Minimum Information Requirement Modelling for Catchment Water Resource Management

Senior Lecturer, Department of Agricultural Engineering, Faculty of Agriculture BSc. (Agric) (Peradeniya), MSc. (AIT), PhD. (Newcastle upon Tyne, UK) Pollution of surface and sub surface water from agricultural nutrients; especially from nitrogen and phosphorus is a widespread environmental problem. Mathematical models play a substantial role in predicting and forecasting hydrological and water quality related issues at different spatial scales. A need of an easily calibratable and minimum information requirement models to be used in predictions it catchment scale and subsequent policy formulation and management was identified in this study. The existed TOPCAT-N model was further developed to add a phosphorus component and efficient model-user interface and was named TOPCAT-NP. To study the model applicability to tropical monsoon affected climatic conditions, field sampling was carried out at upper Uma Oya catchment and its few land use specific sub catchments in central Sri Lanka for a nine month period. Hydrochemical assessment and TOPCAT-NP modelling were performed with collected data. Effect of land use scenarios and the model and parameter uncertainty were also assessed. The TOPCAT-NP predicts flow, nitrate nitrogen, soluble and sediment attached phosphorus at the catchment scale with a relatively few key input parameters. The model stands between complex physically based models such as EPIC and simple catchment scale empirical models such as export coefficient approach. TOPCAT-NP simulates the flow and nutrients at daily or sub daily time steps provided that rainfall and evapotranspiration are input. Improved temporal resolution of the output provides seasonal changes in nutrient mobility for better implementation of management strategies at correct time and place. The hydro-chemical assessment in upper Uma Oya suggests that there is no great threat to the surface water from nutrients though, ground water contains very high levels of nitrates in agricultural areas. The farmers continue to apply over doses of fertiliser to the agricultural fields. Land use mainly agriculture has a prominent effect on surface and ground water nutrient levels. Nutrient release from the land to stream is mainly governed by the storm events. Increasing levels of stream and soil matrix nitrate was observed following storm events. TOPCAT-NP reasonably simulates the flow and nitrate patterns however, the behaviour of Pis highly unpredictable. Land use effect is highly visible in scenario analysis and it also provides guidance to the uncertainty in the predictions. If