Improving the identification of hydrologically sensitive areas using LiDAR DEMs for the delineation and mitigation of critical source areas of diffuse pollution

Abstract

Identifying critical source areas (CSAs) of diffuse pollution in agricultural catchments requires the accurate identification of hydrologically sensitive areas (HSAs) at highest propensity for generating surface runoff and transporting pollutants. A new GIS-based HSA Index is presented that improves the identification of HSAs at the sub-field scale by accounting for microtopographic controls. The Index is based on high resolution LiDAR data and a soil topographic index (STI) and also considers the hydrological disconnection of overland flow via topographic impediment from flow sinks. The HSA Index was applied to four intensive agricultural catchments (~ 7.5–12 km2) with contrasting topography and soil types, and validated using rainfall-quickflow measurements during saturated winter storm events in 2009–2014. Total flow sink volume capacities ranged from 8298 to 59,584 m3 and caused 8.5–24.2% of overland-flow-generating-areas and 16.8–33.4% of catchment areas to become hydrologically disconnected from the open drainage channel network. HSA maps identified ‘breakthrough points’ and ‘delivery points’ along surface runoff pathways as vulnerable points where diffuse pollutants could be transported between fields or delivered to the open drainage network, respectively. Using these as proposed locations for targeting mitigation measures such as riparian buffer strips reduced potential costs compared to blanket implementation within an example agri-environment scheme by 66% and 91% over 1 and 5 years respectively, which included LiDAR DEM acquisition costs. The HSA Index can be used as a hydrologically realistic transport component within a fully evolved sub-field scale CSA model, and can also be used to guide the implementation of ‘treatment-train’ mitigation strategies concurrent with sustainable agricultural intensification.