A Methodology for Assessing The Impact of Landuse Changes on Watershed Runoff

With rapid land development and limited water resources, good quality water becomes an important commodity that every economic sector is competing for. Landuse changes in a watershed can affect the watershed hydrology in various ways. Some types of land development can be associated with increased impervious area causing increase in surface runoff and decrease in ground water recharge. Both of these processes can have large-scale ramifications through time. Increased runoff results in higher flows during rainfall events, which in turn increases the number of times that a river floods the adjacent land areas. Likewise, this increase in runoff and channel flows can drastically increase the erosion of river channel beds and banks, potentially destabilizing bridges or local structures. On the other hand the groundwater recharge decreased due to the increase in the impervious surfaces and decrease in the soil infiltration rate. This may leads to rescission in the river base flow especially during the dry season. Since rainfed agriculture in Malaysia may not have reservoirs for irrigation water supply, it is very important to maintain high base flows so that enough water is available for irrigation during the dry season. 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 main objective of this study was to develop a methodology to assess the impacts of landuse changes on the watershed runoff. 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 Satellite images and GIs were integrated with a developed spatial hydrological model to evaluate the impacts of land development in the Upper Bernam River Basin of Malaysia. The Bernam River is the main source of irrigation water for a rice granary area. A methodology to assess the hydrological impacts due to landuse modifications was developed using a physically based hydrological model and a mathematical model. While conceptual or physically based models are important in understanding hydrological processes, there are many practical situations where the main concern is with making accurate predictions at specific locations. The wellestablished HEC-1 model was calibrated and used to simulate the runoff process. Runoff hydrographs were generated for wet and dry seasons using lumped and distributed modeling concepts. In the distributed modeling approach, hydrographs fiom each sub basin was routed to the outlet point using the Muskingum routing method. Artificial Neural Network (ANN) model was developed because it has the ability to extract the non-linear relation between the inputs and outputs of a process, without the physics being explicitly provided to them, this makes the simulation process more applicable. The models were tested and validated using data collected fiom the study area. The models performances were checked using both graphical and statistical analysis. Mean absolute errors (MAE), mean square error (MSE), root mean square error (RMSE), Theil's coefficient, coefficient of determination (R~),coefficient of efficiency (E), T-test and regression analysis were -use9 as e va uation criteria for model performance. The models show good performance in simulating the runoff process. Results from the hydrological model gave 0.79, I .35, 0.22, 0.91 and 0.67 for MAE, MSE, U, R~ and E, respectively. The weighted curve number (CN) was found to have increased by 2% in year 2001 compared to 1989, and had caused an increase in peak flow by 7%. The effect of change in CN is more on the rising limb of the hydrograph and peak runoff than on the falling limb. As CN increases the rising limb shifted backwards. For the ANN model, it was found that correlation coefficients between simulated and observed flow are 0.94 and 0.89 for the training and testing phases, respectively. The model outputs were within the confidence level of 95 %, and most of the scatter output values were within 15 % deviation bands. The statistical evaluation during the training phase gave the values of 0.001,4.77,0.06 and 0.87 for MAE, MSE, U and E, respectively, and these values were found to be 17.6, 5.6, 0.1 1, and 0.58 for the testing phase, respectively. For both models applications, it was found that the percentage change in runoff due to landuse change is constant for different landuse, irrespective of the rainfall pattern and time of occurrence. The models were then applied to simulate the runoff from future land development for the year 2020 and from different landuse scenarios. Predictions from the hydrological model show that an increase in weighted CN by 7 % and 13 % for the wet and dry seasons, respectively, will cause an increase in flow volume by 53 % and 62 % and increase in peak flow by 80 % and 76 % for the wet and dry seasons, respectively. This methodology can be applied for any future development plans to predict the hydrological impacts to mitigate the risk of floods occurrence and avoid the shortage of irrigation water. The methodology can be used as a 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 cultivable areas based on the availability of the irrigation water due to the land development.

Text FK_2006_18.pdf Download (1MB)

Actions (login required)

View Item