Supiah Shamsudin

Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature

Climate change is believed to have significant impacts on the water basin and region, such as in a runoff and hydrological system. However, impact studies on the water basin and region are difficult, since general circulation models (GCMs), which are widely used to simulate future climate scenarios, do not provide reliable hours of daily series rainfall and temperature for hydrological modeling. There is a technique named as “downscaling techniques”, which can derive reliable hour of daily series rainfall and temperature due to climate scenarios from the GCMs output. In this study, statistical downscaling models are used to generate the possible future values of local meteorological variables such as rainfall and temperature in the selected stations in Peninsular of Malaysia. The models are: (1) statistical downscaling model (SDSM) that utilized the regression models and stochastic weather generators and (2) Long Ashton research station weather generator (LARS-WG) that only utilized the stochastic weather generators. The LARS-WG and SDSM models obviously are feasible methods to be used as tools in quantifying effects of climate change condition in a local scale. SDSM yields a better performance compared to LARS-WG, except SDSM is slightly underestimated for the wet and dry spell lengths. Although both models do not provide identical results, the time series generated by both methods indicate a general increasing trend in the mean daily temperature values. Meanwhile, the trend of the daily rainfall is not similar to each other, with SDSM giving a relatively higher change of annual rainfall compared to LARS-WG.

Assessment of groundwater potential zones in an arid region based on catastrophe theory

Evaluation of groundwater potential is a multi-criteria and multi-level comprehensive assessment system that needs judgment of decision makers in making decision. To avoid subjectivity or the preference of decision makers in the assessment, catastrophe theory based evaluation method is proposed in this study which calculates the importance of one criterion over other by its inner mechanism and thus, avoid subjectivity. The proposed method is applied for the assessment of groundwater potential zones in the arid region of lower Balochistan province of Pakistan. The groundwater is considered as a system with five sub-systems namely, geology, soil, drainage density, slope and rainfall. Seventeen sub-system indicators of groundwater potential are selected for modeling groundwater potential zone. The catastrophe theory is applied to derive the relative weights of indicators in predicting groundwater potential. Thematic maps of sub-systems are integrated within a geographical information system and the groundwater potential zones of the integrated layer are calculated by using the weights of indicators. The results are verified by existing number of tube wells operating in the study area. It has been found that the number of tube wells is more in the area where the groundwater potential is high. The study reveals that catastrophe theory is suitable for assessing groundwater potential.

Spatial assessment of groundwater over-exploitation in northwestern districts of Bangladesh

Groundwater demand in northwestern districts of Bangladesh is increasing rapidly with the growth of population and the expansion of irrigated agriculture. Development and management of groundwater resources are essential to supply the growing population with sufficient water for economic development as well as for the sustainable environment of the region. In the present study, groundwater recharge-abstraction balance method has been used for the spatial assessment of groundwater development potential. The abstraction of groundwater is estimated from irrigation and domestic water demands in the study area. The net recharge calculated from groundwater table fluctuation data, whereas the abstraction of groundwater is estimated from irrigation and domestic water demands in the study area. The study shows that out of twenty-six sub-districts, groundwater exploitation has reached to a critical condition in fourteen subdistricts. Development of surface water resources and water conservation are essential to reduce the stress on groundwater exploitation.

Optimum combination of pond volume and outlet capacity of a stormwater detention pond using particle swarm optimization

Detention ponds are best management practices designed for the treatment and control of urban stormwater. Their design objectives are mainly to control the quantity and quality of urban stormwater at the minimum cost. However, tradeoff exists between these objectives and this call for optimization. Long term hourly rainfall data were analyzed and the rainfall characteristics were obtained. Analytical Probabilistic Models (APM) were employed and the model parameters were derived from the closest stations to the study areas. The APM parameters, along with catchment parameters, were used to develop optimal combination of pond volume and outflow that yield the minimum cost using the APM and Particle Swarm Optimization (PSO). Comparison of the PSO with APM shows that the PSO result is more accurate as it does not need discretization of outlet size. The PSO model was also found to be more robust, computationally cheaper and faster to implement.

Uncertainty Analysis of HEC-HMS Model Parameters Using Monte Carlo Simulation

Abstract Rainfall-runoff modelling was carried out to determine Hydrologic Engineering Centers Hydrologic Modeling System model parameters for catchments in Johor, Malaysia. Uncertainty analysis, using Monte Carlo simulation, with a sample trial of 5,000 is then applied to the model parameters based on uniformly distributed samples. Sixteen sub-catchments drawn from Sungai Johor, Sungai Tebrau, Sungai Skudai and Sungai Segamat were selected. The rainfall-runoff modelling gives a mean correlation coefficient of 0.9038 and mean efficiency index of 81.53%, indicating a good prediction. Results from the uncertainty analysis give values in the range of 1.25–14.99mm for initial loss, with a mean of 8.09 mm. The constant loss rate takes a range of 7.98–299.87 mm/h with mean value of 153.55 mm/h. The range of values for imperviousness is between of 0.017% and 44.99% with mean value of 22.47%. Simulation result for time of concentration is in the range of 0.44–14.53h with mean value of 7.62h. The storage coefficient takes values from 0.22h to 5.16h with mean value of 2.71h. The outcome of this work quantifies the uncertainty associated with these parameters and the result can be used to narrow down the range at which initial estimates are made during future modelling processes.

Tropical stormwater nutrient degradation using nano TiO2 in photocatalytic reactor detention pond

The photo-degradation of nutrients in stormwater in photocatalytic reactor wet detention pond using nano titanium dioxide (TiO2) in concrete was investigated in a scale model as a new stormwater treatment method. Degradation of phosphate and nitrate in the presence of nano-TiO2 under natural ultra violet (UV) from tropical sunlight was monitored for 3 weeks compared with normal ponds. Two types of cement, including ordinary Portland and white cement mixed with TiO2 nano powder, were used as a thin cover to surround the body of the pond. Experiments with and without the catalyst were carried out for comparison and control. Average Anatase diameter of 25 nm and Rutile 100 nm nano particles were applied at three different mixtures of 3, 10 and 30% weight. The amounts of algae available orthophosphate and nitrate, which cause eutrophication in the ponds, were measured during the tests. Results revealed that the utilization of 3% up to 30% weight nano-TiO2 can improve stormwater outflow quality by up to 25% after 48 h and 57% after 3 weeks compared with the control sample in normal conditions with average nutrient (phosphate and nitrate) removal of 4% after 48 h and 10% after 3 weeks.

Sediment phosphorus loadings uncertainty using fuzzy-logic in detention pond at Southern Malaysia

This study vitalized the uncertainty and fuzzy rules consideration in the detention pond sediment phosphorus loadings estimation .Sediment phosphorus is pollutant of primary concern as it may result in adverse environmental effect of the hydrological systems.Detention pond establishmentbecome a practical control measures to improve the downstream water quality.The purpose of this study is to estimate the sediment phosphorus loadingsuncertainty for the detention pond at UniversitiTeknologi Malaysia (UTM) using Fuzzy Logic MUSLE-IHACRES model.The IHACRES model was used to predict the streamflow into the detention pond that later be used in the MUSLE model.The streamflow modelling using IHACRES model showed that the largest bias was -1.2157 mm/day and the smallest bias is -0.0265 mm/day. The highest r2 value was 0.9204 while the lowest was 0.7813. Both statistics showed that the model was able to perform well. The resultsfrom MUSLE-IHACRES model showed that the maximum value ofsediment yield was 254.88 tons/ha /yr and minimum value was 84.40 tons/ha/yr.This study also forecast accumulated sediment loads and depth using MUSLE-IHACRES over 10-100 years. The highestfrequencyor most likely range of sediment phosphorus wasless than 350 ton/year (257tons/ha/year). The average phosphorus content in sediment obtained was 34.0 mg/g and the sediment phosphorus loadings estimated using fuzzy logic was 28.72ton/year.The sediment phosphorus distribution investigated using Fuzzy Logic was presented. Suggested control measures need to be established as the sediment deposition is degrading the pondand approaching the Eutrophic Status.

Optimization of active to permanent pool volumes ratio for wet ponds in tropical catchments

Urban stormwater is the second major urban flow of concern to the drainage engineer and the second largest source of impairment to lakes and estuaries. Safe and efficient removal of urban stormwater is important to maintain public health and safety and to protect the receiving water environment. Detention ponds are stormwater best management practices used for the treatment and control of urban stormwater. Wet detention ponds have two zones: the active and the permanent pool volumes. In this research, long term hourly rainfall and case study catchments data were collected and the effect of varying the ratio of active to permanent pool volumes investigated using analytical probabilistic models. It was observed that the pollution control performance of wet ponds increase with increase in the ratio reaching a peak value of 82% at a ratio of 0.6 and declines. For optimum benefit, design of the wet ponds in tropical catchments should target this point where the pollution control is highest although other design considerations might also need to be considered.

Fitting the distributions of wet spell duration with probability models

The long term rainfall characteristics of an area are best understood if the statistical distributions describing the various rainfall parameters have been modeled. The distributions can be used in applications that need rainfall information such as stormwater management, agriculture and many others. In this paper the suitability of four different types statistical distributions in modeling wet spell duration in Peninsular Malaysia have been tested. Hourly rainfall data, of 10 to 22 years period, from 12 representative stations spread across the Peninsular were collected. Four statistical distributions, namely, Generalized pareto, Exponential, Gamma and Beta distributions were proposed to model the distribution of the wet spell. Kolmogorov-Sminov, Anderson-Darling and Chi-squared goodness-of-fit tests were used to evaluate the model fitness. Based on 6hr storm separation time; the mean rainfall frequency ranges from 115 to 198 events per annum. Statistics of duration shows that Kuala-Lumpur receives the lowest mean duration of 4.08hr per event while Khota-Bahru receives the highest value of 10.47hr. Goodness-of-fit indicates that Generalized pareto, exponential and Gamma distributions can be used at 5% level of significance. However, Generalized pareto is found to fit better than the remaining distributions.