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Updated: Mar 7, 2026

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

在地表水中的营养和沉积物负载的时空空间变异性分析,使用改善的水文建模来对低谷占主导地位的流域进行分析

Mosammat Mustari Khanaum¹, Marinus L Otte², Xuefeng Chu³

¹Department of Civil, Construction and Environmental Engineering (Dept. 2470), North Dakota State University, PO Box 6050, Fargo, ND, 58108-6050, USA. mosammat.khanaum@ndsu.edu.

Environmental monitoring and assessment

|March 5, 2026

概括

识别营养和沉积物污染热点至关重要. 这项研究使用DPCA-SWAT和地质探测器发现降水和土地利用导致污染,特别是在洪水频率较低的干旱时期.

科学领域:

环境科学环境科学
水文学的水文学
水质管理水质管理

背景情况:

营养物质和沉积物污染带来了重大的环境挑战,影响因素之间的对线性往往使其复杂化.
有效的缓解需要识别污染物热点及其主要驱动因素.
空间自关联和地质探测器提供了先进的方法来解决这些复杂问题.

研究的目的:

为了研究营养素 (总和总) 和沉积物污染热点的时空变异性.
确定影响这些污染热点的关键驱动因素.
为最佳管理实践 (BMP) 提供理论指导.

主要方法:

将动态部分贡献区 (DPCA) 模型与土壤和水资源评估工具 (SWAT) 结合起来.
应用莫兰的I空间自相关测试来分析时空变化.
使用地质探测器识别关键影响因素.
在峰值排放数据上进行洪水频率分析.

主要成果:

空间自相关性显示,干旱时期的相关性比潮湿时期更强.
在洪水频率较低的时期,污染热点更加明显.
地质探测器确定了降雨和土地使用土地覆盖 (LULC) 的相互作用是潮湿时期TN和TP的关键驱动因素.
降水和作物管理是潮湿时期沉积物污染的最重要因素.

结论:

配合地质探测器的DPCA-SWAT模型有效地识别了污染物热点及其驱动因素.
了解时空动态和影响因素对于有针对性的污染减缓至关重要.
结果为开发有效的最佳管理实践 (BMP) 提供了宝贵的见解.

关键词:

地质探测器地质探测器通过陆地产生流量.空间自相关性空间自相关性表面的低谷是表面的低谷.水的质量水的质量流域建模的流域模型

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