Revealing spatiotemporal patterns of fertilizer use and agricultural non-point source pollution in smallholder farming watersheds of mountainous and hilly areas
文献类型：期刊论文
| 作者 | Lang, Lichen1,4; Li, Zhihui1,4; Zang, Hongkuan2,5; Gao, Xing4; Wu, Feng1,4; Deng, Wang3; Gao, Ya3 |
| 刊名 | AGRICULTURAL WATER MANAGEMENT
 |
| 出版日期 | 2025-12-20 |
| 卷号 | 322页码:109950 |
| 关键词 | Mountainous and hilly areas (MHAs) Smallholder farming SWAT plus ANPS pollution Agriculture management Spatiotemporal heterogeneity |
| ISSN号 | 0378-3774 |
| DOI | 10.1016/j.agwat.2025.109950 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Mountainous and Hilly Areas (MHAs) are critical for ecological security, water resource conservation, and agricultural production. However, Agricultural Non-Point Source (ANPS) pollution in MHAs remains poorly understood due to the failure of existing models to capture the pronounced spatiotemporal heterogeneity of smallholder farming systems. This study focuses on the Yuanjiang River Basin, a representative subtropical, agriculture-intensive watershed in MHAs, to address both methodological gaps in simulating ANPS pollution and knowledge gaps in understanding its spatiotemporal characteristics. A customized version of the Soil and Water Assessment Tool Plus (SWAT+), referred to as SWAT+-Smallholder Farming Systems (SWAT+-SFS), was developed to simulate variability within Hydrological Response Units (HRUs) in fertilization timing and dynamic postponement behavior in response to real-time rainfall and soil moisture. Three fertilization representation methods were compared: a conventional discrete-event scheme, a spatially split HRU approach, and the proposed SWAT+-SFS method. While the split-HRU approach disrupted the hydrological unit structure, SWAT+-SFS balanced computational efficiency and accuracy. Compared to the conventional discrete-event scheme, the SWAT+-SFS model reduced overestimation of total nitrogen (TN) during the rainy season and substantially improved total phosphorus (TP) simulation, with average validation Kling-Gupta Efficiency (KGE) values increasing by 67.38 % for TN and 57.03 % for TP across monitoring stations. Simulations revealed that surface runoff-driven losses are significantly amplified by fragmented, prolonged fertilization schedules. This study underscores the critical need to account for complex human behaviors when understanding contemporary watershed hydrological and water quality processes, and highlights the importance of timely, science-based management guidance tailored to smallholder farming systems to support sustainable agriculture in MHAs. |
| URL标识 | 查看原文 |
| WOS关键词 | NITROGEN USE EFFICIENCY ; VEGETABLE PRODUCTION ; LAND-USE ; SOIL ; MANAGEMENT ; SYSTEMS |
| WOS研究方向 | Agriculture ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001614159000001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217737]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Wu, Feng |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 2.Tsinghua Univ, Sch Environm, Beijing 100084, Peoples R China; 3.China Univ Geosci, Wuhan 430074, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 5.Beijing Enterprises Water Grp Ltd, Beijing 100102, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Lang, Lichen,Li, Zhihui,Zang, Hongkuan,et al. Revealing spatiotemporal patterns of fertilizer use and agricultural non-point source pollution in smallholder farming watersheds of mountainous and hilly areas[J]. AGRICULTURAL WATER MANAGEMENT,2025,322:109950. |
| APA | Lang, Lichen.,Li, Zhihui.,Zang, Hongkuan.,Gao, Xing.,Wu, Feng.,...&Gao, Ya.(2025).Revealing spatiotemporal patterns of fertilizer use and agricultural non-point source pollution in smallholder farming watersheds of mountainous and hilly areas.AGRICULTURAL WATER MANAGEMENT,322,109950. |
| MLA | Lang, Lichen,et al."Revealing spatiotemporal patterns of fertilizer use and agricultural non-point source pollution in smallholder farming watersheds of mountainous and hilly areas".AGRICULTURAL WATER MANAGEMENT 322(2025):109950. |
入库方式： OAI收割
来源：地理科学与资源研究所
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