Remote estimation of terrestrial evapotranspiration by Landsat 5 TM and the SEBAL model in cold and high‐altitude regions: a case study of the upper reach of the Shule River Basin,China

Evapotranspiration (ET) is an important expenditure in water and energy balances, especially on cold and high‐altitude land surfaces. Daily ET of the upper reach of the Shule River Basin was estimated using Landsat 5 TM data and the Surface Energy Balance Algorithm for Land (SEBAL) model. Based on observations made at the Suli station, the algorithms of land surface temperature and soil heat flux in SEBAL were modified. Land surface temperature was retrieved and compared with ground truth via three methods: the radiative transfer equation method, the mono‐window algorithm, and the single‐channel method. We selected the best of these methods, mono‐window algorithm, for estimating ET. The average error of daily ET estimated by the modified SEBAL model and measured by the eddy covariance system was 16.4%, with a root‐mean‐square error of 0.52 mm d^?1. The estimated ET means were 3.09, 2.48, and 1.48 mm d^?1 on June 9 (DOY 160), June 25 (DOY 176), and July 27 (DOY 208) of the year 2010, respectively. The average estimated ET on the glacier surface of all days was more than 3 mm d^?1, a measurement that is difficult to capture in‐situ and has rarely been reported. This study will improve the understanding of water balance in cold, high‐altitude regions. Copyright © 2016 John Wiley & Sons, Ltd.     

Recharge estimation using remotely sensed evapotranspiration in an irrigated catchment in southeast Australia

Reliable estimates of groundwater recharge are required for the sustainable management of surface and ground water resources in semi‐arid regions particularly in irrigated regions. In this study, groundwater recharge was estimated for an irrigated catchment in southeast Australia using a semi‐distributed hydrological model (SWAT). The model was calibrated under the dry climatic conditions for the period from August 2002 to July 2003 using flow and remotely sensed evapotranspiration (ET). The model was able to simulate observed monthly drain flow and spatially distributed remotely sensed ET. Recharge tended to be higher for irrigated land covers, such as perennial pasture, than for non‐irrigated land. On average, the estimated annual catchment recharge ranged between 147 and 289 mm which represented about 40% of the total rainfall and irrigation inputs. The optimized soil parameters indirectly reflected flow bypassing the soil matrix that could be responsible for this substantial amount of recharge. Overall, the estimated recharge was much more than that previously estimated for the wetter years. Copyright © 2011 John Wiley & Sons, Ltd.     

Evapotranspiration Estimation Based on MODIS Products and Surface Energy Balance Algorithms for Land （SEBAL） Model in Sanjiang Plain, Northeast China

In this study,the Surface Energy Balance Algorithms for Land(SEBAL) model and Moderate Resolution Imaging Spectroradiometer(MODIS) products from Terra satellite were combined with meteorological data to estimate evapotranspiration(ET) over the Sanjiang Plain,Northeast China.Land cover/land use was classified by using a recursive partitioning and regression tree with MODIS Normalized Difference Vegetation Index(NDVI) time series data,which were reconstructed based on the Savitzky-Golay filtering approach.The MODIS product Quality Assessment Science Data Sets(QA-SDS) was analyzed and all scenes with valid data covering more than 75% of the Sanjiang Plain were selected for the SEBAL modeling.This provided 12 overpasses during 184-day growing season from May 1st to October 31st,2006.Daily ET estimated by the SEBAL model was misestimaed at the range of-11.29% to 27.57% compared with that measured by Eddy Covariance system(10.52% on average).The validation results show that seasonal ET from the SEBAL model is comparable to that from ground observation within 8.86% of deviation.Our results reveal that the time series daily ET of different land cover/use increases from vegetation on-going until June or July and then decreases as vegetation senesced.Seasonal ET is lower in dry farmland(average(Ave):491 mm) and paddy field(Ave:522 mm) and increases in wetlands to more than 586 mm.As expected,higher seasonal ET values are observed for the Xingkai Lake in the southeastern part of the Sanjiang Plain(Ave:823 mm),broadleaf forest(Ave:666 mm) and mixed wood(Ave:622 mm) in the southern/western Sanjiang Plain.The ET estimation with SEBAL using MODIS products can provide decision support for operational water management issues.     

Coupling SEBAL with a new radiation module and MODIS products for better estimation of evapotranspiration

ABSTRACT

Evapotranspiration (ET) is an important ecohydrological process especially in arid and semi-arid regions. In this study, a new radiation module based on MODIS data has been coupled with the Surface Energy Balance Algorithms for Land (SEBAL) to better estimate ET. The accuracies of the coupled model for estimating available energy and sensible heat (H) were improved significantly compared with the outputs from the original SEBAL which was based on empirical equations. The coupled SEBAL modelled instantaneous λET agreed much better with observations in the arid land of Central Asia than the original SEBAL, with a bias of ?2.86 W m^-2, root mean square error (RMSE) of 9.75 W m^-2, and normalized RMSE (NRMSE) of 0.13. The accuracy was blurred when scaling ET to a daily or monthly scale, mainly due to the uncertainties associated with temporal upscaling methods that were applied. Sensitivity analysis, which was conducted using numerical variance-based techniques, indicated that the estimated ET is sensitive to the available energy, suggesting the importance of obtaining accurate estimates of net radiation when applying the coupled SEBAL to estimate ET. This study provides a simple and reliable way to utilize MODIS products and contains sensitivity analysis for helping to correctly interpret the outputs, which are both important for large-scale ET estimation.     

一种极干旱区水热通量遥感模型反演

针对极干旱的土壤水热通量遥感估算研究少和缺乏模型验证分析的不足,该文选取新疆塔克拉码干沙漠东南缘米兰绿洲,借助2010年8月7日TM影像数据,结合地面观测数据和土地覆盖类型解译,利用SEBAL模型反演了研究区地表通量。结果表明:该方法在极干旱区的模拟精度较高,研究区地表能量平衡各分量具有明显的时空分布特征。地表通量参数的遥感反演估算对极干旱区的生态保护、灾害监测和地区水资源管理具有重要现实意义。     

风力发电机对黄河三角洲水体蒸发的影响研究

蒸发是湿地水循环的重要组成部分和水分损失的重要途径,风力发电对水体蒸发的影响干扰湿地生态系统的水热平衡。利用SEBAL模型,采用风力发电机建设前2004年、2005年、2009年的Landsat 5数据,风力发电机建成后2013年、2015年的Landsat 8数据,以及MODIS数据和气象数据,通过对比风力发电机建设前后以风机点为中心200m缓冲区范围内水体蒸发的变化,研究风力发电机对黄河三角洲湿地水体蒸发的影响。结果表明:①与建成前相比,风力发电机建成后风机周围各风向水体的蒸发在空间特征上趋于均匀;②与其他风向相比,风力发电机对下风向的影响更大,使下风向水体的蒸发值的均匀程度远大于上风向和旁风向。     

基于SEBAL模型的疏勒河流域蒸散发估算与灌溉效率评价

我国西北干旱区内陆河流域水资源匮乏,水资源利用主要用于农业生产,准确估算内陆河流域蒸散发与农业灌溉效率,对研究内陆河流域气候变化和水资源合理利用具有重要作用。利用基于地表能量平衡方程的SEBAL模型,对2017—2018年疏勒河流域蒸散量进行定量估算与时空分布特征分析,并结合降水量与净灌溉水量数据,对疏勒河流域昌马灌区的年内灌溉水有效利用系数进行估算。结果表明：（1） 疏勒河流域2017—2018年日均ET呈单峰变化趋势,最大值为6月的5. 03 mm·d^–1,最小值为12月的0. 55 mm·d^–1,并存在明显的空间分布差异。（2） 疏勒河流域四季ET差异显著,夏季ET达到最高的201. 83 mm,春秋次之,冬季最低为53. 92 mm;ET由东南向西北逐渐减小,流域上游ET明显高于中下游地区。（3） 昌马灌区各灌溉时段不同的灌溉水量造成了各灌季蒸散量的差异,灌区ET高值区主要分布在中部与东南部,低值区主要分布在西北部和灌区边缘。（4） 昌马灌区年内灌溉水有效利用系数呈下降趋势,其中春灌、夏灌、秋灌和冬灌分别为0. 76、0. 71、0. 69和0. 55,年均灌溉水有效利用系数为0. 67。     

基于遥感技术的祖厉河流域LUCC与蒸散发研究

本文以陇中黄土高原的祖厉河流域为研究区,基于Landsat系列遥感影像,利用主成分变换方法,与地面温度和植被指数相结合,进行土地利用/土地覆盖提取研究,在此基础上,探讨祖厉河流域土地利用/土地覆盖变化(LUCC)及其驱动因素。利用基于TM影像的SEBAL(Surface Energy Balance Algorithm for Land)模型,从祖厉河流域三期影像提取了区域蒸散发通量。首先进行了NDVI、比辐射率和地面温度等地表参数的计算,然后反演了地表的净辐射、土壤热通量和感热通量,根据能量守恒最终获得日蒸散发量。结合气象观测数据反演作物系数,最后计算月蒸散发量。对同期的土地利用/土地覆盖数据和陆面蒸散发量进行对比分析,探讨了土地利用类型的变化对流域内能量和水分时空分异的影响。     

Up-scaling of SEBAL derived evapotranspiration maps from Landsat (30 m) to MODIS (250 m) scale

Remotely sensed imagery of the Earth’s surface via satellite sensors provides information to estimate the spatial distribution of evapotranspiration (ET). The spatial resolution of ET predictions depends on the sensor type and varies from the 30–60 m Landsat scale to the 250–1000 m MODIS scale. Therefore, for an accurate characterization of the regional distribution of ET, scaling transfer between images of different resolutions is important. Scaling transfer includes both up-scaling (aggregation) and down-scaling (disaggregation). In this paper, we address the up-scaling problem.The Surface Energy Balance Algorithm for Land (SEBAL) was used to derive ET maps from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS) images. Landsat 7 bands have spatial resolutions of 30–60 m, while MODIS bands have resolutions of 250, 500 and 1000 m. Evaluations were conducted for both “output” and “input” up-scaling procedures, with aggregation accomplished by both simple averaging and nearest neighboring resampling techniques. Output up-scaling consisted of first applying SEBAL and then aggregating the output variable (daily ET). Input up-scaling consisted of aggregating 30 m Landsat pixels of the input variable (radiance) to obtain pixels at 60, 120, 250, 500 and 1000 m before SEBAL was applied. The objectives of this study were first to test the consistency of SEBAL algorithm for Landsat and MODIS satellite images and second to investigate the effect of the four different up-scaling processes on the spatial distribution of ET.We conclude that good agreement exists between SEBAL estimated ET maps directly derived from Landsat 7 and MODIS images. Among the four up-scaling methods the output simple averaging method produced aggregated data and aggregated differences with the most statistically and spatially predictable behavior. The input nearest neighbor method was the least predictable but was still acceptable. Overall, the daily ET maps over the Middle Rio Grande Basin aggregated from Landsat images were in good agreement with ET maps directly derived from MODIS images.     

Temporal dynamics of evapotranspiration in semiarid native forests in Brazil and Spain using remote sensing

Evapotranspiration (ET) plays an important role in integrated water resource planning, development and management. This process is particularly relevant in semiarid regions. The aim of this study is, hence, to compare spatial and temporal patterns of actual ET, as well as the temporal trends in two different semiarid forests, Caatinga (Brazil) and Tierra de Pinares (Spain). We used the surface energy balance algorithm for land (SEBAL) to assess actual evapotranspiration (ET_a) in both areas. In the Brazilian semiarid forest, Caatinga is the main vegetation, while it is Pinares in Spain. For this purpose, 69 Landsat-5 and 42 Landsat-8 images (1995–2019) were used. The Mann–Kendall test was applied to assess the occurrence of trends in precipitation, temperature and potential ET data; and the Temporal Stability Index (TSI) to know which areas have greater seasonal ET_a. The annual amplitude of the potential evapotranspiration (ET₀) is the same in both areas, however, the Caatinga values are higher. In the Caatinga forest, when ET₀ presents its highest values throughout the year, ET_a presents the lowest, and vice versa. In the Pinares forest, ET_a follows the ET₀ dynamics during the year, and the difference between ET₀ and ET_a is maximum during the summer. The Caatinga forest showed a greater spatial variation of ET_a than the Pinares forest as well as a greater extension with lower temporal stability of ET_a than the Pinares forest. Both the Caatinga forest and the Pinares forest showed significant positive trends in annual ET₀ and ET_a. We estimate that the value of ET_a increases more rapidly in Pinares than in the Brazilian Caatinga. Taking Caatinga as a hydrological mirror, some consequences are expected to Pinares, such as significant changes in the water balance, increase of biodiversity vulnerability, and reduction of water availability in soil and reservoirs.