Abstract:Human activities have modified the environment over the years. Urbanization, agriculture lumbering, mining and other land uses have substantially altered the Earth's surface. Land use and the resultant change in land cover have significant effects on ecological, environmental and hydrologic systems and processes. An understanding of past and present land-cover change, together with an analysis of potential future change, is necessary for proper management; thus, the need for models. Hydrologic models are prima… Show more
“…Land use change impacts various areas including hydrology, socio-economics, ecological, and environmental [1]. This is a triggering factor that leads to a change in the flow pattern due to the temporal variation of the discharge distribution [2].…”
Land use changes are a key factor for altering hydrological response, and understanding its impacts can help to develop a sustainable and pragmatic strategy in order to preserve a watershed. The objective of this research is to estimate the impact of land use changes on Bagmati river discharge and sediment yield at the Khokana gauging station of the Kathmandu valley outlet. This study analyzes the impact of land use changes from the year 2000 to 2010 using a semi-distributed hydrological, Soil Water Assessment Tool (SWAT) model. The Load Estimator (LOADEST) simulates sediment loads on limited available sediment data. Sensitivity analysis is performed using the ParaSole (Parameter Solution) method within SWAT Calibration and Uncertainty Procedure (SWAT-CUP), which shows that Linear parameters for calculating the maximum amount of sediment that can be re-entrained during channel sediment routing is a most sensitive parameter that affect the hydrological response of the watershed. Monthly discharge and sediment data from 1995 to 2002 are used for calibration and remaining monthly discharge and sediment data from 2003 to 2010 are used for validation. Four statistical parameters including the Coefficient of Determination (R 2 ), Nash-Sutcliffe Efficiency (NSE), RMSE-observations' standard deviation ratio (RSR), and Percentage Bias (PBIAS) are estimated in order to evaluate the model performance. The results show a very good agreement between monthly measured and simulated discharge data as indicated by R 2 = 0.88, NSE = 0.90, RSR = 0.34, and PBIAS = 0.03. The model shows nearly the same performance also with sediment data. The land use change data shows about a 6% increase in built-up areas from the years 2000 to 2010, whereas the remaining areas such as Forest, Shrub, Grass, Agriculture, Open Field, and Rivers/Lakes are decreased. The surface runoff contribution to stream flow and sediment yields are increased by 27% and 5% respectively. In the contrary, lateral flow contribution to stream flow and groundwater contribution to stream flow are decreased by 25% and 21%, respectively.
“…Land use change impacts various areas including hydrology, socio-economics, ecological, and environmental [1]. This is a triggering factor that leads to a change in the flow pattern due to the temporal variation of the discharge distribution [2].…”
Land use changes are a key factor for altering hydrological response, and understanding its impacts can help to develop a sustainable and pragmatic strategy in order to preserve a watershed. The objective of this research is to estimate the impact of land use changes on Bagmati river discharge and sediment yield at the Khokana gauging station of the Kathmandu valley outlet. This study analyzes the impact of land use changes from the year 2000 to 2010 using a semi-distributed hydrological, Soil Water Assessment Tool (SWAT) model. The Load Estimator (LOADEST) simulates sediment loads on limited available sediment data. Sensitivity analysis is performed using the ParaSole (Parameter Solution) method within SWAT Calibration and Uncertainty Procedure (SWAT-CUP), which shows that Linear parameters for calculating the maximum amount of sediment that can be re-entrained during channel sediment routing is a most sensitive parameter that affect the hydrological response of the watershed. Monthly discharge and sediment data from 1995 to 2002 are used for calibration and remaining monthly discharge and sediment data from 2003 to 2010 are used for validation. Four statistical parameters including the Coefficient of Determination (R 2 ), Nash-Sutcliffe Efficiency (NSE), RMSE-observations' standard deviation ratio (RSR), and Percentage Bias (PBIAS) are estimated in order to evaluate the model performance. The results show a very good agreement between monthly measured and simulated discharge data as indicated by R 2 = 0.88, NSE = 0.90, RSR = 0.34, and PBIAS = 0.03. The model shows nearly the same performance also with sediment data. The land use change data shows about a 6% increase in built-up areas from the years 2000 to 2010, whereas the remaining areas such as Forest, Shrub, Grass, Agriculture, Open Field, and Rivers/Lakes are decreased. The surface runoff contribution to stream flow and sediment yields are increased by 27% and 5% respectively. In the contrary, lateral flow contribution to stream flow and groundwater contribution to stream flow are decreased by 25% and 21%, respectively.
“…This was employed to confirm the relationship between simulated or predicted values and observed values [1] and to verify the robustness of the model [37]. Four statistical measures were employed.…”
Section: Evaluation Of Model Performancementioning
confidence: 99%
“…Land use change can lead to undesirable effects on ecosystems [1]. Land use and land cover changes are significant causes of water, soil and air pollution [2], which negatively impacts the health of rivers within catchments.…”
Section: Introductionmentioning
confidence: 99%
“…Land use and land cover changes are significant causes of water, soil and air pollution [2], which negatively impacts the health of rivers within catchments. The effects of land use changes can be grouped into hydrologic, socio-economic, ecological and environmental [1]. Most river basins have undergone massive change over the past years due to various land use activities [3].…”
The Soil and Water Assessment Tool (SWAT) is a versatile model presently used worldwide to evaluate water quality and hydrological concerns under varying land use and environmental conditions. In this study, SWAT was used to simulate streamflow and to estimate sediment yield and nutrients loss from the Murchison Bay catchment as a result of land use changes. The SWAT model was calibrated and validated for streamflow for extended periods. The Sequential Uncertainty Fitting (SUFI-2) global sensitivity method within SWAT Calibration and Uncertainty Procedures (SWAT-CUP) was used to identify the most sensitive streamflow parameters. The model satisfactorily simulated stream discharge from the catchment. The model performance was determined with different statistical methods. The results showed a satisfactory model streamflow simulation performance. The results of runoff and average upland sediment yield estimated from the catchment showed that, both have increased over the period of study. The increasing rate of runoff can lead to severe and frequent flooding, lower water quality and reduce crop yield in the catchment. Therefore, comprehensive water management steps should be taken to reduce surface runoff in the catchment. This is the first time the SWAT model has been used in the Murchison Bay catchment. The results showed that, if all uncertainties are minimised, a well calibrated SWAT model can generate reasonable hydrologic simulation results in relation to land use, which is useful to water and environmental resources managers and policy and decision makers.
“…Detection of land use and land cover changes require satellite imageries of two different years as a minimum (Brar, 2013;Ndulue et al, 2015). In that regard, post classification comparison technique was used where independently classified images were compared to determine the changes.…”
Section: Land Use and Land Cover Change Detection And Analysismentioning
The Murchison Bay catchment in the northern shoreline of Lake Victoria basin is a high valued ecosystem because of the numerous human-related activities it supports in Uganda. The catchment has undergone tremendous human-induced land use/cover changes, which have not been quantified. This study aimed at quantifying the land use/cover changes as well as the rate at which these changes occurred over the last three decades in the catchment. This was achieved using remote sensing techniques and Geographic Information System (GIS) to analyse and contextualize the changes. To that effect, images of Landsat satellites MSS, TM, ETM+ and OLI were interpreted using supervised image classification technique to determine the land use/land cover changes from 1984 to 2015. The obtained results indicated that the catchment has undergone huge land use and land cover transformations over the last three decades attributable to rapid population growth and urbanization. The prevailing changes in footprint between 1984 and 2015 were expansions of built-up land (20.58% to 49.59%) and open water bodies (not detected in 1984 to 1.74%), and decreases in the following sectors: agricultural lands (from 43.88% to 26.10%), forestland (from 23.78% to 17.49%), and wetlands (from 11.76% to 5.08%). The changes pose a threat to the environment and water quality of the Murchison Bay and consequently increases National Water and Sewerage Corporation water treatment costs. Therefore, there is the need to take critical and practical measures to regulate and police land use, water use rights and conserve the environment especially wetlands.
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