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基于雨养指示线的灌溉概率指数计算与验证
引用本文:朱秀芳,刘莹,徐昆.基于雨养指示线的灌溉概率指数计算与验证[J].农业工程学报,2022,38(2):50-57.
作者姓名:朱秀芳  刘莹  徐昆
作者单位:1. 北京师范大学遥感科学国家重点实验室,北京 100875;2. 北京师范大学环境演变与自然灾害教育部重点实验室,北京 100875;3. 北京师范大学地理科学学部遥感科学与工程研究院,北京 100875;1. 北京师范大学遥感科学国家重点实验室,北京 100875;3. 北京师范大学地理科学学部遥感科学与工程研究院,北京 100875;4. 山东黄河河务局山东黄河信息中心,济南 250013
基金项目:国家自然科学基金资助项目(42077436);国家重点研发计划资助(2021YFB3901201)
摘    要:发展物理意义明确、指示意义强的灌溉特征参量有助于提高灌溉耕地制图精度.基于灌溉可以减缓或者抑制气象干旱向农业干旱演变的原理,该研究提出了雨养指示线的概念,并基于此发展了灌溉概率指数.选择有良好灌溉数据基础的美国内布拉斯加州为研究区,利用降水、实际蒸散发和潜在蒸散发数据计算的气象干旱指数和农业干旱指数来表征研究区的气象干...

关 键 词:灌溉  耕地  干旱  制图  灌溉特征
收稿时间:2021/8/16 0:00:00
修稿时间:2022/1/1 0:00:00

Calculation and verification of the irrigation probability index using rain-fed indicator line
Zhu Xiufang,Liu Ying,Xu Kun.Calculation and verification of the irrigation probability index using rain-fed indicator line[J].Transactions of the Chinese Society of Agricultural Engineering,2022,38(2):50-57.
Authors:Zhu Xiufang  Liu Ying  Xu Kun
Institution:1. State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China; 2. Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China; 3. Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China;;1. State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China; 3. Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; 4. Yellow River Information Center, Shandong Yellow River Bureau, Jinan 250013, China
Abstract:Abstract: The irrigation area, distribution, amount, and time can greatly contribute to the national food security, economic development, and water resources management in cultivated lands. Among them, the irrigation area and distribution are the most fundamentals to acquiring the irrigation farmland mapping. Most current researches focus on the parameters to represent the vegetation growth or soil moisture, thereby indirectly locating the irrigation situation. However, the specific physical mechanism is still lacking so far. It is also a high demand for the irrigation characteristic parameters with a clear physical meaning and strong indicative significance, further improving the mapping accuracy of irrigated farmland. In this study, a new concept of rain-fed indicator line was extracted to develop the irrigation probability index (IPI), in order to slow down or inhibit the evolution of meteorological to agricultural drought. The Nebraska irrigation data base was selected as the test area. The precipitation, actual and potential evapotranspiration were measured to calculate the crop water deficit index (CWDI) and crop water stress index (CWSI). Then, the CWDI was used to characterize the meteorological drought, whereas, the CWSI was to characterize the agricultural drought in the study area. At first, it was assumed that the agricultural drought was strongly related to the irrigation in the cultivated land under the consistent conditions of meteorological drought. The horizontal coordinate was utilized to represent the meteorological drought, and the vertical coordinate was to represent the agricultural drought. As such, all the scattered pixels of cultivated land in the study area were extracted to form a two-dimension characteristic space. The upper envelope of scattered points was extracted as the rain-fed indicator line, where the distance from each cultivated land pixel to the rain-fed indicator line along the vertical coordinate was defined as the irrigation probability index (IPI). The relationships were then determined between the IPI and real irrigation area, the number of active irrigation wells, the area of irrigation facilities, and the distribution of rivers. The results show that the IPI was much higher in the east, but relatively lower in the west, indicating a better conssistency with the distribution pattern of temperature, precipitation, and agricultural activities in the study area. There was the highest correlation coefficient (0.62) between the sum of county IPI and the real irrigation area, followed by the area of irrigation facilities (0.55), and the lowest with the number of active irrigation wells was 0.51. Three correlation coefficients all passed over the test of 0.05 significance level, indicating that the IPI was effectively characterized the possibility of farmland to be irrigated. More importantly, there was different adaptability of IPI in three climate regions (humid, climate suitable, and arid region). Specifically, the IPI shared a better representation for the irrigation in the climate suitable and the arid areas, compared with the humid. Particularly, the sum of county IPI in climate suitable and arid areas presented a significant positive correlation with the real irrigation area, the number of active irrigation wells, and the area of irrigation facilities. The average IPI also decreased with the increase of the distance to the river. There was no significant correlation between the sum of county IPI and the number of active irrigation wells in the humid area, where the average IPI increased with the increase of distance to the river. The newly-developed IPI in this study can be widely expected to better represent the possibility of farmland to be irrigated, further serving as a physical parameter for the irrigation farmland mapping.
Keywords:irrigation  farmland  drought  mapping  irrigation features
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