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• W3145954612 abstract "Management of nutrient pollution has been recognised as a growing challenge in water resources management. To evaluate the pollution nature and its occurrence in time and space would be necessary for effective management control in changing environment. This was a main focus for developing a new model for this study. It was aimed to incorporate catchment and in-stream process dynamics into nutrient simulation at a river basin scale. The study proposed a novel approach to describe the nutrient generation and release from land surface to the river network system. The surface component takes account of various sources of nutrients and estimates nutrient generation from different land uses. The key nutrients are nitrogen (N) and phosphorus (P). By describing the transformation process of mineralization, immobilization, nitrification and denitrification, the rate of generation of mineralized N and nitrate are determined for different land use types. Similar process is considered for P, which takes account of adsorption and desorption and process of mineralization of P in soil and determines available P in transport. The key innovation in the research was in the mechanism of linking hydrology in relation to catchment nutrient release. The study proposed a flow capacity based nutrient export for accurate prediction of nutrient loads from catchments to the waterways. The seasonal variability and export through various pathways have been considered. First, the model the model was developed using sub-catchment based approach to test the various methods. Based on the outcome the grid-based model was developed. The applicability of the model was evaluated in two river basins, located in Australia and Japan, through calibration and validation. The model was also applied for climate change impact assessment in the Australian catchment. The model results show quite satisfactory performance. High intensity flood events were simulated for the Saru River, Japan. The Nash-Sutcliffe coefficient of model efficiency and r2 values are 0.83 and 0.9 for ORG-N, 0.75 and 0.90 for NO3-N, 0.82 and 0.87 for PO4-P, and 0.80 and 0.83 for PO4-P, respectively. Despite the limitations of observed records, the model could show a reasonable performance in simulating the long term seasonal variations in nutrient levels for the Latrobe River, Australia. The seasonality was strongly co-related with soil-moisture and climate condition, which was predicted well because of the process-based description. The key aspect of this research was enabling of hydro-climate based simulation for prediction of pollution level due to environmental change, which was demonstrated through climate change impact assessment. The effect of temperature rise on the catchment and in-stream process and its impact on NO3-N level was predicted for the Latrobe River. Based on the climate change projection for the region the scenarios were simulated, which revealed that the NO3-N levels are likely to increase by 18-42%. Developing percentile profiles of NO3-N for current and future condition, which are key indicators for water quality status, the study provides a stakeholder's decision making tool for adaptation measures.The integrated model provides a common platform for potential use in various watershed management issues including the regional application of the model for climate change application for soil and water management. The study suggests to incorporate hill slope soil erosion process in the sediment model, which could be useful for soil and land management. It is also suggested to incorporate river sediment and plant interaction modelling in river module so the hydro-ecological study is made possible. The river transport module was developed in such a way that it could also describe the transport process of other pollutants such as bacteria or heavy metals." @default.
• W3145954612 created "2021-04-13" @default.
• W3145954612 creator A5003014046 @default.
• W3145954612 date "2017-02-27" @default.
• W3145954612 modified "2023-09-27" @default.
• W3145954612 title "Process-based modelling of nutrient dynamics and transport at a river basin scale" @default.
• W3145954612 doi "https://doi.org/10.4225/03/58b4b04520db2" @default.
• W3145954612 hasPublicationYear "2017" @default.
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