Combining the triangle method with thermal inertia to estimate regional evapotranspiration — Applied to MSG-SEVIRI data in the Senegal River basin

Spatially distributed estimates of evaporative fraction and actual evapotranspiration are pursued using a simple remote sensing technique based on a remotely sensed vegetation index (NDVI) and diurnal changes in land surface temperature. The technique, known as the triangle method, is improved by utilizing the high temporal resolution of the geostationary MSG-SEVIRI sensor. With 15 min acquisition intervals, the MSG-SEVIRI data allow for a precise estimation of the morning rise in land surface temperature which is a strong proxy for total daytime sensible heat fluxes. Combining the diurnal change in surface temperature, dT_s with an interpretation of the triangular shaped dT_s − NDVI space allows for a direct estimation of evaporative fraction. The mean daytime energy available for evapotranspiration (R_n − G) is estimated using several remote sensors and limited ancillary data. Finally regional estimates of actual evapotranspiration are made by combining evaporative fraction and available energy estimates. The estimated evaporative fraction (EF) and actual evapotranspiration (ET) for the Senegal River basin have been validated against field observations for the rainy season 2005. The validation results showed low biases and RMSE and R² of 0.13 [−] and 0.63 for EF and RMSE of 41.45 W m^− 2 and R² of 0.66 for ET.     

Mapping evapotranspiration using MODIS and MM5 Four-Dimensional Data Assimilation

Evapotranspiration (ET), the sum of evaporation from soil and transpiration from vegetation, is of vital importance in the hydrologic cycle and must be taken into consideration in assessments of the water resources of any region. The MODerate resolution Imaging Spectroradiometer (MODIS) sensor offers a promising opportunity for estimating daily ET with a 1 km spatial resolution, but is hampered by frequent cloud contamination or data gaps from other factors. In this study, 1) a stand-alone ET model was applied and tested during clear or partial cloudy sky conditions using MODIS-based inputs of land surface and atmospheric data and 2) meteorological simulations by using Four-Dimensional Data Assimilation (FDDA) system between MODIS and the 5th Generation Meso-scale Meteorological Model (MM5) was used in cloudy conditions to facilitate continuous daily ET estimates. The MODIS ET algorithm modified from Mu et al. (2007) is based on the Penman-Monteith equation and was applied to predict ET at flux measurement sites. This algorithm considers both the effects of surface energy partitioning processes and environmental constraints on ET. We devised gap-filling approaches for MODIS aerosol and albedo data that were identified as bottlenecks to determine retrieval rates of insolation and ET. MODIS-derived input variables (i.e., meteorological variables and radiation components) for estimating ET showed a good agreement with flux tower observations at each site. The retrieval rate of MODIS ET doubled at four flux measurement sites after gap-filling with negligible compensation was undertaken for accuracy. In spite of the high accuracy of MODIS-derived input variables, MODIS ET showed meaningful errors at the four flux measurement sites. These errors were mainly associated with errors in the estimated canopy conductance. During clear sky conditions, MODIS was used to calculate ET, while the MODIS-MM5 FDDA system provided input variables for the calculation of ET under cloudy sky conditions. The performance of the MODIS-MM5 FDDA system was evaluated by comparing ET based on MODIS, which showed a good agreement with the MODIS ET for various land cover types. Our results indicate that MODIS can be applied to monitor the land surface energy budget and ET with reasonable accuracy and that MODIS-MM5 FDDA has the potential to provide reasonable input data of ET estimation under cloudy conditions.     

Satellite-Based Energy Balance to Assess Within-Population Variance of Crop Coefficient Curves

Quantifying evapotranspiration (ET) from agricultural fields is important for field water management, water resources planning, and water regulation. Traditionally, ET from agricultural fields has been estimated by multiplying the weather-based reference ET by crop coefficients (Kc) determined according to the crop type and the crop growth stage. Recent development of satellite remote sensing ET models has enabled us to estimate ET and Kc for large populations of fields. This study evaluated the distribution of Kc over space and time for a large number of individual fields by crop type using ET maps created by a satellite based energy balance (EB) model. Variation of Kc curves was found to be substantially larger than that for the normalized difference vegetation index because of the impacts of random wetting events on Kc, especially during initial and development growth stages. Two traditional Kc curves that are widely used in Idaho for crop management and water rights regulation were compared against the satellite-derived Kc curves. Simple adjustment of the traditional Kc curves by shifting dates for emergence, effective full cover, and termination enabled the traditional curves to better fit Kc curves as determined by the EB model. Applicability of the presented techniques in humid regions having higher chances of cloudy dates was discussed.     

Assessing Reference Evapotranspiration by the Hargreaves Method in Southern Spain

The Hargreaves method enables reference crop evapotranspiration (ET0) estimation in areas where meteorological information is scarce, as, for example, southern Spain. However, this method is known to produce considerable bias in this region, especially during the dry, hot summer months. An evaluation of the method is made by comparing daily estimates with those made by the more commonly recommended Penman–Monteith method at 16 meteorological stations. Computed ET0 values at the coastal stations are, on average, 0.69 mm?d?1 smaller than the Penman–Monteith estimates whereas at inland stations a small average overestimation of 0.13 mm?d?1 is shown. The adjusted Hargreaves coefficient (AHC), obtained through regression analysis, increases at the coastal stations, on average, to 0.0029, and decreases at the inland stations to 0.0022. Adjustment with the Samani method does generally not produce more accurate estimates in this region. Finally a linear relationship between the AHC and the rate of the average temperature to the average daily temperature range is proposed for the regional adjustment of the Hargreaves coefficient.     

基于遥感的地表蒸散发研究进展

地表蒸散发是整个生物圈、大气圈和水圈中水分循环和能量传输的重要控制因素。遥感技术的应用使得区域尺度的蒸散发估算成为可能,并在过去的几十年中快速发展。研究对遥感蒸散发估算进行了总结与归纳,在此基础上展望了今后的发展方向,明确指出了遥感蒸散发未来研究的突破点及发展方向。提出未来应加强蒸散发尺度效应、夜间蒸散发、不同蒸散发产品的统一真实性检验、国产卫星数据的使用、更高时空分辨率产品的研发以及机器学习在遥感蒸散发产品中的应用。     

基于深度神经网络联合AMSR2和MODIS数据估算全球蒸散发研究

地表蒸散发（ET）是水循环和能量循环的关键组成部分,具有极其重要的应用价值。研究旨在发展一种可靠且高效的深度神经网络（DNN）模型,基于MODIS可见光数据、微波AMSR2亮度温度和数字高程DEM,实现全天候全球高分辨率每日ET的估算。利用FLUXNET和AmeriFlux通量网6种代表性土地覆盖类型的148个站点观测数据来训练和验证DNN模型,结果表明：DNN模型可以有效建立卫星数据（MODIS、AMSR2数据）与ET之间的关系;6种地类的ET估算结果验证的平均绝对误差（MAE）为0.16—0.63 mm/d,均方根误差（RMSE）为0.27—0.89 mm/d,除裸地的决定系数（R2）为0.37以外,其他地类的R2均>0.7。通过对比模型估算的ET与MOD16A2和GLEAM的ET产品,结果表明3种产品的ET空间分布特征相似,ET值非常接近,估算得到的全球2020年日均ET为0—4 mm/d。     

Noise Reduction Methods for Weighing Lysimeters

Mechanical vibration of the grass and crop weighing lysimeters, located at the University of California West Side Field Research and Extension Station at Five Points, Calif. generated noise in lysimeter mass measurements and reduced the quality of evapotranspiration (ET) data. The estimated power spectral density (PSD) for grass lysimeter mass data acquired at 1.3?ms intervals contained a large peak at 11?Hz. Crop lysimeter data produced similar peaks at frequencies greater than 1?Hz. An effective method for eliminating this noise source is arithmetic averaging of the data, which should be acquired sufficiently rapidly to avoid aliasing. The PSD also increased with decreasing frequency in the range 1.0–0.1?Hz. This noise was addressed by Savitsky–Golay (SG) filtering using 7-, 11-, and 15-point filters. Each filter was applied to the same data set consisting of 2,560 measurements taken during a 1-min interval every 10?min over a 26.3-h period. Noise reduction factors, defined as the ratio of standard deviation of filtered lysimeter mass to standard deviation of unfiltered mean values of lysimeter mass for subsequences of the same data, were 0.90, 0.88, and 0.86 for the 7-, 11-, and 15-point filters, respectively. For the daytime data only, the factors were 0.88, 0.85, and 0.83. The SG filters were more effective during daytime when most of the lysimeter ET occurs. These methods are simple enough to be programmed into commercially available dataloggers for real time filtering. Hourly averages of the standard deviations of lysimeter mass measurements bear a distinct nonlinear relationship to hourly mean wind speed confirming earlier suppositions that wind loading causes noise in counterbalanced weighing lysimeters.     

Comparison of Simplified Pan-Based Equations for Estimating Reference Evapotranspiration

Accurate estimation of reference evapotranspiration (ET0) is essential for irrigation practice. Conversion from pan evaporation data to reference evapotranspiration is commonly practiced. The objective of this study was to evaluate the reliability of simplified pan-based approaches for estimating ET0 directly that do not require the data of relative humidity and wind speed. In this study, three pan-based (FAO-24 pan, Snyder ET0, and Ghare ET0) equations were compared against lysimeter measurements of grass evapotranspiration using daily data from Policoro, Italy. Based on summary statistics, the Snyder ET0 equation ranked first with the lowest RMSE value (0.449?mm?day?1). The pan-based equations were additional tested using mean daily data collected in Novi Sad, Serbia. The Snyder ET0 equation best matched ET0 estimates by Penman-Monteith equation at Novi Sad with lowest root mean square error value of 0.288?mm?day?1. The obtained results demonstrate that simplified pan-based equations can be successful alternative to FAO-56 Penman-Monteith equation for estimating reference evapotranspiration. The overall results recommended Snyder ET0 equation for pan evaporation to evapotranspiration conversions. The Snyder ET0 equation consistently provides better results compared to FAO-24 pan equation, although required measurements of only one weather parameter pan evaporation.     

台湾地区蒸散发的遥感估算与时空分析

在地表能量平衡系统(SEBS)基础上,改进了SEBS的地表动量粗糙度、零平面位移及植被高度等参数化方案,并建立适合台湾地区的气温和地表温度相关性模型,构建了改良的定量遥感蒸散模型SEBS-China。选取台湾地区2002年和2003年4季各一晴空代表日,利用MODIS数据模拟了日均实际蒸散发。模拟结果较实测蒸发皿蒸发量偏小,与实际规律相符。分析模拟结果表明:台湾地区的太阳净辐射量、蒸发比和地表蒸散发量在时间分布上呈现出变化分明的年内分布规律:夏秋季比春冬季高,其中7月最大、1月最小。时间上,2002年4个代表日的模拟值普遍高于2003年的4个代表日。在空间上,高值区位于中部山区,并向东西两侧逐渐降低到沿海地区又略有回升。不同土地覆被类型的平均蒸散发量由大到小依次为森林、草地、水体、裸地、城镇建设用地;各行政区陆面蒸散发分布呈现城市明显低于区县的规律。     

Simple Equation to Estimate Reference Evapotranspiration from Evaporation Pans Surrounded by Fallow Soil

Reliable estimates of reference evapotranspiration (ET0) are key elements for efficient water resource management, and estimating ET0, based on “Class ‘A’ pan evaporation” data is common in arid climates. A pan coefficient (Kp), which depends on the distance (or fetch) of green vegetation or fallow soil around the pan (F), wind run (U), and relative humidity (RH), is used to convert from pan evaporation to ET0. Several researchers have developed models for estimating Kp values for pans surrounded by green vegetated fetch, but there is only one equation to estimate Kp values for dry fetch conditions. The equation is complex, so the objective of this research was to develop a new simple equation to estimate Kp under fallow soil fetch conditions. The new Kp equation and the more complex equation were compared with tabular values published by the United Nations Food and Agriculture Organization. The new equation performed slightly better at matching the tabular Kp values than the complex equation. The equation derivation and evaluation are presented.