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Optimal Allocation Of Surface Water Resources For Peri-urban Area To Minimize The Future Demand-supply Gap

Congress: 2015
Author(s): Saravanan Ramasamy (Chennai, India)


Keyword(s): Sub-theme 1: Water supply and demand,
AbstractAbstract The Right to Water and Sanitation has been recognized as a fundamental human right by the United Nations since 2010. However, is this right universal? There are still wide disparities between the Earth's regions. In general allocation of locally available surface water resources reduce extra burden to the centralized water supply systems for widened city limits having rapidly increasing population and one such example Chennai. The expanded Chennai Corporation having the total area increased from 174 km2 to 426 km2. Overall Population Vs Demand Vs supply analysis shows same pattern of supply-demand gap was repeated for every year from 1971 to 2031. Leaving behind the irrigation water demand, net available surface water is considered for optimal allocation that us the lakes and tanks, which are susceptible to render water for the greater Chennai is alone considered. The total volume of surface water available for the greater Chennai is estimated is 0.45Mm³. With the available surface water resources, First priority of water allocation is provided to the municipalities, then to town Panchayats and to village Panchayats is prescribed in the model. In this paper, an optimization problem is formulated for optimal allocation of water resources that can be implemented by considering the constraints of complete utilization of the available surface water resources with the objective of minimizing total future demand-supply gap. The solution to optimization problem is obtained through Genetic Algorithm (GA). The results of the analysis reveals that the optimal water allocation for Peri-Urban Area of Chennai during 2011 maximum of 70 lpcd is required to the municipalities such as Thiruvottiyur, Madhavaram and Ambattur. Then the minimum of 30 lpcd need to be supplied to the village panchayats such as Nolumbur and Karambakkam. The projected optimal water allocation for Peri-Urban Area of Chennai in 2021 and 31, the maximum of 70 lpcd is needed to the village panchayats such as Palavakkam, Semmenchery and Neelankararai respectively. It is concluded that the projected years 2021 and 2031, the water allocation is minimum for most of the Peri-Urban Area of Chennai and is uniform. Introduction The availability of water is becoming scarce and that is not enough to meet the requirements of people. In the Peri-Urban areas of Chennai the demand supply gap of water is expected to grow vigorously in future. The monsoon failure also adds pressure to the existing available sources. To supplement the water supply, Communities may have to bring water in from more distant sources by pipelines encountering losses and more cost effective. Therefore, optimal allocation of surface water resources, of Peri-Urban areas of Chennai need to be arrived to minimize the future demand-supply gap. For the optimal allocation of water resources to meet the growing demand, the supply of water must be optimized to meet the demand. Evolutionary algorithms are particularly efficient in optimization problems. A review of literature indicates that, multi-objective Genetic Algorithm (GA) based on parataxis choice was introduced to optimize water allocation (Meixia,et,al 2002). GA is capable of finding the global optima as opposed by traditional algorithms; Rule chart was obtained which helped the operator to release the quantity of water (Sitaramalakshmi, 2001). The GA based optimization is very effective for management of contaminated aquifers (Katsifarakis, et al, 2009). The river was in direct contact with the aquifer system, contributing to the aquifer recharge from March to November; The Rivers had a positive influence on groundwater recharge (Mohammad Rahman et al 2006). A study has been carried out to demarcate and protect the groundwater recharge zones by using MODFLOW (Saravanan et al, 2010). Genetic algorithm was used to arrive at the optimal rates for pumping and recharge wells in order to capture all the contaminant with minimum quantity of pumping and recharge. (Nambirajan 2007). GA is an effective algorithm for optimizing cropping pattern area in order to achieve maximum profit required (Praveen 2011). Drastic variability in respect of topography, soil strata and hydrogeology of the Nowshera district covering an area of about 1700 sq.km is responsible for vast variation in groundwater availability at various locations (Muhammad Ismail et al 2009). Groundwater flow and contaminant transport can be identified using the model, it was seen that the particles residing in the lakes get migrated towards the wells along with groundwater flow (Dilna 2011). The objectives of this study is to predict future demand and supply scenario and identifying surface water resources to meet the demand of 2031; to estimate the surface water potential of Peri-Urban area to meet the predicted demand-supply scenario and to optimize the allocation of surface water resources in order to minimize the future demand supply gap using GA. Study Area Peri--Urban area of Chennai is located in the Deccan Plateau 6.7 meters above sea level. The rivers Araniyar and Kosathaliyar adjoining the reservoirs around the city light the study area, Chennai city, situated in northern side of the state. Peri--Urban area of Chennai is a flat coastal plain city. The water is sourced thirty kilometers west of Chennai city. The average annual rainfall is 1200 mm. Peri--Urban area within expanded Chennai Corporation limits which includes, 9 Municipalities, 8 Town Panchayats and 25 village panchayats. In this study, the Peri--Urban water resources of Chennai have more number of lakes, ponds and tanks. They are classified into three groups such as, large water bodies, medium water bodies and small water bodies. From the water bodies, the water supply may be distributed to the nearby communities is to be analyzed. Methodology The methodology involves two phases, first phase consist of inventory of water resources used to analyze the present demand supply gap then used for the forecasting the demand supply gap. Once the demand supply gap is estimated the optimization has been performed as phase two using GA to minimize the Demand-Supply gap in the future considering the various constraints with additional surface water sources. Projected Water Demand: The projected water demand of Peri-Urban area of Chennai city is estimated using Geometric increase method. Figure shows the spatial representation of projected water Demand of Peri-Urban area of Chennai city is delineated using the Map-Info software. The Water Demand is increasing every year and having the water demand of 33.804 MLD in 2011, 52.497 MLD in 2021 and 81.520 MLD in 2031 for the Ambattur region is shown in Figure. The minimum Demand of 0.053 MLD in 2011, 0.0658 MLD in 2021 and 0.081 MLD in 2031 for the Karambakkam region. Projected Water Supply: The spatial representation of Projected Water Supply of Peri-Urban area of Chennai city is delineated using the Map-Info software is shown in Figure. The Water Supply is also increasing every year and which does not satisfy the required projected demand. The Water Supply of 20.282 MLD in 2011, 31.498 MLD in 2021 and 48.916 MLD in 2031 for the Ambattur region. Projected Demand-Supply Gap: Projected Demand-Supply Gap spatial representation of Peri-Urban area of Chennai city is delineated using the Map-Info software is shown in Figure 5.20. The maximum Demand-Supply Gap is of 16.032 MLD in 2011, 20.999 MLD in 2021 and 32.620 MLD in 2031 for the Ambattur region. The minimum Demand-Supply Gap of 0.027 MLD in 2011, 0.034 MLD in 2021 and 0.040 MLD in 2031 for the Karambakkam region. Overall population and demand- supply scenarios: The summation of all the population, Demand and Supply for entire greater Chennai, which includes 9 Municipalities, 8 Town Panchayats and 25 village panchayats, is performed. Then, the future projection of population is done by the geometric increase method and the total Demand-Supply is estimated. It is inferred that the overall population Vs demand Vs supply follows the same pattern of supply-demand gap for every year from 1971 to 2031. Which reveals that the existing method of distribution does not solve the demand-supply gap. Irrigation water demand: The water needed for three seasons of the whole ayacut area having paddy, groundnut and pulses is considered. Using the above formula, the agricultural water demand of the Peri-Urban area of Chennai is found to be 0.073Mm³. The lakes and tanks, which are susceptible to render water for the greater Chennai is alone considered from the overall available local surface water resources without compromising the agricultural water demand. The total volume of surface water available for the greater Chennai is estimated is 0.45Mm³. Genetic Algorithm Optimization Results The optimal water allocation pattern can be chosen according to the available surface water resources and the objective function is to minimize demand-supply gap. First priority of water allocation is provided to the municipalities, then to town panchayats and to village panchayats is prescribed in the model. From the analysis, Optimal water allocation results for Peri-Urban Area of Chennai in 2011, the maximum of 70 lpcd is to be required to the municipalities such as Thiruvottiyur, Madhavaram and Ambattur. Then the minimum of 30 lpcd to be supplied to the village panchayats such as Nolumbur and Karambakkam. The Optimal water allocation for Peri-Urban Area of Chennai in 2021, the maximum of 70 lpcd is to be needed to the village panchayats such as Palavakkam and Semmenchery. Then, the Optimization results of water allocation for Peri-Urban Area of Chennai in 2031, the maximum of 70 lpcd is to be given to the village panchayat Neelankararai. For the projected years 2021 and 2031, the water allocation is minimum for most of the Peri-Urban Area of Chennai is identified. This is because the rapid increase in population and the available amount of surface water resources remains the same. CONCLUSIONS The demand-supply analysis for Municipalities, Town panchayats and Village panchayats reveals that the demand-supply gap undergoes 35.6% of increase in every decade. Overall population Vs demand Vs supply follows the same pattern of supply-demand gap for every year from 1971 to 2031. Which reveals that the existing method of distribution does not solve the demand-supply gap problem. Surface water potential of Peri-Urban area of Chennai having nine tanks of capacity 0.45 Mm³ was determined. The tank loss of 60% of the capacity was considered. The agricultural water demand of the Peri-Urban area of Chennai is 0.073Mm³ for three seasons. The net available water for domestic supply leaving behind the agricultural water demand was 0.107 Mm³ and total demand to be satisfied is more than the net available surface water resources. Optimal water allocation for projected years 2011-2031, was minimum for most of the Peri-Urban Area of Chennai is identified. This is because the rapid increase in population and the available amount of surface water resources remains the same. This study considers only the surface water resources for the equitable distribution for Peri-Urban area of Chennai and the status of demand-supply gap in 2011, 2021 and 2031 for the forthcoming years. Incorporating the ground water potential, recharge rate, water from desalination plant etc can be considered for future study to obtain the optimal allocation of water resources. References Anbarasan A. (2010), 'Development of operational guidelines for equitable distribution of surface water to Chennai city', Anna University PhD thesis. Aravindan K. ( 2005), 'Sustainable development of subsurface water for drinking water supply Centre for Water Resources', Anna University M.E thesis. Balambal Usha. (2010), 'Urban water supply planning for Chennai, India-- Future Scenarios' , Anna University M.E thesis. Janakarajan., John Butterworth., Patrick Moriarty. And Charles Batchelor. (2007), 'Strengthened City marginalized peri-urban villages: stakeholder dialogues for inclusive urbanization in Chennai, India'. Negowat project team by IRC International Water and Sanitation Centre, Chapter 3, pp 51. Katsifarakis K.L., Mouti M, Ntrogkouli K, 'Optimization of Groundwater Resources Management in Polluted Aquifers,' Global Nest Journal, vol 11, No 3, pp. 283-290. LIU Meixia and WU Xinmiao (2002), 'Water Resources Optimal Allocation based on Multi-Objective Genetic Algorithm', pp.87-91, Agricultural University of Hebei, Baoding, China.
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