Remote sensing estimation on regional continuous daily evapotranspiration based on Richards equation

WANG Xixuan; KONG Jinling; ZHANG Qiutong; ZHANG Zaiyong; WANG Lizheng

doi:10.16030/j.cnki.issn.1000-3665.202311044

2024 Vol. 51, No. 5

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Article navigation > Hydrogeology & Engineering Geology > 2024 > 51(5): 35-44

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WANG Xixuan, KONG Jinling, ZHANG Qiutong, ZHANG Zaiyong, WANG Lizheng. Remote sensing estimation on regional continuous daily evapotranspiration based on Richards equation[J]. Hydrogeology & Engineering Geology, 2024, 51(5): 35-44. doi: 10.16030/j.cnki.issn.1000-3665.202311044

Citation:

WANG Xixuan, KONG Jinling, ZHANG Qiutong, ZHANG Zaiyong, WANG Lizheng. Remote sensing estimation on regional continuous daily evapotranspiration based on Richards equation[J]. Hydrogeology & Engineering Geology, 2024, 51(5): 35-44. doi: 10.16030/j.cnki.issn.1000-3665.202311044

Remote sensing estimation on regional continuous daily evapotranspiration based on Richards equation

1.
College of Geological Engineering and Geomatics, Chang’an University, Xi’an, Shaanxi　710054, China
2.
College of Water Conservancy and Environment, Chang’an University, Xi’an, Shaanxi　710054, China

More Information

Corresponding author: KONG Jinling, jlkong@163.com

Received Date: 25 November 2023

Revised Date: 18 December 2023

Publish Date: 15 September 2024

Abstract

Abstract

Evapotranspiration (ET) is an important part of water cycle in nature, and the estimation of evapotranspiration on spatio-temporal scale has always been a hot issue. Remote sensing can estimate evapotranspiration on regional scale, but it is difficult to obtain evapotranspiration in continuous time series due to the limitation of satellite transit time. Soil moisture is an important controlling factor of evapotranspiration. Improving the remote sensing evapotranspiration model by combining soil moisture data is of great significance in improving the accuracy of remote sensing evapotranspiration estimation. However, most remote sensing methods give limited consideration to the characterization of soil moisture stress. This study used the evapotranspiration calculated by the vorticity correlation method as the actual evapotranspiration. combining with the single crop coefficient method recommended by FAO, the soil water content information was introduced into the Penman-Monteith formula to calculate the actual evapotranspiration. Based on Richards equation, the one-dimensional vertical soil water movement process under evaporation conditions was simulated to estimate the continuous daily evapotranspiration under soil water stress. Combining with remote sensing data, the regional scale evapotranspiration was estimated. The results show that the actual daily evapotranspiration calculated by the vorticity correlation method has a strong correlation with the potential daily evapotranspiration calculated by P-M formula, with the correlation coefficient of 0.918. With the introduction of soil water content information, the P-M formula improves the estimation accuracy of daily evapotranspiration significantly, and the RMSE reaches 0.133 mm/d. The estimated daily evapotranspiration under soil water stress based on Richards equation is close to the measured value, with the RMSE of 0.288 mm/d. The high value of daily evapotranspiration affected by the topography of the study area is concentrated in the water area and cultivated land area in the middle of the study area. The average daily evapotranspiration under different soil use types is water area > cultivated land > woodland > grassland > unused land, and the results on the regional scale show similar change with that measured in the the station in time series. This study provides basic information for understanding the influence mechanism of soil moisture on evapotranspiration and estimating regional evapotranspiration.
- remote sensing inversion of evapotranspiration /
- vorticity correlation method /
- soil water stress /
- Richards equation /
- P-M formula

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References

[1]	WANG Kaicun,DICKINSON R E. A review of global terrestrial evapotranspiration:Observation,modeling,climatology,and climatic variability[J]. Reviews of Geophysics,2012,50(2):RG2005. Google Scholar
[2]	周剑,程国栋,李新,等. 应用遥感技术反演流域尺度的蒸散发[J]. 水利学报,2009,40(6):679 − 687. [ZHOU Jian,CHENG Guodong,LI Xin,et al. Application of remote sensing technology to estimate river basin evapotranspiration[J]. Journal of Hydraulic Engineering,2009,40(6):679 − 687. (in Chinese with English abstract)] doi: 10.3321/j.issn:0559-9350.2009.06.006 CrossRef Google Scholar ZHOU Jian, CHENG Guodong, LI Xin, et al. Application of remote sensing technology to estimate river basin evapotranspiration[J]. Journal of Hydraulic Engineering, 2009, 40（6）: 679 − 687. （in Chinese with English abstract） doi: 10.3321/j.issn:0559-9350.2009.06.006 CrossRef Google Scholar
[3]	冯景泽,王忠静. 遥感蒸散发模型研究进展综述[J]. 水利学报,2012,43(8):914 − 925. [FENG Jingze,WANG Zhongjing. A review on evapotranspiration estimation models using remotely sensed data[J]. Journal of Hydraulic Engineering,2012,43(8):914 − 925. (in Chinese with English abstract)] Google Scholar FENG Jingze, WANG Zhongjing. A review on evapotranspiration estimation models using remotely sensed data[J]. Journal of Hydraulic Engineering, 2012, 43（8）: 914 − 925. （in Chinese with English abstract） Google Scholar
[4]	HASSAN A,ISMAIL S S,ELMOUSTAFA A,et al. Evaluating evaporation rate from high Aswan Dam Reservoir using RS and GIS techniques[J]. The Egyptian Journal of Remote Sensing and Space Science,2018,21(3):285 − 293. doi: 10.1016/j.ejrs.2017.10.001 CrossRef Google Scholar
[5]	王卓月,孔金玲,李英,等. 基于MOD16的银川平原地表蒸散量时空特征及影响因素分析[J]. 水文地质工程地质,2021,48(3):53 − 61. [WANG Zhuoyue,KONG Jinling,LI Ying,et al. An analysis of spatio-temporal characteristics and influencing factors of surface evapotranspiration in the Yinchuan Plain based on MOD16 data[J]. Hydrogeology & Engineering Geology,2021,48(3):53 − 61. (in Chinese with English abstract)] Google Scholar WANG Zhuoyue, KONG Jinling, LI Ying, et al. An analysis of spatio-temporal characteristics and influencing factors of surface evapotranspiration in the Yinchuan Plain based on MOD16 data[J]. Hydrogeology & Engineering Geology, 2021, 48（3）: 53 − 61. （in Chinese with English abstract） Google Scholar
[6]	范丽. 基于微波遥感土壤水分驱动下的陆面蒸散发估算研究[D]. 鞍山:辽宁科技大学,2021. [FAN Li. Study on estimation of land surface evapotranspiration driven by microwave soil moisture[D]. Anshan:University of Science and Technology Liaoning,2021. (in Chinese with English abstract)] Google Scholar FAN Li. Study on estimation of land surface evapotranspiration driven by microwave soil moisture[D]. Anshan: University of Science and Technology Liaoning, 2021. （in Chinese with English abstract） Google Scholar
[7]	问晓梅. 半干旱地区降露水和蒸发特征研究[D]. 北京:中国气象科学研究院,2009. [WEN Xiaomei. Research of dew and evaporation characteristics of semi-arid area[D]. Beijing:Chinese Academy of Meteorological Sciences,2009. (in Chinese with English abstract)] Google Scholar WEN Xiaomei. Research of dew and evaporation characteristics of semi-arid area[D]. Beijing: Chinese Academy of Meteorological Sciences, 2009. （in Chinese with English abstract） Google Scholar
[8]	AKURAJU V R,RYU D,GEORGE B,et al. Seasonal and inter-annual variability of soil moisture stress function in dryland wheat field,Australia[J]. Agricultural and Forest Meteorology,2017,232:489 − 499. doi: 10.1016/j.agrformet.2016.10.007 CrossRef Google Scholar
[9]	周剑,吴雪娇,李红星,等. 改进SEBS模型评价黑河中游灌溉水资源利用效率[J]. 水利学报,2014,45(12):1387 − 1398. [ZHOU Jian,WU Xuejiao,LI Hongxing,et al. Improved SEBS model for evaluating irrigation water use efficiency in the middle reaches of the Heihe River[J]. Journal of Hydraulic Engineering,2014,45(12):1387 − 1398. (in Chinese with English abstract)] Google Scholar ZHOU Jian, WU Xuejiao, LI Hongxing, et al. Improved SEBS model for evaluating irrigation water use efficiency in the middle reaches of the Heihe River[J]. Journal of Hydraulic Engineering, 2014, 45（12）: 1387 − 1398. （in Chinese with English abstract） Google Scholar
[10]	FU Jianyu,WANG Weiguang,SHAO Quanxi,et al. Improved global evapotranspiration estimates using proportionality hypothesis-based water balance constraints[J]. Remote Sensing of Environment,2022,279:113140. doi: 10.1016/j.rse.2022.113140 CrossRef Google Scholar
[11]	ALLEN R G,PEREIRA L S,RAES D,et al. Crop evapotranspiration :Guidelines for computing crop water requirements,F[M]. Finland:Agricultural and Food Sciences,Environmental Science,1998. Google Scholar
[12]	李毅,付亚亚,唐德秀,等. 砂石覆盖条件下冬小麦蒸散量的单、双作物系数法估算[J]. 农业机械学报,2018,49(3):261 − 270. [LI Yi,FU Yaya,TANG De xiu,et al. Estimation of evapotranspiration of winter wheat based on single and dual crop coefficient approaches under sand gravel mulching conditions[J]. Transactions of the Chinese Society for Agricultural Machinery,2018,49(3):261 − 270. (in Chinese with English abstract)] Google Scholar LI Yi, FU Yaya, TANG De xiu, et al. Estimation of evapotranspiration of winter wheat based on single and dual crop coefficient approaches under sand gravel mulching conditions[J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49（3）: 261 − 270. （in Chinese with English abstract） Google Scholar
[13]	余昭君,胡笑涛,冉辉,等. 基于波文比-能量平衡法的半湿润地区葡萄园蒸发蒸腾量估算[J]. 干旱地区农业研究,2020,38(4):175 − 183. [YU Zhaojun,HU Xiaotao,RAN Hui,et al. Estimation of grape evapotranspiration in semi-humid region based on Bowen ratio energy balance method[J]. Agricultural Research in the Arid Areas,2020,38(4):175 − 183. (in Chinese with English abstract)] Google Scholar YU Zhaojun, HU Xiaotao, RAN Hui, et al. Estimation of grape evapotranspiration in semi-humid region based on Bowen ratio energy balance method[J]. Agricultural Research in the Arid Areas, 2020, 38（4）: 175 − 183. （in Chinese with English abstract） Google Scholar
[14]	张堂堂,文军,李振朝,等. 基于微波遥感参数估算区域蒸散发的方法研究[J]. 高原气象,2013,32(6):1651 − 1657. [ZHANG Tangtang,WEN Jun,LI Zhenchao,et al. A method for determing regional evaportranspiration based on microwave sensing technique[J]. Plateau Meteorology,2013,32(6):1651 − 1657. (in Chinese with English abstract)] doi: 10.7522/j.issn.1000-0534.2013.00152 CrossRef Google Scholar ZHANG Tangtang, WEN Jun, LI Zhenchao, et al. A method for determing regional evaportranspiration based on microwave sensing technique[J]. Plateau Meteorology, 2013, 32（6）: 1651 − 1657. （in Chinese with English abstract） doi: 10.7522/j.issn.1000-0534.2013.00152 CrossRef Google Scholar
[15]	王韦娜,张翔,张立锋,等. 蒸渗仪法和涡度相关法测定蒸散的比较[J]. 生态学杂志,2019,38(11):3551 − 3559. [WANG Weina,ZHANG Xiang,ZHANG Lifeng,et al. A comparison study of the evapotranspiration measured by lysimeter and eddy covariance[J]. Chinese Journal of Ecology,2019,38(11):3551 − 3559. (in Chinese with English abstract)] Google Scholar WANG Weina, ZHANG Xiang, ZHANG Lifeng, et al. A comparison study of the evapotranspiration measured by lysimeter and eddy covariance[J]. Chinese Journal of Ecology, 2019, 38（11）: 3551 − 3559. （in Chinese with English abstract） Google Scholar
[16]	年雁云. 黑河流域河流分布数据集[Z]. 兰州:国家冰川冻土沙漠科学数据中心,2020. [NIAN Yanyun. River Distribution dataset of the Heihe river basin[Z]. Lanzhou:National glacier frozen soil desert science data center,2020. (in Chinese)] Google Scholar NIAN Yanyun. River Distribution dataset of the Heihe river basin[Z]. Lanzhou: National glacier frozen soil desert science data center, 2020. （in Chinese） Google Scholar
[17]	刘良云,张肖. 2020年全球30米地表覆盖精细分类产品V1.0[Z]. 北京:中国科学院空天信息创新研究院,2021. [LIU Liangyun,ZHANG Xiao. Fine classification products V1.0 of global 30-meter surface coverage in 2020[Z]. Beijing:Aerospace Information Research Institute,Chinese Academy of Sciences,2021. (in Chinese)] Google Scholar LIU Liangyun, ZHANG Xiao. Fine classification products V1.0 of global 30-meter surface coverage in 2020[Z]. Beijing: Aerospace Information Research Institute, Chinese Academy of Sciences, 2021. （in Chinese） Google Scholar
[18]	刘绍民,车涛,徐自为,等. 祁连山综合观测网:黑河流域地表过程综合观测网(大满超级站气象要素梯度观测系统-2020)[Z]. 北京:国家青藏高原科学数据中心,2021. [LIU Shaomin,CHE Tao,XU Ziwei,et al. Qilian Mountains integrated observatory network:Dataset of Heihe integrated observatory network (an observation system of Meteorological elements gradient of Daman Superstation,2020)[Z]. Beijing:National Tibetan Plateau / Third Pole Environment Data Center,2021. (in Chinese)] Google Scholar LIU Shaomin, CHE Tao, XU Ziwei, et al. Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network （an observation system of Meteorological elements gradient of Daman Superstation, 2020）[Z]. Beijing: National Tibetan Plateau / Third Pole Environment Data Center, 2021. （in Chinese） Google Scholar
[19]	LIU S M,XU Z W,WANG W Z,et al. A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem[J]. Hydrology and Earth System Sciences,2011,15(4):1291 − 1306. doi: 10.5194/hess-15-1291-2011 CrossRef Google Scholar
[20]	刘绍民,车涛,徐自为,等. 祁连山综合观测网:黑河流域地表过程综合观测网(大满超级站涡动相关仪-2020)[Z]. 北京:国家青藏高原科学数据中心,2021. [LIU Shaomin,CHE Tao,XU Ziwei,et al. Qilian Mountains integrated observatory network:Dataset of Heihe integrated observatory network (eddy covariance system of Daman Superstation,2020)[Z]. Beijing:National Tibetan Plateau / Third Pole Environment Data Center,2021. (in Chinese)] Google Scholar LIU Shaomin, CHE Tao, XU Ziwei, et al. Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network （eddy covariance system of Daman Superstation, 2020）[Z]. Beijing: National Tibetan Plateau / Third Pole Environment Data Center, 2021. （in Chinese） Google Scholar
[21]	刘绍民,车涛,徐自为,等. 祁连山综合观测网:黑河流域地表过程综合观测网(花寨子站涡动相关仪-2020)[Z]. 北京:国家青藏高原科学数据中心,2021. [LIU Shaomin,CHE Tao,XU Ziwei,et al. Qilian Mountains integrated observatory network:Dataset of Heihe integrated observatory network (eddy covariance system of Huazhaizi station,2020)[Z]. Beijing:National Tibetan Plateau / Third Pole Environment Data Center,2021. (in Chinese)] Google Scholar LIU Shaomin, CHE Tao, XU Ziwei, et al. Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network （eddy covariance system of Huazhaizi station, 2020）[Z]. Beijing: National Tibetan Plateau / Third Pole Environment Data Center, 2021. （in Chinese） Google Scholar
[22]	刘绍民,车涛,徐自为,等. 祁连山综合观测网:黑河流域地表过程综合观测网(张掖湿地站涡动相关仪-2020)[Z]. 北京:国家青藏高原科学数据中心,2021. [LIU Shaomin,CHE Tao,XU Ziwei,et al. Qilian Mountains integrated observatory network:Dataset of Heihe integrated observatory network (eddy covariance system of Zhangye wetland station,2020)[Z]. Beijing:National Tibetan Plateau / Third Pole Environment Data Center,2021. (in Chinese)] Google Scholar LIU Shaomin, CHE Tao, XU Ziwei, et al. Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network （eddy covariance system of Zhangye wetland station, 2020）[Z]. Beijing: National Tibetan Plateau / Third Pole Environment Data Center, 2021. （in Chinese） Google Scholar
[23]	张甘霖,刘峰. 中国高分辨率国家土壤信息网格基本属性数据集(2010—2018)[Z]. 北京:国家青藏高原科学数据中心,2021. [ZHANG Ganlin,LIU Feng. Basic soil property dataset of high-resolution China Soil Information Grids (2010−2018)[Z]. Beijing:National Tibetan Plateau / Third Pole Environment Data Center,2021. (in Chinese)] Google Scholar ZHANG Ganlin, LIU Feng. Basic soil property dataset of high-resolution China Soil Information Grids （2010−2018）[Z]. Beijing: National Tibetan Plateau / Third Pole Environment Data Center, 2021. （in Chinese） Google Scholar
[24]	LIU Feng,ZHANG Ganlin,SONG Xiaodong,et al. High-resolution and three-dimensional mapping of soil texture of China[J]. Geoderma,2020,361:114061. doi: 10.1016/j.geoderma.2019.114061 CrossRef Google Scholar
[25]	赵天杰,宋沛林,张永强,等. 中国1千米分辨率逐日全天候地表土壤水分数据集(2003-2022)[Z]. 北京:国家青藏高原科学数据中心,2021. [ZHAO Tianjie,SONG Peilin,ZHANG Yongqiang,et al. Daily all weather surface soil moisture data set with 1 km resolution in China (2003-2022)[Z]. Beijing:National Tibetan Plateau / Third Pole Environment Data Center,2021. (in Chinese)] Google Scholar ZHAO Tianjie, SONG Peilin, ZHANG Yongqiang, et al. Daily all weather surface soil moisture data set with 1 km resolution in China （2003-2022）[Z]. Beijing: National Tibetan Plateau / Third Pole Environment Data Center, 2021. （in Chinese） Google Scholar
[26]	姚云军,刘绍民,尚珂. 祁连山地区基于MODIS的逐日地表蒸散发数据(2020)(ETHi-merge V1.0)[Z]. 北京:国家青藏高原科学数据中心,2021. [YAO Yunjun,LIU Shaomin,SHANG Ke. Daily MODIS-based land surface evapotranspiration dataset of 2020 in Qilian Mountain area (ETHi-merge V1.0)[Z]. Beijing:National Tibetan Plateau / Third Pole Environment Data Center,2021. (in Chinese)] Google Scholar YAO Yunjun, LIU Shaomin, SHANG Ke. Daily MODIS-based land surface evapotranspiration dataset of 2020 in Qilian Mountain area （ETHi-merge V1.0）[Z]. Beijing: National Tibetan Plateau / Third Pole Environment Data Center, 2021. （in Chinese） Google Scholar
[27]	张颀. 灌区农田土壤水分运移模型研究与预测[D]. 乌鲁木齐:新疆农业大学,2005. [ZHANG Qi. Study and prediction of the soil water transport model in irrigation field[D]. Urumqi:Xinjiang Agricultural University,2005. (in Chinese with English abstract)] Google Scholar ZHANG Qi. Study and prediction of the soil water transport model in irrigation field[D]. Urumqi: Xinjiang Agricultural University, 2005. （in Chinese with English abstract） Google Scholar
[28]	BERG Alexis,SHEFFIELD Justin,MILLY P C D. Divergent surface and total soil moisture projections under global warming[J]. Geophysical Research Letters,2017,44(1):236 − 244. doi: 10.1002/2016GL071921 CrossRef Google Scholar