Evaluating the risk of non-point source pollution from biosolids: integrated modelling of nutrient losses at field and catchment scales

Abstract

A semi-distributed model, INCA, has been developed to determine the fate and distribution of nutrients in terrestrial and aquatic systems. The model simulates nitrogen and phosphorus processes in soils, groundwaters and river systems and can be applied in a semi-distributed manner at a range of scales. In this study, the model has been applied at field to sub-catchment to whole catchment scale to evaluate the behaviour of biosolid-derived losses of P in agricultural systems. It is shown that process-based models such as INCA, applied at a wide range of scales, reproduce field and catchment behaviour satisfactorily. The INCA model can also be used to generate generic information for risk assessment. By adjusting three key variables: biosolid application rates, the hydrological connectivity of the catchment and the initial P-status of the soils within the model, a matrix of P loss rates can be generated to evaluate the behaviour of the model and, hence, of the catchment system. The results, which indicate the sensitivity of the catchment to flow paths, to application rates and to initial soil conditions, have been incorporated into a Nutrient Export Risk Matrix (NERM).

Targeting priority management areas for multiple pollutants from non-point sources

“…Generally, NPS pollutants are transported from extensive areas of a watershed but almost 90% of NPS exports are from relatively small areas [3]. In this respect, a watershed manager needs to gain insights into the spatial dynamics of priority management areas (PMAs) or critical source areas (CSAs) as an inherent part of all watershed programs [4,5].…”

Spatial distribution of non-point source nitrogen in urban area of Beijing City, China

“…With the effective control of point source pollution, Non-point source (NPS) has become the major cause of water pollution in many countries, such as the UK (Whitehead et al 2007), China (Ding et al, 2010) and the USA (Emili and Greene 2013). For rivers and lakes in urban areas, NPS pollution in the form of runoff from urban areas has contributed greatly to the degradation of flow in the receiving water bodies (Sartor et al 1972;Kang et al, 2013).…”

Upstream to downstream: a multiple-assessment-point approach for targeting non-point-source priority management areas at large watershed scale

“…First, there was a general trend of reduced agricultural areas from upstream to downstream in the Daning watershed. This trend implied reduced P loss potentials among those downstream areas because agricultural lands generally induce a greater impact on the export of P than other land uses (Whitehead et al, 2007;Gong et al, 2011;Shen et al, 2012Shen et al, , 2013. Second, the upstream P concentrations have been diluted during the transport process because of the long hydrological residence time within the downstream river network (Arheimer and Brandt, 2000;Bae and Ha, 2006;Zhou and Gao, 2011).…”

“…As widely accepted concepts, priority management areas (PMAs) are defined as those areas where the risk potential of certain pollutants exceeds local loss tolerance or contributes more pollutant to the nearby water body (Carpenter et al, 1998;Ghebremichael et al, 2013). Many successes of the NPS control efforts have been reported based on PMAs (Ghebremichael et al, 2010;Kovacs et al, 2012;Setegn et al, 2006;Strauss et al, 2007;Tripathi et al, 2003;White et al, 2009;Whitehead et al, 2007;Yeghiazarian et al, 2006;Zhou and Gao, 2011). Today, the targeting of watershed PMAs has been integrated as an inherent part of largescale watershed management programs, such as the Total Maximum Daily Load (TMDL) (Savage and Ribaudo, 2013;Sahoo et al, 2013;White et al, 2009).…”