GIS-based methodologies for assessing nitrate, nitrite and ammonium distributions across a major UK basin, the Humber

Abstract

Abstract. The distributions of nitrate, nitrite and ammonium at various monitoring sites across the Humber basin (area 24 000 km2) were examined within a Geographical Information System (GIS) framework. This basin contains diverse characteristics, from areas of high population and industry to rural and arable regions. The Humber River is a major provider of and nutrient fluxes to the North Sea from the UK. Within the GIS analysis, the distributions of mean and mean flow weighted concentrations, flux and flux per unit area, were investigated. Empirical relationships between land characteristics and water quality for the whole catchment draining to each water quality monitoring site were established. Thirty-eight catchments were chosen for this analysis, with areas ranging from 46 km2 to 8225 km2. These catchments are distributed across the Humber, encompassing the different conditions across the basin, thus allowing relationships between water quality and catchment characteristics to be used to estimate the nitrogen concentrations and flux throughout the basin river network. The main water quality data source was the Land Ocean Interaction Study (LOIS) dataset. The Environment Agency of England and Wales water quality datasets were used to infill areas of sparse LOIS monitoring network density within the Humber. The work shows the feasibility of estimating nitrate and, to a lesser extent, nitrite and ammonium concentrations and fluxes across the river network based on land characteristics, using a GIS methodology. The estimations work particularly well for the main river channels. However, there are local anomalies which are more difficult to predict. Maps showing concentration variations at 500 m intervals along the Humber basin river networks are presented; these are of particular value for environmental managers and socio-economists. Keywords: GIS, nitrate, nitrite, ammonium, catchment characteristics