Spatial Distribution Of Evapotranspiration Research Articles

Spatiotemporal Variations in Evapotranspiration and Their Driving Factors in Southwest China between 2003 and 2020

The widespread distribution of karst landforms has led to a shortage of water resources in Southwest China. Understanding the spatiotemporal variations in and driving factors of evapotranspiration (ET) in this area is crucial for understanding and predicting severe water resource shortage. This study conducted trend analysis using meteorological data from 2003 to 2020 as well as remote sensing products such as Penman–Monteith–Leuning equation version 2 (PML-V2) ET. The factors influencing the spatial distribution pattern of average ET were identified using a geographical detector. Partial correlation analysis was performed to characterize the relationships between ET and the factors governing its variations, determined using the random forest model. The results demonstrated the following: (1) The average ET decreased with increasing latitude and altitude, primarily affected by the landform type in terms of longitude and displaying “W”-shaped fluctuations. Overall, the annual ET exhibited a significant (p < 0.05) increasing trend, with 72.63% of its area under the increasing trend. (2) The results of the geographic detector indicated sunshine duration as the strongest explanatory factor of the spatial distribution of ET, followed by enhanced vegetation index (EVI), landform type, precipitation, elevation, slope, and aspect. Instead of an individual factor, the interplay between multiple factors more considerably influenced the spatial distribution pattern of ET. (3) The EVI exhibited an overall increasing trend, with a significant increase over 73.59% of the study area and a positive correlation with ET. Thus, the increase in EVI had the strongest impact on ET in the study area, which was further confirmed by the results of the random forest model for 42.92% of the study area. Thus, the present findings clarify the spatiotemporal variations in and driving factors of ET in Southwest China and can serve as a benchmark for policies aiming to develop and manage water resources in this region.

Spatiotemporal Variation Characteristics of Reference Evapotranspiration and Relative Moisture Index in Heilongjiang Investigated through Remote Sensing Tools

Reference evapotranspiration (ET0) is one of the significant parameters in agricultural irrigation, especially in Heilongjiang, a big agricultural province in China. In this research, the spatiotemporal variation characteristics of evapotranspiration (ET), relative moisture index (MI) and influencing factors of ET0 in Heilongjiang, which was divided into six ecology districts according to landforms, were analyzed with meteorological data observed over 40 years from 1980 and MOD16 products from 2000 to 2017 using Morlet wavelet analysis and partial correlation analysis. The results indicated that (1) the spatial distribution of ET and PET in Heilongjiang in humid, normal and arid years showed a distribution of being higher in the southwest and lower in the northwest, and higher in the south and lower in the north. The PET was higher than ET from 2002 to 2017, and the difference was small, indicating that the overall moisture in Heilongjiang was sufficient in these years. (2) In the last 40 years, the ET0 increased while the annual MI decreased. The annual minimum of MI in the six regions of Heilongjiang was −0.25, showing that all six regions were drought free. (3) The importance of the meteorological factors affecting ET0 was ranked as average relative humidity > average wind speed > sunshine duration. This research provides scientific guidance for the study of using remote sensing to reverse ET.

A remote sensing-based method for daily evapotranspiration mapping and partitioning in a poorly gauged basin with arid ecosystems in the Qinghai-Tibet Plateau

Accurate estimation and partitioning of terrestrial evapotranspiration (ET) is essential for understanding the hydrological cycle and water use efficiency at different scales. Such knowledge is particularly important for sustainable water resources management in arid ecosystems. A daily scale framework for continuous ET mapping and partitioning was proposed in this study based on a universal solution of the traditional Ts-VI models. Its essence is to transform the Ts-VI feature space from regional to pixel scale on the basis of surface energy balance principle. Consequently, the ET estimation and partitioning was only related to the boundary conditions at pixel scale, regardless of the Ts-VI configuration over the spatial domain. We demonstrated the framework with MODIS (Moderate Resolution Imaging Spectroradiometer) products in Qaidam Basin, a poorly gauged basin with arid ecosystems in the Qinghai-Tibet Plateau in China. The scheme was performed pixel by pixel using as much of the remote sensing observations as possible, aiming at that it could be applied to other poorly gauged regions. The comparative analysis indicates that our ET estimates agreed well with three readily available ET products and those retrieved from water balance analysis. The advantages of our universal Ts-VI model mainly lie in its high spatial resolution and daily continuity, which enables it to capture the spatial details and temporal variations more accurately. The results show that our annual average ET estimation from 2001 to 2020 was around 179.20 mm/year, which was very close to its annual average precipitation. The annual average soil evaporation (E) and plant transpiration (T) was 168.77 and 10.43 mm/year, accounting for 94 % and 6 % of the total ET, respectively. ET in Qaidam Basin decreased generally from southeast to northwest and from surrounding mountains to the interior with significant vertical zonality. Consequently, ET of different landscapes followed the order: woodland > shrubland > alpine vegetation > alpine meadow > bare rock > alpine grassland > salt crust > desert grassland > bare soil > gobi > sandy land. As an arid basin, the spatial distribution of ET in Qaidam Basin was mainly controlled by precipitation. However, with the further decrease of temperature in high mountains, ET started to be controlled by energy availability rather than water availability. Accordingly, the variations of our ET estimates with altitude increased first and then decreased, with a peak value of 287.67 mm observed at altitudes of 4600–4800 m.

Spatial distribution of evapotranspiration by fractional vegetation cover index on irrigated cropland banana (Musa Spp.) in the semiarid

Water management can be done in many ways, but the methods that use evapotranspiration (ET) are the most common. The Penman-Monteith FAO56 (PM) standard method is effectively used to estimate evapotranspiration and, in this way, ensure proper water application. In addition, remote sensing is also used for water management. The free availability of software and high-resolution satellite imagery opens many possibilities. Methods such as spatial distribution of ET provide an overall view that contributes to better use of water resources. In this sense, the objective of this study is to demonstrate the spatial distribution of ET determined by the PM method by using an index that measures fractional vegetation cover (Fc). For this purpose, data from weather stations and Landsat 8 collection 2 level 1 image from the OLI/TIRS sensor in spectral bands 4 and 5 were used. The study area is a dwarf silver banana plantation located in the semiarid region of northeastern Brazil, in the Missão Velha city area. The spatialization starts with the determination of the normalized difference vegetation index (NDVI), followed by the determination of the Fc, using the ET from the PM method together with the crop coefficient (Kc). Evapotranspiration mapping images with internalized calibration (METRIC) corresponding to the same location and date were also used to compare and analyze the results. The novelty of this study is utilizing the ET determinate with weather station data and make the spatial distribution of ET (SPD-ET) in satellite images, from a practical and easy way, which can be quickly replicated and used by anyone. The linear regression between SPD-ET and METRIC-ET gives an R2 above 0.80; similar results were obtained for the linear regression between EToF and Fc, with an R2, also above 0.80. The mean values between METRIC-ET and SPD-ET have a deviation of 1.62 mm d-1. The mean absolute percent error between METRIC-ET and SPD-ET was 9.75%, while between EToF and Fc 5.28%. The mean absolute percent error between METRIC-ET and SPD-ET was 9.75%, whereas between EToF and Fc it was 5.28%. Since the difference between the methods is just under 10%, we can conclude that spatializing ET with Fc is as accurate as ET, which was obtained from METRIC.

Changes in land use and cover and their consequences on the spatial distribution of evapotranspiration and climatic elements in southwest Piauí, MATOPIBA

With the advance of agriculture in Brazil, the occurrence of environmental disturbances that can reach different levels, such as the change of use and land cover, is perceived. In the southwest of Piauí, it is noticeable the large portion of Cerrado that has been replaced by crops and pastures, resulting in several impacts, such as changes in evapotranspiration. In the literature there are several methods to estimate it, among them the remote sensing techniques stand out. Therefore, the objective of this work was to quantify agricultural expansion and understand its consequences on real evapotranspiration and on the configuration of meteorological elements in the municipality of Baixa Grande do Ribeiro, through the products of the United States Geological Survey (USGS) accessed through Google Earth. Engine. Platform (GEE), between 2000 and 2020. The real evapotranspiration (ETa) and leaf area index (LAI) data come from the MODIS sensor products. The meteorological data were obtained from the website of the National Aeronautics and Space Administration Prediction Of Worldwide Energy Resources (NASA POWER). The maps were made in QGIS 3.18.1 software from data processed on the GEE platform. The evolution of forest and agricultural areas and images of land use and cover were obtained using the MapBiomas platform. It was observed that between 2000 and 2020, about 27% of the area of native vegetation was replaced, and soybean cultivation grew by approximately 2618%. In addition, the removal of native vegetation for the establishment of pastures and agricultural crops has contributed to the reduction of evapotranspiration and the leaf area index, in addition, it may be associated with the increase in surface and air temperatures and reduction of the relative humidity of the air. This implies the need to create and implement public policies aimed at controlling deforestation in the region, as well as greater inspection in the sphere of environmental crimes.

Assessment of an extended SPARSE model for estimating evapotranspiration from directional thermal infrared data

The spatial distribution of evapotranspiration is often obtained from dual source energy balance models forced by surface temperature data. The use of multi-angular remotely-sensed thermal data in such methods makes them susceptible to directional-anisotropy/thermal-radiation directionality effects that may result from the satellite's position, relative to the Sun, at overpass time. It is therefore important to have these effects accounted for to ensure realistic flux retrievals irrespective of sensor viewing position. At present, dual source models generally interpret surface temperature according to two sources, representing the soil surface and the vegetation. This may be insufficient to adequately represent the limiting temperature conditions that not only depend on the source type but also on their exposure to the Sun. Here, we present a modified version of the SPARSE (Soil Plant Atmosphere Remote Sensing Evapotranspiration) model, wherein the original SPARSE is modified to incorporate sunlit/shaded soil/vegetation elements and coupled with a radiative transfer model that links these four component emissions to out-of-canopy directional radiances as observed by remote sensors. An initial evaluation is carried out to check the model's capability in retrieving surface fluxes over diverse environments instrumented with in-situ thermo-radiometers. When run with nadir-acquired thermal data, both algorithms show no observable difference in their retrieval of total fluxes. We nonetheless show that by incorporating the solar direction and discriminating between sunlit and shaded elements, the partitioning of these overall fluxes between the soil and vegetation can be improved especially in water-stressed environments. We also test the sensitivity of flux and component temperature estimates to the viewing direction of the thermal sensor by using two sets of TIR data (nadir and oblique) acquired simultaneously to force the models and show that sensitivity to viewing direction is significantly reduced. This is an important aspect particularly when using high resolution spatial and temporal data from Earth observation missions that inherently have to consider a wide-range of viewing angles in their design.

Changes in Land Use and Cover and Their Consequences on the Spatial Distribution of Evapotranspiration and Climatic Elements in Southwest Piauí

Changes in Land Use and Cover and Their Consequences on the Spatial Distribution of Evapotranspiration and Climatic Elements in Southwest Piauí

Estimating the spatial distribution of evapotranspiration within the Pra River Basin of Ghana

It is important in water resource planning to accurately estimate the spatial distribution of evapotranspiration (ET) as an input parameter for hydrological studies. Although, conventional pan evaporation, lysimetric and eddy covariance techniques have been used, they only estimate point values. Hence, this study aimed at estimating the spatial distribution of ET within the Pra River Basin (a forest ecological zone) of Ghana, using cloud-free Landsat 8 (OLI/TIRS) satellite images employing the SEBAL methodology. The study further estimates the spatial distribution ET in relation to major climatic variables, Land Use Land Cover (LULC) types and energy balance components. The overall spatial distribution of ET had a mean value of 5.63 mm/day. Spatial distribution of ET (mm/day) for water body (5.51–7.81) and uncultivated forest (5.10–7.71) were high, while moderately average values were observed for logged forest (4.80–7.51). Settlement and bare landscapes observed low rates ((2.05–5.10) mm/day). Spatially, ET was higher in the upper western, central and the eastern parts of the basin, but lower in the northern part and pockets of areas at the southern part of the basin where settlement/bare landscape and logged forest dominate. Areas with high temperature and high solar radiation experiences high ET, while low wind speed, low to average temperature and solar radiation areas experience low ET. Also, areas with both high net radiation and ground heat flux but low to average sensible heat flux experiences high ET and vice versa. Linear regression analysis showed good fit with slope of 0.76 and R2 of 0.93 indicating that 93 % of the variations in observed field measurement of ET fitted perfectly well with ET distributions generated by the SEBAL model.

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.

Determination of crop coefficients and spatial distribution of evapotranspiration and net irrigation requirement for three commonly cultivated crops in South‐East Nigeria

AbstractEffective crop production is one major way of ensuring food security, but basic information on evapotranspiration and net irrigation requirement are needed. ETc, NIR and their spatial distribution were studied for three commonly cultivated crops in south‐east Nigeria, namely African spinach (Amarathus hybridus), Nsukka yellow pepper (Capsicum Chinese Nsukkadrilus) and maize (Zea mays). The average daily ETc from lysimetric water balance studies and Kc were 3.9, 4.20 and 3.7 mm and 0.87, 0.93 and 0.82 for spinach, pepper, and, maize, respectively. The statewide annual evapotranspiration for the crops was between 1070 and 1450 mm. The average annual ranges of NIR were 408–706, 524–706 and 450–621 mm for African spinach, Nsukka yellow pepper and maize, respectively. Statewide, Imo and Abia states do not require irrigation annually. Mapping spatially interpolated evapotranspiration and NIR has not only provided information on areas where weather stations are not available but have also provided information for farmers, water managers and policy makers for effective water resources management and improved crop production for food security in the south‐east of Nigeria. © 2020 John Wiley & Sons, Ltd.

Temporal and Spatial Distribution of Evapotranspiration and Its Influencing Factors on Qinghai-Tibet Plateau from 1982 to 2014

Evapotranspiration is the key driving factor of the earth's water cycle, and an important component of surface water and energy balances. Therefore, it also reflects the geothermal regulation function of ecohydrological process. The Qinghai-Tibet Plateau is the birthplace of important rivers such as the Yangtze River and the Yellow River. The regional water balance is of great significance to regional ecological security. In this study, ARTS, a dualsource remote sensing evapotranspiration model developed on a global scale, is used to evaluate the actual evapotranspiration (ET) in the Qinghai-Tibet Plateau from 1982 to 2014, using meteorological data interpolated from observations, as well as FPAR and LAI data obtained by satellite remote sensing. The characteristics of seasonal. interannual and dynamic changes of evapotranspiration were analyzed. The rates at which meteorological factors contribute to evapotranspiration are calculated by sensitivity analysis and multiple linear regression analysis, and the dominant factors affecting the change of evapotranspiration in the Qinghai-Tibet Plateau are discussed. The results show that: (1) The estimated values can explain more than 80% of the seasonal variation of the observed values (R2 = 0.80, P < 0.001), which indicates that the model has a high accuracy. (2) The evapotranspiration in the whole year, spring, summer and autumn show significant increasing trends in the past 30 years, but have significant regional differences. Whether in the whole year or in summer, the southern Tibetan Valley shows a significant decreasing trend (more than 20 mm per 10 years), while the Ali, Lhasa Valley and Haibei areas show increasing trends (more than 10 mm per 10 years). (3) Sensitivity analysis and multiple linear regression analysis show that the main factor driving the interannual change trend is climate warming, followed by the non-significant increase of precipitation. However, vegetation change also has a considerable impact, and together with climate factors, it can explain 56% of the interannual variation of evapotranspiration (multiple linear regression equation R2 = 0.56, P < 0.001). The mean annual evapotranspiration of low-cover grassland was 26.9% of high-cover grassland and 21.1% of medium-cover grassland, respectively. Considering significant warming and insignificant wetting in the Qinghai-Tibet Plateau, the increase of surface evapotranspiration will threaten the regional ecological security at the cost of glacial melting water. Effectively protecting the ecological security and maintaining the sustainable development of regional society are difficult and huge challenges.

The spatial variability of actual evapotranspiration across the Amazon River Basin based on remote sensing products validated with flux towers

Actual evapotranspiration (ET) is a major component of the water balance. While several international flux measurement programs have been executed in the tropical rain forest of the Amazon, those measurements represent the evaporative process at a few selected sites only. The aim of this study is to obtain the spatial distribution of ET, using remote sensing techniques, across the entire Amazon River Basin. Results from six global ET products based on remote sensing techniques (GLEAM, SEBS, ALEXI, CMRSET, MOD16, and SSEBop) were merged to obtain an ensemble prediction of the ET rates for the complex and in-accessible environment of the Amazon at a spatial resolution of 250 m. The study shows that the basin-wide average ET is 1316 mm/year with a standard deviation of 192 mm/year. This new ET-Amazon product was validated against seven different historic flux tower measurements. The energy balance closure of the in situ measurements varied between 86 and 116%. Only months with more than 70% completeness of in situ measurements were considered for validation. Different procedures for closure correction were included in the analyses. The correlation between measured and remotely sensed ET is good (R2 > 0.97 for consecutive periods of 2 to 12 months), and the bias correction is negligible for the energy balance residual method, which seemed most favorable. Monthly ET values have more uncertainty. The monthly RMSE values vary between 7.4 and 27.8 mm/month (the average RMSE is 22.2 mm/month), and the coefficient of determination (R2) varies between 0.48 and 0.87 (the average R2 is 0.53). The ET from the water balance is 1380 mm/year, being − 64 mm/year difference and 4.6% less than ET derived from the water balance. The evaporation from the Amazon basin inside Brazil is 5063 km3/year, followed by Peru with 1165 km3/year. ET-Amazon shows more spatial details and accuracy than alternative global ET products such as LandFlux-EVAL, Model Tree Ensemble (MTE), and WACMOS-ET. This justifies the development of new regional ET products.

Investigating the temporal and spatial variations of water consumption in Urmia Lake River Basin considering the climate and anthropogenic effects on the agriculture in the basin

Urmia Lake River Basin (ULRB) is one of the most important habitats in the world and one of the major agricultural regions in Iran. On average, the ratio of irrigation to evapotranspiration in this basin is more than 73%. Investigating the irrigation water requirement pattern changes and the spatial distribution of evapotranspiration during the basin development period on a regional scale play important roles in understanding the basin situation. In this study, the actual evapotranspiration has been estimated by SEBAL model. By estimating the precipitation distribution in the basin, the agricultural irrigation water requirement pattern has been calculated using the land use map in 1995, 2010 and 2014 in the total agricultural lands and in its 7 major subbasins where ET changes from 369 to 1000 mm. The maximum irrigation water consumption were 535 million cubic meters in Urmia subbasin (2010) and then 469 million cubic meters in Miandoab Subbasin (2014), While its average was 2108 million cubic meters in the basin. Furthermore, the maximum and minimum levels of evapotranspiration pattern in the total agricultural lands were 765 and 555 mm in 2010 and 1995, respectively. This study included (1) a comparison between regional irrigation water requirement in the basin and (2) investigating the causes of (including natural and anthropogenic) changes in the amount of irrigation water consumption over the years. The study approach provided a simple but powerful assessment to describe the irrigation water consumption pattern in the subbasins using the minimum ground data and to identify the water management strategies in basin agriculture and climate changes.

Evaluation of SEBS Algorithm for Estimation of Daily Evapotranspiration Using Landsat-8 Dataset in a Semi-Arid Region of Central Iran

Evapotranspiration is one the most important parameters in the hydrological cycle and plays a significant role in energy balance of the earth’s surface. Traditional field-based measurements approaches for calculation of daily evapotranspiration are valid only for local scales. Using advanced remote sensing technology, the spatial distribution of evapotranspiration may now be quantified more accurately. At the present study, daily evapotranspiration is estimated using Landsat 8 datasets based on the Surface Energy Balance System (SEBS) algorithm over the Zayanderud Dam area in central Iran. For this purpose, three Landsat 8 datasets in the years 2013, 2014 and 2015 covering the study area were atmospherically corrected using the FLAASH approach. The biophysical parameters of the earth’s surface for SEBS algorithm, such as normalized difference vegetation index (NDVI), Leaf area index (LAI), fractional vegetation cover (FC) were extracted from the visible and near infrared bands and land surface temperature was computed from thermal bands the Landsat 8 datasets. The spatial distribution of daily ET was provided separately for each year. In addition to the SEBS algorithm, the Penman-Monteith method was applied to estimate the daily ET from meteorological datasets which was obtained from two synoptic stations within the study area. Finally, the simulated daily ET values from both SEBS and Penman-Monteith method were compared to observed values obtained from a lysimeter within the study area. Although the estimated results from both SEBS and Penman-Monteith show a strong correlation with the observed values, the derived ET maps and following analysis demonstrated SEBS has higher accuracy and strength in estimation of daily ET in Zayanderud Dam region.

Estimation of spatial and temporal water requirements of grain amaranth using satellite, local and virtual weather stations datasets in Uganda

In this study, an integrated approach incorporating Remote Sensing (RS), Geographical Information System (GIS), local meteorological weather stations’ data and NASA’s virtual meteorological stations’ data were used to quantify Grain Amaranth (GA) water requirements in Uganda. Penman-Monieth method within CropWAT8 model and Surface Energy Balance Algorithm for Land (SEBAL) Model was used to quantify the evapotranspiration. Normalized Difference Vegetation Index (NDVI), daily spatial distribution of Evapotranspiration (ET), Land Surface Temperature (LST) and surface albedo were extracted from satellite imagery. The ratio of effective rainfall (Pe) to Potential Evapotranspiration (PET) – (Pe/PET) and time series for NDVI were computed to determine the growth stage of GA in different areas. The GA water demand was the highest in Karamoja sub-region (467.5 mm/season) and the lowest in Tororo (174.1 mm/season). The growing season for GA in most areas of Uganda was from March to December. Estimation of evapotranspiration in Karamoja sub-region with SEBAL model corresponded to the NDVI extracted, especially for highly vegetated areas. CROPWAT indicated that if GA was planted during the late September and early October in Karamoja sub-region, despite the decreasing moisture levels, the crop could have sufficient water supply during emergence to maturity. The ability to utilize low available moisture levels makes GA a potential crop to bridge the gap (due to the elongated drought) for the food production cycle in Karamoja sub-region. Keywords: Grain Amaranth, water requirement, remote sensing, SEBAL, evapotranspiration, Uganda DOI: 10.3965/j.ijabe.20160902.1676 Citation: Kyagulanyi J, Kabenge I, Banadda N, Muyonga J, Mulamba P, Kiggundu N. Estimation of spatial and temporal water requirements of grain amaranth using satellite, local and virtual weather stations datasets in Uganda. Int J Agric & Biol Eng, 2016; 9(2): 85－97.

Groundwater-dependent ecosystems: recent insights from satellite and field-based studies

Abstract. Groundwater-dependent ecosystems (GDEs) are at risk globally due to unsustainable levels of groundwater extraction, especially in arid and semi-arid regions. In this review, we examine recent developments in the ecohydrology of GDEs with a focus on three knowledge gaps: (1) how do we locate GDEs, (2) how much water is transpired from shallow aquifers by GDEs and (3) what are the responses of GDEs to excessive groundwater extraction? The answers to these questions will determine water allocations that are required to sustain functioning of GDEs and to guide regulations on groundwater extraction to avoid negative impacts on GDEs. We discuss three methods for identifying GDEs: (1) techniques relying on remotely sensed information; (2) fluctuations in depth-to-groundwater that are associated with diurnal variations in transpiration; and (3) stable isotope analysis of water sources in the transpiration stream. We then discuss several methods for estimating rates of GW use, including direct measurement using sapflux or eddy covariance technologies, estimation of a climate wetness index within a Budyko framework, spatial distribution of evapotranspiration (ET) using remote sensing, groundwater modelling and stable isotopes. Remote sensing methods often rely on direct measurements to calibrate the relationship between vegetation indices and ET. ET from GDEs is also determined using hydrologic models of varying complexity, from the White method to fully coupled, variable saturation models. Combinations of methods are typically employed to obtain clearer insight into the components of groundwater discharge in GDEs, such as the proportional importance of transpiration versus evaporation (e.g. using stable isotopes) or from groundwater versus rainwater sources. Groundwater extraction can have severe consequences for the structure and function of GDEs. In the most extreme cases, phreatophytes experience crown dieback and death following groundwater drawdown. We provide a brief review of two case studies of the impacts of GW extraction and then provide an ecosystem-scale, multiple trait, integrated metric of the impact of differences in groundwater depth on the structure and function of eucalypt forests growing along a natural gradient in depth-to-groundwater. We conclude with a discussion of a depth-to-groundwater threshold in this mesic GDE. Beyond this threshold, significant changes occur in ecosystem structure and function.

Spatial–temporal dynamics of gross primary productivity, evapotranspiration, and water-use efficiency in the terrestrial ecosystems of the Yangtze River Delta region and their relations to climatic variables

Moderate Resolution Imaging Spectroradiometer (MODIS) products and climate data collected from meteorological stations were used to characterize the spatial–temporal dynamics of gross primary productivity (GPP), evapotranspiration (ET), and water-use efficiency (WUE) in the Yangtze River Delta (YRD) region and the response of these three variables to meteorological factors. The seasonal patterns of GPP and WUE showed a bimodal distribution, with their peak values occurring in May and August, and April and October, respectively. By contrast, the seasonal variation of ET presented a unimodal pattern with its maximum in July or August. The spatial distribution of ET and GPP was similar to higher values occurring in the south. From 2001 to 2012, GPP in the eastern YRD decreased, while GPP in the western part increased. In comparison, over the 12 years, ET in the northern part of YRD decreased, while ET in the southern part increased. The spatial distribution and spatial variation of WUE were both similar to those of GPP. This implies that the changes in WUE are primarily controlled by the variations in GPP. The annual average WUE over vegetation types followed the order of: evergreen broadleaf forest (1.95 g C kg−1 H2O) > deciduous broadleaf forest (1.87 g C kg−1 H2O) > evergreen needle leaf forest (1.70 g C kg−1 H2O) > deciduous needle leaf forest (1.68 g C kg−1 H2O) > grassland (1.66 g C kg−1 H2O) > cropland (1.61 g C kg−1 H2O). Both GPP and ET increased with increasing annual mean temperature (Ta) and annual mean precipitation across all of the plant function types. WUE decreased as vapour pressure deficit (VPD) increased in all of the biomes. Interestingly, the relationship between WUE and VPD was the most significant in broadleaf forest. Whether this phenomenon is universal should be investigated in future studies.

Wavelet-multivariate relevance vector machine hybrid model for forecasting daily evapotranspiration

Evapotranspiration (ET) is one of the main components of the hydrological cycle. It is a complex process driven mainly by weather parameters, and as such, is characterized by high non-linearity and non-stationarity. This paper introduces a methodology combining wavelet multiresolution analysis with a machine learning algorithm, the multivariate relevance vector machine (MVRVM), in order to predict 16 days of future daily reference evapotranspiration (ETo). This methodology lays the ground for forecasting the spatial distribution of ET using Landsat satellite imagery, hence the choice of 16 days, which corresponds with the Landsat overpass cycle. An accurate prediction of daily ETo is needed to improve the management of irrigation schedules as well as the operations of water supply facilities like canals and reservoirs. In this paper, various wavelet decompositions were performed and combined with MVRVM to develop hybrid models to predict ETo over a 16-days period. These models were compared to a MVRVM model, and models accuracy and robustness were evaluated. The addition of 10 days of forecasted air temperature as additional inputs to the forecasting models was also investigated. The results of the wavelet-MVRVM hybrid modeling methodology showed that a reliable forecast of ETo up to 16 days ahead is possible.

The responses of evapotranspiration due to changes of LUCC under seawater intrusion in a coastal region

The paper provides a coherent pattern identification analysis of the impacts of coastal land use and land cover (LULC) on evapotranspiration (ET) under the impact of seawater intrusion. The study applied the Landsat satellite data to characterize the LULC at Laizhou Bay, Shandong Province, China. Then, the ET and heat fluxes were estimated using the surface energy balance algorithm for land model with two-time phase thermal infrared band images and regional surface parameters. This allowed for the eventual linkage of seawater intrusion to land use/cover changes (LUCC) and ET variations over time. The case study discussed in this paper carried out a coastal landscape dynamics assessment using multi-source and multi-sensor remote sensing technologies. The results are: (1) due to its distance from the sea, the vegetation index (modified soil-adjusted vegetation index, MSAVI) gradually increases with the gradual increase of land use grade (Uindex); (2) there are a variety of types of relational patterns between parameters (LST, G(n), MSAVI, and Uindex) and ET (positive, negative, and no relationship); and (3) seawater intrusion significantly affected the spatial pattern of LUCC, which evidently affected the spatial distribution of ET. The spatial distribution pattern and change characteristics of ET were formed by double driving forces of seawater intrusion and LUCC under the background effects of regional climate.

Relations between surface evapotranspiration and water table: A case study base on remote sensing

Estimation of land surface evapotranspiration (ET) is one of the most difficult tasks in the field of hydrology and water resources. In this study, ET in the Golmud Region is estimated using remote sensing techniques, which own the characteristics of high efficiency, precision, large-scale and visualization. The Golmud Region has a specific geographic feature and it is an important mineral production base in China. However, the health of ecosystem in this region is just enduring severe water resources stress. Surface energy balance system model being an applicable model with good theoretic basis to estimate land surface ET with less meteorological data requirement, and the improved model is used to estimate land surface ET and analyzes the relationship with the water level in the Golmud Region on the basis of MODIS data. Results show that annual ET is single-peak distributed in month scale with a well seasonal variation. Spatially, Land surface spatial distribution of ET from south to north, from high altitude to low altitude mountain plain, ET following a decrease in the ground water table, so come to that the groundwater depth is the most important controlling factor of ET. The improved model is also suitable for other similar areas. Key words: Land surface evapotranspiration, remote sensing, MODIS, Golmud Region