Development of Multiple Linear Regression Models for Predicting the Stormwater Quality of Urban Sub-Watersheds (original) (raw)
Stormwater Runoff Quality Characterization at Tropical Urban Catchment
International journal of Environmental Science and Technology
Due to differences in rainfall regimes and management practices, tropical urban catchments are expected to behave differently from temperate catchments in terms of pollutant sources and their transport mechanism. Storm Water Management Model (SWMM) was applied to simulate runoff quantity (peakflow and runoff depth) and quality (total suspended solids and total phosphorous) in residential, commercial and industrial catchments. For each catchment, the model was calibrated using 8–10 storm events and validated using seven new events. The model performance was evaluated based on the relative error, normalized objective function, Nash–Sutcliffe coefficient and 1:1 plots between the simulated and observed values. The calibration and validation results showed good agreement between simulated and measured data. Application of Storm Water Management Model for predicting runoff quantity has been improved by taking into account catchment’s antecedent moisture condition. The impervious depressi...
Modeling the Influence of Meteorological Variables on Runoff in a Tropical Watershed
Civil Engineering Journal, 2020
Proper understanding of the historical annual runoff characteristics with respect to climate impacts is essential for effective planning as well as the management of water resources in river basins. In this study, the climate-flood model which connects the runoff and climate was developed for Adada River Nigeria. Thirty years records of climatic and runoff data were used to develop a multiple linear regression model. The coefficient of determination was evaluated for the developed model, and the hypothesis was equally tested with the aid of t-test and one-way analysis of variance. The multiple regression analysis indicated that the climate-flood model was statistically significant (p˂0.05) in predicting the annual runoff. The results also show that the climatic variables accounted for 66.1% of runoff variation due to the undisturbed gauging basin of the river. The wind speed and the duration of sunlight were not statistically significant predictors of runoff in the area. These results...
DEVELOPMENT OF A REGRESSION MODEL FOR RUNOFF OF SURMA RIVER BY MULTIPLE REGRESSION ANALYSIS
Proceedings of the 5th International Conference on Advances in Civil Engineering (ICACE 2020) 4-6 March 2021, CUET, Chattogram-4349, Bangladesh Imam, Rahman and Pal (eds.), 2021
The Surma River is one of the major rivers of the Surma-Meghna River system in Bangladesh. In this study, eleven hydrologic/meteorological parameters-rainfall, average temperature, relative humidity, actual vapor pressure, evaporation, solar radiation, actual sunshine hour, cloud cover, SOI, El Nino index, wind speed are selected for developing a runoff model for Surma River by a statistical approach. Data are collected from BWDB, BMD, BARC, and NOAA. From our study, it is found that the runoff of this study area is sensitive to only three independent variables e.g., rainfall, actual vapor pressure, and actual sunshine hour. The other eight selected variables are omitted from the equation as they are poorly correlated showing insignificant correlation values. From the correlation between the dependent variable and independent variable, the ones having the lowest correlation have been omitted in this case Evaporation, SOI, El-Nino Index, and Wind Speed were found to be the most poorly correlated with r values-0.048,-0.027, 0.093 and-0.026 respectively. Then, Average Temperature, Solar radiation, Cloud Cover are omitted depending on the correlation between independentindependent variables, In the next, regression analysis is done on the rest of the variables. Depending on Pvalue, R 2, and adjusted R 2 value, three independent variables e.g., rainfall, actual vapor pressure, and actual sunshine hour are found sensitive in the study. Finally, a linear and a nonlinear multiple regression equation is developed using solveradd-ins of Microsoft excel. The runoff model is calibrated for the year range of 2009 to 2010 at Kanaighat station. The calibrated model shows that the monsoon season gives a shift of the observed runoff than the regression runoff whereas pre-monsoon and late monsoon are well matched. Calibration is followed by validation for the same station for the year 2010 to 2011. Graphical plot and RMSD value show that the non-linear runoff equation gives a better prediction than the linear one. The runoff model developed in this study can be used for determining the runoff of the Surma River. While runoff estimation through numerical modeling is highly complex, time-consuming, and sometimes difficult to visualize, this kind of regression model is very simple, quick, easy to develop, and easily understandable as well. Besides, the predicted values for different hydrologic/meteorological variables like relative humidity, actual vapor pressure, evaporation, solar radiation, actual sunshine hour, cloud cover, SOI, El Nino index, wind speed, etc. are easily available for different RCP ensembles. Hence, this runoff model can be easily used for determining future runoff of the Surma River as well.
Stormwater quality modeling in urbanized areas
E3S Web of Conferences, 2018
Stormwater quality modeling with the use of Stormwater Management Model (SWMM) is presented. The model has been calibrated on the basis of measurements of flow and stormwater quality performed on a real catchment in Łódź, Poland. Calibrated model parameters and the correlations between the quality indexes are given. This will allow application of the model to other urban catchments equipped with storm drainage systems.
Quality Assessment of Rain and Storm Water Runoff for Nairobi City Industrial and Sub-Urban Areas
Nairobi like most cities in the world is faced with water shortages because all the surface water sources have been tapped and the ground water overexploited, yet the water demand continues to rise as the population grows. The city must therefore seek alternative means of water supply. One of the promising sources is rainwater harvesting, which has successfully been adopted to supply water in many other cities. However, there is a concern about the quality of the rainwater falling through a heavily industrialized city atmosphere and flowing over polluted grounds. There is need to determine the quality of rainwater and the resulting storm water so as to make a decision on the best application or treatment of the water. The purpose of the study was therefore to determine the physical and chemical properties of rain and storm water runoff in suburban and industrial settings in Nairobi. Two sites were indentified namely Upper Kabete Campus (heavily vegetated agricultural suburb), and Jomo Kenyatta International Airport (heavily industrialized area of the city) to assess the water quality of rainwater received and storm water runoff exiting to drains. Water samples were collected directly from falling rain and also from runoff water at the sites for laboratory analysis. The samples were analyzed for water quality parameters namely pH, alkalinity, hardness, total dissolved solids, chlorides, calcium, nitrates, iron. The results from the two sites were compared statistically. It was found that the quality of rain water does not differ significantly in physiochemical parameters at 0.05 significant levels between the suburban and industrial setting. The falling rainwater was only slightly above the WHO requirements and required only modest treatment whole the storm water was significantly above the WHO limits and either need treatment or may be used for non potable application. Results of the study are useful in addressing challenges of water quality partly by encouraging use of rain and storm water for non portable uses and preserving the limited treated water for essential household uses.