Spatial Variability Of Evapotranspiration Research Articles

Cascade effects of climate and vegetation influencing the spatial variation of evapotranspiration in China

Evapotranspiration (ET) is generally affected by climate and vegetation, but the main factor controlling the spatial variation of ET largely varied with different regions. Clarifying the characteristics and dominant factor of ET in China is essential for understanding the regional ecosystem water balance. This study quantitatively assessed the magnitude and spatial variations of ET in China's terrestrial ecosystems using data measured by eddy covariance from 150 observation sites and investigated its underlying direct and indirect influencing factors. The results demonstrated that the ET of China's terrestrial ecosystems varied from 146.95 to 1125.33 mm, with an average value of 551.00 ± 204.12 mm. The ET showed a general increasing trend from the North to South, aligning with the latitudinal patterns of water availability (mean annual precipitation (MAP)), energy conditions (mean annual net radiation (MARn), and mean annual temperature (MAT)). Compared to regions at the same latitude, the North China Plain exhibited relatively higher ET because of the extensive cropland sites in the area. Furthermore, significant positive linear correlations were found between ET and MAT in the majority of ecosystems. However, a negative correlation of ET with MAT was observed in grasslands, which may be attributed to inconsistent responses of ET to MAT on the Tibetan Plateau and Inner Mongolia. Fractional vegetation coverage (FVC) exhibited a more significant direct influence on ET than climate factors (MARn, MAT, and MAP). Nevertheless, climate factors not only exert a direct influence on ET but also have cascade effects that affect FVC, thereby indirectly influencing the ET. When considering these cascade effects, MAP emerged as the dominant driver of spatial variations in ET of China's terrestrial ecosystems. This study provides essential information on variations of ET in China's terrestrial ecosystem and valuable insights for future explorations into the adaptive mechanisms underlying spatial variations of ET.

A Hybrid Framework for Simulating Actual Evapotranspiration in Data-Deficient Areas: A Case Study of the Inner Mongolia Section of the Yellow River Basin

Evapotranspiration (ET) plays an important role in transferring water and converting energy in the land–atmosphere system. Accurately estimating ET is crucial for understanding global climate change, ecological environmental problems, the water cycle, and hydrological processes. Machine learning (ML) algorithms have been considered as a promising method for estimating ET in recent years. However, due to the limitations associated with the spatial–temporal resolution of the flux tower data commonly used as the target set in ML algorithms, the ability of ML to discover the inherent laws within the data is reduced. In this study, a hybrid framework was established to simulate ET in data-deficient areas. ET simulation results of a coupled model comprising the Budyko function and complementary principle (BC2021) were used as the target set of the random forest model, instead of using the flux station observation data. By combining meteorological and hydrological data, the monthly ET of the Inner Mongolia section of the Yellow River Basin (IMSYRB) was simulated from 1982 to 2020, and good results were obtained (R2 = 0.94, MAE = 3.82 mm/mon, RMSE = 5.07 mm/mon). Furthermore, the temporal and spatial variations in ET and the influencing factors were analysed. In the past 40 years, annual ET in the IMSYRB ranged between 241.38 mm and 326.37 mm, showing a fluctuating growth trend (slope = 0.80 mm/yr), and the summer ET accounted for the highest proportion in the year. Spatially, ET in the IMSYRB showed a regular distribution of high ET in the eastern region and low ET in the western area. The high ET value areas gradually expanded from east to west over time, and the area increased continuously, with the largest increase observed in the 1980s. Temperature, precipitation, and normalized difference vegetation index (NDVI) were found to be the most important factors affecting ET in the region and play a positive role in promoting ET changes. These results provide an excellent example of long-term and large-scale accurate ET simulations in an area with sparse flux stations.

Lumped variable representing the integrative effects of climate and underlying surface system: Interpreting Budyko model parameter from earth system science perspective

Parametric Budyko models express the ratio of annual actual evapotranspiration (ET) to annual precipitation (P) as a function of dryness index, i.e., annual potential evapotranspiration (ET0)/P (denoted as DI) and model parameter at a catchment. Generally the model parameter is assumed to reflect factors besides DI, especially the underlying surface features. However, recent studies have revealed its relations with DI, which forces us to further examine its connotation. We revisited the derivation of three parametric Budyko equations and found that model parameter was essentially a lumped variable representing the integrative effects of climate and underlying surface system. Then taking 15 typical catchments in the Chinese Loess Plateau as the study area, we explored the controls of Budyko-Fu model parameter (w) and their differences in temporal (between-years) and spatial (between-catchments) processes. As expected, w was affected by both climate and underlying surface factors. Specifically, DI, climate seasonality and asynchrony index (SAI) and Normalized Difference Vegetation Index (NDVI) influenced w in both temporal and spatial processes; besides, catchment relief ratio (CR) and relative infiltration capacity (ks/ir) also affected w in spatial process. SAI was strongly correlated with DI and its close relationship with w essentially conveyed DI's influence. Considering the inherent connection between DI and the inverse w, DI was not included in the empirical formula for w. SAI and NDVI remained independent in temporal process and the empirical formula for w with these two factors modeled annual ET well (MAE = 15.03 mm). In spatial process, SAI, NDVI, CR, and ks/ir were interconnected and by using any one the spatial variation of ET was captured adequately (MAE = 11.16, 11.74, 11.27, and 10.43 mm, respectively). Our results demonstrate theoretically and empirically the importance of viewing Budyko model parameter from earth system science perspective and focusing on the differences of its controls in spatiotemporal processes.

Estimating the Temporal and Spatial Variations in Evapotranspiration with a Nonlinear Evaporation Complementary Relationship Model in Hyper-arid Areas

Estimating the Temporal and Spatial Variations in Evapotranspiration with a Nonlinear Evaporation Complementary Relationship Model in Hyper-arid Areas

Temporal and Spatial Variation Characteristics of Actual Evapotranspiration in the Yiluo River Basin Based on the Priestley–Taylor Jet Propulsion Laboratory Model

Evapotranspiration is an important part of the hydrological cycle, affecting the terrestrial hydrological process and the relationship between water resource transformation. Analyzing and mastering the temporal and spatial variations in evapotranspiration are of great significance for the rational development, utilization, and protection of water resources in the basin. Based on MODIS remote sensing data and combined with meteorological and hydrological data, the PT-JPL model was used to estimate the actual evapotranspiration of the Yiluo River Basin, and the applicability of the PT-JPL model for estimating actual evapotranspiration in the basin was analyzed. The spatial and temporal characteristics of actual evapotranspiration in the Yiluo River Basin were analyzed, and the correlation between actual evapotranspiration in the basin and influencing factors such as precipitation, temperature, and vegetation was explored. The main conclusions are as follows: the PT-JPL model has good applicability in the Yiluo River Basin; the total actual evapotranspiration in the basin showed a decreasing trend, which was consistent with the trend of precipitation, indicating that the actual evapotranspiration may be limited by water conditions in the study area. The evapotranspiration of the basin was higher in the upstream and lower in the downstream, which may be related to the better vegetation coverage in the upper basin than in the downstream. As an important indicator of vegetation change, NDVI showed a good correlation with evapotranspiration, which also verified this. In addition, the correlation between evapotranspiration and temperature was also good.

Global land surface evapotranspiration monitoring by ETMonitor model driven by multi-source satellite earth observations

Evapotranspiration (ET) is an essential ecohydrological process linking the land surface energy, water and carbon cycles, and plays a critical role in the earth system. ET remains one of the most problematic components of the water cycle to be determined due to the heterogeneity of the landscape and the complexity of driving factors. The satellite-based earth observation is expected to provide ET information at large-scales. However, accurate global ET information, with spatially and temporally continuous coverage at moderate-to-high resolution, is still scarce. In this paper, a combined model, called ETMonitor, with multi-process parameterizations, was improved and applied to estimate the global ET, mainly using the biophysical and hydrological parameters/variables retrieved from satellite observations. The ETMonitor model was improved in several aspects in this study to generate the global ET datasets during 2000–2019 at daily/1-km resolution, including: 1) adopting high temporal resolution surface water cover and snow/ice cover as input, to simulate the impact of their seasonal change on ET variation; 2) parameterizing the impact of soil moisture on plant transpiration and soil evaporation using high resolution soil moisture, which was downscaled to 1-km resolution from the coarse resolution data retrieved from microwave remote sensing observation; 3) involving a better soil heat flux estimation to reduce its impact on the uncertainty of estimated ET; 4) being calibrated based on global ground flux observations to achieve better accuracy. The estimated daily ET was validated based on the global in situ observations at site scale across various ecosystems, with overall high correlation (0.75), low bias (0.08 mm d-1), and low root mean square error (0.93 mm d-1). It had good ability to partition total ET to plant transpiration and soil evaporation indicated by the good agreement with the ground isotope measurements in a growing season at one site in the northwest China. The estimated global ET was cross-validated by comparing with other existing ET products, and it showed the global ET estimated by ETMonitor could capture the expected global ET patterns both in space and in time. It also indicated the superiority of the ET product by ETMonitor in the following aspects: capability in capturing the seasonal dynamics of waterbody evaporation and sublimation; better performance in capturing the spatial variation of ET in the irrigated cropland regions and mountain regions with complex terrain than other global ET products, e.g., the GLEAM and MOD16 ET products; capability of ET component partitioning at high spatial (1-km) and high temporal (daily) resolutions with good accuracy. The estimated plant transpiration, soil evaporation, canopy rainfall interception loss, and water body evaporation and snow sublimation accounted for 61.54 % (±0.44 %), 19.08 % (±0.54 %), 13.54 % (±0.49 %), and 5.84 % (±0.24 %), respectively, of the total ET on global average. The ETMonitor global ET dataset could provide important information on studies of global terrestrial water and energy cycles and climate change studies, and water resources management at global and regional scales.

Evapotranspiration Seasonality over Tropical Ecosystems in Mato Grosso, Brazil

Brazilian tropical ecosystems in the state of Mato Grosso have experienced significant land use and cover changes during the past few decades due to deforestation and wildfire. These changes can directly affect the mass and energy exchange near the surface and, consequently, evapotranspiration (ET). Characterization of the seasonal patterns of ET can help in understanding how these tropical ecosystems function with a changing climate. The goal of this study was to characterize temporal (seasonal-to-decadal) and spatial patterns in ET over Mato Grosso using remotely sensed products. Ecosystems over areas with limited to no flux towers can be performed using remote sensing products such as NASA’s MOD16A2 ET (MOD16 ET). As the accuracy of this product in tropical ecosystems is unknown, a secondary objective of this study was to evaluate the ability of the MOD16 ET (ETMODIS) to appropriately represent the spatial and seasonal ET patterns in Mato Grosso, Brazil. Actual ET was measured (ETMeasured) using eight flux towers, three in the Amazon, three in the Cerrado, and two in the Pantanal of Mato Grosso. In general, the ETMODIS of all sites had no significant difference from ETMeasured during all analyzed periods, and ETMODIS had a significant moderate to strong correlation with the ETMeasured. The spatial variation of ET had some similarity to the climatology of Mato Grosso, with higher ET in the mid to southern parts of Mato Grosso (Cerrado and Pantanal) during the wet period compared to the dry period. The ET in the Amazon had three seasonal patterns, a higher and lower ET in the wet season compared to the dry season, and minimal to insignificant variation in ET during the wet and dry seasons. The wet season ET in Amazon decreased from the first and second decades, but the ET during the wet and dry season increased in Cerrado and Pantanal in the same period. This study highlights the importance of deepening the study of ET in the state of Mato Grosso due to the land cover and climate change.

Assessing variability of soil water balance components measured at a new lysimeter facility dedicated to the study of soil ecosystem services

Diversifying annual crop rotations is postulated to promote soil ecosystem services throughreduction of greenhouse gas emissions, control of soil evaporation, moderation of soil freeze-thaw cycles, increases in soil organic carbon, and reduced nutrient leaching, all of which are processes that are impacted by the waterbalance. A newly-installed facility with large monolithic weighing soil lysimeters dedicated to studying changes in soil ecosystem services induced by rotation diversification was installed in June 2016 in Elora, ON, Canada. The high-precision lysimeters, nine for each of two different soils (silt loam, loamy sand) are a closed system to fully evaluate water balance components.In the first year of operation, the lysimeters were not subject to any diversification treatments. This provided an opportunity to study water budget components (precipitation, P; evapotranspiration, ET; change is soil storage,ΔS; drainage, D) measured by the 9 replicate lysimeters for each soil type. The objectives of this study were to1) determine the total uncertainty of P, ET,ΔS and D induced bydatasmoothing and gap fillingdataprocedures; and 3) characterize the spatial variability of water budget components for the baseline year. Cumulative sums of water balance variables from data processing procedures found that the adaptive window and adaptive threshold (AWAT) data smoothing method introduced minimal errors (0.2 to 1.9%). Filling missing data gaps using data from replicate lysimeters, i.e., lysimeters of the same soil type and agronomy, introduced errors of only 0.3 to 0.5% for P and ET (120-day sums). There was greater uncertainty for D andΔS (10.8% and 2.1%, respectively) because of the variability in D. P showed a small degree of spatial variation across all 18 lysimeters, with variations being 1.5% of the mean cumulative sums when using data with no gaps, which demonstrated the high precision of the lysimeter measurements. Spatial variability of evapotranspiration (ET) was higher (6.1% for the silt loam and5.7% for the loamy sand), but within the range of variability estimated for similar lysimeter facilities. The differences in plant cover on individual lysimeters were the main source of variation forETandΔS. Results inform future comparisons of water budget componentsfor other lysimeter sitesand demonstratethe suitability of this facility for examining the complex impacts of crop diversification on soil ecosystem services, providing a basis for future evaluations of water balance components.

Spatial variability of evapotranspiration and pressure on groundwater resources: remote sensing monitoring by crop type in the Bekaa plain, Lebanon

The lack of data on water consumption by agriculture in the context of climate change led the authors to estimate the water balance of the Bekaa Valley. Plots were mapped according to the normalized difference vegetation index profiles of spring and summer crop with the Sentinels-2 images. Surface energy balance model python (PYSEBAL) estimated the seasonal evapotranspiration (ETseason) and net irrigation requirements (NIRseason). Spring and summer crop maps were accurate: 90% and 93%. The results of PYSEBAL were validated by the comparison between averaged daily ET of PYSEBAL and FAO-56 method (root mean square error from 0.38 to 1.93 and the mean average error from 0.33 to 1.64 mm / day). The water balance was negative: 0.16 km3 of groundwater was extracted against 0.10 km3 of rainfall available for aquifer recharge in 2017. This is explained by ET/ha/season (alfalfa: 1094 mm / ha / season, orchards 881, corn 719, tobacco 606, cucumber 558, late potatoes 487, summer vegetables 483, early potatoes 467, vineyard 390, spring vegetables 237, and wheat 313). ETseason varies according to temperature (strong correlation between daily ET and temperature, Pearson: 0.74), relative humidity (Pearson: −0.65), surface radiation (Pearson: 0.75), and percentage of sand in the soil and its depth (strong negative Pearson: −0.62 and −0.57).

Simulation of Evapotranspiration Based on BEPS-TerrainLab V2.0 from 1990 to 2018 in the Dajiuhu Basin

Accurate estimations of evapotranspiration (ET) are essential for understanding land-atmosphere coupling and atmosphere-underlying surface energy and water vapor exchanges. Based on input data processing, this paper simulates the temporal and spatial variation of ET in the Dajiuhu Basin from 1990 to 2018 using the BEPS-TerrainLab V2.0 model. Compared with the ET measured by an eddy covariance (EC) tower, the model explained 80.1% of the ET variation. From 1990 to 2018, the average annual ET in the Dajiuhu Basin was 1262.7 mm/yr indicating a downward trend (−27.12 mm/yr). In 2005, a sudden change point was observed based on the Mann-Kendall (MK) test and 3-year moving t-test. Around 2005, the downward trend in ET slowed and the proportional trend of ET to precipitation changed from upward trend to downward trend. Regarding spatial distribution, the ET in the basin's central part was smaller than that in the basin's surrounding area, the ET of the southern slope was higher than that of the northern slope, and the decrease in the ET rate on the sunny side was lower than that on the shady side. ET decreased as the elevation increased, with the fastest decrease observed between 2184 and 2384 m. For different landcover types, the average ET exhibited the following order: deciduous forest > mixed forest > wetland > grass > agriculture land. Decreased solar radiation is the main reason for the decreased ET in the Dajiuhu Basin, followed by increased wind speed and relative humidity, which together contribute 83.9% to the ET trend. This paper provides a theoretical basis for the study of ET changes and the mechanism of ET and provides a decision-making reference for water resource management in the Dajiuhu Basin and even the South-to-North Water Transfer Project.

High-resolution spatially explicit land surface model calibration using field-scale satellite-based daily evapotranspiration product

High-resolution simulation of water budgets across the agricultural landscape is critically important to a variety of applications, such as precision agriculture, water resources management, and environmental quality assessment. Model-data integration has been shown to be an effective approach to reduce model uncertainties and there is a growing opportunity to improve land surface modeling through spatially explicit calibration with satellite data in recent decades. Recently, a satellite-based daily 30-m resolution evapotranspiration (ET) product BESS-STAIR has been developed, achieving a high performance and well capturing the spatial and temporal dynamics of ET across the U.S. Corn Belt. To explore the potential of high-resolution spatially explicit calibration for advancing land surface modeling at fine scales, we carried out calibration experiments for the Noah-MP land surface model (LSM) over cropland using this newly developed BESS-STAIR ET. We first used Sobol sensitivity analysis to identify the most sensitive parameters for the Noah-MP’s ET simulation. The most sensitive vegetation (minimum stomatal resistance) and soil parameters (saturated hydraulic conductivity, saturated matric potential, and a soil pore size distribution parameter) were calibrated using BESS-STAIR ET to improve model simulation of surface water balance. We conducted calibration experiments at 8 eddy covariance flux tower sites that grew maize and soybean across the U.S. Corn Belt, as well as a regional calibration study on the Spoon River watershed in Champaign, Illinois. When benchmarked with flux tower measurements, the BESS-STAIR ET–calibrated model (driven by flux tower forcing) on average reduced the RMSE of hourly ET from 61 W/m2 to 47 W/m2 for maize, and from 66 W/m2 to 53 W/m2 for soybean, and matched the performance of directly calibrating using flux tower measured ET. The regional study found that calibration using BESS-STAIR ET also improved the simulation of long-term regional water budgets and achieved better performance of ET than traditionally lumped calibration using streamflow. Further analysis revealed that the high-resolution calibration can resolve the spatial variations of ET to a certain extent, and the accuracy of the calibration can be largely attributed to the low bias and excellent long-term correlation of the BESS-STAIR ET data itself. Our study thus demonstrates the effectiveness of high-resolution model calibration and provides important implications in field-scale hydrological modeling and precision agricultural applications.

Study on the spatial-temporal variation in evapotranspiration in China from 1948 to 2018

It is of great significance for the efficient utilization of water resources and the construction of the ecological environment in China to fully understand the evolution process of the spatial-temporal pattern of evapotranspiration (ET). With the use of the v2.0 and v2.1 ET data sets combined with the Global Land Data Assimilation System and Noah model, this paper selects pixels as the basic research object to analyse the spatial-temporal variation in ET in China during the 71 years from 1948 to 2018. We first applied the TFPW-MK test to study the annual ET trend in China throughout the 71-year period, including the ET trend of each month from January to December and the annual total ET trend. Moreover, we examined the spatial variation in these trends. In addition, we calculated the variation coefficient of the time series of each pixel’s ET throughout the 71-year period and the variation coefficient of the spatial distribution of ET in each year to analyse the spatial-temporal fluctuations in ET in the study area. Finally, the Hurst index was adopted to evaluate the future ET trend. Based on these analyses, we observed the following novel spatial-temporal characteristics of ET: from 1948 to 2018, (1) the ET in most regions covered by 89.5% of all pixels in China exhibits an increasing trend. (2) The ET trend in China varies greatly with the change in months, and many regions show the most or least obvious increasing trend (or decreasing trend) at different times. (3) The area with an increasing trend is the largest in May and the smallest in December, and more than half of the pixels in all months of a year reveal an increasing trend. (4) In the northeast, west and south regions of China, the monthly fluctuation in the ET trend is relatively large, which indicates that the ET trend in these regions is greatly affected by the month. (5) The fluctuation in ET in China is larger in the north than it is in the south and larger in the west than it is in the east. The most stable fluctuation occurs in East China. (6) The ET trend of almost all the pixels in the study area remains consistent from 1948 to 2018, and there are large areas with a notable continuity. This results in the spatial variation in ET in the study area increasing.

CloudRoots: integration of advanced instrumental techniques and process modelling of sub-hourly and sub-kilometre land–atmosphere interactions

Abstract. The CloudRoots field experiment was designed to obtain a comprehensive observational dataset that includes soil, plant, and atmospheric variables to investigate the interaction between a heterogeneous land surface and its overlying atmospheric boundary layer at the sub-hourly and sub-kilometre scale. Our findings demonstrate the need to include measurements at leaf level to better understand the relations between stomatal aperture and evapotranspiration (ET) during the growing season at the diurnal scale. Based on these observations, we obtain accurate parameters for the mechanistic representation of photosynthesis and stomatal aperture. Once the new parameters are implemented, the model reproduces the stomatal leaf conductance and the leaf-level photosynthesis satisfactorily. At the canopy scale, we find a consistent diurnal pattern on the contributions of plant transpiration and soil evaporation using different measurement techniques. From highly resolved vertical profile measurements of carbon dioxide (CO2) and other state variables, we infer a profile of the CO2 assimilation in the canopy with non-linear variations with height. Observations taken with a laser scintillometer allow us to quantify the non-steadiness of the surface turbulent fluxes during the rapid changes driven by perturbation of photosynthetically active radiation by cloud flecks. More specifically, we find 2 min delays between the cloud radiation perturbation and ET. To study the relevance of advection and surface heterogeneity for the land–atmosphere interaction, we employ a coupled surface–atmospheric conceptual model that integrates the surface and upper-air observations made at different scales from leaf to the landscape. At the landscape scale, we calculate a composite sensible heat flux by weighting measured fluxes with two different land use categories, which is consistent with the diurnal evolution of the boundary layer depth. Using sun-induced fluorescence measurements, we also quantify the spatial variability of ET and find large variations at the sub-kilometre scale around the CloudRoots site. Our study shows that throughout the entire growing season, the wide variations in stomatal opening and photosynthesis lead to large diurnal variations of plant transpiration at the leaf, plant, canopy, and landscape scales. Integrating different advanced instrumental techniques with modelling also enables us to determine variations of ET that depend on the scale where the measurement were taken and on the plant growing stage.

Landsat Hourly Evapotranspiration Flux Assessment using Lysimeters for the Texas High Plains

Evapotranspiration (ET) is one of the biggest data gaps in water management due to limited ET measurements, and further, spatial variability in ET is difficult to capture. Satellite-based ET estimation has great potential for water resources planning as it allows estimation of agricultural water use at field, landscape, and watershed scales. However, uncertainties with satellite data derived ET are a major concern. This study evaluates hourly satellite-based ET from 2001–2010 for the growing season (May–October) under irrigated and dryland conditions for both tall and short crops. The evaluation was conducted using observed ET from four large weighing lysimeters at the United States Department of Agriculture Agricultural Research Service (USDA-ARS) Conservation and Production Research Laboratory in Bushland, Texas. Hourly ET from satellite data were derived using the Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) model. Performance statistics showed that satellite-based hourly estimates compared to lysimeter measurements provided good performance with an root-mean-square error(RMSE) of 0.14 mm, Nash–Sutcliffe efficiency (NSE) of 0.57, and R2 of 0.62 for ET for dryland crops, and RMSE of 0.16, NSE of 0.63, and R2 of 0.65 for irrigated crops. METRIC provided accurate hourly ET estimates that may be useful for irrigation scheduling and other water resources management purposes based on the hourly assessment.

Temporal and spatial variation of evapotranspiration and grassland vegetation cover in Duolun County, Inner Mongolia

Temporal and spatial variation of evapotranspiration and grassland vegetation cover in Duolun County, Inner Mongolia

Seasonal ground ice impacts on spring ecohydrological conditions in a western boreal plains peatland

AbstractPeatlands in the Western Boreal Plains act as important water sources in the landscape. Their persistence, despite potential evapotranspiration (PET) often exceeding annual precipitation, is attributed to various water storage mechanisms. One storage element that has been understudied is seasonal ground ice (SGI). This study characterized spring SGI conditions and explored its impacts on available energy, actual evapotranspiration, water table, and near surface soil moisture in a western boreal plains peatland. The majority of SGI melt took place over May 2017. Microtopography had limited impact on melt rates due to wet conditions. SGI melt released 139mm in ice water equivalent (IWE) within the top 30cm of the peat, and weak significant relationships with water table and surface moisture suggest that SGI could be important for maintaining vegetation transpiration during dry springs. Melting SGI decreased available energy causing small reductions in PET (<10mm over the melt period) and appeared to reduce actual evapotranspiration variability but not mean rates, likely due to slow melt rates. This suggests that melting SGI supplies water, allowing evapotranspiration to occur at near potential rates, but reduces the overall rate at which evapotranspiration could occur (PET). The role of SGI may help peatlands in headwater catchments act as a conveyor of water to downstream landscapes during the spring while acting as a supply of water for the peatland. Future work should investigate SGI influences on evapotranspiration under differing peatland types, wet and dry spring conditions, and if the spatial variability of SGI melt leads to spatial variability in evapotranspiration.

Long-Term Spatiotemporal Dynamics of Terrestrial Biophysical Variables in the Three-River Headwaters Region of China from Satellite and Meteorological Datasets

Terrestrial biophysical variables play an essential role in quantifying the amount of energy budget, water cycle, and carbon sink over the Three-River Headwaters Region of China (TRHR). However, direct field observations are missing in this region, and few studies have focused on the long-term spatiotemporal variations of terrestrial biophysical variables. In this study, we evaluated the spatiotemporal dynamics of biophysical variables including meteorological variables, vegetation, and evapotranspiration (ET) over the TRHR, and analyzed the response of vegetation and ET to climate change in the period from 1982 to 2015. The main input gridded datasets included meteorological reanalysis data, a satellite-based vegetation index dataset, and the ET product developed by a process-based Priestley–Taylor algorithm. Our results illustrate that: (1) The air temperature and precipitation over the TRHR increased by 0.597 °C and 41.1 mm per decade, respectively, while the relative humidity and surface downward shortwave radiation declined at a rate of 0.9% and 1.8 W/m2 per decade during the period 1982–2015, respectively. We also found that a ‘dryer warming’ tendency and a ‘wetter warming’ tendency existed in different areas of the TRHR. (2) Due to the predominant ‘wetter warming’ tendency characterized by the increasing temperature and precipitation, more than 56.8% of areas in the TRHR presented a significant increment in vegetation (0.0051/decade, p < 0.05), particularly in the northern and western meadow areas. When energy was the limiting factor for vegetation growth, temperature was a considerably more important driving factor than precipitation. (3) The annual ET of the TRHR increased by 3.34 mm/decade (p < 0.05) with an annual mean of 230.23 mm/year. More importantly, our analysis noted that ET was governed by terrestrial water supply, e.g., soil moisture and precipitation in the arid region of the western TRHR. By contrast, atmospheric evaporative demand derived by temperature and relative humidity was the primary controlling factor over the humid region of the southeastern TRHR. It was noted that land management activities, e.g., irrigation, also had a nonnegligible impact on the temporal and spatial variation of ET.

Modeling soil water balance and irrigation strategies in a flood-irrigated wheat-maize rotation system. A case in dry climate, China

Demand for irrigation water has been steadily increasing in arid regions where intensification of crop production is supported by flood-irrigation. An assessment of irrigation performance, water productivity, and irrigation schedules is critical to water conservation in dry climates. In this study, we conducted a field experiment to compare soil water balance in a flood-irrigated wheat-maize rotation system during the growing season of 2015–2016. We then modeled the soil water balance and improved irrigation strategies by coupling Hydrus-1D with the CROPWAT model, and using evapotranspiration calculated from climatic data. The calibrated Hydrus-1D model was used to simulate the temporal and spatial variation of evapotranspiration and deep percolation based on measured soil water distribution of soil profiles in the unsaturated zone. Results showed that using soil hydraulic parameters from inversion modeling can simulate soil water flow in multi-layer soil during a crop growing season. Simulation results indicated that about 36.6 and 40.6% (478.6 and 680.1 mm) of total water input in 2015 and 2016, respectively, was consumed by evapotranspiration. Furthermore, simulated deep percolation amounted for approximately 32.3 and 42.9% (403.9 and 696.6 mm) of the total amount of irrigation water in 2015 and 2016, respectively. These results indicated that only a small proportion of irrigation water was used by crops for transpiration. In addition, irrigation performance indicators such as relative water supply, relative irrigation supply, depleted fraction, and overall consumed ratio values indicated poor performance of irrigation practices in the study area. Particularly, crop yields did not increase with increases in irrigation water in flood-irrigated fields during the last ten years. Results of the CROPWAT model indicated that combinations of a fixed irrigation depth and timing, of 40 mm every 10 days, and 50 mm every 10 days were reasonable for wheat and maize, respectively, given the sandy soil in the study area. The improved irrigation strategies will limit water irrigation loss to 20% without significant effects on crop yields. This study provides an alternative approach for estimating deep percolation and crop water requirements supporting management efforts in water conservation in dry climates.

Seasonal and Inter-annual Variation of Evapotranspiration in Amazonia Based on Precipitation, River Discharge and Gravity Anomaly Data

We analyzed seasonal and spatial variations of evapotranspiration (ET) for five Amazon sub-basins and their response to the 2015/16 El Nino episode using a recently developed water-budget approach. ET varied typically between ~7 and 10 cm/month with exception of the Xingu basin for which it varied between 10 and 15 cm/month. Outstanding features of ET seasonality are (i) generally weak seasonality, (ii) two ET peaks for the two very wet catchments Solimoes and Negro, with one occurring during the wet season and one during the drier season, and (iii) a steady increase of ET during the second half of the dry season for the three drier catchments (Madeira, Tapajos, Xingu). Peak ET occurs during the first half of the wet season consistent with leaf flush occurring before the onset of the wet season. With regards to inter-annual variation, we found firstly that for the Solimoes and Madeira catchments the period with large positive wet season anomalies (2012–2015) is associated with negative ET anomalies, and negative SIF (solar induced fluorescence) anomalies. Furthermore, we found negative ET of several cm/months and SIF (up to 50%) anomalies for most of the Amazon basin during the 2015/16 El Nino event suggesting down-regulation of productivity as a main factor of positive carbon flux anomalies during anomalously hot and dry conditions. These results are of interest in view of predicted warmer and more erratic future climate conditions.

Estimating evapotranspiration of pistachio crop based on SEBAL algorithm using Landsat 8 satellite imagery

Stationary actual evapotranspiration (ET) estimation methods deal with some issues such as maintenance problems, the point data recording for a particular location, the complex hydrological process calculation, and requiring the expert workers. To solve this, ET estimation methods like Surface Energy Balance Algorithm for Land (SEBAL) method can be used based on the satellite images. However, the efficiency of the SEBAL model varies in ET estimation for different products and environmental conditions. On the other hand, pistachio is an important crop of Iran which little investigation were accomplished to estimate its ET using the presented models. Therefore, the purpose of this study is to investigate the efficiency of SEBAL algorithm in estimating ET of pistachio crop. In this regard, actual ET of a 100 hectares pistachio farm, located in Safaeieh region in the Semnan province, Iran, was selected as the study area. Implementations were performed using 29 Landsat 8 Operational Land Imager (OLI) images during the 2013–2017 period. The results were verified and compared with the results of evapotranspiration in standard condition estimated by the Intelligent Meteorological instrument (iMetos-Pessl) as the ground truth. The results of this study indicate the determination coefficient and Root Mean Square Error (RMSE) of the estimated actual ET for pistachio plant as 0.8 and 2.5 mm, respectively. Moreover, the results indicate the high spatial variability of ET in the pistachio growth period and the need to use a satellite data analysis method, like the SEBAL method, to prepare the ET map. Overall, the results show the good efficiency of the SEBAL model for estimating the actual ET of the pistachio product.