group V (Fig. 7(a)). In the Yellow River bain, thi relationhip eem to be a ombination of linear and power funtion of LAI, e.g. in the ae of vegetation Group III (Fig. 7(b)). The number in the legend braket in Fig. 7 are the data amount ampled in the individual bain during (alo ee Sample olumn for the ame vegetation group in Table 2). The regreion wa made by inorporating LAI in the Mekong and a ombination of LAI and LAI in the Yellow, where wa determined by applying the SPSS Nonlinear Regreion proedure with a funtion of ln(pet) = a + b LAI for eah group. The multiple regreion reult are lited in Table 2. The

12 Evapotranpiration in the Mekong and Yellow river bain 633 LAI wet (a) LAI wet = P dry R 2 = (b) LAI wet = P wet R 2 = P dry (mm) () Point2 (Foret) P wet (mm) LAI wet Point3 (Cropland) P dry (mm) P wet (mm) P dry +P wet (mm) (d) (e) (f) Loe Plateau Year Fig. 6 Vegetation LAI wet and preipitation during over the Loe Plateau: (a) regreion relationhip between LAI wet and P dry ; (b) regreion relationhip between LAI wet and P wet ; () LAI wet ; (d) P dry ; (e) P wet ; and (f) P dry +P wet. predition error, equal to {(PET predited from the regreion relationhip between PET v RET and/or other variable) (PET etimated uing the S-W model)}/(pet etimated uing the S-W model) are hown in Fig. 7() for January Deember in randomly eleted year between 1981 and 2000 when NDVI data are available. Generally, by inorporating LAI, the quality of the

13 634 Maihun Zhou et al. Table 1 Seaonal vegetation LAI and preipitation over the Loe Plateau. Year LAI wet P dry (mm) P wet (mm) (dry winter) (dry winter) (dry winter) (dry winter) (wet winter) (wet winter) (wet winter) (wet winter) (a) 2.0 (b) ln(pet) (mm/day) Group V in Mekong ln(pet) = LAI R 2 = Cropland (8345) Cropland/Natural Vegetated Moai (1449) () LAI ln(pet) (mm/day) Group III in Yellow Linear: R 2 = ln(pet) = LAI Combination: R 2 = ln(pet) = LAI LAI Mekong Point 1 Point 2 Point 3 Yellow Point 1 Point 2 Point 3 LAI Cloed Shrubland (501) Woody Savanna (249) Savanna (21) Cropland (2629) Cropland/Natural Vegetated Moai (2797) 15 Error (%) LAI Fig. 7 Satter plot between logarithmi PET and LAI (a) for vegetation Group V in Mekong; (b) for vegetation Group III in Yellow; and () predition error of multiple regreion on three eleted point orreponding to LAI.

14 Evapotranpiration in the Mekong and Yellow river bain 635 Table 2 Multiple regreion between PET (mm d -1 ), RET (mm d -1 ), limati variable and LAI. Category Land over (IGBP ode) Sample (a) Mekong River bain ln(pet) = b0 + b1 ln(ret) + b2 Var + b3 LAI Var b0 b1 b2 b3 R 2 σ Copyright 2007 IAHS Pre Group I Evergreen needleleaf foret (2) 4811 P Deiduou broadleaf foret (4) 1359 Mixed foret (5) 3077 Group II Cloed hrubland (6) 536 T Group III Woody avanna (8) 613 No Group IV Open hrubland (7) 123 T Graland (10) 2456 Barren or parely vegetated (16) 2 Group V Cropland (12) 8345 No Cropland/natural vegetation moai (14) 1449 Group VI Water bodie (17) 229 No (b) Yellow River bain ln(pet) = b0 + b1 ln(ret) + b2 T + b3 LAI + b4 LAI b0 b1 b2 b3 b4 R 2 σ Group I Deiduou needleleaf foret (2) Deiduou broadleaf foret (4) 462 Group II Mixed foret (5) Group III Cloed hrubland (6) Woody avanna (8) 249 Savanna (9) 21 Cropland (12) 2629 Cropland/natural vegetation moai (14) 2797 Group IV Open hrubland (7) Graland (10) Barren or parely vegetated (16) 110 Urban and built-up (13) 7 Group V Water bodie (17) P: monthly preipitation (mm month -1 ); T: daily mean temperature ( C); No: no limate variable ignifiantly involved; σ: tandard error (mm d -1 ). Evapotranpiration in the Mekong and Yellow river bain 635

15 636 Maihun Zhou et al. predition i improved, but large error perit whih are unrelated to LAI. We were unable to fit a good funtion to aount for the trongly nonlinear relationhip between PET and LAI and found no aurate tatitial relationhip between PET and RET. Limited validation of S-W etimate with available field data Nobuhiro et al. (2008) meaured the evapotranpiration in the O Thom I waterhed of the Mekong River bain in Cambodia, where the vegetation i a relatively unditurbed evergreen broadleaf foret with mean and maximum tree height of 27.2 and 45.1 m, repetively. By uing the heat balane method (inorporating the Bowen ratio) (Hattori, 1985), the average daily evapotranpiration wa etimated to be 4.45 mm d -1. During , average PET wa etimated to be 7.2, 4.3 mm d -1 in Marh and Otober, repetively, and 5.3 mm d -1 for the whole year. Average RET wa etimated to be 5.0 mm d -1 in Marh, 3.4 mm d -1 in Otober, and 3.94 mm d -1 for the whole year. Obviouly, ompared to the etimate of RET, the etimate of PET are loer to the field meaurement. The Yellow River bain i loated in a emi-arid region. It i diffiult to find a waterhed where the LAI of the vegetation over i at a high level and oil moiture approahe field apaity for a period long enough to arry out an experiment for potential evapotranpiration meaurement. Even though there i heavy rainfall (high intenity in a hort time) in ummer (MViar et al., 2007b), mot of it fluhe into the river a urfae flow and the low infiltration i quikly exhauted by the high potential evapotranpiration. However, at the rop point (Point 3), the larget annual PET etimated from the S-W model orrepond to the mot evere drought year in the lat entury (OSFCDRH and NWRHI, 1997). Another way to validate the etimate of PET i by applying the water balane equation to a wet bain, i.e. ET = P Q, where all element are bain-averaged annual value (Donohue et al., 2007). When the bain i wet, the environment i energy-limited and ET an repreent PET. However, our databae i not uffiient to upport thi analyi. CONCLUSIONS Thi tudy provide etimate of potential evapotranpiration a input to drive hydrologial modelling of large river bain in poorly monitored or ungauged region. The etimate of RET and PET over the Mekong and Yellow River bain are patially very different. The etimate of FAO-56 P-M i a good integrated limati index whih i able to reflet the temporal hange and patial ditribution of limate, and the S-W etimate reflet the limate variability and the vegetation ditribution and development. Preliminary invetigation into the relationhip between FAO-56 P-M and S-W etimate ugget that developing an empirial relationhip between them may be worthwhile. Large preditive error exit beaue of the trong nonlinearity and atter between PET and the LAI of the vegetation. Available relevant field data are very are, and the only available data ugget that the S-W etimate may be more realiti. Conequently, ue of the S-W model, albeit more omplex, i reommended beaue of it more robut phyial bai, and beaue it uefully aount for the effet of hanging land urfae ondition on PET. The etimated PET derived in thi manner an be ued to provide a diret input to hydrologial model without the need to ue empirial pan or rop oeffiient, whih would be required if pan evaporation or RET were ued. It wa found that vegetation ondition in ummer i primarily ontrolled by the regional anteedent preipitation in the preeding old and dry eaon over the Loe Plateau in the middle reahe of the Yellow River. Aknowledgement We are pleaed to aknowledge the finanial upport of the Core Reearh for Evolutional Siene and Tehnology (CREST) Program of the Japan Siene and Tehnology

16 Evapotranpiration in the Mekong and Yellow river bain 637 Corporation (JST) through the reearh projet of Sutainable waterhed management in the Yellow River, of the Minitry of Eduation, Culture, Sport, Siene and Tehnology (MEXT), Japan, through the reearh projet of RR2002(6): Model development, imulation and aement on the effet of human ativitie and natural hange on the water reoure in Mekong River bain, of the Preident Sientifi Fund of South China Agriultural Univerity through the reearh projet Development of a ditributed waterhed hydrologial model and integrated management of water reoure (7600-K07050), and of the Department of Eduation of Guangdong Provine through the reearh projet Non-point oure pollution of Hanjiang River bain and the ditributed hydrologial and environmental imulation ( ). We would like to expre our appreiation to two anonymou referee for their thorough review and inightful omment that greatly improved our final manuript. REFERENCES Allen, R. G., Pereira, L. 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