| 基于SWAT和PLUS模型的窟野河流域径流对土地利用变化的响应及预测 |
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| 引用本文： | 杨智勇,牛健植,樊登星,张卓佩,杜洲,赵春光.基于SWAT和PLUS模型的窟野河流域径流对土地利用变化的响应及预测[J].水土保持学报,2024,38(1):289-299. |
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| 作者姓名： | 杨智勇 牛健植 樊登星 张卓佩 杜洲 赵春光 |
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| 作者单位： | 1. 北京林业大学水土保持学院, 水土保持国家林业和草原局重点实验室, 北京 100083;2. 林业生态工程教育部工程研究中心, 北京 100083;3. 鄂尔多斯市水旱灾害防御技术中心, 内蒙古 鄂尔多斯 017000 |
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| 基金项目： | 国家重点研发计划项目(2022YFF1300804) |
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| 摘 要： | 目的]为揭示窟野河流域径流对土地利用变化的响应，并预测未来径流变化。方法]以窟野河流域为研究区，基于SWAT和PLUS模型，通过2000年、2005年、2010年、2015年、2020年和预测得到的自然发展情景下2025年、2030年7期土地利用数据，定量分析径流在不同土地利用情景下的变化。结果](1)SWAT模型率定期和验证期的R2和NS均>0.7;PLUS模型总体精度为0.877 4,Kappa系数为0.802 1,2个模型在窟野河流域适用性较好；(2)2000—2020年，窟野河流域林地、建设用地面积分别增加102.92,600.90 km2,耕地、草地、水域和未利用地分别减少277.15,366.25,40.44,19.98 km2;(3)窟野河流域年平均径流深整体呈现“上游低，下游高，西部低，东部高”的空间分布格局；(4)在保证其他输入数据不变的情况下，改变土地利用数据，情景分析结果表明，林地、草地面积减少会促进径流，建设用地面积增加同样会促进径流；(5)自然发展情景下，2025年和2030年窟野河...
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| 关 键 词： | 土地利用变化 径流模拟 SWAT模型 PLUS模型 窟野河流域 |
| 收稿时间： | 2023/8/11 0:00:00 |
| 修稿时间： | 2023/9/25 0:00:00 |
Response and Prediction of Runoff to Land Use Change in Kuye River Basin Based on SWAT and PLUS Models |
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| YANG Zhiyong,NIU Jianzhi,FAN Dengxin,ZHANG Zhuopei,DU Zhou,ZHAO Chunguang.Response and Prediction of Runoff to Land Use Change in Kuye River Basin Based on SWAT and PLUS Models[J].Journal of Soil and Water Conservation,2024,38(1):289-299. |
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| Authors: | YANG Zhiyong NIU Jianzhi FAN Dengxin ZHANG Zhuopei DU Zhou ZHAO Chunguang |
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| Institution: | 1. State Forestry and Grassland Administration Key Laboratory of Soil and Water Conservation, College of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China;2. Engineering Research Center of Forestry Ecological Engineering, Ministry of Education, Beijing 100083, China;3. Ordos Flood and Drought Disaster Prevention Technology Center, Ordos, Inner Mongolia 017000, China |
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| Abstract: | Objective] The study is aimed at revealing the response of runoff to land use change in the Kuye River Basin and predicting future runoff change. Methods] Taking the Kuye River Basin as the study area, based on the SWAT and PLUS models, the changes of runoff under different land use scenarios were quantitatively analyzed by using the land use data of 2000, 2005, 2010, 2015, 2020 and the data of 2025 and 2030 that were predicted from the natural development scenario. Results] (1) The R2 and NS of the SWAT model during the periodic and validation periods were greater than 0.7. The overall accuracy of PLUS model was 0.877 4, and the Kappa coefficient was 0.802 1. The two models had good applicability in the Kuye River Basin. (2) From 2000 to 2020, forest land and construction land increased by 102.92 and 600.90 km2, respectively, while cultivated land, grassland, water area, and unused land decreased by 277.15, 366.25, 40.44 and 19.98 km2, respectively. (3) The average annual runoff depth in the Kuye River Basin presented a spatial distribution pattern of "lower in the upper reaches, higher in the lower reaches, lower in the west, and higher in the east". (4) Changing land use data while ensuring that other input data remains unchanged, the results of scenario analysis showed that the decrease of forest land and grassland area would promote runoff, and the increase of construction land area would also promote runoff. (5) Under the natural development scenario, there was no significant change in the spatial distribution pattern of land use in the Kuye River Basin in 2025 and 2030, and the land use was still dominated by cultivated land and grassland, with the average annual runoff increasing by 3.21% and 5.00%, respectively, compared with 2020. Conclusion] There was a close relationship between land use and runoff change. From the perspective of scenario analysis, forest land and grassland inhibited runoff, while construction land promoted runoff. Under the future natural development scenario, runoff increased with land use change. The research could provide scientific basis for the optimization of land use structure and rational planning of water and soil resources in the Kuye River Basin. |
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| Keywords: | land use change|runoff simulation|SWAT model|PLUS model|Kuye River Basin |
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