Journal of Environmental Engineering · 2024 · 17 citations · 45 references
ComputingEarth SciencesWatershed ManagementGeographic Information SystemsSpatial AnalysisSpatial StatisticsGeostatistical AnalysisHot Spot AnalysisNonpoint Source Pollution ControlSpatial Cluster AnalysisSpatial Distribution AnalysisSpatial Statistical ModelingAgricultural Nonpoint Source PollutionAgricultural Nonpoint Source Pollution ControlAnselin Local Moran's IHotspot AnalysisMoran's INonpoint Source Pollution AssessmentPollution Load AssessmentSource Area Analysis
Agricultural nonpoint source pollution (ANPS) can cause systemic pollution of the ecological environment, directly threatening sustainable agricultural development and human health and safety. Accurate estimation of ANPS loads, clarification of the sources and spatial distribution patterns of ANPS, and effective control and management of ANPS in the watershed require identifying critical source areas. This case study focuses on the Danjiang River basin, a critical water source for China’s South-to-North Water Division and demonstrates the efficiency of ArcGIS’s spatial statistical analysis methods in discovering the hidden spatial pattern of ANPS and extracting the causes associated with the spatial pattern, as well as the accuracy of identifying critical source areas of ANPS. In this study, two spatial statistical analysis methods, Anselin local Moran’s I and hot-spot analysis (Getis–Ord Gi*), are applied to propose a method for accurately identifying critical source areas of ANPS based on the spatial distribution of ANPS loads. The results of the study are as follows: (1) based on the MIKE LOAD model, the annual ANPS loads of chemical oxygen demand (COD), ammonia nitrogen (NH4), total nitrogen (TN), and total phosphorus (TP) in the Danhan River basin are calculated as 182,530.15, 16,137.39, 58,285.92, and 2,962.84 t/yr, respectively. (2) Clusters are mainly distributed in the southwestern part of the watershed, and the spatial pattern is directly related to land use and rural population; the spatial pattern of outliers is related to agricultural modes and geographical characteristics. (3) Hot spot clusters are concentrated in the hinterland of Hanzhong Plain; the regional specialty of agriculture is the dominant factor in determining the spatial pattern of cold-spot and hot-spot clusters. (4) Based on these findings, seven critical subbasins and one critical source area of ANPS that need to be prioritized for control in the study area are identified.
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Managing nitrogen to restore water quality in China
Chaoqing Yu, Xiao Huang, Han Chen et al. · Nature · 2019 · 1.1K citations · Full text
John L. Stoddard, John Van Sickle, Alan T. Herlihy et al. · Environmental Science & Technology · 2016 · 243 citations · Full text
Natural Sciences, Earth Sciences, Environmental Sciences +17