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ARTICLE
Year : 2015  |  Volume : 5  |  Issue : 1  |  Page : 31-35

Groundwater Simulation Model for Sirhind Canal Tract of Punjab


Department of Soil and Water Engineering, Punjab Agricultural University, Ludhiana, Punjab, India

Date of Web Publication16-Jan-2015

Correspondence Address:
Pamela Miglani
Department of Soil and Water Engineering, Punjab Agricultural University, Ludhiana, Punjab
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0976-8580.149482

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   Abstract 

Groundwater is the basic source of irrigation in the state of Punjab. Due to seasonal supply of surface water, groundwater is used dominantly in the state, which has led to the alarming decrease in the water levels. To understand the spatial and temporal pattern of groundwater, a groundwater model for Sirhind Canal Tract of Punjab was simulated using PMWIN. The model was calibrated for the period of 1996-97 to 2000-01 and validated for the period 2001-02 to 2005-06.Recharge due to irrigation and rainfall was estimated in accordance with GEC (1997) methods. Different statistical tests revealed that there was good agreement between observed and simulated hydraulic heads. Sensitivity analysis showed that the model was more sensitive to specific yield then hydraulic conductivity values. The simulated model can be effectively used for sustainable management of water resources.

Keywords: Groundwater modeling, Groundwater recharge, Groundwater resources, Groundwater simulation, MODFLOW


How to cite this article:
Miglani P, Aggarwal R, Kaur S. Groundwater Simulation Model for Sirhind Canal Tract of Punjab. J Eng Technol 2015;5:31-5

How to cite this URL:
Miglani P, Aggarwal R, Kaur S. Groundwater Simulation Model for Sirhind Canal Tract of Punjab. J Eng Technol [serial online] 2015 [cited 2018 Dec 19];5:31-5. Available from: http://www.onlinejet.net/text.asp?2015/5/1/31/149482


   1. Introduction Top


Groundwater is vital to many nations. Worldwide, some 2000 million people, innumerable farmers and many industrial premises depend on it for their water supply. Accelerated development over the past few decades has resulted in great social and economic benefits, by providing low-cost, drought-reliable and (mainly) high-quality water supplies for both the urban and rural population and for irrigation of (potentially high-value) crops [1] .

Punjab, an agrarian Indian State, contributes about 33% rice and 52% wheat to the central pool from its meager area, which is 1.5% of the total geographical area of India. The total water requirement for Punjab, with the present cropping pattern and practices and industrial uses, is estimated at 4.4 Million hectare-metres (Mha-m) against the total water availability of 3.13 Mha-m [2],[3] , of which 1.45 Mha-m is from canals and 1.68 Mha-m is from rainfall and seepage. The deficit of almost 1.27 Mha-m is met by groundwater withdrawal that has consequently led to a decrease in the groundwater levels in the state. The lowering of groundwater levels has resulted in a reduction in individual well yield, growth in well population, failure of bore wells, drying up of dug wells and increase in power consumption [4] . Though high crop water-use negatively impacts groundwater, unreasonable reductions in crop water-use could adversely affect agricultural production [5] . Therefore to improve and sustain agricultural production of the state, it is necessary to prevent further deterioration of groundwater resources. This, in turn, requires an assessment of water resources availability, water needs, water balance of the area and understanding of the groundwater system. The first and foremost step for formulating any management strategy is continuous monitoring and management of a reliable database. Groundwater modeling can play a vital role in the assessment of water resources potential of the region. Using different modeling tools one can describe the regional flow pattern, the proper definition of goals and related criteria and a monitoring network for groundwater flow and groundwater pumpage [6] .

With the above background, the purpose of this study was to adopt MODFLOW [7],[8] for simulating groundwater behavior of Sirhind Canal Tract of Punjab to manage regional hydraulic regime for sustainable crop production.

1.1 Study area

For the present study, Sirhind Canal Tract of Punjab was opted as the study area [Figure 1]. The region is located in the Indo-Gangetic plain and lies in the south of the river Sutlej between 29°32' and 31°22' North latitude and East longitude 74°30' and 76°51'.
Figure 1: Location map of Sirhind canal tract of Punjab

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The Sirhind canal tract comprising of 2.58 Mha of the State, is bounded by Shivalik foothills zone in east and north-east, Ghagger River towards south, Bhakra main line (BML) in south-east and Rajasthan feeder canal in the west. Administrately, districts namely Sangrur, Bathinda, Fatehgarh Sahib, Patiala, Roopnagar, Mansa, Ludhiana, Moga fall completely and parts of districts Faridkot, Ferozepur and Mukstar are covered in this tract. The region lies between 190 and 340 m above the mean sea level with an average gradient of 0.68 m per 1000 m. The tract is formed by the variety of soils viz; Sierozem, arid and brown soil, tropical arid brown soil.

The climate of the Sirhind canal tract is determined by the extremes of hot and cold conditions. The cold season is from the middle of November to the early part of March. The succeeding period up to the end of June is the hot season. July, August and half of September constitute the south-west of monsoon, the period of mid-September to about middle of November may be termed as post-monsoon or transitional period. June is generally the hottest month. December and January are the coldest month. The rainfall in the tract increases from southwest towards the northeast. More than 70% of the rainfall is received during the period July to September. The average annual rainfall is 370 mm ranging from 206 mm to 613 mm from last 10 years.

1.2 Groundwater simulation model

For this, MODFLOW in the PMWIN environment has been used to simulate groundwater behavior of the study area [9],[10],[11] . The model, based on the three dimensional movement of ground water in a heterogeneous and anisotropic aquifer is given by the following partial differential equation:



where,

K xx,K yy, K zz = Hydraulic conductivity along x, y and z coordinate axes (L/T)

h = Hydraulic head (L)

w = Volume flux per unit volume representing source/sink (1/T)

Ss = Specific storage of porous media (1/L)

t = Time (T)

1.3 Aquifer discretization

The aquifer of the study area was discretized into a finite difference grid with 12 rows and 15 columns (180 cells). A constant grid spacing of 15 km × 15 km (225 km 2 ) was used. The boundary of the aquifer was approximated in a linear stepwise fashion as shown in [Figure 2].
Figure 2: Descretization map of Sirhind canal tract of Punjab

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In the figure, only a portion of the finite difference grid actually overlies the aquifer. One hundred and sixteen cells out of 180 cells in the aquifer were considered as part of the study area and included in the simulation process, that is, 26,100 km 2 of the area was used out of the total area of 40,500 km 2 .

As the sides of the study area is bounded by River Satluj in the north, Rajasthan Feeder in the west, BML in the east and Ghagger river in the south therefore the boundaries along these sides were considered as constant head boundaries, which mean the hydraulic head remains same throughout the simulation period.

1.4 Stress period

Ten years of data from 1996-97 to 2005-06 was used for simulation of the groundwater model and individual stress period of 365 days were used to observe the yearly affect of recharge and draft on groundwater system.

1.5 Spatial parameters

MODFLOW requires initial hydraulic heads at the beginning of the flow simulation. For transient flow simulations, the initial heads must be the actual values. The initial conditions used for model simulation were specified as for pre-monsoon 1996 that is, on June 1, 1996. For each time step after the first, the head distribution at the start of one-time step is set equal to the head distribution at the end of previous time step. From lithological data point values of hydraulic conductivity, [Figure 3] and specific yield [Figure 4] and bottom elevation were interpolated for the model.
Figure 3: Specific yield map of the Sirhind canal tract

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Figure 4: Hydraulic conductivity map of the Sirhind canal tract

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1.6 Temporal parameters

Flow packages are designed to simulate temporal parameters such as recharge and draft. For computing groundwater draft, the quantity of groundwater pumped in different season during the year 1996-97 to 2005-06 was calculated based on the number of tube wells in the area and using draft norms as given by GEC,1997 [10] . The total draft values thus obtained were modified using the multiplication factor based on the variation in the amount of rainfall from normal seasonal rainfall value. The actual block-wise groundwater draft for each of the season from different years was distributed to each of the model cells falling in the block as per the area of the cell in that block.

The recharge for each of the discretized cell was considered as the sum of recharge from rainfall and recharge from canal seepage and recharge from return flow of irrigation. The average value of 25% of total rainfall has been assumed as groundwater recharge. The seepage from unlined canal was taken as 25 ha-m/day/10 6 m 2 of the wetted area. For lined canal seepage losses were taken as 20% of the value for unlined canals. Percolation from canal irrigated areas was taken as 50% of the water delivered at the outlet for paddy fields. Percolation from area irrigated by well was taken as 45% of water delivered at the outlet for paddy fields. Based upon the actual canal water releases from 1996 to 97 onwards and the established seepage norms, the recharge from the canal network was computed at each cell from the block-wise seepage losses. Similarly, the recharge due to rainfall and return flow from canal and tube well-irrigated area was distributed as per the area of the cell falling in a particular block.

1.7 Model calibration and validation

The model was calibrated by adjusting aquifer parameters, boundary conditions, and stresses within plausible ranges and hence that modeled hydraulic heads are matched with the historic field-measured values for the period. Then model was calibrated using the data for the period 1996-97 to 2000-01 and validated for the years 2001-02 to 2005-06.


   2. Results and Discussion Top


2.1 Groundwater draft

Groundwater draft utilized for the irrigation purpose during period 1996-97to 2005-06 is given in [Table 1]. A perusal of [Table 1] shows that groundwater draft varied from 317.83 mm to 571.65 mm. The average annual groundwater draft during the study period is 445.38 mm.
Table 1: Annual groundwater draft and recharge (mm) from rainfall, canal seepage, canal releases and tube well draft

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2.2 Groundwater recharge

Annual rainfall for the Sirhind canal tract district for the period 1996-97 to 2005-06 was used to estimate rainfall recharge. [Table 1] reveals that the recharge from the rainfall in the tract varied from the maximum of 154.57 mm and minimum to 51.59 mm. The average recharge from rainfall is about 92.52 mm. The recharge from rainfall is 29 % of the total recharge.

2.3 Seepage from the canal network

The canal water supplies to Sirhind canal tract was estimated using norms GEC, 1997 [12] . The recharge from the canal network (Main canal, distributaries and branches) was calculated proportionately on the basis of the length of the canal passing through each block. The recharge from the canal network for period 1996-97 to 2005-06 is given in [Table 1]. A perusal of [Table 1] reveals that the recharge from the canal network varied from 19.63 mm to 37.79 mm. The average recharge from canal seepage is about 30.09 mm which is 9.2% of the total recharge.

2.4 Return flow from canal irrigated area

Deep percolation from canal irrigated area was estimated by using the canal water utilized in the Sirhind canal tract and the norms given by GEC, 1997 [10] . The recharge from canal irrigated area for period 1996-97 to 2005-06 is given in [Table 1]. A perusal of [Table 1] reveals that the recharge from canal irrigated area varied from 37.86 mm to 61.59 mm. The average recharge from canal irrigated area is 53.20 mm. The recharge from canal irrigated area is 16.2% of the total recharge.

2.5 Return flow from the tube well-irrigated area

Due to the insufficient canal water supply, the irrigation is mainly done by the tube wells. The recharge contribution from the areas was worked out for the period 1996-97 to 2005-06. The recharge from tube well-irrigated area varied from 98.20 mm to 191.86 mm. The average recharge from tube well-irrigated area is 152.49 mm. The recharge from tube well-irrigated area is 46.4% of the total recharge.

2.6 Calibration, validation and sensitivity analysis of the groundwater model

During the calibration period, the mean absolute error (MAE) value ranged from 0.50 m to 0.58 m. Average RMSE values worked out to be 0.71 m. The modified hydrologic parameters decided at the time of calibration were used to perform simulations for the validation period. During the validation period (2000-01 to 2005-06), the MAE value ranged from 0.48 m to 0.55 m. Average RMSE values worked out to be 0.62 m. The simulation error for calibration and validation period [Table 2] was within allowable limit as reported by various research workers [13],[14],[15],[16] .
Table 2: Statistical methods used on observed and predicted hydraulic heads (m)


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2.7 Sensitivity analysis

The sensitivity of the model to variation in hydraulic conductivity and specific yield was studied. Varying the individual parameter within allowable limits, simulation runs were carried out separately. Firstly hydraulic conductivity values were varied by ±30% of the initial values and keeping the specific yield values as the same, the hydraulic heads were computed. To observe the changes done by specific yield, half to double of its initial values were varied. It was observed that the model was more sensitive to change in a specific yield values.

2.8 Groundwater levels

The hydrograph showing the simulated and observed hydraulic head at some randomly selected grid points are given in [Figure 5]. The observed and corresponding simulated water table contour maps are given in [Figure 6]. These figures indicate that observed and predicted values matches closely. The reason for this variation may be that the seepage from the canal network has been computed as a single lumped value for each block and distributed among the cells falling in the block.
Figure 5: Comparison of observed and predicted hydraulic head

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Figure 6: Observed and predicted water level (m) in the year

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   3. Conclusions Top


The study gives an insight of spatial and temporal variation of groundwater behavior in the Sirhind canal tract of Punjab. The tube well irrigation system in the state of Punjab has increased and led to the decrease of groundwater levels with alarming rates, which are well-captured by the simulated model. The present model can be further used successfully to simulate the effect of different groundwater management practices on groundwater regime and thereby help to scrutinize the best practice that ensures groundwater levels at pre-determined depth and can be selected for sustainable crop production.

 
   References Top

1.
M. Abdelrhem, K. Rashid, and A. Ismail, "Integrated groundwater management for great man-made river project in Libya," European Journal of Scientific Research, Vol. 22, no. 4, pp. 562-569, 2008.  Back to cited text no. 1
    
2.
S. S. Prihar, S. D. Khepar, S. Raghbir, S. S. Grewal, and S. K. Sondhi, "Water resources of Punjab: a critical concern for the future of its agriculture," Ludhiana: Bulletin, Punjab Agricultural University; pp. 54, 1993.  Back to cited text no. 2
    
3.
Anonymous, "Agriculture Production Pattern Adjustment Programme in Punjab for Productivity and Growth," A Report to the Government of Punjab, Chief Ministers Advisory Committee on Agriculture Policy and Restructuring, pp.123, 2002.  Back to cited text no. 3
    
4.
M. Imtiyaz, and D. J. Rao, "Influence of overexploitation on groundwater Ecosystem in hard rock terrain," Proceedings of International Groundwater Conference, Jaipur, India, pp. 1922, 2008.  Back to cited text no. 4
    
5.
Y. Hu, J. P. Moiwo, Y. Yang, S. Han, and Y. Yang, "Agricultural water-saving and sustainable groundwater management in Shijiazhuang Irrigation District, North China Plain," Journal of Hydrology, Vol. 393, no. 3-4, pp. 219-232, 2010.  Back to cited text no. 5
    
6.
S. Kaur, R. Aggarwal, and A. Soni, "Study of Water-Table Behaviour for India Punjab using GIS," Water Science and Technology, Vol. 63, no. 8, pp. 1574-1581, 2010.  Back to cited text no. 6
    
7.
A. W. Harbaugh, and M. G. McDonald, "Programmer's documentation for MODFLOW-96, an update to the U.S. Geological Survey modular finite-difference ground-water flow model," Open-File Report 96-486.U.S. Geological Survey, pp. 220, 1996.  Back to cited text no. 7
[PUBMED]    
8.
M. G. McDonald, and A. W. Harbaugh, "A modular three dimensional finite difference ground water flow model," USGS Techniques of Water Resources Investigations. Book, 1996.  Back to cited text no. 8
    
9.
H. Biswas, A. Melesse, M. McClain, and M. Sukop, "Groundwater flow modeling using PMWIN model in the Wakal River basin, Rajasthan, India," Eos, Transactions American Geophysical Union, Vol. 89, no. 23, 2008. [JtAssem.Suppl, Abstract H41B-04].  Back to cited text no. 9
    
10.
H. D. Palma, and L. R. Bentley, "A regional-scale groundwater flow model for the Leon-Chinandega aquifer, Nicaragua," Hydrogeology Journal Vol. 15, no. 8, pp. 1457-1472, 2007.  Back to cited text no. 10
    
11.
W. Y. El Shar, and J. F. Rihani, "Application of the high performance computing techniques of Parflow simulator to model groundwater flow at Azraq," Water Resources Management, Vol. 21, no. 2, pp. 409-425, 2007.  Back to cited text no. 11
    
12.
GEC 1997, "Groundwater Resource Estimation Methodology - Report of the Groundwater Resource Estimation Committee," New Delhi: Ministry of Water Resources, Government of India; 1997.  Back to cited text no. 12
    
13.
M. P. Kaushal, "Simulation approach for optimal allocation of water resources in a tract," Ph.D. dissertation. Punjab Agricultural University, Ludhiana, India, 1988.  Back to cited text no. 13
    
14.
P. Singh, "Groundwater Basin Simulation of Upper Bari Doab Canal Tract.M.Tech Thesis," Ludhiana India: Punjab Agricultural University; 1990.  Back to cited text no. 14
    
15.
A. K. Jain, "Development of an expert system for optimal utilization of water resources," Ph.D Dissertation, Punjab Agricultural University, Ludhiana, India, 1995.  Back to cited text no. 15
    
16.
R. Aggrawal, "Optimal groundwater management in South West Punjab. Ph.D. Dissertation," Ludhiana, India: Punjab Agricultural University; 2001.  Back to cited text no. 16
    

 
   Authors Top


Dr. Pamela Miglani, ex student of Punjab Agricultural University has specialization in Groundwater Modeling (MODFLOW), developed decision support system for groundwater resource management. Adequate exposure to GIS





Dr. Rajan Aggarwal, working as Senior Research Engineer cum Principal Investigator of AICRP Groundwater Utilization in the Department Soil & Water Engineering with specialization in Groundwater modeling, Rainwater harvesting and Climate resilient agriculture. Published more than 130 publications in international/national Journals, book chapters etc



Dr. Samanpreet Kaur, working as Assistant Research Engineer in AICRP Groundwater Utilization in the Department Soil & Water Engineering with specialization in GIS, Groundwater, Crop and Climate modeling. Published more than 33 publications in refereed international/national Journals


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
 
 
    Tables

  [Table 1], [Table 2]


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