FLUS-CSLE模型预测黄土高原典型流域不同土地利用变化情景土壤侵蚀

流域土壤侵蚀预测对于了解未来土壤侵蚀发展趋势，制定未来水土保持治理策略具有重要意义。为了提出一种适用于黄土高原地区的易于评估未来不同土地利用管理策略的土壤侵蚀预测方法，该研究基于地形、降雨、土壤、遥感影像数据，完成韭园沟流域2010-2020年的土地利用空间分布解译，并计算历史时期（2010-2020）的土壤侵蚀模数，基于未来土地利用模拟（Future Land Use Simulation，FLUS）模型完成流域2025年土地利用分布状况预测，以此为基础获得未来植被覆盖措施因子和耕作措施因子，结合CSLE模型预测2025年自然发展、经济增长、生态保护3种不同土地利用变化情景下土壤侵蚀状况。结果表明：1）韭园沟流域土地利用类型主要为草地（面积占比62.23%）和林地（28.41%），其次是耕地、建筑物和水体，在2010-2020年期间土地利用空间分布格局经历了较大变化，林、草地面积增加8.36%，耕地面积减少30.3%。2）流域2010、2015、2020年这3 a间土壤侵蚀模数平均值分别为19.49、15.83、20.7 t/(hm2·a)，整体呈现先降低后增加的趋势，不同土地利用类型的土壤侵蚀模数由大到小为耕地（40.56 t/(hm2·a)）、草地（18.79 t/(hm2·a)）、建设用地（10.25 t/(hm2·a)）、林地（8.02 t/(hm2·a)）。3）在积极的生态保护情景下，2025年林、草地面积较自然发展情景基本持平但林地面积比例有所增加，较经济增长情景林、草地面积增加5.06%，耕地面积较自然发展情景增加1.20%，较经济增长情景减少14.73%。4）2025年流域自然发展、经济增长、生态保护情景下土壤侵蚀模数分别为24.3、22.9、18.3 t/(hm2·a)。采取积极的生态保护情景发展模式，建设用地面积适度扩张可以兼顾生态保护和经济发展的需要。该研究为流域未来的土地利用规划以及水土保持治理提供参考。

Prediction of soil erosion under different land uses in the typical watershed of the Loess Plateau based on FLUS-CSLE model

Abstract: As the most prominent ecological environment problem in the Loess Plateau, soil erosion seriously threatens ecological balance and food security, restricts economic and social development, and frequent human activities are drastically changing the spatial pattern of land use in the region. Therefore, it is of great significance to propose a soil erosion prediction method that is easy to evaluate soil erosion in the Loess Plateau under different land use management strategies in the future for soil erosion control and regional coordinated development. In this study, the Jiuyuangou watershed was used as the research object, and the FLUS model was used to predict the spatial distribution pattern of land use in different scenarios in the future. Based on this, the vegetation coverage factor B and the tillage measure factor T in the future scenario were calculated. The CSLE model was used to evaluate the soil erosion status in the historical period (2010-2020 ), and combined with the B and T factors in the future scenarios to predict the soil erosion status under different land use change scenarios in 2025. Based on the soil erosion status under different land use change scenarios in the future, the response of different land use types and soil erosion status is analyzed, which provides scientific reference and suggestions for the formulation of future land use management strategies in the watershed. The results show that: (1) The main land use types in Jiuyuangou watershed are grassland (62.23%) and forest land (28.41%), followed by cropland, buildings, and water . From 2010 to 2020, the spatial distribution pattern of land use has undergone great changes, with the area of forest and grassland increasing by 8.36% and the area of cropland decreasing by 30.3%. (2) The average values of soil erosion modulus in the three years of 2010, 2015, and 2020 are 19.49 t hm-2 yr-1, 15.83 t hm-2 yr-1, and 20.7 t hm-2 yr-1 respectively, showing a trend of first decreasing and then increasing. The soil erosion modulus of different land use types is cropland (40.56 t hm-2 yr-1)>grassland (18.79 t hm-2 yr-1)> building (10.25 t hm-2 yr-1)>forest land (8.02 t hm-2 yr-1). (3) Under the ecological protection scenario, the area of forest and grassland will increase by 1.63% and 5.06% respectively compared with the natural development and economic growth scenarios in 2025, and the area of cropland will decrease by 1.2% and 14.73% respectively compared with the natural development and economic development scenarios. (4) In 2025, the soil erosion modulus under the natural development, economic growth, and ecological protection scenarios of the watershed will be 24.3 t hm-2 yr-1, 22.9 t hm-2 yr-1 and 18.3 t hm-2 yr-1 respectively. Taking an active ecological protection development mode and appropriately expanding the building area can meet the needs of ecological protection and economic development. The research results provide scientific reference for the future land use planning and soil and water conservation management of the watershed and provide a fast and efficient soil erosion prediction method for different future land use scenarios.