Estimated Evapotranspiration Values Research Articles

Assessing field scale spatiotemporal heterogeneity in salinity dynamics using aerial data assimilation

Soil moisture and salinity shifts within the root zone can significantly alter crop yields. Thus, spatiotemporal dynamics of these parameters are essential for precision crop management. Airborne or spaceborne earth observation methods based on vegetation and soil observations have sometimes been used with limited success to indirectly understand parameters like soil salinity. These datasets lack spatiotemporal resolution to discern field-scale heterogeneities, and estimates’ accuracy is poor. A Metropolis-Hasting Markov Chain-Monte Carlo (MCMC) based method was developed to estimate field-scale soil salinity by assimilating estimated evapotranspiration (ET) data obtained from aerial canopy temperature sensing with ET outputs from a one-dimensional soil-water transport model. By aligning the two estimated ET values, we inferred anticipated soil salinity levels in a mature pecan orchard (28,951 m2). Our results aligned closely with in-situ measurements with a spatial cross-correlation more than 0.86 and highlighted the expected heterogeneities and nonlinearities. This research offers an approach to refine the current state-of-the-art crop models by accounting for field scale heterogeneities using remotely sensed data. This assimilation method will pave the way for a more inclusive agricultural system modeling that can infer critical but hard-to-measure soil properties from easier-to-obtain remotely sensed datasets. Though this paper concentrates on aerial observations, we anticipate similar methods can be used for satellite-based imagery, especially those with high spatial, temporal, and spectral resolutions.

Spatial-temporal variations in evapotranspiration across the continental United States: An atmospheric water balance perspective

Accurate estimation of terrestrial evapotranspiration (ET) is crucial for understanding land–atmosphere interactions, but is challenging on the regional scales. The water balance approach, including terrestrial and atmospheric water balance (TWB and AWB), provides a simple tool for estimating regional ET. This study estimated ET values based on the AWB approach (ETAWB) over the continental United States (CONUS) for the period 1979–2021. Validations using TWB-based ET estimates (ETTWB) suggest that ETAWB is accurate. ETAWB demonstrates comparable interannual variability with the other three long-term ET products over the CONUS and is consistent with ETTWB in the majority of basins. The 43-year CONUS averaged ETAWB is 548 ± 26 mm/year, with higher values in the eastern region and the coastal regions in the western CONUS, and lower values in the western arid regions. During 1979–2021, increasing trends of ETAWB are observed in the eastern CONUS, while decreasing trends occurred in the western regions. The intercomparison between ETAWB, GLEAM, Noah, and ERA5 illustrates similar spatial patterns and linear trends. In the water-limited arid basins, ETAWB anomalies over time show strong agreements with precipitation anomalies. The results of this study indicate that the AWB approach provides reasonable regional-to-continental terrestrial ET estimates over the CONUS, serving as a reference for hydrological and climatic modeling.

Evaluating the impact of different UAV thermal sensors on evapotranspiration estimation

Accurate evapotranspiration (ET) estimation is vital for precise irrigation management. Remote sensing provides a unique method for obtaining spatial and temporal ET information. With technological advancements, several unmanned aerial vehicle (UAV) thermal sensors have been developed. However, the impact of thermal sensors on ET estimation is unclear. This study evaluated the impact of different UAV thermal sensors, including Micasense Altum and Flir Duo Pro-R (FDP-R), on ET estimation using the Two Source Energy Balance (TSEB) model. A field experiment was conducted during the 2021 sorghum growing period, with irrigation treatments consisting of four different regimes: full irrigation (S1), 70 % of S1 (S2), 40 % of S1 (S3), and rainfed (S4). The results revealed no statistically significant differences between the estimated ET values using Micasense Altum and FDP-R thermal sensors. The TSEB model's performance was entirely satisfactory for full irrigation, with RMSE values of 5.63 mm for Micasense Altum and 7.17 mm for FDP-R, in 10 days. However, the accuracy deteriorated with increasing water stress, reaching 29.02 mm for Micasense Altum and 25.12 mm for FDP-R, in 10 days in rainfed plots. The study results highlight the capability of both Micasense Altum and FDP-R thermal sensors to provide comparable ET estimates, particularly under full irrigation conditions. However, the decline in accuracy with increased water stress underlines a potential limitation of the TSEB model when applied to varying irrigation regimes. These insights emphasize the importance of adjustment of TSEB input parameters such as αPT coefficient, resistance terms etc. and sensor technologies, particularly in water-stressed environments, to ensure accurate ET estimation. This study demonstrated the potential of high-resolution UAV thermal sensors for precision irrigation management tasks. Further studies with different thermal sensors are needed to understand this technology's benefits fully. The impact of different climate conditions on ET estimation should also be explored for accurate results.

Spatial and temporal estimation of actual evapotranspiration of lower Bhavani basin, Tamil Nadu using Surface Energy Balance Algorithm for Land Model

Estimating evapotranspiration's spatiotemporal variance is critical for regional water resource management and allocation, including irrigation scheduling, drought monitoring, and forecasting. The Surface Energy Balance Algorithm for Land (SEBAL) method can be used to estimate spatio-temporal variations in evapotranspiration (ET) using remote sensing-based variables like Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), surface albedo, transmittance, and surface emissivity. The main aim of the study was to evaluate the actual evapotranspiration for the lower Bhavani basin, Tamil Nadu based on remote sensing methods using Landsat 8 data for the years 2018 to 2020. The actual evapotranspiration was estimated using SEBAL model and its spatial variation was compared over different land covers. The estimated values of daily actual evapotranspiration in the lower Bhavani basin ranged from 0 to 4.72 mm day-1. Thus it is evident that SEBAL model can be used to predict ET with limited ground base hydrological data. The spatially estimated ET values will help in managing the crop water requirement at each stage of crop and irrigation scheduling, which will ensure the efficient use of available water resources.

Estimating Canopy-Scale Evapotranspiration from Localized Sap Flow Measurements

The results reported in this work are based in part on measurements of sap flow in a few select trees on a representative riparian forest plot coupled with a forest-wide randomized sampling of tree sapwood area in a watershed located along the Pacific coast in Santa Cruz County, California. These measurements were upscaled to estimate evapotranspiration (ET) across the forest and to quantify groundwater usage by dominant phreatophyte vegetation. Canopy cover in the study area is dominated by red alder (Alnus rubra) and arroyo willow (Salix lasiolepis), deciduous phreatophyte trees from which a small sample was selected for instrumentation with sap flow sensors on a single forest plot. These localized sap flow measurements were then upscaled to the entire riparian forest to estimate forest ET using data from a survey of sapwood area on six plots scattered randomly across the entire forest. The estimated canopy-scale ET was compared to reference ET and NDVI based estimates. The results show positive correlation between sap flow based estimates and those of the other two methods, though over the winter months, sap flow-based ET values were found to significantly underestimate ET as predicted by the other two methods. The results illustrate the importance of ground-based measurements of sap flow for calibrating satellite based methods and for providing site-specific estimates and to better characterize the ET forcing in groundwater flow models.

Spatiotemporal variations in evapotranspiration and its influencing factors in the semiarid Hailar river basin, Northern China

Evapotranspiration (ET) is a critical variable in the world's water cycle, and plays a significant role in estimating the impact of environmental change on the regional hydrothermal cycle. Moreover, as an essential of eco-hydrological processes, changes in ET may exceptionally impact the local climate and provide indicative information on the eco-system's functioning. The Hailar River Basin (HRB), located in northern China, is one of the most sensitive areas to climate warming. Under the influence of climate change in recent years, the vegetation dynamics of the basin have been significant and have had profound effects on the regional water cycle conditions and hydrological processes. The HRB is located in a semiarid region and ET is the main mode of water consumption. The ET response to climate change and vegetation dynamics is the focus of research on ecohydrological processes in this basin. In this study, a distributed hydrological model, the BTOPMC model, is used to evaluate the actual ET in the HRB from 1981 to 2020, based on in situ meteorological data as well as LAI data obtained by satellite remote sensing. The seasonal, interannual and spatial dynamics of ET were characterized. The contribution of meteorological factors to ET was calculated by sensitivity analysis and multiple linear regression analysis, and the predominant elements influencing the difference in ET in the HRB were also discussed. The results show that: (1) estimated ET values can clarify over 85% of the seasonal variation in the observed values (R2= 0.79, P < 0.001; R2= 0.84, P < 0.001), which demonstrates that the model has a high precision. (2) Over the past 40 years, the annual ET has shown a clear increasing trend and a large spatial heterogeneity in its spatial distribution, which is consistent with the trend of vegetation. It mainly shows that the eastern forest area is larger than the central forest–grass transition area and the western meadow steppe area. (3) Sensitivity and influential factor contribution analyses show that the main factor driving interannual variability in ET is climate warming, followed by precipitation. At the same time, vegetation dynamics also play a crucial role in ET, especially in areas with different vegetation types and high coverage, while climatic factors also have a strong influence on ET indirectly through vegetation. Due to its special geographic location, the HRB is more sensitive to global climate change and is a typical ecologically fragile area. Therefore, this study has important scientific value and social significance for maintaining ecological security and the sustainable use of water resources.

Desarrollo de un algoritmo de programación SIG para estimar la evapotranspiración en los cultivos mediante sensores remotos

A study was conducted to evaluate the feasibility of GIS programming as a potential tool in the automation of image processing obtained by the LANDSAT 8 satellite to estimate evapotranspiration (ET) in crops. The objective was to develop an algorithm in python language implementing the SEBAL model. 35 complex equations were developed, which were automated for the processing of 13 scenes, thus covering the entire vegetative cycle of corn cultivation on the "Rancho Las Mercedes" property. For the validation of the results, the data measured by the INIFAP weather station network was consulted on the dates corresponding to the images. The results obtained show an RMSE ranging from 0.001 for the month of June to 0.013 for the month of April. The instantaneous ET values are between the ranges of 0.01 mm / hr and 0.80 mm / hr. Maps of their spatial distribution were generated, where it can be seen that the lowest ET values, those close to zero, correspond to human settlements and bare soils, while the highest values correspond to sites of vigorous vegetation and bodies of water.

Comparative Assessment of Reference Evapotranspiration Estimation Using Conventional Method and Machine Learning Algorithms in Four Climatic Regions

Reference evapotranspiration (ETo) is considered as an essential component in hydrological and agro meteorological processes. Its accurate estimation becomes an imperative in the planning and management of irrigation practices. ETo estimation also plays a vital role in improving the irrigation efficiency, water reuse and irrigation scheduling. The conventional physical model of Penmen Montieth (PM56) developed by Food and agriculture organization (FAO) has been recommended worldwide for ETo estimation. This model was firstly used in this study to determine ETo by using required meteorological data and obtained results used as referenced values. Afterward, five data machine learning algorithms/data driven models, support vector machine (SVM), multilayer perceptron (MLP), group method of data handling (GMDH), general regression neural network (GRNN) and cascade correlation neural network (CCNN), were applied to estimate ETo values. The climatic data of maximum and minimum temperatures, wind speed, average relative humidity and sunshine hours of six stations from Pakistan was used to train and test data driven model. Data driven models were also applied on other climatic stations without training data which lie in China, New Zealand and USA to further validate and investigate their performance. Comparison results indicated that model efficiency (ME) and correlation coefficient (r) of SVM were obtained (ranges: ME = 95–99%; r = 0.96–1) maximum for all the selected stations. Alternatively, model errors (RMSE = 0.016, MSE = 0.0001 & MAE = 0.08) for SVM were found minimum in comparison to GMDH, MLP, CCNN and GRNN. In addition, all data driven models show enough divergence from hyper arid to high humid climate except SVM which shows almost identical results for all the climatic zones in comparison to standard FAO-PM56 method. Finally, it can be concluded that SVM could be considered as a reliable alternative method for ETo estimation among data driven models.

Estimation of evapotranspiration in lesser Himalayas using remote sensing based surface energy balance algorithm

In this study, remote sensing-based algorithm, METRIC is used to estimate evapotranspiration (ET) over a mountainous watershed in the lesser Himalayas in Uttarakhand, India. ET estimates of METRIC are compared with the ET values determined by using FAO Penman-Monteith equation and crop coefficients. In its original form, METRIC underestimated the ET values considerably with mean absolute error (MAE) of 0.95 mm/day. A modification is incorporated in METRIC for better representation of the effect of rainfall on the ET process. The proposed modification estimates ET at the hot pixel using daily rainfall and meteorological data. Using the modification, the MAE is reduced to 0.44 mm/day and underestimation of ET is reduced from 20.9% to 8.4%. This study contributes to the better understanding of ET in the lesser Himalayas of Uttarakhand. It also underlines the importance of accurate assignment of ET to the hot pixel for accurate estimation of ET using METRIC.

Analyzing water table depth fluctuation response to evapotranspiration involving DRAINMOD model

A proper prediction of the water table (WT) depth in hydrological models highly depends on the accuracy of evapotranspiration (ET) estimation. In this study, the response of WT fluctuations to changes in ET was investigated involving the DRAINMOD water management model. The WT depth data were measured during three canola growing seasons (2011-12, 2015-16 and 2016-17) in a paddy field with two subsurface drainage systems (drain depth of 65 cm with two spacing of 15 m and 30 m) in the north of Iran. For the growing seasons, ET was estimated through 17 equations including five temperature- based, four radiation- based, three pan evaporation- based, four combination- based and one mass transfer- based equations. The estimated ET values was then applied in the calibrated DRAINMOD model to simulate the corresponding WT depths in the drainage systems. The reliability of various ET estimation methods and the model predictions were evaluated using determination coefficient (R2), root mean square error (RMSE), error percentage (PE) and mean absolute deviation (MAD). Compared to the FAO- Penman-Monteith equation, the FAO-24 radiation (R2 = 0.90, RMSE = 0.31 mm d-1, MAD =0.71 mm d-1 and PE = - 0.95%), Blaney- Criddle (R2 = 0.93, RMSE = 0.38 mm d-1, MAD =0.76 mm d-1 and PE = - 6.24%), Irmak (R2 = 0.87, RMSE =0.87 mm d-1, MAD =0.41 mm d-1 and PE = - 11.09%) and FAO- 24 pan (R2 = 0.86, RMSE =0.45 mm d-1, MAD =0.80 mm d-1 and PE = - 16.18%) provided the best estimations of ET. However, the best prediction of the WT depths were obtained for the Rohwer and pan evaporation- based equations. These methods considerably improved the reliability of the DRAINMOD predictions in comparison with the Thornthwaite method which is a default method for ET calculation in the model. Based on the results, the Rohwer and FAO-24 pan equations are recommended as suitable methods for estimating ET in the DRAINMOD model for the study area.

Remote sensing as a tool to determine biophysical parameters of irrigated seed corn crop

In recent years, many studies have been conducted combining orbital remote sensing data and crop growth models for vegetation monitoring, evapotranspiration estimation and quantification of biophysical parameters, e.g., NDVI, surface temperature, albedo, and biomass. The aim of the present study was to estimate evapotranspiration (ETr), biomass (BIO), and water productivity (WP) for irrigated seed corn crop using the SAFER algorithm and Landsat 8 satellite images. For this, eight cloud-free images were acquired at different phenological stages over the interest area on the United States Geological Survey website and meteorological data. ETr was estimated by the SAFER algorithm, BIO by the Monteith model, and WP by the BIO/ETr ratio. ETr values ranged from 0 to 6 mm d?1, with the highest values coinciding with the period of high vegetative crop vigor, while the lowest values were found at the sowing season. The highest biomass values were observed from images at 46 and 62 days after sowing (DAS), corresponding to 286 and 289 kg ha?1 d?1, respectively. The highest mean of water productivity was observed at 62 DAS, with 6.9 kg m?3 of water, corresponding to the period of maximum vegetative crop vigor. The application of the SAFER model together with Landsat 8 satellite images was an alternative to identifying the spatial and temporal variation of biophysical parameters of the corn crop. It could assist in the management of water in irrigated agriculture and decision making in large-sized farms.

Predictive Evapotranspiration Equations in Rain Gardens

Current stormwater control measure (SCM) design often does not include the dynamic process of evapotranspiration (ET) for vegetated systems. This study compared two reference ET equations with a three-year data set from rain garden weighing lysimeters. The outcome was a tool to incorporate ET into SCM design. The weighing lysimeters at Villanova University, located in southeastern Pennsylvania, were used to measure water budget parameters for three scenarios: sandy loam with UO, sand with an unconstricted outflow (UO), and sand with internal water storage (IWS). The two ET models explored were the ASCE Penman-Monteith equation (a robust model) and the Hargreaves equation (a simple model). Estimated ET values from these two equations, both with and without modifications for water availability and crop presence, were compared and calibrated (if modified) with observed data. Comparisons and calibrations were performed on a daily and storm basis to explore the applicability of the two ET models for continuous and storm approaches. The observed ET was 28%–52% of inflow over the continuous three-year period and 16–30 mm on a storm scale, making ET a significant part of the lysimeters’ water budget. Due to the experimental nature of the lysimeters, 12 of the 36 study months had additional simulated runoff, such that a smaller ET as a percentage of inflow was expected in the rain garden SCM’s water balance. The Hargreaves and ASCE Penman-Monteith equations without modification provided an adequate estimate for rain garden ET for all systems at the storm scale. Modifications to ET estimations produced by both equations through crop coefficients and a soil moisture extraction function provided a good model for storm-scale ET by reducing errors and increasing efficiencies for all weighing lysimeter types. Evapotranspiration estimates from both unmodified equations provided, at best, a marginally better estimate than the average observed rate for continuous daily rain garden ET. The application of crop coefficients and a soil moisture extraction function to both equations reduced errors in ET estimates and increased the equations’ predictive power (Nash-Sutcliffe efficiency) for all weighing lysimeter types. Both equations with modifications on a daily scale produced good ET estimates for the IWS system. For both equations, crop coefficients were found in an expected range for UO systems (0.3–1.5) but were high in the IWS system (1.6–2.0). Soil moisture extraction functions were not needed to calibrate the IWS equations on the storm scale. Both the Hargreaves equation and the ASCE Penman-Monteith equation provided an adequate model (especially with modifications) to incorporate ET into a design-storm approach to SCM design. Use of both predictive models on a daily scale has potential use in continuous simulation, as in most cases the ET estimations predicted by the equations provided a better estimate than the average of the observed daily ET rates.

Estimating daily evapotranspiration based on a model of evaporative fraction (EF) for mixed pixels

Abstract. Currently, applications of remote sensing evapotranspiration (ET) products are limited by the coarse resolution of satellite remote sensing data caused by land surface heterogeneities and the temporal-scale extrapolation of the instantaneous latent heat flux (LE) based on satellite overpass time. This study proposes a simple but efficient model (EFAF) for estimating the daily ET of remotely sensed mixed pixels using a model of the evaporative fraction (EF) and area fraction (AF) to increase the accuracy of ET estimate over heterogeneous land surfaces. To accomplish this goal, we derive an equation for calculating the EF of mixed pixels based on two key hypotheses. Hypothesis 1 states that the available energy (AE) of each sub-pixel is approximately equal to that of any other sub-pixels in the same mixed pixel within an acceptable margin of error and is equivalent to the AE of the mixed pixel. This approach simplifies the equation, and uncertainties and errors related to the estimated ET values are minor. Hypothesis 2 states that the EF of each sub-pixel is equal to that of the nearest pure pixel(s) of the same land cover type. This equation is designed to correct spatial-scale errors for the EF of mixed pixels; it can be used to calculate daily ET from daily AE data. The model was applied to an artificial oasis located in the midstream area of the Heihe River using HJ-1B satellite data with a 300 m resolution. The results generated before and after making corrections were compared and validated using site data from eddy covariance systems. The results show that the new model can significantly improve the accuracy of daily ET estimates relative to the lumped method; the coefficient of determination (R2) increased to 0.82 from 0.62, the root mean square error (RMSE) decreased to 1.60 from 2.47 MJ m−2(decreased approximately to 0.64 from 0.99 mm) and the mean bias error (MBE) decreased from 1.92 to 1.18 MJ m−2 (decreased from approximately 0.77 to 0.47 mm). It is concluded that EFAF can reproduce daily ET with reasonable accuracy; can be used to produce the ET product; and can be applied to hydrology research, precision agricultural management and monitoring natural ecosystems in the future.

Required Interval of Weather Data for Proper Irrigation Scheduling

CLIMATE variability is very common in Egypt recently, therefore studying its effects on irrigation scheduling for crops is important. The objective of this study was to define a number of years of former weather data prerequisite to estimate evapotranspiration (ETo) to schedule irrigation in three sites in Egypt (El-Gharbia, Beni Swief and Sohag). Daily values of weather data were collected for 10 years (2008-2017).Monthly ETo values were calculated by The BISm model. Descriptive statistics (mean, range, R2, CV and SD) were done to determine the temporal and spatial variability between monthly values of weather elements, as well as ETo. Furthermore, assessment of ETo values trend (decreasing or increasing) was done.The results showed that there were increasing temporal and spatial trends in the 10-year weather data, as well as ETo values in the 3 sites. However, it was more pronounced from 2015 to 2017. Furthermore, the results indicated that the range, CV% and SD were lower in the 3-year interval (2015-2017), compared to 10-year interval for all sites. There were stronger relationships between weather elements and ETo values in the 3-year interval, compared to 10-year interval, as represented by R2 values.Thus, it can be concluded that the recent 3-year interval is the most suitable interval for ETo calculation for proper irrigation scheduling to improve water management on field level in Egypt.

The performance of fuzzy regression method for estimating of reference evapotranspiration under controlled environment

With the objective of evaluating the performance of fuzzy regression method for estimating the reference evapotranspiration in greenhouse, a lysimeter study was conducted to determine the evapotranspiration (ETo) rates for grass crop. Daily outputs from model have been tested against reference evapotranspiration data computed by the lysimeter to assess the accuracy of the model. The estimated ETo values from a fuzzy regression model using five input parameters, including maximum and minimum temperature, mean relative humidity, wind speed and solar radiation were obtained with RMSE = 0.68 mm/day, R2 = 0.98. The accuracy of fuzzy 1 was the best but the accuracy of the fuzzy 3 was the worse for estimating daily evapotranspiration. The RMSE values of fuzzy 1, fuzzy 2, Fuzzy 3 were 0.68, 0.99 and 1.307, respectively. Thus, fuzzy 1 approaches work well for the data set used in greenhouse condition.

西北干旱区河西走廊荒漠绿洲土地覆盖类型与蒸散的关系研究——基于Landsat 8和ZY3数据融合

PDF HTML阅读 XML下载 导出引用 引用提醒 西北干旱区河西走廊荒漠绿洲土地覆盖类型与蒸散的关系研究——基于Landsat 8和ZY3数据融合 DOI: 10.5846/stxb201807161532 作者: 作者单位: 中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室/中国科学院大学。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室/中国科学院大学。,中国科学院西北生态环境资源研究院临泽内陆河流域研究站/中国科学院生态水文与流域科学重点实验室/中国科学院大学。 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划项目（2017YFC0504303）；国家自然科学基金项目（41771041，41501044，41701035） Relationship between land cover type and evapotranspiration on the basis of Landsat 8 and ZY3 data fusion approach for a desert oasis in the middle Hexi corridor area of the arid regions of northwestern China Author: Affiliation: Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, University of Chinese Academy of Sciences.,Linze Inland River Basin Research Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences.,Linze Inland River Basin Research Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences.,Linze Inland River Basin Research Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences.,Linze Inland River Basin Research Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, University of Chinese Academy of Sciences.,Linze Inland River Basin Research Station; CERN/Key Laboratory of Ecohydrology and Watershed Science, Chinese Academy of Sciences/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, University of Chinese Academy of Sciences. Fund Project: National Key Research and Development Plan（2017YFC0504303）；The National Natural Science Foundation of China （41771041；41501044；41701035） 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:蒸散是地表水热平衡的重要分量，也是陆地生态过程与水文过程之间的重要纽带，尤其在干旱区地-气相互作用、碳循环、水循环等过程所包含的物质与能量交换中占有极其重要的地位。基于Landsat 8遥感影像和资源三号影像（ZY3）的高分辨率植被信息，利用SEBS模型对西北干旱区河西走廊中段临泽绿洲北部区域地表蒸散量进行了估算，并用绿洲内部和绿洲-荒漠过渡带两个通量塔涡动相关数据对模型进行评估，分析了不同土地覆盖类型对蒸散量空间分布的影响。结果表明：（1） SEBS模型模拟值与实测日蒸散值之间拟合效果较好，且在均一地表时（绿洲农田区）估算精度更高（R2=0.96，P < 0.001），RMSE、MAE分别为0.84 mm/d、0.56 mm/d；（2）从季节变化来看蒸散量与作物生长密切相关，夏季灌溉和降雨使得研究区水分充足，植被覆盖度高，蒸散量相应增加，在绿洲地区可达5.95 mm/d，而冬季最小仅为0.52 mm/d；（3）从蒸散量的空间变化来看，水体蒸散值最大，其余依次为农田、防护林、裸地和灌木丛，说明除水体外，随着植被覆盖的增大，蒸散量也逐渐增加。通过ZY3影像的高分辨率植被信息与Landsat 8影像热红外数据融合，提高了SEBS模型对该区域蒸散量的模拟效果，增进了我们对绿洲下垫面与大气间水热交换规律、水文过程、生态-水文相互作用的深入理解。 Abstract:Evapotranspiration is a major component of water and heat exchange in terrestrial ecosystems, as it acts as a critical link between ecological and hydrological processes, particularly for the exchange of mass and energy involved in land surface-air interaction, carbon cycle, and hydrological cycle in arid regions. In this study, we used Landsat 8 remote-sensing images and resources NO.3 (ZY3) images, with high-resolution vegetation information, and surface energy balance system (SEBS) model to estimate surface evapotranspiration (ET) in a desert oasis in the middle Hexi corridor area of the arid regions of northwestern China. We compared the estimated ET values with the measured values by using the eddy covariance method. We also spatially analyzed the effects of land cover types on ET. The main results of this study indicated that (1) the estimated daily ET was consistent with the corresponding measured values, especially for homogeneous underlying surface such as oasis (R2=0.96, P < 0.001) with low values of RMSE (0.84 mm/d) and MAE (0.56 mm/d). (2) In terms of seasonal changes, ET is closely related to phonological period, highest in summer, followed by spring, autumn, and winter (e.g., daily ET was 5.95 mm/d for cropland within the oasis, as opposed to 0.52 mm/d in winter), because of the peaked plant cover and summer rainfall in this study area. (3) With respect to spatial variations in ET, the surface ET for water body was the highest, followed by those for cropland, shelterbelt, bare land, and shrubland; this suggested that evapotranspiration also increases gradually with the increase in plant cover, except for water body. In addition, performance of the SEBS model for estimating ET in this region was fairly good when applying the data fusion of high-resolution vegetation information of ZY3 and thermal infrared data of the Landsat 8 remote-sensing images was performed. All these results have enhanced our understanding of the patterns of water and heat exchange between the underlying surface and atmosphere, which play a key role in hydrological and ecological processes or interaction between ecological and hydrological processes locally in arid desert oasis area. Our findings may provide some scientific insights into the decision-making for rational water utilization by the local government. 参考文献 相似文献 引证文献

Satellite-based ET estimation using Landsat 8 images and SEBAL model

Estimation of evapotranspiration is a key factor to achieve sustainable water management in irrigated agriculture because it represents water use of crops. Satellite-based estimations provide advantages compared to direct methods as lysimeters especially when the objective is to calculate evapotranspiration at a regional scale. The present study aimed to estimate the actual evapotranspiration (ET) at a regional scale, using Landsat 8 - OLI/TIRS images and complementary data collected from a weather station. SEBAL model was used in South-West Parana, region composed of irrigated and dry agricultural areas, native vegetation and urban areas. Five Landsat 8 images, row 223 and path 78, DOY 336/2013, 19/2014, 35/2014, 131/2014 and 195/2014 were used, from which ET at daily scale was estimated as a residual of the surface energy balance to produce ET maps. The steps for obtain ET using SEBAL include radiometric calibration, calculation of the reflectance, surface albedo, vegetation indexes (NDVI, SAVI and LAI) and emissivity. These parameters were obtained based on the reflective bands of the orbital sensor with temperature surface estimated from thermal band. The estimated ET values in agricultural areas, native vegetation and urban areas using SEBAL algorithm were compatible with those shown in the literature and ET errors between the ET estimates from SEBAL model and Penman Monteith FAO 56 equation were less than or equal to 1.00 mm day-1.

English

A number of methods have been developed to estimate reference crop evapotranspiration (ETo), but most of the reliable methods are complex and parameter rich models and therefore difficult to apply in data scarce regions. This study was conducted to determine suitable simple ETo methods in Cape Coast by comparing estimated ETo values of three indirect-measurement methods: Hamon, Hargreaves, Blaney Criddle; and two direct-measurement methods: Class A pan and Piche evaporimeter with the Food and Agriculture Organization (FAO) Penman-Monteith equation (FAO56-PM) estimated ETo values. All the methods underestimated ETo values obtained by the FAO56-PM method. However, the estimated ETo values by the Hamon, Hargreaves, and Blaney-Criddle are strongly correlated (R = 0.89, 0.87 and 0.81 respectively), while the Class A pan and Piche evaporimeter methods are weakly correlated (R= 0.37 and 0.31, respectively) with the FAO56-PM method. All but the Piche evaporimeter methods appeared suitable for estimating ETo in the study area. The Class A pan, though weakly correlated with the FAO56-PM method, was also suitable because it had the least mean absolute error (MAE; 0.26 mm day-1) and mean absolute percentage error (MAPE; 6.5%) among the other methods and its ETo curve was closer to the FAO56-PM’s. Key words: Reference crop evapotranspiration, Cape Coast, Food and Agriculture Organization (FAO) Penman-Monteith equation, direct-measurement method.

Remote Estimation of a Managed Pine Forest Evapotranspiration with Geospatial Technology

<abstract> Remote sensing has increasingly been used to estimate evapotranspiration (ET) and its supporting parameters in a rapid, accurate, and cost-effective manner. The goal of this study was to develop remote sensing-based models for estimating ET and the biophysical parameters canopy conductance (g_c), upper-canopy temperature, and soil moisture for a mature loblolly pine forest ( L.) in the Parker Tract in eastern North Carolina. To validate the remote sensing approach, we acquired long-term on-site eddy flux measurements, including micrometeorological variables and water and energy fluxes. Other measured and derived ET-associated parameters include forest g_c, leaf area index, canopy absorbed radiation, canopy temperature, and soil moisture. Multi-temporal cloud-free (≤10% cloud cover) Landsat 7 ETM+ satellite images from 2006-2012 were acquired. Field data for the 2 h (12:00 noon to 2:00 p.m.) means were used in the model, coinciding with the image acquisition time. Individual Landsat bands (1 through 7) and developed image vegetation indices (NDVI, SAVI, and VVI) for the study site were obtained through automated geospatial models and were correlated to measured ET flux and related parameters. An excellent coefficient of determination (R² = 0.93, n = 42) was obtained for the upper-canopy temperature versus band 6 (thermal infrared) model. However, a low correlation (R² = 0.36, n = 6) was obtained for g_c versus band 5 (mid-infrared) model. The correlation for soil moisture versus band 7 was poor (R² = 0.05, n = 42), perhaps due to heavy canopy and pine litter ground cover. However, the ET estimation model with multiple image information variables, such as bands 5 and 7, provided a good correlation (R² = 0.55, n = 35) with less spatial and temporal variation in the datasets, along with no data mining application in model building. Therefore, this study suggests that the remote sensing approach is promising for estimating ET with good accuracy (average model prediction residual error = 25.46 W m^-2, 6.18% of the average ET values used in the analysis) for a mature homogenous pine forest. Further work is needed to develop robust remote sensing-based ET models by including spatial variability, sound data mining, high-resolution imagery, and advanced image processing to account for potential modeling uncertainties.

Calibration of Hargreaves–Samani and Priestley–Taylor equations in estimating reference evapotranspiration in the Northwest of Iran

ABSTRACTAccurate estimation of reference evapotranspiration (ETo) is essential for water resources management and irrigation systems scheduling, especially in arid and semiarid regions such as Iran. In the present research, constant coefficients of Hargreaves–Samani (CH–S) and Priestley–Taylor (CP–T) equations were locally calibrated to estimate the ETo based on the FAO–Penmen–Monteith (PM) method as standard method. For this purpose, meteorological data of eight synoptic stations located in the northwest of Iran were used during the period of 1997–2008. The outcomes showed that the values of CH–S and CP–T were 0.0026 (instead of 0.0023) and 1.68 (instead of 1.26), respectively. Also, at stations with high wind speed, the values of calibrated coefficients of CH–S and CP–T were maximum. Then, the estimated ETo values using adjusted CH–S and CP–T coefficients were compared to the obtained actual ETo values by PM method using root mean square error and mean bias error indices. The results indicated that the new calibrated H–S and P–T equations have good agreement with the PM method for estimation of the ETo. Moreover, the equation of Ravazzani et al. was calibrated in the studied region. It was concluded that in general, the mentioned equation was shown better performance than original H–S equation.