| 引用本文: | 刘馨井雨,韩旭东,张晓春,等.基于SEBAL模型和环境卫星的区域蒸散发量及灌溉水利用系数估算研究[J].灌溉排水学报,0,():-. |
| LIU Xinjingyu,HAN Xudong,ZHANG Xiaochun,et al.基于SEBAL模型和环境卫星的区域蒸散发量及灌溉水利用系数估算研究[J].灌溉排水学报,0,():-. |
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| 摘要: |
| 【目的】探索基于遥感技术建立准确快捷评估区域蒸散发量和灌溉水利用系数的方法。【方法】以河套灌区义长灌域为研究区，基于SEBAL（Surface Energy Balance Algorithm for Land）模型和较高时空分辨率的环境卫星影像，建立了SEBAL遥感蒸散发模型，并与降水量、灌水量和地下水位数据结合计算了研究区的灌溉水利用系数。【结果】SEBAL模型反演的作物蒸散发量的平均绝对误差在5%以内；2013―2017年研究区灌溉水利用系数在0.427～0.572之间，平均值0.492，高于河套灌区的平均水平。人民支渠区的灌溉水利用系数在0.447～0.688之间，均值为0.516。研究区地下水补给量均值为52.13 mm，约占灌水量的3%～7%，忽略地下水补给量会对灌溉水系数准确计算带来0.03～0.08的误差。【结论】本文基于SEBAL遥感蒸散发模型快速测算了灌溉水利用系数，计算结果具有较好的精度和可信度。模型尺度差异性较小，在不同空间尺度的适用性较好。 |
| 关键词: 灌溉水利用系数;SEBAL模型;环境卫星;区域蒸散发 |
| DOI： |
| 分类号:TV93 |
| 基金项目:国家重点研发计划项目(2016YFC0400203、2018YFC1508301、2018YFC1508302)，湖北省自然科学基金（2019CFB507） |
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| Evaluation on Regional Evapotranspiration and Water Efficiency of Irrigation Based on SEBAL Model and HJ Satellite Data |
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LIU Xinjingyu1, HAN Xudong1, ZHANG Xiaochun1, WANG Xiugui1, YANG Liqing2, CHANG Zhifu2, Liu Hui2
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1.State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan;2.Yichang Irrigation Bureau of Hetao, Bayannur
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| Abstract: |
| 【Objective】 Water efficiency of irrigation is an important index to evaluate agricultural water use efficiency, which plays a significant role in agriculture water-saving practice. However, the traditional way to measure water efficiency of irrigation cost large amounts of time and money while with poor precision. This paper aims to put forward a fast and convenient method to estimate regional crop evapotranspiration (ET) and water efficiency of irrigation based on remote sensing data. 【Method】Yichang irrigation district of Hetao Irrigation District in Inner Mongolia was chosen as the study area. The HJ satellite images were collected and preprocessed to classify the planting structures for the three main crops which were wheat (Triticum aestivum L.), maize (Zea mays L.) and sunflower (Helianthus annuus L.) in the research district using decision tree along with the supervised classification. And then based on the SEBAL (Surface Energy Balance Algorithm for Land) model and HJ1B satellite data, the SEBAL model was established on the platform of ENVI and IDL, which was applied to estimate the ET of three main crops in the study area with the Digital Elevation Model (DEM) data the additional Landsat data from 2013 to 2017. Furthermore, water efficiency of irrigation from 2013 to 2017 in the district was evaluated combined with the rainfall information, irrigation data and groundwater data. 【Result】The classification relative error of sunflower from 2013 to 2018 in all years are less than 5%, and the relative error of maize and wheat are less than 20%. The calculated ET based on SEBAL model is relatively accurate with average relative error less than 5%, which shows that the estimation accuracy of ET is obviously improved by the high spatial and temporal resolution remote sensing images. The ET of maize is the largest, which is larger than 600 millimeters, followed by the sunflower with about 500 millimeters, and wheat is the least with about 450 millimeters. The water efficiency of irrigation in Yichang irrigation district calculated by the head and tail method with the meteorological data, irrigation data and drainage data is between 0.427 and 0.572 with an average of 0.492, and in Yonglian irrigation sub-district is 0.447 to 0.688 with an average 0.516. 【Conclusion】 The SEBAL model provides a fast and accurate method to estimate the regional ET and water efficiency of irrigation. The average groundwater recharge in study area is 52.13mm, which accounts for 3%～7% total irrigation water, and the neglect of which takes about 0.03～0.08 absolute error for estimation the water efficiency of irrigation. There is almost no difference for the water efficiency of irrigation between the two districts in different spatial scales, which shows the established model can also be applied to small region. |
| Key words: Water efficiency of irrigation; SEBAL model; HJ satellite; Regional evapotranspiration |
