Khairi Khalid

Discharge Assessment by Using Integrated Hydrologic Model for Environmental Technology Development

River water quality degradation is one of the most significant environmental challenges. Over the years, many models have been used to investigate the current state of Malaysian rivers and its effects to the environment. River discharge is an important factor in water quality investigation. An integrative computational model, GIS coupled with SWAT model was being used to predict river discharge of this research. The simulation results in the period 1999 to 2010 represented fluctuation of discharge relatively well with both R2 and NSI values were above 0.6. The results proved that the development of integrative GIS technology coupled with SWAT model is a good tool for environmental technology development in terms of investigating the current state of Langat river water quality as well as the capability of simulating the river discharge in the river basin. This shows that GIS-SWAT interface can be a reliable tool for water quality modeling in Malaysia in the future and further development on the software technology is a benefit for the water resources and environmental studies.

An Assessment of Water Demand in Malaysia Using Water Evaluation and Planning System

Water supply and demand is one of the hot topics discussed in the community today. Higher growth rate of the population has drawn heavily on the natural resource base in Malaysia. Trend of supply and demand in the Langat catchment, water availability assessment and water storage capacity to supply and demand were investigated using a new accounting concept and analytical approach, Water Evaluation and Planning (WEAP) system. The assessment model is computed based on three scenarios—Scenario 1: Higher Population Growth, Scenario 2: Water Year Method and Scenario 3: Extended Dry Climate Sequence. The study found that Langat catchment is relatively sensitive to the growth of demands, suggesting that slight changes in population growth will alter the present water availability. Furthermore, the populations increase to 7 % with the increment of climate variation of the current condition, thus exposing the study area with water scarcity problem.

The Development and Application of Malaysian Soil Taxonomy in SWAT Watershed Model

The concept of watershed modeling is embedded in the interrelationships of geo-spatial data and hydro-meteorological data and represented through mathematical abstractions. The behavior of each process is controlled by its own characteristics as well as by its interaction with other processes active in the catchment. The hydrological models vary from empirical models to stochastic models of various kinds and finally to the more recent distributed models. In recent years, distributed watershed models have been increasingly used to implement alternative management strategies in the areas of water resource allocation, flood control, impact assessments for land use and climate change, and pollution control. Many of these models share a common base in their endeavor to incorporate the heterogeneity of the watershed and the spatial distribution of topography, vegetation, land use, soil characteristics, and rainfall. This study attempts to provide a framework of hydrological assessment using a Malaysian soil data as a soil characteristics input in Soil Water Assessment Tool (SWAT) model in its place of using the USDA Soil Taxonomy database. This chapter reports a SWAT simulation output using a Malaysian soil data from the SWAT input file. It was found that the SWAT model can be successfully applied for hydrological evaluation of the Langat River basin, Malaysia. To the Langat River basin, SCS runoff curve number (CN), base flow alpha factor (ALPHA_BF), and groundwater delay (GW_Delay) were found to be the most sensitive input parameters. The works attempting a hydrological simulation using a local soil data directly from Malaysian soil database are still in the programming stages. A same methodology is suggested to be practiced in other open source hydrological models.

Langat River Basin Hydrologic Model Using Integrated GIS and ArcSWAT Interface

Increase of socio-economic activities in the urban area has led to many water scarcity problems. Thus, the need to investigate the current state of Langat river is increasing. An integrative computational model, ArcSWAT with GIS interface was being used to predict daily stream flow of the study area. Historical data from years 1999 to 2010 was used for modeling purposes. The results reviewed that the calibrated model is able to simulate the flow for the river basin successfully with the R2 = 0.64 and Nash-Sutcliffe Index, NSI= 0.64. The results proved that GIS technology and ArcSWAT model is capable for simulating the stream flow in the Langat river basin and can be applied for other river basins. This shows that SWAT can be a tool for a hydrologic modeling in Malaysia in the future.

Application on One-at-a-T ime Sensitivity Analysis of Semi-Distributed Hydrological Model in Tropical Watershed

Abstrac t—A soil and water assessment tool (SWAT) model has been employed for the Langat River basin, Malaysia to predict stream flows. The basin was divided into 27 sub basins comprising 193 hydrological response units. Monthly calibration and validation were performed using the measured discharge data of the Kajang station. One-at-a-time sensitivity analysis using Sequential Uncertainty Fitting (SUFI-2) algorithms was performed to examine the critical input variables of the study area. It was found that the SWAT model can be successfully applied for hydrological evaluation of the basin and the SCS runoff curve number, base flow alpha factor and groundwater delay were found to be the most sensitive parameters. The next step should be conducting a 30 years continuous hydrological modeling. It is needed to analyze the water balance and the hydrological trends of the basin due to the basin experienced major land used changes since 1980 for urbanization activities.

Simulation of upper Kuantan River basin streamflow using SWAT model

This paper examines the capabilities of Soil and Water Assessment Tools (SWAT) in simulating streamflow in a tropical watershed - upper Kuantan river basin. Two statistical metrics were used for model evaluation; i) coefficient of determination (R2) and ii) Nash-Sutcliffe efficiency index (NSI). The calibration result shows that there is a good agreement between the observed and simulated monthly streamflow with R2=0.84 and NSI=0.82. For validation the result is acceptable which the value of R2=0.59 and NSI=0.57. The results suggest that SWAT model is able to simulate the hydrologic characteristics of the tropical watershed well.

Water Quality Measures Using QUAL2E: A Study on RoL Project at Upper Klang River

The degradation of the water quality and ecosystem are vulnerable to urbanization processes and activities. Increase numbers of population and industrial activities continue to increase a consumption of water and followed by the increasing of waste discharges to the natural waterways. These issues are very critical mostly in the developing countries and not excluded to the upper part of the Klang River basin. The current Water Quality Index (WQI) at both inlet and outlet of the study area is falling under Class III. The mitigation processes are needed to improve the index value before further degradation of the river downstream Furthermore the stream flows that passage the city centre of Kuala Lumpur needed to be maintained in order to boost economic sector growth like tourism and other business activities. The Department of Irrigation and Drainage, Government of Malaysia is currently initiating the River of Life (RoL) rehabilitation program to mitigate the water quality and quantity of Klang River. This paper presents the current water quality study of the upper part of Klang River, which consists of six water quality parameter. This study involved an in situ works and followed by a laboratory investigation. Data analysis was carried out using QUAL2E software and proposes mitigation measures which to satisfy the objective of the RoL program. The study area was exposed to a high concentration of Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD) and Ammoniacal Nitrogen (AN) which contributed to the pollution of the river. At high numbers of total coliform also redound to the unsafe and unhealthy for portable water. In QUAL2E, a total maximum daily load (TMDL) analysis was calculated from a stream outfall and Indah Water Konsortium (IWK) outlet and finally the prediction load was carried out in order to be conformed for Class II. The study shows that the QUAL2E software was performed well in simulating the water quality parameter and able to incorporate in the rehabilitation program at the study area in order to conserve the natural qualities of the environment.

Calibration Assessment of the Distributed Hydrologic Model Using SWAT-CUP

The idea of distributed hydrologic modeling is embedded in the interrelationships of geospatial and hydro-meteorological data and represented by mathematical abstractions. The behavior of each process is controlled by its attributes as well as by its interaction with other processes active in the catchment. Model calibration is the process of estimating model parameters by comparing model predictions to a given set of assumed conditions with observed data under the same circumstances. The Soil Water Assessment Tool-Calibration Uncertainties Program (SWAT-CUP) is a computer model for calibrations of SWAT model is utilized in the study for the simulation of the daily streamflow. For Langat River Basin, the coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE) and PBIAS for the calibration period were found as 0.75, 0.70, and 0.15, respectively, which confirms the satisfactory performance of the model.

Sediment Load Distribution Analysis of Langat River Basin, Selangor

Rapid development in urban areas and uncontrolled deforestation are among the factors that contribute to the pollution of rivers through the process of erosion and sedimentation resulting from such activities. Stormwater runoff will flash out all the eroded soil and sediments to the downstream area, and sedimentation will occur in rivers and lead to other environmental problem. This research aims to evaluate the formation of suspended sediment and bedload sediment at the upper part of Langat River Basin, one of the most important river water catchments in Peninsular Malaysia. Sediment samples were collected using sediment grabber and analyzed in the laboratory. Three parameters were quantified throughout this study, namely concentration of suspended sediment (mg/L), river discharge values (m3/s), and grain size distribution (g). The result showed that the estimated mean sediment load flow into Langat River is 5267.73 ton/km2/year. Distributions of sediment grain size in upstream of Langat River consist of very rough sediment grains, showing a possibility of logging and deforestation activities within the catchment area. Hence, a long-term preventive measure such as environmental policies regulating land use development and management practices should be formulated and implemented to fix the sedimentation problems in Langat River Basin.

Optimizing Network Architecture of Artificial Neural Networks (ANNs) in Rainfall-Runoff Modeling

Artificial neural networks (ANNs) are general-purpose techniques that can be used for nonlinear data-driven rainfall-runoff modeling. The fundamental issue to build a worthwhile model by means of ANNs is to recognize their structural features and the difficulties related to their construction. Without a doubt, the magnitude and quality of data, the type of noise, and the mathematical properties of the algorithm for estimating the usual large number of parameters are critical for the simplification performances of ANNs. There are many avoiding overfitting techniques in improving the generalization of ANNs. This paper was reported the optimization of the hidden neurons of nonlinear autoregressive with external inputs (NARX) neural network of the tropical river basin. For the Langat River Basin, eight or ten hidden neurons were found to be the most optimal for the ANN model. The next steps should be conducting the optimum numbers of inputs delay to be used for the model since the precise combination of the network architectures features will improve the accuracy level of ANN model.