Decision support system for optimal design and operation of ponds for watershed runoff management

With climate change and rapid land development the extremes in occurrence of floods and droughts are inevitable. More frequent floods are occurring with bigger losses and damage to properties and lives. On the other hand, agricultural droughts are also more frequent causing shortages of water for crop irrigation during dry seasons. Severe floods and droughts in any watershed or river basin under rapid development make water resources management a very important criteria for environmental and agriculture sustainability.The Upper Bernam River Basin (UBRB) Malaysia is the main source of irrigation water supply for a 20,000 ha rice granary. There is no dam reservoir for irrigation, but irrigation is by river diversion of the river irrigation system. Landuse has rapidly changed from 1984 until today. This result in shortage of irrigation water supply during low flow months whereas several floods incidents were observed lately. Therefore, it is very important to control floods during high flow months and also maintain high base flows so that enough water is available for irrigation during the low flow months. Understanding how the landuse change influences the river basin hydrology may enable planners to formulate policies to minimize the undesirable effects of land development. The objectives of this study were to assess the impacts of landuse changes on the watershed runoff in a humid tropical river basin and to develop a decision support system based on continuous hydrological simulation integrated with optimization algorithm to determine the optimal ponds locations, sizes and operations for floods control during high flow months and maintain river flow during low flow months. The need for spatial and temporal land-cover change detection over a larger scale makes satellite imagery the most cost effective, efficient and reliable source of data. The applicability of GIS makes it an important and efficient tool for spatial hydrologic modeling. In this study the integration of GIS and Soil and Water Assessment Tool (ARCSWAT) were used to evaluate the impacts of current and planed of landuse changes on stream flow quantity in the study area.The study was conducted using 27 years of records (1981-2007). Calibration and validation of the model were performed initially. Model performance was checked using both graphical and statistical indicators. During calibration, the annual, monthly and daily flow results were 0.82, 0.65, 0.68, 0.81, 0.62 and 0.58 for R2 and E, respectively and 1.00, 0.93, 0.89, 0.99, 0.92 and 0.88 respectively during validation. As for forecasting validation, R2 and E were 0.98, 0.86, 0.55, 0.91, 0.84 and 0.53 respectively. In general, the model showed good performance in simulating flow as well as forecasting. Five scenarios were performed to identify the individual effect of mixed landuse change on stream flow. The scenario results demonstrated that landuse changes were responsible for an increase in the annual flow depth of 8% to 39%, and 16% to 59% during high flow months. Landuse changes also caused a decrease of 3% to 32% during low flow months. Flow forecasting for the year 2020 using 30 forecasting cycles was found to be the optimal for the study area. The results showed that there was a decrease by 50% below the monthly irrigation water demand during low flow months, which emphasized the need to include structural best management practices (BMPs) such as ponds in the study area for future land development plan to mitigate the future landuse changes on flow quantity. A watershed runoff management decision support system model (WARM-DSS) was developed to maintain the future development rate with concern for mitigation of its impact to the environment and water quantity. The model showed generally good performance in simulating the runoff with reasonable statistical indicators (3.75, 4.46, 0.034, 0.99 and 0.98 for MAE, RMSE, U, R2 and E, respectively). For 2020 expected landuse changes in the study area, the model was applied with flood and drought return periods of 2, 5, 10, 20, 50 and 100 years. The results were twelve ponds with total maximum area of 2900 ha, maximum storage capacity of 1.45 x 108 m3 and specific daily operation were found to be the optimal to achieve the targeted flow during both high flow months and low flow months. The reduction in floods were 20%, 59%, 79%, 140%, 206% and 304% for the return periods of 2, 5, 10, 20, 50 and 100, respectively. While the increases in flow for the drought return periods were 19%, 40%, 47%, 43%, 37% and 30%.The developed model in this study has high potentiality to be applied for any future development plans to predict the hydrological impacts, to mitigate the risk of floods, and to avoid the shortage of irrigation water. The model also works as a framework for science-based decision making tool when formulating landuse policies. It can be a practical tool for hydrologists, engineers and town and country planners. The irrigation engineers can use this tool during the planning for irrigation water supply and determination of future ponds location and size to increase the availability of the irrigation water and temporary storage of flood water.

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