PLANNING FOR OPTIMUM USE OF WATER RESOURCES OF MRP COMPLEX USING MIKE BASIN

Transcription

1 J. Indian Water Resour. Journal Soc., of Vol. Indian 33 Water No. 1, Resources January, Society, 2013 Vol 33, No. 1, January, 2013 PLANNING FR PTIMUM USE F WATER RESURCES F MRP CMPLEX USING MIKE BASIN S.K. Jaiswal 1, M. K. Verma 2 and Mohan Gupta 3 ABSTRACT This paper deals with the application of simulation software MIKE BASIN (2009) for optimum utilization of water resources of MRP Complex. Mahanadi Reservoir Project (MRP) Complex is a multipurpose multi-reservoir system. It consists of Mahanadi basin and Pairi basin. This project comprises of four reservoirs. There is inter-basin transfer of water from Sondur reservoir in Pairi basin to Dudhawa reservoir in Mahanadi basin through a feeder canal. MIKE BASIN has extensive reservoir modeling capabilities, and accommodate multi-purpose reservoirs and multiple reservoir systems. The philosophy behind MIKE BASIN is to keep modeling simple and intuitive, yet provide in-depth insight for planning and management. In this paper, an attempt has been made to decide the strategies for optimum use of water available in the reservoirs of MRP Complex. There are three possible ways of supplying water from the two upstream reservoirs to the Ravishankar reservoir. These three ways of supplying water has been simulated in MIKE BASIN and designated as three models. The simulation has been run for twenty one years (1975 to 1995) historical data. To check the efficiency of models the annual deficit between demand and supply has been computed for each model. The results of these three models have been compared with the results of earlier reported optimization model. The total deficit for twenty one years was found minimum in the first model hence this is the efficient model. First Model is then run for recent data ( ). The model is working well for the recent data ( ). Key words: ptimum use, MRP Complex, MIKE Basin model. INTRDUCTIN The increasing demand of water due to population growth and industrialization has created pressure on the available water resources. This problem can be solved by optimum utilization of the available resources in the existing reservoir system. The operation of multiple reservoir system is a complex decision making process involving many variables and many objectives. With the advent of digital computer in recent past, the research and application of systems analysis in the area of water resources planning and management has received a big impetus. The basic techniques used in water resources systems analysis are optimization and simulation. The basic techniques used in water resources systems analysis are optimization and simulation. Simulation is a technique by which we imitate the behavior of a system. We use simulation to answer what-if type questions, as against optimization where we look for the best possible solution. Simulation is a very powerful technique in analyzing most complex water resource system in detail for performance evaluation. In many situations, however, decision makers would be interested in examining a number of scenarios rather than just looking at one single solution that is optimal. By repeatedly simulating the system with various sets of inputs it is possible to obtain optimal solutions (Vedula and Mujumdar, 2006). Application of various mathematical modeling procedures is greatly benefitted by the excellent review presented by Yeh (1985) and Labadie (2004). Application of Reservoir-System simulation and optimization models is presented by Wurbs (1993). Afzali et al. (2008) presented a multireservoir 1. Department of Civil Engg., B.I.T. Durg (CG), , India. skjaiswal67@yahoo.com 2. Department of Civil Engg., N.I.T. Raipur (CG), , India. mkseem670@rediffmail.com 3. Department of Civil Engg., B.I.T. Durg (CG), , India. info@mohangupta.com Manuscript No reliability-based simulation model considering the integrated operation of the systems. Cutlac and Horbulyk (2011) used the publicly developed Aquarius modeling software to examine the effect on economic welfare of alternative surface water allocations in the Alberta portion of the South Saskatchewan River Basin in Canada. Application of simulation software MIKE BASIN for water management strategies in a watershed of Mun River Basin located in Northeast Thailand was reported by Jha and Gupta (2003). Rani and Moreira (2010) presented a survey of simulation and optimization modeling approaches used in reservoir systems operation problems. Reichold et al. (2010) presented a methodology to identify watershed management strategies that will have a minimal impact on the flow regime and downstream ecosystems. This methodology utilizes a simulation-optimization framework. Neelakantan and Pundarikanthan (2000) used a backpropagation neural network to approximate the simulation model developed for the Chennai city water supply problem. For multi-reservoir operation problem simulation technique is very useful. As the MRP Complex is a multi-reservoir system, it has been decided to use simulation technique for finding the optimum way of using water of this system. Simulation software MIKE BASIN (2009) has been used for analysis in this work. MIKE BASIN has extensive reservoir modeling capabilities, and accommodate multi-purpose reservoirs and multiple reservoir systems. The philosophy behind MIKE BASIN is to keep modeling simple and intuitive, yet provide in-depth insight for planning and management. STUDY AREA Mahanadi is an important river system of Chhattisgarh state. It is classified amongst the twelve major river basins in the country. The Mahanadi Reservoir Project Complex (MRP Complex) consists of Mahanadi basin and Pairi basin. The index map of MRP Complex is shown in Figure 1. This project comprises of four reservoirs namely Ravishankar Sagar 15

2 PAIRI BASIN MAHANADI BASIN L E G E N D 20 0 R I V E R : 20 0 C A T C H M E N T B U N D A R Y D A M / W E I R : R E SE R V I R 1 : R A V I S H A N K A R S A G A R 3 : D U D H A W A 2 : M U R U M S I L L I 4 : S N D U R I N T E R - B A S I N L I N K C A N A L 5 : S N D U R F E E D E R C A N A L Fig. 1: Index map of MRP complex Table 1: Catchment Area at Dam sites Sr. No. Name of the Site Gross Intercepted Unintercepted 1. Ravishankar Sagar Dam Dudhawa Dam 621 Nil Murumsilli Dam 484 Nil Sondur Dam 512 Nil 512 [Unit: Square Kilometer (sq. km.)] Table 2: Reservoir Capacities (in Mm 3 ) Sr. No. Reservoir Storage Capacity at Live Storage MWL FRL DSL 1. Ravishankar Sagar Dudhawa Murumsilli Sondur Reservoir, Murumsilli Reservoir and Dudhawa Reservoir in Mahanadi basin and Sondur Reservoir in Pari basin. Ravishankar Sagar Reservoir is constructed across Mahanadi river, Dudhawa reservoir is situated on upstream of Ravishankar Sagar Reservoir on Mahanadi river and Murumsilli Reservoir is constructed across Silliyari river a tributary of Mahanadi river on upstream of Ravishankar Sagar Reservoir. Sondur reservoir is situated at the upstream of Dudhawa reservoir and constructed across Sondur river in Pairi basin. Sondur and Dudhawa reservoirs are connected by an interbasin link canal called Sondur Feeder canal. This interbasin link canal transfer water from Sondur reservoir in Pairi basin to Dudhawa reservoir in Mahanadi basin. Sondur feeder canal feed water to Dudhawa reservoir as well as it irrigates some command area. There is no direct irrigation through Dudhawa and Murumsilli reservoirs, they feed water to Ravishankar Sagar reservoir. The MRP Complex is intended to provide irrigation and to meet municipal and industrial demands of Bhilai Steel Plant (BSP) and its township. Few of the statistical and physical features of the MRP complex are 16

3 given in tables 1 and 2. Thus Mahanadi Reservoir Project Complex is a multipurpose multi-reservoir system. Mahanadi is a mansoon fed river and almost all the inflows in to the reservoir of the system are observed in mansoon months and rest of the year the inflow is practically nil. It has been experienced that the annual inflow is insufficient to meet all the requirements in some of the years. To mitigate the shortfalls in the supply of water for meeting various demands in the system it is necessary to develop a methodology for optimum use of water resources of Mahanadi Reservoir project Complex. The data used in this work were collected from the various reports of Water Resources Department of Chhattisgarh Government such as report of Central Water and Power Research Station, "Development of Decision Support System for Mahanadi Project", Final Report (Feb. 1994), Govt. of Madhya Pradesh, "M.P. Major Irrigation Project - Mahanadi Project", Feb. 1990, Govt. of Chhattisgarh, "Mahanadi Reservoir Project (Major Irrigation Project), Water Resources Department", January METHDLGY This paper deals with the application of simulation software MIKE BASIN (2009) for detail scenario analysis for optimum utilization of water resources of MRP system. The performance evaluation of the models of present work has been done with that of the earlier reported PGP optimization model (Verma, 2010). For the purpose of direct and justifiable comparison of performance of MIKE BASIN simulation models, the same data set that is used in earlier reported model has been used. Then the best simulation model has been selected for application to MRP system with recent data. MIKE BASIN Simulation Model for MRP System The model of MRP complex has been developed in MIKE BASIN using the model building blocks available in the software. Following input data are required in the software for model building: (i) Physical features of the reservoir such as dead storage level, minimum operational level, critical water level, full reservoir, and maximum water level, Fig. 2: Mike Basin model setup of MRP-Complex 17

4 (ii) Inflow in the reservoir, (iii) Elevation Area Capacity data of reservoir, (iv) Evaporation loss from reservoir, (v) Demand data of different users.(table 3, 4 and 5) The following priority order on the utilization of storage of MRP system has been used in the model as per the recommendation of Government- (i) First priority has been given to municipal and industrial use. (ii) Second priority has been given to Irrigation demand for Kharif and Rabi season. In MRP complex, Ravishankar reservoir is connected with two upstream reservoirs Murumsilli and Dudhawa and there is inter basin transfer of water from Sondur reservoir to Dudhawa reservoir. The Mike Basin model setup of MRP complex has been shown in Figure 2. For different need water is supplied through Ravishankar reservoir only, hence Dudhawa and Murumsilli reservoirs are feeder reservoirs. Sondur reservoir feed water to Dudhawa reservoir as well as it irrigates some command area. In this work it has been tried to analyze the different alternative ways of operating reservoirs of the MRP complex as against finding the single optimum solution. Simulation technique has been used to analyze different alternatives and then best performing alternative has been identified. This analysis will provide the optimum sequence of operating the reservoirs of the complex. For integrated operation of reservoir Muskingum routing procedure has been used. By observing the Figure 2, it is clear that there is only one way of supplying water from Sondur to Dudhawa but there are three possible ways of supplying water from Murumsilli and Dudhawa reservoirs to Ravishankar Sagar reservoir. These three ways of supplying water has been simulated in MIKE BASIN software and designated as three models. These three models are: (i) (ii) Model-I: In this model Murumsilli reservoir has been given first priority and Dudhawa has been given 2 nd priority to feed water to Ravishankar reservoir. Model-II: In this model Dudhawa reservoir has been given first priority and Murumsilli has been given 2 nd priority to feed water to Ravishankar reservoir. (iii) Model-III: In this model Murumsilli and Dudhawa have been given equal priority to feed water to Ravishankar reservoir. The above three models have been simulated in MIKE BASIN. To find the optimum model, the annual deficit between demand and supply for different users has been calculated for each model. The model having least value of deficit for a specified duration will be the optimum model. To make the models more efficient the following additional conditions have been incorporated in the models. (a) At Ravishankar reservoir the priority of downstream users have been fixed as follows: (i) M & I demand (Table 3) have been given first priority. (ii) The irrigation demand of Mahanadi feeder canal (MFC) (Table 4) has been given second priority. (iii) The irrigation demand of Mahanadi Main Canal (MMC) (Table 5) has been given third priority. (b) At Sondur reservoir the first priority has been given to supply water for irrigation and second priority to supply water to the Dudhawa reservoir. For starting period of operation the initial storage in the reservoirs is taken as their corresponding dead storages. Table 3. Municipal and Industrial Demand (Mm 3 ) Sr. No. Month Municipal Demand Industrial Demand Total M & I Demand 1. June July August September ctober November December January February March April May

5 Table 4. Monthly Demand Series for MFC command area (Mm 3 ) Year JUN JUL AUG SEP CT NV DEC JAN FEB MAR APR MAY Table 5. Monthly Demand Series for MMC command area (Mm 3 ) Year JUN JUL AUG SEP CT NV DEC JAN FEB MAR APR MAY

6 Approach Adopted for the Present Study The approach adopted in the present study can be enumerated sequentially as follows: (i) The three simulation models, Model-I, Model-II and Model-III for MRP system have been first run for 21 years (1975 to 1995) with historical data and the results of these models have been compared with the earlier reported model. ut of the three models the optimum model is selected. (ii) The optimum model is then run for recent data of 13 years ( ). Results and Analysis of Simulation Model with Historical Data For meaningful comparison, the three simulation models are run using the same inflow and demand data as used in the earlier reported optimization model (PGP model). The 21 years (1975 to 1995) data have been used for this purpose. The monthly operation policy for individual year is determined using the simulation models, Model-I, Model-II and Model-III. The reservoirs were considered at the dead storage level at the beginning of June in the year The monthly deficit between demand and supply have been computed and totaled for each year to determine the total yearly deficit. The results obtained with the Model-I, Model-II and Model-III have been compared (Table 6) with the results of PGP model (Verma, 2010). The total deficit for 21 years has been computed for all the three models. The model having least value of total deficit will be the most efficient model. ut of the three models the total deficit was found minimum in Model-I, hence Model-I is the efficient model. The results of this model have been compared with the results of earlier reported optimization model (PGM model) (Verma, 2010). As the results of the Model-I is very close to the result of optimization model, hence Model-I is optimum model. The total deficit in Model-I is Mm 3 which is very close to Mm 3, the total deficit in PGM model. The accuracy of Model-I is 98.5%. Table 6. Comparison of Yearly Deficit Yearly Deficit (Mm 3 ) Year Model-I Model-II Model-III Earlier Model Total

7 Table 7. Yearly Deficit in Model-I for historical data and in 2003). Hence the simulation Model-I is successful for recent data also. Year % yearly deficit in Table 8. Yearly Deficit in Model-I for recent data The percentage yearly deficit for Model-I has been calculated and presented in Table 7. Analysis of the results in the Table 7 shows that for most of the year the deficit is less than 10%. In water resources less than 10% deficit is not considered as deficit. ut of the 21 years only 2 years have the deficit more than 10%, hence the model-i is 90.5% time successful. Results and Analysis of ptimum Simulation Model with Recent Data As discussed in the previous section, it was found that the simulation Model-I is the optimum model for operation of reservoirs of MRP complex. Now this optimum simulation Model-I is applied to MRP system with recent data of 13 years ( ). By the analysis of 21 years (1979 to 1995) demand data it was found that the variation in demand is very small, hence the average value of demand has been used for period 1996 to The monthly operation policy for individual year is determined using the optimum simulation model-i. The reservoirs were considered at the dead storage level at the beginning of June in the year The monthly deficit between demand and supply have been computed and totaled for each year to determine the total yearly deficit. The results have been shown in Table 8. It is observed from Table 8 that for most of the year the deficit is less than 10%. nly for 2 years the deficit is slightly more than 10%, (10.63% in 2001 Year % yearly deficit Table 9. Annual spill from Ravishankar Sagar Reservoir Year Annual Spill(Mm 3 ) Average Anuual Spill The spill analysis for Mahanadi Basin has been done for the effective utilization of the spill water of the system. The spill of Mahanadi Basin is through the Ravishankar Sagar Reservoir. The amount of annual spill has been computed for the period 1996 to The results of annual spill analysis have been shown in Table 9. The average annual spill from Ravishankar Sagar Reservoir is Mm 3. Adjoining to the Ravishankar Sagar Reservoir there is Tandula Reservoir. Since last ten years there is scarcity of water in Tandula Reservoir, it is filled less than 50% of its storage capacity. In this work it is proposed to utilise the spill water of Ravishankar Sagar reservoir by transferring it to Tandula reservoir through an interlinking canal. 21

8 CNCLUSINS In the first part of this paper the three simulation models (Model-I, Model-II and Model-III) have been applied with the same data set which has been used in the earlier reported study. It is observed that the simulation Model-I perform better than the Model-II and Model-III. The results of Model-I is very close to the results of earlier reported optimization model, hence performance of model-i is satisfactory and is identified as the suitable model for MRP system. In the second part of the study, the Model-I is applied to MRP system for recent data set. It has been observed that for most of the year the deficit is less than the permissible limit. Hence the performance of simulation model-i for recent data set is satisfactory. The spill analysis for Mahanadi Basin has been done. The average annual spill from Mahanadi Basin is Mm 3. For effective utilization of this spill water, it is proposed to transfer this water to adjoining Tandula Reservoir, as there is shortage of water every year. REFERENCES 1. Afzali, R., Mousavi, S. J. and Ghaheri, A Reliability-Based Simulation-ptimization Model for Multireservoir Hydropower Systems perations: Khersan Experience. J. of Water Resources Planning and Management. 134 (1): Cutlac, I.M. and Horbulyk, T.M., ptimal Water Allocation under Short-Run Water Scarcity in the South Saskatchewan River Basin. J. of Water Resources Planning and Management. 137 (1): Central Water and Power Research Station, Khadakwasla, Pune (India). "Development of Decision Support System for Mahanadi Project", Final Report (Feb. 1994). 4. Govt. of Madhya Pradesh, "M.P. Major Irrigation Project - Mahanadi Project", Feb Govt. of Chhattisgarh, "Mahanadi Reservoir Project (Major Irrigation Project) Water Resources Department", January Jha M. K. and Gupta A. D., Application of MIKE BASIN for Water Management Strategies in a Watershed. Water International, Vol. 28., No.1, Labadie, John W., ptimal peration of Multireservoir System: State-of-the-Art Review. Journal of Water Resources Planning and Management, Vol.130, No.2, Mike Basin A Modeling System for River Basin Management and Planning. User Guide. 9. Neelakantan, T. R. and Pundarikanthan, N. V., Neural Network Based Simulation ptimization Model for Reservoir peration. Journal of Water Resources Planning and Management, Vol. 126, No. 2, Rani, D. and Moreira, M.M Simulation ptimization Modeling: A Survey and Potential Application in Reservoir Systems peration. Water Resources Management. 24 (6): Reichold, L., Zechman, E.M., Brill, E.D. and Holmes, H Simulation-ptimization Framework to Support Sustainable Watershed Development by Mimicking the Predevelopment Flow Regime. J. of Water Resources Planning and Management, ASCE. 136 (3): Vedula, S. and Mujumdar, P.P Water Resources System. The McGraw-Hill Companies. ISBN No Verma, M.K., Shrivastava, R.K. and Tripathi, R.K., Evaluation of Min-Max, Weighed and Preemptive Goal Programming Models with Reference to Mahanadi Reservoir Project Complex. Journal of Water Resources Management, Springer Netherland. 24 (2): Wurb, R. A., Reservoir-System Simulation and ptimization Models. Journal of Water Resources Planning and Management, Vol. 119, No. 4, Yeh, William W-G, Reservoir Management and peration Models : A State of- the- Art Review. Water Resources Research, Vol.21, No.12,