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 (~7.5-12km(2)) 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 59,584m(3) 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 5years 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.

Identifying Surface Runoff Pathways for Cost-Effective Mitigation of Pollutant Inputs to Drinking Water Reservoir

“…Pollutant transport via surface runoff is especially intensified in catchments which are hydrologically sensitive to rainfall (vulnerable to contamination following precipitation events). The factors facilitating this phenomenon are: low permeability of soils, high slope gradients and the lack of vegetation cover [10][11][12]. The observed climate change and increased heavy rainfall lead to significant and rapid transfers of nutrients to surface water.…”

“…The data from classic water monitoring carried out by government institutions (with monthly or even biweekly sampling) are insufficient to accurately identify nitrogen and phosphorus loads entering surface waters. Nowadays, research related to the mitigation of surface runoff impact on water bodies concentrates on identifying pollution paths and: (i) designating areas within a catchment that are prone to generating runoff (hydrologically sensitive areas (HSAs)); (ii) designating areas with the highest transfer risk of pollutants-critical source areas (CSAs), potential pollutant loading is connected here to being prone to generating runoff (HSA + high risk of pollutant mobilisation); (iii) identifying interfaces between pollution source areas and buffer zones [6,10,15,17,18]. Such research is in turn the basis for cost-effective planning, targeted mitigation measures and the evaluation of the effectiveness of existing security measures i.e., riparian buffer zones (resource protection areas (RPAs)).…”

“…Over the last decade, remote sensing and GIS tools have become increasingly integrated. Remotely sensed data can be processed and analysed fast using GIS software [10,17,22]. Wider and faster access to geospatial data enables a dynamic growth of research related to the risk of surface runoff generation [28].…”

“…Wider and faster access to geospatial data enables a dynamic growth of research related to the risk of surface runoff generation [28]. Digital Elevation Models (DEMs) and Digital Terrain Models (DTMs) obtained from Light Detection and Ranging (LiDAR) turn out to be particularly useful [10,29].…”

“…The effective area of riparian buffer which takes part in pollutant and sediment removal is much smaller when concentrated (channelised) on surface flow crosses or even bypasses vegetation strips. Nowadays, methods based on using high resolution remote sensing data offer the opportunity to take a new look at the transport of nutrients and sediment to surface waters and to precisely indicate surface runoff pathways, taking into account terrain microtopography (small grooves or furrows) and to quickly diagnose the problem of concentrated surface flow, both on a field and catchment scale, omitting time-consuming field studies usually carried out in small areas [10,16,17,26,28,29].…”