Citation
Mohamed, Mustafa Yousif
(2006)
A Methodology for Assessing The Impact of Landuse Changes on Watershed Runoff.
Doctoral thesis, Universiti Putra Malaysia.
Abstract
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.
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