Groundwater modeling of Musi basin Hyderabad, India: a case study
- 121 Downloads
In general, groundwater flow and transport models are being applied to investigate a wide variety of hydrogeological conditions besides to calculate the rate and direction of movement of groundwater through aquifers and confining units in the subsurface. Transport models estimate the concentration of a chemical in groundwater which requires the development of a calibrated groundwater flow model or, at a minimum, an accurate determination of the velocity and direction of groundwater flow that is based on field data. All the available hydrogeological, geophysical and water quality data in Musi basin, Hyderabad, India, were fed as input to the model to obtain the groundwater flow velocities and the interaction of surface water and groundwater and thereby seepage loss was estimated. This in turn paved the way to calculate the capacity of the storage treatment plants (STP) to be established at the inlets of six major lakes of the basin. The total dissolved solid was given as the pollutant load in the mass transport model, and through model simulation, its migration at present and futuristic scenarios was brought out by groundwater flow and mass transport modeling. The average groundwater velocity estimated through the flow model was 0.26 m/day. The capacities of STP of various lakes in the study area were estimated based on the lake seepage and evaporation loss. Based on the groundwater velocity and TDS as pollutant load in the lakes, the likely contamination from lakes at present and for the next 20 years was predicted.
KeywordsGroundwater Modeling Hydrogeology Pollutant Storage treatment plant Musi basin
Identification of parameters characterizing the physical framework of the aquifer and stresses acting on it.
Estimation of the relevant hydrogeological parameters at as many points as possible, particularly those at the boundaries
Interpolation/extrapolation of these parameters to characterize the entire area of study
Integration of the entire data to conceptualize and resurrect the natural system.
An appropriate mathematical description of the conceptual model giving spatiotemporal relationship between those parameters constrained by the relevant fundamental laws of hydraulics, mass transport, etc.
A solution of mathematical equations describing the groundwater regime in terms of observables such as groundwater levels or concentrations of pollutants.
A sensitivity analysis of the model to identify those parameters which need to be estimated more accurately, and also to decipher the error bounds.
Refinement of the model to progressively bring in plausibility and compatibility between field estimates of various geohydrological parameters through the process of model calibration and validation.
Prognosis of the aquifer response to evolve efficient management options for optimal utilization of groundwater resources.
All the parameters in Eq. (1) should be known at maximum number of points. The validity and applicability of an aquifer model directly depend upon the adequacy and reliability of the data. A comprehensive understanding of the study needs a few relevant topics including geology of the area of study, and therefore it is organized as “Location and geology of study area,” “Physical framework and stresses on the groundwater regime,” “Methodology of study” under which are “Lake water budget,” “Groundwater flow modeling,” “Capacity of storage treatment plant (STP),” “Results and discussion” followed by “Conclusions.”
Location and geology of study area
Physical framework and stresses on the groundwater regime
The physical framework of an aquifer model is defined by the hydrogeological parameters, namely the transmissivity (T) and storativity (S), boundary conditions and the hydraulic heads. The hydrogeological parameters T and S are estimated through long duration pumping tests. The boundary conditions include constant head, no flow or constant flow which may exist at the geometrical boundaries of the aquifer under study. The hydraulic heads (water level) are the most important observable parameter which characterize the response of an aquifer system. Since the model response is calibrated with the observed hydraulic heads, care should be taken to collect maximum data on water level from observation wells and these data have to be reduced with reference to a common datum, namely mean sea level (msl). The stresses on groundwater regime include the input to and output from the aquifer system. Recharge due to precipitation, infiltration from surface water bodies like rivers, lakes, tanks, canals, irrigation return seepage and lateral groundwater inflow comprise the input to an aquifer system. All the above data required for groundwater flow modeling are also required for mass transport modeling. In the mass transport model, the pollutant is a major input termed as stresses on the quality of groundwater. Groundwater draft, evapotranspiration, lateral groundwater outflow, effluence to surface water bodies comprise the output from an aquifer.
Methodology of study
Lake water budget
Thus, there is not a unique solution to estimating groundwater inflow to or outflow from a lake. At best, only the net groundwater flux to the lake (GWLake) can be estimated, or one of the two terms in Eq. (4) is set to zero to allow the other to be estimated (Cole and Fisher 1979; Cook et al. 1977). The contribution of the lake to the groundwater was estimated through the flow model by simulating the lake water and groundwater interaction.
Groundwater flow modeling
No flow occurs across the watershed boundaries and these boundaries coincide approximately with groundwater divides.
Groundwater recharge takes place from the top layer of the watershed.
Continuous groundwater pumping is prevalent in the watershed due to urbanization and land cover.
The groundwater withdrawal was estimated based on the well inventory, average running hour of pumps and residential distribution in the area.
As the watershed is a closed one with streamlet, some outflow may take place.
Seepage from the lakes was an additional input of recharge to the watershed.
Assigned lake water and lake bed levels in the simulated model
Name of the lake
Assigned lake water level (m)
Assigned bed level (m)
Sensitivity analysis for permeability (K) variance
Assigned permeability (m/day)
Mean absolute error
Groundwater balance under steady state conditions
Zone budget of lakes in NE Musi basin
Name of the lake
Lake contribution to groundwater (m3/day)
Groundwater contribution to lake (m3/day)
Net contribution to groundwater (m3/day)
Computed lake water seepage from groundwater flow model and proposed capacity of STPs in NE Musi basin
Name of the lake
Lake contribution to groundwater (MLD)
Evaporation loss @ 4.5 mm/day (MLD)
Proposed STP capacity (MLD)
Capacity of storage treatment plant (STP)
The computed seepage loss from RK Puramcheruvu is 0.6 MLD. An STP of 0.6 MLD for tertiary treatment has been functioning on Nadimicheruvu. The lake surface area is about 10 ha, and evaporation loss at the rate of 4.5 mm/day from the lake water surface works out to be 0.45 MLD. As the lake is situated in recharge area of the watershed, it contributes 1 MLD as seepage to the groundwater. Under lake restoration, it is envisaged to maintain FTL at Nadimicheruvu, and then it would need a supply of 1.5 176 MLD of treated wastewater. On a conservative basis with allowance for some outflow from the lake, an STP of 2 MLD capacity may be established. Thus, it is recommended to enhance the present capacity of the STP to 2 MLD at Nadimicheruvu. Further, it satisfies the growing urbanization and the disposal of sewerage volume in near future. The computed seepage losses from Bandacheruvu are 0.8 MLD. Based on the experience of Nadimicheruvu and computed seepage losses from groundwater flow model, it is recommended that STPs with a capacity of 2 MLD each may be constructed at RK Puramcheruvu and Bandacheruvu (Table 5). In the case of Patelcheruvu, the groundwater and lake water interaction suggested that it would require about 1 MLD capacity for meeting the requirement of evaporation and seepage losses (Table 5). The surrounding intensive urbanization plays an important role in the downstream lakes. Thus, it would be appropriate to commission an STP of 3 MLD at Patelcheruvu. The seepage loss in Peddacheruvu is about 1.5 MLD and evaporation loss is about 1 MLD (Table 5). The minimum capacity of 2.5 MLD is required for meeting the daily demands of lake water budget. But the ambience of urbanization is very high around Peddacheruvu for generation of higher volumes of domestic sewerage. Some industrial discharges adjoining the lake are letting out their wastewater into the lake. Considering all the above conditions, it is recommended for the construction of an STP with a capacity of 10 MLD for tertiary treatment.
Results and discussion
Models are used to calculate the rate and direction of movement of groundwater through aquifers and confining units in the subsurface. Accordingly, the present study has revealed that the average groundwater velocity estimated through the flow model was 0.26 m/day. The capacities of STP of various lakes in the study area were estimated based on the lake seepage and evaporation loss. Based on the groundwater velocity and TDS as pollutant load in the lakes, the likely contamination from lakes at present and for the next 20 years was predicted.
The authors record their sincere thanks to the Chairman, Executive Director and all the Engineers and Staff of Hyderabad Urban Development Authority (HUDA) for providing all the necessary help in the implementation of this piece of work.
No funding was received.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
Adhered to all forms of ethical standard.
Informed consent was obtained from all individual participants included in the study.
- Anderson MP, Wang HF (1982) Introduction to groundwater modeling. W.H. Freeman and Company, San FranciscoGoogle Scholar
- Anderson MP, Woessner WW (1992) Applied groundwater modeling—simulation of flow and advective transport. Academic Press, San DiegoGoogle Scholar
- Bear J (1972) Dynamics of fluid in porous media. American Elsevier Publishing Company, New YorkGoogle Scholar
- Bear J (1979) Hydraulics of grounwater. Macgraw Hill, New York, pp 1–567Google Scholar
- Bear J, Verruijt A (1979) Modeling groundwater flow and pollution. Kluwer Academic Publishers Group, AucklandGoogle Scholar
- Fried JJ (1975) Groundwater pollution, theory, methodology, modeling and practical rules. Elsevier Scientific Publishing Company, New YorkGoogle Scholar
- Grove DB, Stollenwork KG (1984) Computer model of one-dimensional equilibrium controlled sorption processes. U.S. Geol. Survey Water Resources Investigations Report 84-4059, pp 5–8Google Scholar
- Guiger N, Franz T (1996) Visual MODFLOW: users guide, Waterloo Hydrogeologic, and Waterloo, Ontario, CanadaGoogle Scholar
- Javandel I, Doughty C, Sang CF (1984) Groundwater transport: handbook of mathematical models. Am Geophys Union Water Resour Monogram 10:228–229Google Scholar
- Kinzelbach W (1986) Ground water modelling. Elsevier, AmsterdamGoogle Scholar
- Konikow LF, Bredehoeft JD (1978) Computer model of two dimensional solute transport and dispersion in groundwater. In: Techniques of water-resources investigations of the USGS Chapter C2, Book 7, pp 90–92Google Scholar
- Konikow LF, Grove DB (1977) Derivation of equations describing solute transport in groundwater, US Geol. Survey Water Resources Investigations. Report, pp 77–19: 30Google Scholar
- Konokow LF (1976) Modelling solute transport in groundwater. In: International conference on environmental sensing and assessment proceedings, 20–30, Las Vegas, NVGoogle Scholar
- Konokow LF (1977) Modelling chloride movement in the alluvial aquifer at rocky mountain Arsenal, Colorado, U.S Geol. Surv. Water Supply Paper 2044, U.S. Government Printing Office, Washington DC, pp 1–43Google Scholar
- Konokow LF (1978) Calibration of groundwater models. In: Proceedings of the speciality conference on verification of mathematical and physical models in hydraulic engineering. ASCE College Park, Matyland August, Report. 9-11, pp 87–93Google Scholar
- Krishnan MS (1960) Precambrian stratigraphy of India. Report 21st International Geol. Cong. Norden. 9, pp 95–107Google Scholar
- McDonald JM, Harbaugh AW (1988) A modular three-dimensional finite difference groundwater flow model, techniques of water resources. Investigations of the U.S. Geological Survey Book, 6, pp 586–589Google Scholar
- Rao VVSG, Sankaran S, Venkateswarlu M, Chandrasekar SVN, Mahesh Kumar K (2003) Data on watershed covering Patelcheruvu, Peddacheruvu and Nallacheruvu, Technical Report No. NGRI-2003-Groundwater 379Google Scholar
- Sitaramayya S (1968) Structure, petrology and geochemistry of granites of Ghatkesar, A.P. PhD Thesis (Unpublished), Osmania University, HyderabadGoogle Scholar
- Zheng C (1990) MT3D, A Modular three-dimensional transport model for simulation of advection, dispersion and chemical reactions of contaminants in groundwater system prepared for the U.S. Environmental protection AgencyGoogle Scholar
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.