Classification and Estimation of Irrigation Waters Based on Remote Sensing Images: Case Study in Yucheng City (China)
文献类型：期刊论文
| 作者 | Lu, Qingshui1,2; Liang, Shangzhen3; Xu, Xinliang4
|
| 刊名 | SUSTAINABILITY
 |
| 出版日期 | 2018-10-01 |
| 卷号 | 10期号:10页码:12 |
| 关键词 | Yellow River Downstream Plain irrigated cropland category well irrigation canal irrigation minimum irrigation water amount |
| ISSN号 | 2071-1050 |
| DOI | 10.3390/su10103503 |
| 通讯作者 | Lu, Qingshui(luqs@lreis.ac.cn) |
| 英文摘要 | The downstream plain of the Yellow River is experiencing some of the most severe groundwater depletion in China. Although the Chinese government has issued policies to ensure that the Yellow River can provide enough irrigation waters for this region, groundwater levels continue to decrease. Yucheng City was selected as a case study. A new method was designed to classify the cropland into various irrigated cropland. Subsequently, we analyzed data regarding these irrigated-cropland categories, irrigation norms, and the minimum amount of irrigation water being applied to cropland. The results showed that 91.5% of farmland can be classified as double irrigated (by both canal/river and well water), while 8.5% of farmland can be classified as well irrigated. During the irrigation season, the sediments brought in by the river have blocked portions of the canals. This has led to 23% of the double-irrigated cropland being irrigated by groundwater, and it is thus a main factor causing reductions in groundwater supply. These blocked canals should be dredged by local governments to mitigate local groundwater depletion. The method for classifying irrigated cropland from high-resolution images is valid and it can be used in other irrigated areas with a declining groundwater table for the sustainable use of groundwater resources. |
| WOS关键词 | LAND |
| 资助项目 | Natural Science Foundation of Beijing[9182004] ; National Natural Science Foundation of China[31670471] ; National Social Science Fund Project of China[17AJL008] |
| WOS研究方向 | Science & Technology - Other Topics ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000448559400145 |
| 出版者 | MDPI |
| 资助机构 | Natural Science Foundation of Beijing ; National Natural Science Foundation of China ; National Social Science Fund Project of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/52476]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Lu, Qingshui |
| 作者单位 | 1.Univ Jinan, Coll Business, Jinan 250022, Shandong, Peoples R China 2.Univ Jinan, Inst Green Dev, Jinan 250022, Shandong, Peoples R China 3.Water Bur Yucheng City, Yucheng 251200, Shandong, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resource Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Qingshui,Liang, Shangzhen,Xu, Xinliang. Classification and Estimation of Irrigation Waters Based on Remote Sensing Images: Case Study in Yucheng City (China)[J]. SUSTAINABILITY,2018,10(10):12. |
| APA | Lu, Qingshui,Liang, Shangzhen,&Xu, Xinliang.(2018).Classification and Estimation of Irrigation Waters Based on Remote Sensing Images: Case Study in Yucheng City (China).SUSTAINABILITY,10(10),12. |
| MLA | Lu, Qingshui,et al."Classification and Estimation of Irrigation Waters Based on Remote Sensing Images: Case Study in Yucheng City (China)".SUSTAINABILITY 10.10(2018):12. |
入库方式： OAI收割
来源：地理科学与资源研究所
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