Spatial Patterns Of Evapotranspiration Research Articles

Tradeoffs Between Temporal and Spatial Pattern Calibration and Their Impacts on Robustness and Transferability of Hydrologic Model Parameters to Ungauged Basins

AbstractOptimization of spatially consistent parameter fields is believed to increase the robustness of parameter estimation and its transferability to ungauged basins. The current paper extends previous multi‐objective and transferability studies by exploring the value of both multi‐basin and spatial pattern calibration of distributed hydrologic models as compared to single‐basin and single‐objective model calibrations, with respect to tradeoffs, performance and transferability. The mesoscale Hydrological Model (mHM) is used across six large central European basins. Model simulations are evaluated against streamflow observations at the basin outlets and remotely sensed evapotranspiration patterns. Several model validation experiments are performed through combinations of single‐ (temporal evaluation through discharge) and multi‐objective (temporal and spatial evaluation through discharge and spatial evapotranspiration patterns) calibrations with holdout experiments saving alternating basins for model evaluation. The study shows that there are very minimal tradeoffs between spatial and temporal performance objectives and that a joint calibration of multiple basins using multiple objective functions provides the most robust estimations of parameter fields that perform better when transferred to ungauged basins. The study indicates that particularly the multi‐basin calibration approach is key for robust parametrizations, and that the addition of an objective function tailored for matching spatial patterns of ET fields alters the spatial parameter fields while significantly improving the spatial pattern performance without any tradeoffs with discharge performance. In light of model equifinality, the minimal tradeoff between spatial and temporal performance shows that adding spatial pattern evaluation to the traditional temporal evaluation of hydrological models can assist in identifying optimal parameter sets.

A framework for estimating actual evapotranspiration through spatial heterogeneity-based machine learning approaches

Actual evapotranspiration (ET) is a key variable controlling the exchange of energy and water in terrestrial ecosystems. The spatial heterogeneity of ET patterns poses a great challenge for regional ET estimation over heterogeneous landscapes. In this study, we proposed a framework for estimating ET through interactive detector for spatial associations (IDSA)-based machine learning (ML) approaches by combining data from remote sensing and four flux towers distributed in the Hai River Basin. The IDSA model was applied to explore individual and interactive determinants of ET over the Hai River Basin. In addition, the geographical regions of ET were determined according to the spatial heterogeneity. Then we simulated ET in each geographical region separately using three ML models, including random forest, gradient boosting decision tree, and Cubist. General ML models without considering spatial heterogeneity were used for comparison, and evaluations were conducted with the eddy covariance flux tower observations at the site scale, also with water balance ET at the basin scale. The results demonstrated that the spatial patterns of ET were difficult to be explained by individual environmental variables (64.9 %). The maximum interpretability was improved by about 11.2 % through the interaction of air temperature (T) and normalized different vegetation index (NDVI). The framework developed in this study had excellent performance with coefficient of determination (R2) ranging from 0.807 to 0.811, root mean square error (RMSE) ranging from 0.654 mm/day to 0.661 mm/day, and mean absolute error (MAE) ranging from 0.470 mm/day to 0.485 mm/day. It was superior to general ML models at the site and basin scales. Additionally, the ET simulated by IDSA-based ML models were in good agreement with the reference product, further illustrating its reliability. The proposed framework provides a theoretical basis for in-depth understanding of spatial heterogeneity of ET and a new perspective for ET prediction over large scales.

Evaluating the Potential of Different Evapotranspiration Datasets for Distributed Hydrological Model Calibration

Evapotranspiration (ET), a key component of the hydrological cycle, has a direct impact on runoff and water balance. Various global satellite-based and numerical datasets provide continuous and high spatiotemporal resolution data, which makes it possible to calibrate hydrological parameters against ET. However, the accuracy of ET datasets varies with region and algorithm, introducing uncertainties in hydrological parameter calibration. This study focused on evaluating the potential of different ET datasets in the calibration of distributed hydrological model parameters. Five different ET datasets (PML, SEBAL, EB-ET, GLASS, REA-ET) were evaluated using the water balance method to explore the effect of intrinsic dataset accuracy on applications. The benchmark calibration scheme calibrated parameters by using observed streamflow data from the outlet. Two calibration schemes were proposed to take advantage of the temporal dynamics and spatial patterns of the raw ET datasets. The results show that the model parameters calibrated by all selected ET datasets produced satisfactory results in streamflow simulations. These results were dependent on the calibration schemes and accuracy of ET datasets. Overall, the scheme calibrated by using temporal dynamics of ET at the grid scale provided better streamflow simulations at the basin outlet than the scheme calibrated by using spatial patterns of ET at the basin scale. Three metrics (bias, root mean square error [RMSE], and correlation coefficient [R]) showed that there is a high potential for selected ET datasets to improve soil moisture simulations, as compared to the benchmark scheme. Parameters calibrated by EB-ET and PML datasets provided the best performance in the simulation of streamflow at the outlet and the sub-basin scale. The calibration case with the SEBAL dataset showed the highest potential to improve soil moisture simulation. The annual average ET estimates of these three datasets were closest to the water balance-based ET values.

Climate Normalized Spatial Patterns of Evapotranspiration Enhance the Calibration of a Hydrological Model

Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement has been supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET are often driven by underlying climate gradients, and with this study, we argue that gradient dominated patterns may hamper the potential of spatial pattern-oriented evaluation frameworks. We hypothesize that the climate control of spatial patterns of ET overshadows the effect model parameters have on the simulated patterns. To address this, we propose a climate normalization strategy. This is demonstrated for the Senegal River basin as a modeling case study, where the dominant north-south precipitation gradient is the main driver of the observed hydrological variability. We apply the mesoscale Hydrological Model (mHM) to model the hydrological cycle of the Senegal River basin. Two multi-objective calibration experiments investigate the effect of climate normalization. Both calibrations utilize observed discharge (Q) in combination with remote sensing ET data, where one is based on the original ET pattern and the other utilizes the normalized ET pattern. As objective functions we applied the Kling-Gupta-Efficiency (KGE) for Q and the Spatial Efficiency (SPAEF) for ET. We identify parameter sets that balance the tradeoffs between the two independent observations and find that the calibration using the normalized ET pattern does not compromise the spatial pattern performance of the original pattern. However, vice versa, this is not necessarily the case, since the calibration using the original ET pattern showed a poorer performance for the normalized pattern, i.e., a 30% decrease in SPAEF. Both calibrations reached comparable performance of Q, i.e., KGE around 0.7. With this study, we identified a general shortcoming of spatial pattern-oriented model evaluations using ET in basins dominated by a climate gradient, but we argue that this also applies to other variables such as, soil moisture or land surface temperature.

Spatial Patterns in Actual Evapotranspiration Climatologies for Europe

Spatial patterns in long-term average evapotranspiration (ET) represent a unique source of information for evaluating the spatial pattern performance of distributed hydrological models on a river basin to continental scale. This kind of model evaluation is getting increased attention, acknowledging the shortcomings of traditional aggregated or timeseries-based evaluations. A variety of satellite remote sensing (RS)-based ET estimates exist, covering a range of methods and resolutions. There is, therefore, a need to evaluate these estimates, not only in terms of temporal performance and similarity, but also in terms of long-term spatial patterns. The current study evaluates four RS-ET estimates at moderate resolution with respect to spatial patterns in comparison to two alternative continental-scale gridded ET estimates (water-balance ET and Budyko). To increase comparability, an empirical correction factor between clear sky and all-weather ET, based on eddy covariance data, is derived, which could be suitable for simple corrections of clear sky estimates. Three RS-ET estimates (MODIS16, TSEB and PT-JPL) and the Budyko method generally display similar spatial patterns both across the European domain (mean SPAEF = 0.41, range 0.25–0.61) and within river basins (mean SPAEF range 0.19–0.38), although the pattern similarity within river basins varies significantly across basins. In contrast, the WB-ET and PML_V2 produced very different spatial patterns. The similarity between different methods ranging over different combinations of water, energy, vegetation and land surface temperature constraints suggests that robust spatial patterns of ET can be achieved by combining several methods.

A parallel computing-based and spatially stepwise strategy for constraining a semi-distributed hydrological model with streamflow observations and satellite-based evapotranspiration

Satellite-based products can provide valuable information for model calibrations and evaluations. However, effectively and efficiently constraining hydrological models with both satellite-based information and streamflow measurements remains a challenge. Here, a parallel computing-based and spatially stepwise strategy that enables separate optimizations of different objective functions in a spatially distributed and parallel manner was proposed for model calibration with streamflow observations and satellite-based evapotranspiration (ET). The new calibration strategy (M5) was tested with the Soil and Water Assessment Tool (SWAT) model in the upper Heihe River basin of China, a mountainous watershed on the northeastern Qinghai-Tibet Plateau. The performance of M5 was evaluated and compared with two single-variable calibration strategies, i.e., streamflow-only calibration and ET-only calibration, and with two multivariate calibration methods, i.e., joint calibration and stepwise calibration. Results indicate that M5 achieves the best model performance among the five calibration strategies in reproducing temporal variations of streamflow and ET. Moreover, M5 improves the simulation of the spatial pattern of ET and attains a higher spatial efficiency than the other calibration strategies. M5 also exhibits a higher computational efficiency, with a magnitude up to 2 times greater than the other calibration strategies, due to the application of parallel computing. Further analysis demonstrates that the new calibration strategy can lead to a synergic relationship between the simulation accuracy of streamflow and ET, underscoring the added value of satellite-based products for model calibrations.

Spatiotemporal Patterns of Terrestrial Evapotranspiration in Response to Climate and Vegetation Coverage Changes across the Chinese Loess Plateau

Spatiotemporal patterns of evapotranspiration (ET) and its controlling factors are important for ecosystem services and water resources management in the Chinese Loess Plateau (CLP). In this study, we assessed the spatial patterns of ET and then investigated the interannual variability of ET and its relationships with climate variability and vegetation coverage changes at the timescales of annual, active growing season, as well as different seasons across the entire CLP from 2000 to 2014. A MODIS-derived ET dataset, ground-based datasets of precipitation and atmospheric evaporative demand (AED), and a remote-sensing dataset of Normalized Difference Vegetation Index (NDVI) were comprehensively analyzed. Results showed that mean annual ET varied distinctly among different vegetation zones, generally higher in the more humid southeastern parts of the CLP. Summer ET and ET over active growing season significantly increased for more than 40% of the entire CLP area, and winter ET significantly decreased over ~70% of the entire CLP region, while annual ET, spring ET, and autumn ET remained quite stable during 2000–2014. Per-pixel interannual variability of ET was mainly positively correlated with that of precipitation and NDVI except for winter, but negatively correlated with AED trends. Our study also demonstrated that ET variation trends were exactly consistent for the entire CLP region, the areas mainly implemented with the Grain for Green (GFG) project, and other CLP areas not implemented with the GFG project during 2000–2014. Our findings suggest that the spatiotemporal patterns of CLP ET were mainly water-limited, and climate variability played an essential role in shaping the interannual variability of ET in the CLP. This study will improve our understanding on the ET variations over water-limited areas under climate and vegetation coverage changes.

Response of Wetland Evapotranspiration to Land Use/Cover Change and Climate Change in Liaohe River Delta, China

This study aims to investigate the effects of land use/cover change (LUCC) and climate change on wetland evapotranspiration (ET), and to identify the importance of the main effect factors in the spatiotemporal dynamics of ET. In the wetland of Liaohe River Delta, China, the ET of eight growing seasons during 1985–2017 was estimated using the surface energy balance algorithm for land (SEBAL) model with Landsat and meteorological data. Results show that the average relative error of regional ET estimated by the SEBAL model is 9.01%, and the correlation coefficient between measured and estimated values is 0.61, which indicates that the estimated values are reliable. This study observed significant spatial and temporal variations in ET across the region of interest. The distribution of the average and relative change rate of daily ET in the study area showed bimodal characteristics, that is, the lowest trough occurred in 2005, whereas crests occurred in 1989 and 2014. Simultaneously, the daily ET varied with the land use/cover area. Regional daily ET displays highly heterogeneous spatial distribution, that is, the ET of different land uses/cover types in descending order is as follows: water body, wetland vegetation, non-wetland vegetation, and non-vegetation (except water area). Therefore, the spatial pattern of ET is relevant to the land use/cover types to some extent. In addition, the temporal variation of wetland ET is closely related to landscape transformation and meteorological factor change. A strong correlation was found between ET and the weighted values of meteorological factors, with a correlation coefficient of 0.69. Meanwhile, the annual fluctuations of daily ET and the weighted values were relatively similar. Therefore, the findings highlight the importance of using cheap and readily available remote sensing data for estimating and mapping the variations in ET in coastal wetland.

Earth Observations-Based Evapotranspiration in Northeastern Thailand

Thailand is characterized by typical tropical monsoon climate, and is suffering serious water related problems, including seasonal drought and flooding. These issues are highly related to the hydrological processes, e.g., precipitation and evapotranspiration (ET), which are helpful to understand and cope with these problems. It is critical to study the spatiotemporal pattern of ET in Thailand to support the local water resource management. In the current study, daily ET was estimated over Thailand by ETMonitor, a process-based model, with mainly satellite earth observation datasets as input. One major advantage of the ETMonitor algorithm is that it introduces the impact of soil moisture on ET by assimilating the surface soil moisture from microwave remote sensing, and it reduces the dependence on land surface temperature, as the thermal remote sensing is highly sensitive to cloud, which limits the ability to achieve spatial and temporal continuity of daily ET. The ETMonitor algorithm was further improved in current study to take advantage of thermal remote sensing. In the improved scheme, the evaporation fraction was first obtained by land surface temperature—vegetation index triangle method, which was used to estimate ET in the clear days. The soil moisture stress index (SMSI) was defined to express the constrain of soil moisture on ET, and clear sky SMSI was retrieved according to the estimated clear sky ET. Clear sky SMSI was then interpolated to cloudy days to obtain the SMSI for all sky conditions. Finally, time-series ET at daily resolution was achieved using the interpolated spatio-temporal continuous SMSI. Good agreements were found between the estimated daily ET and flux tower observations with root mean square error ranging between 1.08 and 1.58 mm d−1, which showed better accuracy than the ET product from MODerate resolution Imaging Spectroradiometer (MODIS), especially for the forest sites. Chi and Mun river basins, located in Northeast Thailand, were selected to analyze the spatial pattern of ET. The results indicate that the ET had large fluctuation in seasonal variation, which is predominantly impacted by the monsoon climate.

Spatial-temporal evolution of vegetation evapotranspiration in Hebei Province, China

Evapotranspiration (ET) is the sum of soil or water body evaporation and plant transpiration from the earth surface and ocean to the atmosphere, and thus plays a significant role in regulating carbon and water resource cycles. The time-series data set from the remote sensing MOIDS product (MOD16) was used to study the spatial-temporal evolution of vegetation evapotranspiration in salinized areas during 2000–2014 by analyzing the variability, spatial patterns and Mann-Kendall (MK) nonparametric trends for the time series. The results indicate that inter-annual and intra-annual variations of ET across various vegetated areas show seasonal changes, with the abnormal months identified. The cultivated land displays a greater degree of spatial heterogeneity and the spatial pattern of ET in the area covered by broadleaved deciduous forests corresponds to a higher ET rate and increased water consumption. A widespread decline of ET is observed only in cultivated areas. However, agricultural cultivation doesn't worsen water shortage and soil salinization problems in the region, and water shortage problems are worsening for other vegetated areas. This research provides a basis of reference for the reasonable allocation of water resources and restructuring of vegetation patterns in salinized areas.

Spatiotemporal Analysis of Actual Evapotranspiration and Its Causes in the Hai Basin

Evapotranspiration (ET) is an important component of the eco-hydrological process. Comprehensive analyses of ET change at different spatial and temporal scales can enhance the understanding of hydrological processes and improve water resource management. In this study, monthly ET data and meteorological data from 57 meteorological stations between 2000 and 2014 were used to study the spatiotemporal changes in actual ET and the associated causes in the Hai Basin. A spatial analysis was performed in GIS to explore the spatial pattern of ET in the basin, while parametric t-test and nonparametric Mann-Kendall test methods were used to analyze the temporal characteristics of interannual and annual ET. The primary causes of the spatiotemporal variations were partly explained by detrended fluctuation analysis. The results were as follows: (i) generally, ET increased from northwest to southeast across the basin, with significant differences in ET due to the heterogeneous landscape. Notably, the ET of water bodies was highest, followed by those of paddy fields, forests, cropland, brush, grassland and settlement; (ii) from 2000 to 2014, annual ET exhibited an increasing trend of 3.7 mm per year across the basin, implying that the excessive utilization of water resources had not been alleviated and the water resource crisis worsened; (iii) changes in vegetation coverage, wind speed and air pressure were the major factors that influenced interannual ET trends. Temperature and NDVI largely explained the increases in ET in 2014 and can be used as indicators to evaluate annual ET and provide early warning for associated issues.

Evaluation of Spatio-Temporal Patterns of Remotely Sensed Evapotranspiration to Infer Information about Hydrological Behaviour in a Data-Scarce Region

Information about the hydrological behaviour of a river basin prior to setting up, calibrating and validating a distributed hydrological model requires extensive datasets that are hardly available for many parts of the world due to insufficient monitoring networks. In this study, the focus was on prevailing spatio-temporal patterns of remotely sensed evapotranspiration (ET) that enabled conclusions to be drawn about the hydrological behaviour and spatial peculiarities of a river basin at rather high spatial resolution. The prevailing spatio-temporal patterns of ET were identified using a principal component analysis of a time series of 644 images of MODIS ET covering the Wami River basin (Tanzania) between the years 2000 and 2013. The time series of the loadings on the principal components were analysed for seasonality and significant long-term trends. The spatial patterns of principal component scores were tested for significant correlation with elevations and slopes, and for differences between different soil texture and land use classes. The results inferred that the temporal and spatial patterns of ET were related to those of preceding rainfalls. At the end of the dry season, high ET was maintained only in areas of shallow groundwater and in cloud forest nature reserves. A region of clear reduction of ET in the long-term was related to massive land use change. The results also confirmed that most soil texture and land use classes differed significantly. Moreover, ET was exceptionally high in natural forests and loam soil, and very low in bushland and sandy-loam soil. Clearly, this approach has shown great potential of publicly available remote sensing data in providing a sound basis for water resources management as well as for distributed hydrological models in data-scarce river basins at lower latitudes.

Modeling and Partitioning of Regional Evapotranspiration Using a Satellite-Driven Water-Carbon Coupling Model

The modeling and partitioning of regional evapotranspiration (ET) are key issues in global hydrological and ecological research. We incorporated a stomatal conductance model and a light-use efficiency-based gross primary productivity (GPP) model into the Shuttleworth–Wallace model to develop a simplified carbon-water coupling model, SWH, for estimating ET using meteorological and remote sensing data. To enable regional application of the SWH model, we optimized key parameters with measurements from global eddy covariance (EC) tower sites. In addition, we estimated soil water content with the principle of the bucket system. The model prediction of ET agreed well with the estimates obtained with the EC measurements, with an average R2 of 0.77 and a root mean square error of 0.72 mm·day−1. The model performance was generally better for woody ecosystems than herbaceous ecosystems. Finally, the spatial patterns of ET and relevant model outputs (i.e., GPP, water-use efficiency and the ratio of soil water evaporation to ET) in China with the model simulations were assessed.

Spatial-Temporal Patterns and Controls of Evapotranspiration across the Tibetan Plateau (2000–2012)

Evapotranspiration (ET) is a key factor to further our understanding of climate change processes, especially on the Tibetan Plateau, which is sensitive to global change. Herein, the spatial patterns of ET are examined, and the effects of environmental factors on ET at different scales are explored from the years 2000 to 2012. The results indicated that a steady trend in ET was detected over the past decade. Meanwhile, the spatial distribution shows an increase of ET from the northwest to the southeast, and the rate of change in ET is lower in the middle part of the Tibetan Plateau. Besides, the positive effect of radiation on ET existed mainly in the southwest. Based on the environment gradient transects, the ET had positive correlations with temperature (R>0.85, p<0.0001), precipitation (R > 0.89, p < 0.0001), and NDVI (R > 0.75, p < 0.0001), but a negative correlation between ET and radiation (R = 0.76, p < 0.0001) was observed. We also found that the relationships between environmental factors and ET differed in the different grassland ecosystems, which indicated that vegetation type is one factor that can affect ET. Generally, the results indicate that ET can serve as a valuable ecological indicator.

Estimating irrigation inputs for distributed hydrological modelling: a case study from an irrigated catchment in southeast Australia

Adequate irrigation inputs are essential for the application of hydrological models in irrigated catchments, but reliable data on both the amount and the frequency of irrigation applications are often missing at an appropriate spatial scale. In this paper, we demonstrate and test approaches to estimate irrigation inputs for distributed hydrological modelling. In this context, the Soil and Water Assessment Tool was applied to simulate water balances for an irrigated catchment in southeast Australia during the period 2008–2010. Two methods for estimating irrigation inputs were tested. One method was based on a fixed irrigation application rate, whereas the other one had variable irrigation rates depending on season and the irrigated crop. These two approaches were also compared with the ‘auto-irrigation’ method within the Soil and Water Assessment Tool model. The method with variable irrigation rates resulted in the most reasonable interpretation of the readily available irrigation data, consistent estimates of irrigation runoff coefficients throughout the year and the best fit to observed data on both drain flows at the catchment outlet and spatial evapotranspiration patterns. We also found that the different irrigation inputs significantly affected simulated water balances, in particular deep percolation under relatively dry climatic conditions. All these results suggest that it is possible to infer irrigation inputs from readily available data and local knowledge, adequate for hydrological modelling in irrigated catchments. Our study also demonstrates that, in order to predict reliable water balances in irrigated catchments, an accurate knowledge of irrigation scheduling and irrigation runoff is required. Copyright © 2015 John Wiley & Sons, Ltd.

A case study of regional eco-hydrological characteristics in the Tao River Basin, northwestern China, based on evapotranspiration estimated by a coupled Budyko Equation-crop coefficient approach

In a case study in Tao River Basin, China, we derived a high spatial-resolution regional distribution of evapotranspiration (ET) using the single crop coefficient method and Budyko equation. We then further analyzed the spatio-temporal characteristics of this diverse eco-hydrological basin from 2001–2010. The results suggest that the single crop coefficient method based on leaf area index captures better spatial and temporal dynamics of the regional ET than did the Budyko Equation method. The rising temperature was the main reason for the increasing ET in the Tao River Basin during 2001–2010. Areas with high ET efficiency were distributed mainly in the areas where the vegetation coverage was high, and a lower runoff coefficient responded. The estimated spatial patterns of ET allowed an improved understanding of the eco-hydrological processes within the Tao River Basin and the method used might be generalized as a reference for future regional-scale eco-hydrological research.

Comparison of three dual‐source remote sensing evapotranspiration models during the MUSOEXE‐12 campaign: Revisit of model physics

AbstractVarious remote sensing‐based terrestrial evapotranspiration (ET) models have been developed during the past four decades. These models vary in conceptual and mathematical representations of the physics, consequently leading to different performances. Examination of uncertainties associated with limitations in model physics will be useful for model selection and improvement. Here, three dual‐source remote sensing ET models (i.e., the Hybrid dual‐source scheme and Trapezoid framework‐based ET Model (HTEM), the Two‐Source Energy Balance (TSEB) model, and the MOD16 ET algorithm) using ASTER images were compared during the MUSOEXE‐12 campaign in the Heihe River Basin in Northwest China, aiming to better understand the differences in model physics that potentially lead to differences in model performance. Model results were first compared against observations from a dense network of eddy covariance towers and isotope‐based evaporation (E) and transpiration (T) partitioning. Results show that HTEM outperformed the other two models in simulating ET and its partitioning, whereas MOD16 performed worst (i.e., ET root‐mean‐square errors are 42.3 W/m2 (HTEM), 49.8 W/m2 (TSEB), and 95.3 W/m2 (MOD16)). On to model limitations, HTEM tends to underestimate ET under high advection due mostly to the underestimation of temperatures for the wet edge in its trapezoidal space. For TSEB, large uncertainties occur in determining the initial Priestley‐Taylor coefficient and the iteration procedure for ET partitioning, leading to overestimation/underestimation of T/E in most cases, particularly over sparse vegetation. Primary use of meteorological data for MOD16 does not effectively capture the soil moisture restriction on ET, and therefore results in unreasonable spatial ET patterns.

Evapotranspiration and its main controlling mechanism over the desert riparian forests in the lower Tarim River Basin

Evapotranspiration (ET) and its controlling mechanism over the desert riparian forests in arid regions are the important scientific basis for the water resources managements of the lower reaches of the inland rivers of China. Nearly three years of continuous measurements of surface ET, soil water content at different depths and groundwater table over a typical Tamarix spp. stand and a typical Populus euphratica stand were conducted in the lower reach of the Tarim River. The ET seasonal trends in the growing season were controlled by plant phenology, and ET in non-growing season was weak. The diurnal variations of ET resulting from the comprehensive effects of all atmospheric factors were significantly related with reference ET. The spatial pattern of ET was determined by vegetation LAI, more vegetation coverage, more ET amount. Groundwater is the water source of surface ET, and the soil water in shallow layers hardly took part in the water exchange in the groundwater-soil-plant-air system. The temporal processes of ET over the Tamarix stand and the Populus stand were similar, but the water consumption of the well-grown Populus euphratica was higher than that of the well-grown Tamarix spp. Further analysis indicates that plant transpiration accounts for most of the surface ET, with soil evaporation weak and negligible; groundwater table is a crucial factor influencing ET over the desert riparian forests, groundwater influences the processes and amounts of ET by controlling the growth and spatial distribution of desert riparian forests; quantifying the water stress of desert riparian forests using groundwater table is more appropriate, rather than soil water content. Based on the understanding of ET and water movements in the groundwater-soil-plant-air system, a generalized framework expressing the water cycling and its key controlling mechanism in the lower reaches of the inland rivers of China is described, and a simple model to estimate water requirements of the desert riparian forests is presented.

Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China

Evapotranspiration (ET) is a key component of terrestrial ecosystems because it links the hydrological, energy, and carbon cycles. Several satellite-based ET models have been developed for extrapolating local observations to regional and global scales, but recent studies have shown large model uncertainties in ET simulations. In this study, we compared eight ET models, including five empirical and three process-based models, with the objective of providing a reference for choosing and improving methods. The results showed that the eight models explained between 61 and 80% of the variability in ET at 23 eddy covariance towers in China and adjacent regions. The mean annual ET for all of China varied from 535 to 852mmyr−1 among the models. The interannual variability of yearly ET varied significantly between models during 1982–2009 because of different model structures and the dominant environmental factors employed. Our evaluation results showed that the parameters of the empirical methods may have different combination because the environmental factors of ET are not independent. Although the three process-based models showed high model performance across the validation sites, there were substantial differences among them in the temporal and spatial patterns of ET, the dominant environment factors and the energy partitioning schemes. The disagreement among current ET models highlights the need for further improvements and validation, which can be achieved by investigating model structures and examining the ET component estimates and the critical model parameters.

Remote sensing temporal and spatial patterns of evapotranspiration and the responses to water management in a large irrigation district of North China

To deal with water resources crisis caused by climate change and intensified human activities, the Hetao Irrigation District of Inner Mongolia in North China has been experiencing rehabilitation for water-saving since 1999. This has significantly changed its regional hydrological cycle and thus water use patterns over different land use types. In this paper, Surface Energy Balance Algorithm for Land (SEBAL) model fed with MODIS data was applied in Hetao area from 2000 to 2010 to examine the spatial and temporal patterns of evapotranspiration (ET). The SEBAL estimated ET agreed well with that from other methods in the study area. The results indicate that inter-annual variability in ET over agricultural land, water body, woodland and irrigated grassland are primarily explained by the variation of reference ET. So it is with the seasonal variability in agricultural land ET on monthly basis. However, the inter-annual variations of ET over sandy land, Gobi desert and mountain areas are mainly controlled by precipitation. Over the study period, a reduction in river water diversion for irrigation has not reduced the agricultural land ET, indicating no significant impact on agricultural production. But ET over the non-irrigated grassland tends to decrease, which was likely caused by declining groundwater table in recent years.