We propose a long-term parameterization scheme for two critical parameters, zero-plane displacement height (d) and aerodynamic roughness length (z0m), that we further use in the Surface Energy Balance System (SEBS). A sensitivity analysis of SEBS indicated that these two parameters largely impact the estimated sensible heat and latent heat fluxes. First, we calibrated regression relationships between measured forest vertical parameters (Lorey’s height and the frontal area index (FAI)) and forest aboveground biomass (AGB). Next, we derived the interannual Lorey’s height and FAI values from our calibrated regression models and corresponding forest AGB dynamics that were converted from interannual carbon fluxes, as simulated from two incorporated ecological models and a 2009 forest basis map These dynamic forest vertical parameters, combined with refined eight-day Global LAnd Surface Satellite (GLASS) LAI products, were applied to estimate the eight-day d, z0m, and, thus, the heat roughness length (z0h). The obtained d, z0m and z0h were then used as forcing for the SEBS model in order to simulate long-term forest evapotranspiration (ET) from 2000 to 2012 within the Qilian Mountains (QMs). As compared with MODIS, MOD16 products at the eddy covariance (EC) site, ET estimates from the SEBS agreed much better with EC measurements (R2 = 0.80 and RMSE = 0.21 mm·day−1).

Time series of regional 2° × 2° Gravity Recovery and Climate Experiment (GRACE) solutions of surface water mass change have been computed over Africa from 2003 to 2012 with a 10-day resolution by using a new regional approach. These regional maps are used to describe and quantify water mass change. The contribution of African hydrology to actual sea level rise is negative and small in magnitude (i.e., −0.1 mm/y of equivalent sea level (ESL)) mainly explained by the water retained in the Zambezi River basin. Analysis of the regional water mass maps is used to distinguish different zones of important water mass variations, with the exception of the dominant seasonal cycle of the African monsoon in the Sahel and Central Africa. The analysis of the regional solutions reveals the accumulation in the Okavango swamp and South Niger. It confirms the continuous depletion of water in the North Sahara aquifer at the rate of −2.3 km3/y, with a decrease in early 2008. Synergistic use of altimetry-based lake water volume with total water storage (TWS) from GRACE permits a continuous monitoring of sub-surface water storage for large lake drainage areas. These different applications demonstrate the potential of the GRACE mission for the management of water resources at the regional scale.

This volume provides in-depth coverage of the latest in remote sensing of hydrological extremes: both floods and droughts. The book is divided into two distinct sections floods and droughts and offers a variety of techniques for monitoring each. With rapid advances in computer modelling and observing systems, floods and droughts are studied with greater precision today than ever before. Land surface models, especially over the entire Continental United States, can map the hydrological cycle at kilometre and sub-kilometre scales. In the case of smaller areas there is even higher spatial resolution and the only limiting factor is the resolution of input data. In-situ sensors are automated and the data is directly relayed to the world wide web for many hydrological variables such as precipitation, soil moisture, surface temperature and heat fluxes. In addition, satellite remote sensing has advanced to providing twice a day repeat observations at kilometre to ten-kilometre spatial scales. We are at a critical juncture in the study of hydrological extremes, and the GPM and SMAP missions as well as the MODIS and GRACE sensors give us more tools and data than were ever available before. A global variety of chapter authors provides wide-ranging perspectives and case studies that will make this book an indispensable resource for researchers, engineers, and even emergency management and insurance professionals who study and/or manage hydrological extremes.

The estimation of large-scale evapotranspiration (ET) is complex, and typically relies on the outputs of land surface models (LSMs) or remote sensing observations. However, over some regions of Africa, inconsistencies exist between different estimations of ET fluxes, which should be investigated. In this study, we evaluate and combine different ET estimates from moderate-resolution imaging spectroradiometer (MODIS), Global Land Data Assimilation System (GLDAS) and terrestrial water budget (TWB) approaches over the Volta Basin, West Africa. ET estimates from water balance equation are obtained as residuals from monthly terrestrial water-storage (TWS) changes derived from Gravity Recovery and Climate Experiment (GRACE), Tropical Rainfall Measurement Mission (TRMM)'s rainfall data, and in situ discharge from Akosombo Dam (Ghana). An averaged estimation of ET time series is derived from all the ET estimations under study, while taking into account their uncertainties. The resulting ensemble-averaged ET was then used to assess each of the individual ET estimates. Overall, out of the seven investigated ET estimates (two from the water balance approach of which one considers water storage using GRACE-derived TWS and the other ignoring it, four from GLDAS and one from MODIS), only MODIS (28.12 mm month–1), GLDAS–NOAH (32.74 mm month–1) and TWB (32.84 mm month–1) were found to represent the range of variability close to the computed averaged reference ET (30.25 mm month–1). ET estimations inferred from MODIS were also found to represent relatively lower magnitude of uncertainties, that is, 3.99 mm month–1 over the Volta Basin (cf. 7.06 and 18.85 mm month–1 for GLDAS-NOAH and TWB-based ET estimations, respectively).

The complexity involved in accurate estimation and numerical simulation of regional evapotranspiration (ET) can lead to inconsistency among techniques, usually attributed to methodological deficiencies. Here we hypothesize instead that discrepancies in ET estimates should be expected in some cases and can be applied to measure the effect of anthropogenic influences in developed river basins. We compare an ensemble of corrected ET estimates from land surface models with Gravity Recovery and Climate Experiment and Moderate Resolution Imaging Spectroradiometer satellite‐based estimates in the intensively managed Colorado River Basin to contrast the roles of natural variability and human impacts. Satellite‐based approaches yield larger annual amplitudes in ET estimates than land surface model simulations, primarily during the growing season. We find a total satellite‐based ET flux of 142 ± 7 MAF yr−1 (175 ± 8.63 km3 yr−1), with 38% due to anthropogenic influences during summer months. We evaluate our estimates by comparison with reservoir storage and usage allotment components of the basin water management budget.

The availability of hydrologic components data is an important step for hydrological modeling and water resource management in the world, e.g., Runoff. Unfortunately, the in situ observations are very sparse globally, particularly in Africa. In this paper, Runoff variations in the Nile River Basin (NRB) estimated and investigated from Gravity Recovery and Climate Experiment (GRACE) from January 2003 to August 2016 based on water balance equation as well as other satellite measurements. The longtime, seasonal, and interannual variations of runoff are studied. Also, the monthly variations of runoff from GRACE are compared with runoff products from the MODerate Resolution Imaging Spectroradiometer (MODIS), which shows a moderate coincidence with the runoff from the Global Land Data Assimilation Systems (GLDAS) and MERRA-2 with the correlation coefficient of 0.67 and 0.62, respectively.

The Yanqi basin is the main irrigated and active agroecosystem in semi-arid Xinjiang, northwestern China, which further seeks responses to the profound local water-related drawbacks in relation to the unceasing landscape desiccation and scant precipitation. Yet, it comes as an astonishment that a few reported near-surface items and water vapor fluxes as so far required for water resources decision support, particularly in a scarce observation data region. As a contributive effort, here we adjusted the sensible heat flux (H) calibration mechanism of Surface Energy Balance Algorithm for Land (SEBAL) to high-resolution satellite dataset coupled with in-situ observation, through a wise guided “anchor” pixel assortment from surface reflectance-α, Leaf area index-LAI, vegetation index-NDVI, and surface temperature (Pcold, Phot) to model the robustness of energy fluxes and Evapotranspiration-ETa over the basin. Results reasonably reflected ETa which returned low RMSE (0.6 mm d−1), MAE (0.48 mm d−1) compared to in-situ recordings, indicating the competence of SEBAL to predict vapor fluxes in this region. The adjustment unveiled the estimates of the land-use contribution to evapotranspiration with an average ranging from 3 to 4.69 mm d−1, reaching a maximum of 5.5 mm d−1. Furthermore, findings showed a high striking energy dissipation (LE/Rn) across grasslands and wetlands. The vegetated surfaces with a great evaporative fraction were associated with the highest LE/Rn (70–90%), and water bodies varying between 20% and 60%, while the desert ecosystem dissipated the least energy with a low evaporative fraction. Still, besides high portrayed evaporation in water, grasslands and wetlands varied interchangeably in accounting for the highest ETa followed by cropland. Finally, a substantial nexus between available energy (Rn-G) and ETa informed the available energy, influenced by NDVI to be the primary driver of these oases’ transpiration. This study provides essentials of near-surface energy fluxes and the likelihood of ETa with considerable baseline inferences for Yanqi that may be beneficial for long-term investigations that will attend in agrometeorological services and sustainable management of water resources in semi-arid regions.

The Northern Sub-Saharan African (NSSA) region, which accounts for 20%-25%of the global carbon emissions from biomass burning, also suffers from frequent drought episodes and other disruptions to the hydrological cycle whose adverse societal impacts have been widely reported during the last several decades. This paper presents a conceptual framework of the NSSA regional climate system components that may be linked to biomass burning, as well as detailed analyses of a variety of satellite data for 2001-2014 in conjunction with relevant model-assimilated variables. Satellite fire detections in NSSA show that the vast majority (greater than 75%) occurs in the savanna and woody savanna land-cover types. Starting in the 2006-2007 burning season through the end of the analyzed data in 2014, peak burning activity showed a net decrease of 2-7% /yr in different parts of NSSA, especially in the savanna regions. However, fire distribution shows appreciable coincidence with land-cover change. Although there is variable mutual exchange of different land cover types, during 2003-2013, cropland increased at an estimated rate of 0.28% /yr of the total NSSA land area, with most of it (0.18% /yr) coming from savanna.During the last decade, conversion to croplands increased in some areas classified as forests and wetlands, posing a threat to these vital and vulnerable ecosystems. Seasonal peak burning is anti-correlated with annual water-cycle indicators such as precipitation, soil moisture, vegetation greenness, and evapotranspiration, except in humid West Africa (5 deg-10 deg latitude),where this anti-correlation occurs exclusively in the dry season and burning virtually stops when monthly mean precipitation reaches 4 mm/d. These results provide observational evidence of changes in land-cover and hydrological variables that are consistent with feedbacks from biomass burning in NSSA, and encourage more synergistic modeling and observational studies that can elaborate this feedback mechanism.

Terrestrial water storage changes (TWSCs) retrieved from the Gravity Recovery and Climate Experiment (GRACE) satellite mission have been extensively evaluated in previous studies over large basin scales. However, monitoring the TWSC at small basin scales is still poorly understood. This study presented a new method for calculating TWSCs at the small basin scales based on the water balance equation, using hydrometeorological and multi-source data. First, the basin was divided into several sub-basins through the slope runoff simulation algorithm. Secondly, we simulated the evapotranspiration (ET) and outbound runoff of each sub-basin using the PML_V2 and SWAT. Lastly, through the water balance equation, the TWSC of each sub-basin was obtained. Based on the estimated results, we analyzed the temporal and spatial variations in precipitation, ET, outbound runoff, and TWSC in the Ganjiang River Basin (GRB) from 2002 to 2018. The results showed that by comparing with GRACE products, in situ groundwater levels data, and soil moisture storage, the TWSC calculated by this study is in good agreement with these three data. During the study period, the spatial and temporal variations in precipitation and runoff in the GRB were similar, with a minimum in 2011 and maximum in 2016. The annual ET changed gently, while the TWSC fluctuated greatly. The findings of this study could provide some new information for improving the estimate of the TWSC at small basin scales.

Terrestrial carbon and water cycles are interactively linked at various spatial and temporal scales. Evapotranspiration (ET) plays a key role in the terrestrial water cycle, altering carbon sequestration of terrestrial ecosystems. The study of ET and its response to climate and vegetation changes is critical in China because water availability is a limiting factor for the functioning of terrestrial ecosystems in vast arid and semiarid regions. To constrain uncertainties in ET estimation, the process-based Boreal Ecosystem Productivity Simulator (BEPS) model was employed in conjunction with a newly developed leaf area index (LAI) data set, MODIS land cover, meteorological, and soil data to simulate daily ET and water yield at a spatial resolution of 500 m over China for the period from 2000 to 2010. The spatial and temporal variations of ET and water yield were analyzed. The influences of climatic factors (temperature and precipitation) and vegetation (land cover types and LAI) on these variations were assessed. Validations against ET measured at five ChinaFLUX sites showed that the BEPS model was able to simulate daily and annual ET well at site scales. Simulated annual ET exhibited a distinguishable southeast to northwest decreasing gradient, corresponding to climate conditions and vegetation types. It increased with the increase of LAI in 74% of China's landmass and was positively correlated with temperature in most areas of southwest, south, east, and central China. The correlation between annual ET and precipitation was positive in the arid and semiarid areas of northwest and north China, but negative in the Tibetan Plateau and humid southeast China. The national annual ET varied from 345.5 mm in 2001 to 387.8 mm in 2005, with an average of 369.8 mm during the study period. The overall rate of increase, 1.7 mm yr(-1) (R-2 = 0.18, p = 0.19), was mainly driven by the increase of total ET in forests. During 2006-2009, precipitation and LAI decreased widely and consequently caused a detectable decrease in national total ET. Annual ET increased over 62.2% of China's landmass, especially in the cropland areas of the southern Haihe River basin, most of the Huaihe River basin, and the southeastern Yangtze River basin. It decreased in parts of northeast, north, northwest, south China, especially in eastern Qinghai-Tibetan Plateau, the south of Yunnan Province, and Hainan Province. Reduction in precipitation and increase in ET caused vast regions in China, especially the regions south of Yangtze River, to experience significant decreases in water yield, while some sporadically distributed areas experienced increases in water yield. This study shows that the terrestrial water cycles in China's terrestrial ecosystems appear to have been intensified by recent climatic variability and human induced vegetation changes.

Terrestrial Water Storage (TWS) data, now available for more than 15 years, as furnished by the Gravity Recovery and Climate Experiment (GRACE) satellite mission provided remarkable insights into the hydrological cycle. An expanding volume of scientific literature bears testimony to this. Besides identifying the alarming rate of both global groundwater storage depletion and polar ice cap melt, which are considered as its major accomplishments, the GRACE dataset also provided an exceptional resource for the improvement of the hydrological models. Such studies, although large in number, can be broadly classified into two categories: (1) Model evaluation studies, comparing regional or global model outputs with GRACE-derived hydrological parameters and (2) data assimilation techniques, where GRACE data is incorporated into the modeling framework. Model evaluation techniques vary in terms of the choice of hydrologic parameter, which in most cases is TWS or groundwater. On the other hand, data assimilation strategies in most of the studies use ensemble Kalman filter or its variant to incorporate the information derived from GRACE data into the models. This chapter reviews the integration methodologies highlighting the different aspects of model improvement such as the hydrologic parameter of interest, complexity of the model framework, and representation of hydrological processes. However, the present discussion is restricted to conceptual hydrological models and do not include statistical or GRACE-based water balance models.

Summary This study represents the first attempt to examine the spatial and seasonal variations of the surface water budget by using state-of-the-art datasets for sixteen large Canadian drainage basins with a total area of 3.2 million km2. The datasets used include two precipitation grids produced using measurements and reanalysis models, land surface evapotranspiration and water surface evaporation estimated using the EALCO model, streamflow measured at hydrometric stations, and total water storage change derived from GRACE satellite observations. The monthly water imbalance resulted from these datasets varied from 7.0 mm month−1 to 21 mm month−1 among the studied basins, which was 30% on average of the corresponding monthly precipitation. The accumulated water budget imbalance over the 7 years of 2002–2008 varied from close to zero to ±10 mm month−1. The positive and negative imbalances among the sixteen basins were largely offset and the all-basin imbalance was very close to 0. The uncertainties in precipitation, streamflow, evapotranspiration and total water storage change all contributed to the water budget imbalance and their relative magnitudes were found to vary with basin and season. In most cases, precipitation showed the largest uncertainties, which had similar magnitudes to the water budget imbalances. While improvements are noted in comparison with previous water budget studies over the regions, the water imbalance obtained for some basins is quite large, suggesting that considerable improvements in both the observation networks and models are necessary before the water budget closure can be substantially improved over this region.

Regional scale water management analysis increasingly relies on integrated modeling tools. Much recent work has focused on groundwater?surface water interactions and feedbacks. However, to our knowledge, no study has explicitly considered impacts of management operations on the temporal dynamics of the natural system. Here, we simulate twenty years of hourly moisture dependent, groundwater-fed irrigation using a three-dimensional, fully integrated, hydrologic model (ParFlow-CLM). Results highlight interconnections between irrigation demand, groundwater oscillation frequency and latent heat flux variability not previously demonstrated. Additionally, the three-dimensional model used allows for novel consideration of spatial patterns in temporal dynamics. Latent heat flux and water table depth both display spatial organization in temporal scaling, an important finding given the spatial homogeneity and weak scaling observed in atmospheric forcings. Pumping and irrigation amplify high frequency (sub-annual) variability while attenuating low frequency (inter-annual) variability. Irrigation also intensifies scaling within irrigated areas, essentially increasing temporal memory in both the surface and the subsurface. These findings demonstrate management impacts that extend beyond traditional water balance considerations to the fundamental behavior of the system itself. This is an important step to better understanding groundwater?s role as a buffer for natural variability and the impact that water management has on this capacity.

Precipitation minus evapotranspiration, the net flux of water between the atmosphere and Earth's surface, links atmospheric and terrestrial water budgets and thus represents an important boundary condition for both climate modeling and hydrological studies. However, the atmospheric-terrestrial flux is poorly constrained by direct observations because of a lack of unbiased measurements. Thus, it is usually reconstructed from atmospheric reanalyses. Via the terrestrial water budget equation, water storage estimates from the Gravity Recovery and Climate Experiment (GRACE) combined with measured river discharge can be used to assess the realism of the atmospheric-terrestrial flux in models. In this contribution, the closure of the terrestrial water budget is assessed over a number of European river basins using the recently reprocessed GRACE release 05 data, together with precipitation and evapotranspiration from the operational analyses of high-resolution, limited-area NWP models [Consortium for Small-Scale Modelling, German version (COSMO-DE) and European version (COSMO-EU)] and the new COSMO 6-km reanalysis (COSMO-REA6) for the European Coordinated Regional Climate Downscaling Experiment (CORDEX) domain. These closures are compared to those obtained with global reanalyses, land surface models, and observation-based datasets. The spatial resolution achieved with the recent GRACE data allows for better evaluation of the water budget in smaller river basins than before and for the identification of biases up to 25 mm month(-1) in the different products. Variations of deseasoned and detrended atmospheric-terrestrial flux are found to agree notably well with flux derived from GRACE and discharge data with correlations up to 0.75. Finally, bias-corrected fluxes are derived from various data combinations, and from this, a 20-yr time series of catchment-integrated water storage variations is reconstructed.

Over 50% of the world's population live within 3 km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future.

Lidar-measured snow depth and model-estimated snow density can be combined to map snow water equivalent (SWE). This approach has the potential to transform research and operations in snow-dominated regions, but sources of uncertainty need quantification. We compared relative uncertainty contributions from lidar depth measurement and density modeling to SWE estimation, utilizing lidar data from the Tuolumne Basin (California). We found a density uncertainty of 0.048 g cm 3 by comparing output from four models. For typical lidar depth uncertainty (8 cm), density estimation was the dominant source of SWE uncertainty when snow exceeded 60 cm depth, representing >70% of snow cover and 90% of SWE volume throughout the basin in both 2014 and 2016. Density uncertainty accounts for 75% of the SWE uncertainty for a broader range of snowpack characteristics, as measured at SNOTEL stations throughout the western U.S. Reducing density uncertainty is essential for improved SWE mapping with lidar.

Large-scale water balance in the Australian continent is examined over an 8-year period (2003–2010) with three commonly used satellite based water cycle components: precipitation (P) from the Tropical Rainfall Measuring Mission (TRMM), evapotranspiration (ET) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and terrestrial water storage change (ΔS) from the Gravity Recovery and Climate Experiment (GRACE). First we evaluate the water balance using the three products over areas with limited annual streamflow to eliminate the influence of runoff in the analysis. We observe more frequent and better closure and consistency in the water balance from the three components over the central part of Western Australia, where low precipitation, high elevation and low relief exist. The data are more coherent at seasonal and annual scales compared to the monthly scale. Application of the three products in Lake Eyre Basin (an internal drainage system) suggests a maximum 6.2 mm/year groundwater inflow to the basin, which is consistent with the regional groundwater flow direction in the area. This result also indicates that the absolute integrated error of the combination of three products should be smaller than 6.2 mm/year, which is about 2.1% of annual precipitation in the basin. If this relative error is assumed for the whole continent, water balance calculation using the three products over the whole Australian continent results in 144.7 ± 11.3 mm/year estimated total runoff to the surrounding oceans during the study period. We found that this estimate is comparable to the estimates of 50–150 mm/year from the Australian Bureau of Meteorology and National Water Commission.

GPS monitoring of solid Earth deformation due to surface loading is an independent approach for estimating seasonal changes in terrestrial water storage (TWS). In western United States (WUSA) mountain ranges, snow water equivalent (SWE) is the dominant component of TWS and an essential water resource. While several studies have estimated SWE from GPS-measured vertical displacements, the error associated with this method remains poorly constrained. We examine the accuracy of SWE estimated from synthetic displacements at 1,395 continuous GPS station locations in the WUSA. Displacement at each station is calculated from the predicted elastic response to variations in SWE from SNODAS and soil moisture from the NLDAS-2 Noah model. We invert synthetic displacements for TWS, showing that both seasonal accumulation and melt as well as year-to-year fluctuations in peak SWE can be estimated from data recorded by the existing GPS network. Because we impose a smoothness constraint in the inversion, recovered TWS exhibits mass leakage from mountain ranges to surrounding areas. This leakage bias is removed via linear rescaling in which the magnitude of the gain factor depends on station distribution and TWS anomaly patterns. The synthetic GPS-derived estimates reproduce approximately half of the spatial variability (unbiased root mean square error 50%) of TWS loading within mountain ranges, a considerable improvement over GRACE. The inclusion of additional simulated GPS stations improves representation of spatial variations. GPS data can be used to estimate mountain-range-scale SWE, but effects of soil moisture and other TWS components must first be subtracted from the GPS-derived load estimates.

Expert elicitation with the participation of 35 experts was used to estimate a water balance for the nested Ahlergaarde and Holtum catchments in Western Denmark. Average annual values of precipitation, evapotranspiration, and surface runoff as well as subsurface outflow and recharge and their uncertainty were estimated in a multistep elicitation, where experts first gave their opinion on the probability distribution of their water balance component of interest, then the average annual values and uncertainty of water balance components and catchment-scale water balances were obtained by reaching consensus during group discussions. The obtained water balance errors for the 1055 km2 Ahlergaarde catchment and 120 km2 Holtum catchment were −5 and −62 mm/yr, respectively, with an uncertainty of 66 and 86 mm/yr, respectively. As an advantage of the expert elicitation, drawing on the intuitive experience and capabilities of experts to assess complex, site-specific problems, the contribution of independent sources of uncertainties to the total uncertainty was also evaluated similarly to the subsurface outflow component, which traditionally is estimated as the residual of the water balance.

Evapotranspiration (ET) is one of the key variables in water cycle and ecological systems, whereas it is difficult to quantify ET variations from traditional observations in large river basins, e.g., Mississippi River basin (MRB). In this paper, a new geodetic tool, i.e., Global Positioning System (GPS), is used for the first time to estimate monthly ET variations at a regional scale. Based on the water balance equation, the monthly ET variation is estimated using the GPS-derived terrestrial water storage (TWS) from January 2006 to July 2015 in MRB. The annual amplitude of GPS-inferred TWS in MRB agrees well with the results of Gravity Recovery and Climate Experiment. The ET variations from the water balance approach agree well with the land surface modeling and remote sensing data. The correlation of GPS-inferred ET with other ET products is higher than 0.8, which indicates that the GPS-estimated ET well characterizes the ET variations in MRB. The annual amplitude of GPS-inferred ET variations is 47.9 mm/month, which is close to that from land surface modeling of North American Land Data Assimilation System, and a little larger than MODerate Resolution Imaging Spectroradiometer. The mean monthly ET reaches its maximum in June-July and its minimum in December, which is consistent with the periodic pattern of radiative energy in a year. Furthermore, the ET variations are mainly dominated by the temperature change in MRB.