环境科学
水文地质学
水资源管理
流域
水质
水文学(农业)
地下水
污染
农业
环境资源管理
工程类
地理
生态学
生物
考古
岩土工程
地图学
作者
Richard J. Cooper,Kevin M. Hiscock,Andrew Lovett,Stephen J. Dugdale,Gisela Sünnenberg,N. Garrard,Faye N. Outram,Zanist Q. Hama-Aziz,Lister Noble,Melinda Lewis
标识
DOI:10.1016/j.hydroa.2018.100007
摘要
Mitigating agricultural water pollution requires changes in land management practices and the implementation of on-farm measures to tackle the principal reasons for water quality failure. However, a paucity of robust empirical evidence on the hydrological functioning of river catchments can be a major constraint on the design of effective pollution mitigation strategies at the catchment-scale. In this regard, in 2010 the UK government established the Demonstration Test Catchment (DTC) initiative to evaluate the extent to which on-farm mitigation measures can cost-effectively reduce the impacts of agricultural water pollution on river ecology while maintaining food production capacity. A central component of the DTC platform has been the establishment of a comprehensive network of automated, web-based sensor technologies to generate high-temporal resolution empirical datasets of surface water, soil water, groundwater and meteorological parameters. In this paper, we demonstrate how this high-resolution telemetry can be used to improve our understanding of hydrological functioning and the dynamics of pollutant mobilisation and transport under a range of hydrometerological and hydrogeological conditions. Furthermore, we demonstrate how these data can be used to develop conceptual models of catchment hydrogeological processes and consider the implications of variable hydrological functioning on the performance of land management changes aimed at reducing agricultural water pollution.
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