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The application of system dynamics techniques is gaining significance and is much needed for an effective management of the depleting water resources in a dynamically complex region and considers it as the feedback from the system. The present study deals with the application of a system dynamic approach to simulate a chain of four tanks in the Guduvanchery watershed, Tamil Nadu, India. Standard data-driven models cannot be effectively used due to a lack of quality data for ungauged basins. VENSIM was used for the system dynamic simulation to assess water availability for the sustainable management of water resources. Inflow into the four tanks, net losses in each tank, and crop water requirement were given as inputs into VENSIM. Along with different models, an extensive field survey was carried out to quantify each input component. Based on system dynamics simulation, only 28% of the total available water is used for irrigation and the rest is wasted due to evaporation, transition loss, and spill from the tanks. It was found that there was approximately 5.46 MCM of surface water available in the watershed, and it will be able to supply the domestic demand of the watershed of 0.672 MCM in addition to the irrigation requirement.

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  • Hydrological modelling and simulation are essential for the effective management of water resources in semi-arid regions.

  • The present study deals with the application of a system dynamic approach to simulate a chain of four tanks.

  • The water balance study for the chain of tanks indicates that only 28% of the total available water is used for irrigation, with the remainder lost due to evaporation, transition loss, and spill.

chain of tanks, hydrological modelling, NRCS model, runoff, simulation, VENSIM
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South India has a rich tradition of tanks. Tank irrigation is a storage-based irrigation scheme widely practised in south India; and hence, the terminology ‘tank’ is limited to India only. The area under tank irrigation declined drastically from the 1970s and has led to an increased extraction of groundwater. Also, India is rapidly urbanizing; consequently, the demand for water is increasing in most cities as every urban citizen requires almost double the amount of water than a rural citizen requires. Furthermore, since India's cities face water shortages, groundwater abstraction has become unavoidable, resulting in a decline in the groundwater table. There is an urgent need to improve the groundwater table in cities in order to sustain the groundwater resource. This research pertains to a scientific approach to accessing the available surface water potential from a chain of four tanks in the Guduvanchery watershed. The land-use changes in the peri-urban areas modify the drainage pattern, thereby changing the catchment area of the tanks leading to water stagnation and flooding consequently reducing the inflow into the tanks. A scientific approach is needed to assess the present status of existing water bodies and surface water budgeting to identify the opportunities for sustainable surface water use.

The water requirement is increasing to meet the demand of the growing population due to urbanization. The assessment of the water availability in a watershed is essential for an efficient water management. The Natural Resource Conservation Service (NRCS) model (SCS 1956) is widely accepted for runoff computation for small watersheds. The NRCS runoff curve number method was extensively used by researchers for runoff computation (Meher & Jha 2011; Tedela et al. 2012; Panahi 2013; Raji et al. 2021). For a long time, the model has been used to simulate the hydrology of minor watersheds all over the world. Several researchers in Tamil Nadu used the NRCS curve number approach and found it to be beneficial for estimating surface runoff in several basins. (Mohan & Abraham 2010; Viji et al. 2015; Santhanam & Abraham 2018). An elaborative study on the Soil Conservation Service-curve number (SCS-CN) method was conducted by Mishra & Singh (2004). Runoff computation by CN Nomograph for watersheds was demonstrated by Srinivas et al. (1997). Soulis et al. (2009) applied the Soil Conservation Service (SCS) method for a forest watershed and found it very effective in runoff computation. The NRCS runoff curve number approach can be utilized for runoff estimation in small ungauged watersheds, according to Krisnayanti et al. (2021). Remote sensing and GIS technique were found to be very effective in the SCS-CN model with spatial and temporal variabilities in soil and land use (Zhan & Huang 2004; Geetha et al. 2007; Satheeshkumar et al. 2017).

Modelling of ungauged catchments using catchment runoff response similarity was worked by Tegegne & Kim (2018). The robustness of agricultural reservoirs in ungauged catchments under climate change was studied using a Ratio Correction Factors-Based Calibration and Run theory (Lee et al. 2020). Jun et al. (2020) used flood vulnerability as a criterion for prioritizing and assessing the reservoir study. The flood indicators created in the study were shown to be beneficial in determining the impact of hydraulic structure repair. The SWAT model was used by Ramabrahmam et al. (2021) to study the hydrological processes and flow routing in the Salivagu watershed tank cascade system in Telangana, which improved the knowledge of hydrological processes in ungauged cascading tank systems in tropical semi-arid environments. Hamzah et al. (2021) examined the performance of three imputation approaches in predicting the recurrence in streamflow datasets: robust random regression imputation (RRRI), k-nearest neighbours (k-NN), and classification and regression tree (CART). Furthermore, the whole historical daily streamflow data from 2012 to 2014 (as training dataset) were used to assess and validate the effectiveness of the imputation methods in addressing missing streamflow data. Following that, streamflow rates in Malaysia's Langat River Basin were restored using all three methods combined with multiple linear regressions (MLRs).

There are various studies related to the use of VENSIM in the simulation of reservoirs in water resources. Based on long-term aquifer responses to hydrological variability, Niazi et al. (2014) evaluated the recharge and outflow dynamics within the Sirik area of the Iran aquifer system. A regional modelling framework that includes aquifer storage and recovery (ASR) as well as a dam design was constructed utilizing VENSIM's system dynamics (SD) modelling. ASR was found to be a beneficial technique for farmers and the groundwater system using the SD model of the groundwater flow and the complete SD model developed in the study. Mandal et al. (2019) studied the impact of climate change on hydropower production from a multi-reservoir system using a VENSIM model and demonstrated the robustness of SD modelling. Ganji & Nasseri (2021) developed an SD model using Vensim to simulate the effects of climate change on the water quality and quantity of the Karoun River, Iran. It was reported that SD is the best tool for assessing various scenarios because of its feedback loops. Nozari et al. (2021) assessed the performance of Dez Reservoir using the SD method in VENSIM. The simulation was carried out after assessing the effective parameters and their relationships. It was reported that SD-simulated releases met downstream demands and the method is very accurate in simulating the performance of the surface tank system.

It is very important to plan how to utilize the existing water and create a balance between the requirement and availability. The main objective of the study is to assess the surface water availability through the simulation of the chain of tanks. The uniqueness of the study is that the watershed is ungauged. Due to urbanization and depleting water supplies, the irrigated areas of the tanks have been drastically decreasing at an alarming rate. Standard data-driven models cannot be effectively used due to a lack of quality data for ungauged basins. Many hydrological models are at the basin scale, which have only limited regional and local applications. A micro-level simulation study with adequate field observations was carried out to solve the problem. Uncertainties in data and modelling are reduced by doing field verification. The results from the study can be used to derive the strategies to increase utilizable water in ungauged watersheds.

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The Guduvanchery watershed covering an area of 50 km2 is a part of the Adyar basin, in the Kancheepuram district of Tamil Nadu. The region lies between the latitudes of 12 °50′N and 12 °47′N, and the longitudes of 80 °02′E and 80 °06′E. The elevation ranges from 0.5 to 230 m above sea level. The district's temperatures range from 37.1 to 20.5 °C. Figure 1 shows an index map of the study area. The peculiar problems faced by the watershed include the following: (i) watershed lying in the over-exploited block; (ii) large-scale development in this area due to fast urbanization; and (iii) continuous reduction in cropping area. The North-East monsoon brings rain to the study region mostly in October and November. The yearly average rainfall is 1,150 mm. The chain of tanks in Guduvanchery consists of four tanks, namely Kayarambedu tank, Kannivakkam tank, Perumattunallur tank, and Nandhivaram tank. A spill from the Kayarambedu tank is flowing to the Nandhivaram tank, one from the Kannivakkam tank is flowing to the Perumattunallur tank, and then finally reaches the Nandhivaram tank. Hydraulic particulars of the tanks and crop and irrigation details were collected from the Public Works Department (Table 1). The available daily rainfall data during the period 2000–2014 for Chengalpet were collected from the India Meteorological Department (IMD), Pune, India.
Table 1

Tank particulars of the watershed

DescriptionKayarambedu tankKannivakkam tankPerumattunallur tankNandhivaram tank
Bund length (m) 1,000 700 1,300 1,000 
Original ayacut (ha) 172.80 57 58.68 339.50 
Present ayacut (ha) 136.07 7.44 Nil 136.50 
Capacity (MCM) 1.33 0.39 2.06 1.69 
No. of sluice 2 2 2 5 
No. of weir 1 1 2 2 
Water spread area (km2) 0.98 0.28 0.93 4.58 
DescriptionKayarambedu tankKannivakkam tankPerumattunallur tankNandhivaram tank
Bund length (m) 1,000 700 1,300 1,000 
Original ayacut (ha) 172.80 57 58.68 339.50 
Present ayacut (ha) 136.07 7.44 Nil 136.50 
Capacity (MCM) 1.33 0.39 2.06 1.69 
No. of sluice 2 2 2 5 
No. of weir 1 1 2 2 
Water spread area (km2) 0.98 0.28 0.93 4.58 
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Figure 1
An index map of the study area.
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An index map of the study area.

Figure 1
An index map of the study area.
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An index map of the study area.

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The methodology consists of data collection and field survey, net loss calculation, irrigation demand computation, inflow estimation, and tank simulation. The methodology adopted is given in Figure 2. An extensive field data collection and questionnaire survey were necessary during each stage, especially to check the inflow calculated from hydrological modelling and to get the net losses. Toumi & Remini (2021) did an extensive field survey to determine the phenomenon of water leakage at the Hammam Grouz dam in Algeria. Eberlein & Peterson (1992), Vensim (2014) was used for the tank simulation. The inflow is computed using the NRCS model and is verified using the change in storage computed using the tank water levels. The net loss is calculated using the reduction in water level during the periods of no rainfall. The simulation model was run with monthly time step.
Figure 2
Flow charts explaining the methodology.
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Flow charts explaining the methodology.

Figure 2
Flow charts explaining the methodology.
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Flow charts explaining the methodology.

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Inflow estimation

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Using a daily time step, the United States Department of Agriculture (USDA), NRCS—Hydrologic model was used to assess surface runoff from rainfall (Chow et al. 1988).
(1)
(2)
where P is the rainfall, in mm, CN is the curve number which ranges between 0 and 100, S is the potential maximum retention, Ia is the initial abstraction, (Ia = 0.2 S), and Q is the runoff, in mm.
Curve numbers take care of the surface condition of the watershed. Dry condition (Antecedent Moisture Condition (AMC) I) and wet condition (AMC III) are assessed using 5-day antecedent rainfall. Less than 13, 13–28, and above 28 mm rainfall during the antecedent 5-day period gives rise to AMC I, II, and III status, respectively (Chow et al. 1988). The curve numbers for each land use can be obtained for average AMC II and can be converted for other conditions using the following relationships (Chow et al. 1988).
(3)
(4)
where CNI is the CN for AMC I, CNII is the CN for AMC II, and CNIII is the CN for AMC III.

The NRCS model was employed with a daily time step to estimate runoff from 2000–2001 to 2013–2014. The inflow estimated is verified by estimating the change in storage by conducting the field study.

Irrigation demand computation

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The area under tank irrigation is called ayacuts. Irrigation is practised only in the ayacuts of Nandhivaram and Kayarambedu tanks. A questionnaire survey was carried out to learn about the cropping season and crops cultivated. Brouwer & Heibloem's approach (1986) for calculating irrigation water demand was used. The Blaney–Criddle equation was used to compute potential evapotranspiration. Potential evapotranspiration (ETo) by the Blaney–Criddle method (Doorenbos & Pruitt 1977) is given by
(5)
where Tmean is the average daily temperature (°C) and p is the average daily percentage of annual daylight hours.
The crop coefficient (Kc) for paddy was estimated for various stages and crop water need was determined as
(6)

Other water requirements are taken into account, such as the amount of water required for saturating the soil for land preparation (SAT), percolation and seepage losses (PSL), and the amount of water required to establish a water layer (WL).

The effective rainfall (Pe) is calculated using the formulae

  • Pe = 0.8 P − 25 when P > 75 mm/month, and

  • Pe = 0.6 P − 10 when P < 75 mm/month where P is rainfall in mm/month.

Irrigation water demand was calculated as
(7)

Tank simulation

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The tank simulation was carried out using the VENSIM (Eberlein & Peterson 1992) software.

Figure 3 shows the stock and flow diagram of the tank system developed in VENSIM. In Figure 3, the stock variables (tank) are rectangles, fluxes (flow rates) are arrows as seen in the figure (inflow, outflow, and losses), the interdependency of the variables is represented by arrows, and other parameters are represented as auxiliary variables.
Figure 3
Indicator diagram—VENSIM.
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Indicator diagram—VENSIM.

Figure 3
Indicator diagram—VENSIM.
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Indicator diagram—VENSIM.

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The mass balance equation is
(8)

  • where ΔS is the change in storage, I is the inflow, and O is the outflow.

Inflow is from the rainfall and outflow is the release for irrigation through sluice and/or spills.

Evaporation and infiltration from the tank together are accounted as net losses.

The equation becomes
(9)

The following details were given as input for the tank simulation:

  • The monthly inflow

  • Water depth–water spread area–storage capacity relationship

  • Monthly net loss in the depth unit

  • Full tank capacity

  • Tank storage at the start of the simulation

The net loss due to both evaporation and infiltration estimated in the depth unit is multiplied by the average water spread area (water spread area at the beginning and end of the period). The water spread area corresponding to given storage is determined by interpolating the storage capacity–water spread area relationship.

For a given period, the inflow is added to the beginning storage to determine the total storage (TS). The demand for irrigation (DI) and the net losses (NL) requirement is to be met from TS. If TS is very high, then the tank gets filled up reaching its full capacity (FC) and spill (SPL) occurs. The cases that arise are:

Case (A) TS < NL

Case (B)  TS < NL + DI

Case (C) TS > NL + DI, and

     TS(NL + DI) < FC

Case (D)  TS > NL + DI, and

     TS(NL + DI) > FC

The procedure followed in each case is as follows:

Case (A)  NL is equal to TS, No water is released to meet DI.

     End storage is zero.

Case (B)  Release to irrigation is equal to (TS-NL). DI is met partially. End storage is zero.

Case (C)  DI is met in full, NL is met, End storage = TS (DI + NL)

Case (D)  DI is met in full, NL is met, End storage = FC,

  SPL = TS(DI + NL + FC)

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The satellite imagery Resourcesat-2, LISS IV FMX dated 12 June 2014 obtained from NRSC, Hyderabad, toposheet and Google map were used to create a base map of the Guduvanchery watershed. The watershed boundary was taken from Watershed Atlas (AIS and LUS 1990) and verified with satellite imagery. The drainage area/catchment area for Kayarambedu, Kannivakkam, Perumattunallur, and Nandhivaram tanks were demarcated utilizing satellite imagery, toposheet, and Google Earth map. A contour map was drawn for the watershed of tanks in order to identify low-lying areas and also to identify the tank connectivity (Figure 4). Land-use maps of the watersheds of all four tanks are prepared with satellite imagery using ArcGIS software and the area under each land-use category was determined. Details of the land-use category and the areal extent under each category for the free catchment area of the four tank watersheds are given in Figure 5.
Figure 4
Elevation contours and flow directions for the tank watershed.
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Elevation contours and flow directions for the tank watershed.

Figure 4
Elevation contours and flow directions for the tank watershed.
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Elevation contours and flow directions for the tank watershed.

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Figure 5
A land-use map of the watershed of the Guduvanchery chain of tanks.
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A land-use map of the watershed of the Guduvanchery chain of tanks.

Figure 5
A land-use map of the watershed of the Guduvanchery chain of tanks.
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A land-use map of the watershed of the Guduvanchery chain of tanks.

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Water levels were measured for the period 18 September–30 November 2014 for all four tanks using scales prepared especially for that purpose. Figure 6 shows the daily rainfall and the water level in all four tanks during the year 2014. During periods when there was no rain, the water level dropped. The average water level decline per day for no rainfall periods is used to compute the net loss from the tank due to evaporation and infiltration from the tank bed. The daily net losses were computed for Kayarambedu, Kannivakkam, Perumattunallur, and Nandhivaram tanks and are 0.94, 0.79, 0.91, and 0.63 cm, respectively. A spot level survey was conducted for all four tanks to determine the elevation–water spread area–storage capacity relationship. The water spread areas for various depths were calculated using the elevation contours. The difference in contour height and average water spread area of the contours is used to calculate the storage capacity between the consecutive contours. Utilizing the water level in the tank, actual tank storage was computed. The water level in the tank is measured from a scale (Gauge) painted in posts fixed specially for that purpose. The spill level of the deepest sluice is taken as the datum and the depth of water in the tank is measured considering the datum as zero. By measuring the change in water level in the tank, the change in storage and, thus, the inflow into the tanks were determined.
Figure 6
Daily rainfall and water level in tanks during the year 2014.
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Daily rainfall and water level in tanks during the year 2014.

Figure 6
Daily rainfall and water level in tanks during the year 2014.
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Daily rainfall and water level in tanks during the year 2014.

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Hydrological modelling of tanks

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Water potential assessment for the four tank watersheds namely Kayarambedu, Kannivakkam, Perumattunallur, and Nandhivaram tanks were carried out by applying USDA–NRCS model using the inputs daily rainfall, land use, and hydrological soil group for the watershed (NRCS 2007). These watersheds fall under the Hydrologic soil group ‘D’. Hydrological modelling employs a daily time step and assumes the water year to be July–June of the ensuing year. For Kayarambedu and Kannivakkam tanks, only free catchment exists, whereas for Perumattunallur and Nandhivaram tanks, both free catchment and intercepted catchment are present. The catchment area which drains only into the tank under consideration is the free catchment. The free catchment areas of Kayarambedu, Kannivakkam, Perumattunallur, and Nandhivaram tanks are 3.375, 1.675, 2.721, and 12.882 km2, respectively. Hydrological modelling for all four tanks is carried out only with free catchment. From the land-use category, the weighted curve number for Kayarambedu, Kannivakkam, Perumattunallur, and Nandhivaram tank catchment areas was found to be 80.52, 81.48, 83.21, and 82.56, respectively. The hydrological model is then used to determine runoff for the 14 years, namely from 2000–2001 to 2013–2014 on daily basis. Water levels in the tanks were monitored daily during September–November 2014. The runoff calculated using the NRCS model for the same time period was compared to the amount of water collected in the tank by actual daily tank stage measurement during the rainy season, thus field verifying the NRCS model. Monthly runoff was determined by summing up the daily runoff (Table 2). These monthly runoffs are used as input for simulation.

Table 2

Estimated rainfall and runoff from the NRCS model for the study period

Water yearRainfall
Runoff from tank catchments
No. of daysDepth mmKayarambedu
Kannivakkam
Perumattunallur
Nandhivaram
Depth mm% of RainfallDepth mm% of RainfallDepth mm% of RainfallDepth mm% of Rainfall
2000–2001 39 1,092.3 247.81 22.69 262.91 24.07 292.36 26.77 280.92 25.72 
2001–2002 49 1,211.1 290.20 23.96 303.02 25.02 328.01 27.08 318.29 26.28 
2002–2003 28 575.7 67.79 11.78 72.91 12.66 83.30 14.47 79.20 13.76 
2003–2004 65 1,765.8 423.48 23.98 446.16 25.27 490.31 27.77 473.16 26.80 
2004–2005 44 1,648.0 653.76 39.67 677.49 41.11 722.30 43.83 705.12 42.79 
2005–2006 59 3,608.0 2,110.84 58.50 2,156.32 59.76 2,240.11 62.09 2,208.29 61.21 
2006–2007 38 1,379.0 624.76 45.31 640.69 46.46 670.45 48.62 659.10 47.80 
2007–2008 71 1,899.5 668.71 35.20 691.46 36.40 734.79 38.68 718.11 37.81 
2008–2009 44 1,238.8 464.20 37.47 479.68 38.72 508.76 41.07 497.65 40.17 
2009–2010 55 1,439.0 489.95 34.05 508.76 35.36 544.62 37.85 530.82 36.89 
2010–2011 67 1,489.0 410.98 27.60 428.94 28.81 463.17 31.11 449.98 30.22 
2011–2012 52 1,810.0 597.66 33.02 625.41 34.55 678.42 37.48 658.00 36.35 
2012–2013 60 1,435.4 397.87 27.72 415.07 28.92 448.35 31.24 435.43 30.34 
2013–2014 64 769.3 111.55 14.50 117.33 15.25 129.06 16.78 124.42 16.17 
Minimum 28 575.7 67.79 11.78 72.91 12.66 83.30 14.47 79.20 13.76 
Maximum 71 3,608.0 2,110.84 58.50 2,156.32 59.76 2,240.11 62.09 2,208.29 61.21 
Water yearRainfall
Runoff from tank catchments
No. of daysDepth mmKayarambedu
Kannivakkam
Perumattunallur
Nandhivaram
Depth mm% of RainfallDepth mm% of RainfallDepth mm% of RainfallDepth mm% of Rainfall
2000–2001 39 1,092.3 247.81 22.69 262.91 24.07 292.36 26.77 280.92 25.72 
2001–2002 49 1,211.1 290.20 23.96 303.02 25.02 328.01 27.08 318.29 26.28 
2002–2003 28 575.7 67.79 11.78 72.91 12.66 83.30 14.47 79.20 13.76 
2003–2004 65 1,765.8 423.48 23.98 446.16 25.27 490.31 27.77 473.16 26.80 
2004–2005 44 1,648.0 653.76 39.67 677.49 41.11 722.30 43.83 705.12 42.79 
2005–2006 59 3,608.0 2,110.84 58.50 2,156.32 59.76 2,240.11 62.09 2,208.29 61.21 
2006–2007 38 1,379.0 624.76 45.31 640.69 46.46 670.45 48.62 659.10 47.80 
2007–2008 71 1,899.5 668.71 35.20 691.46 36.40 734.79 38.68 718.11 37.81 
2008–2009 44 1,238.8 464.20 37.47 479.68 38.72 508.76 41.07 497.65 40.17 
2009–2010 55 1,439.0 489.95 34.05 508.76 35.36 544.62 37.85 530.82 36.89 
2010–2011 67 1,489.0 410.98 27.60 428.94 28.81 463.17 31.11 449.98 30.22 
2011–2012 52 1,810.0 597.66 33.02 625.41 34.55 678.42 37.48 658.00 36.35 
2012–2013 60 1,435.4 397.87 27.72 415.07 28.92 448.35 31.24 435.43 30.34 
2013–2014 64 769.3 111.55 14.50 117.33 15.25 129.06 16.78 124.42 16.17 
Minimum 28 575.7 67.79 11.78 72.91 12.66 83.30 14.47 79.20 13.76 
Maximum 71 3,608.0 2,110.84 58.50 2,156.32 59.76 2,240.11 62.09 2,208.29 61.21 
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Table 2 shows annual rainfall and runoff estimates from the NRCS model for the four tanks from 2000–2001 to 2013–2014. Fifty per cent dependable flow of 1.567, 0.804, 1.384, and 6.411 MCM is observed during 2008–2009 for Kayarambedu, Kannivakkam, Perumattunallur, and Nandhivaram watersheds, respectively.

Irrigation water demand computation

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Of the four tanks, Kannivakkam and Perumattunallur tanks have no ayacut area (irrigated area) under cropping. Hence, irrigation demand is computed only for the ayacuts of two tanks, namely Kayarambedu and Nandhivaram tanks. Kayarambedu tank has an ayacut of 136.07 ha. Paddy is cultivated from September to February of the ensuing year using water from the Kayarambedu tank as per the existing practices. Nandhivaram tank has an ayacut of 136.50 ha. Paddy crop is cultivated from October to March of the ensuing year with water supply from Nandhivaram tank as per the existing practices. Irrigation water demand was calculated for the representative year 2008–2009. A representative computation of irrigation demand for paddy for Kayarambedu tank ayacut is given in Table 3. The crop coefficient was adopted based on the type of crop and stages of the crop. The irrigation demand for paddy crop in the Kayarambedu and Nandhivaram ayacut areas works out to around 1,211 and 1,184 mm, respectively (Table 4). For Kayarambedu and Nandhivaram ayacuts, the actual irrigation water requirements calculated are 1,730.80 and 1,629.60 mm, respectively, assuming 70% efficiency. A questionnaire survey was conducted with 73 farmers in Kayarambedu tank ayacut and 76 farmers in Nandhivaram tank ayacut. This is to assess the status of the ayacut area. The area irrigated is around 70 ha as against 136.50 ha furnished by the Public Works Department, Government of Tamil Nadu.

Table 3

Details of computation of irrigation demand for paddy for the year 2008–2009 for the Kayarambedu tank ayacut

Month
ItemSeptemberOctoberNovemberDecemberJanuaryFebruarySeason
Percentage of annual daytime hours, p 0.28 0.27 0.26 0.26 0.26 0.27  
Average temperature Tmean (oC) 29.55 28.00 26.00 24.80 24.60 25.80  
Potential evapotranspiration, ETo (mm/day)  5.64 5.19 4.95 5.02 5.27  
Crop coefficient, Kc  1.10 1.10 1.20 1.30 1.00  
Crop water requirement ETcrop (mm/day)  6.20 5.71 5.94 6.53 5.27  
ETcrop (mm/month)  192.24 171.26 184.10 202.39 147.42  
SAT, mm 200.00       
PSL, mm/month @4 mm/day  124.00 120.00 124.00 124.00 112.00  
WL, mm  100.00      
Pe, mm 78.20 178.20 402.20 42.20 0.00 0.00  
Irrigation demand, mm 121.80 238.04 0.00 265.90 326.51 259.42 1,211.67 
Month
ItemSeptemberOctoberNovemberDecemberJanuaryFebruarySeason
Percentage of annual daytime hours, p 0.28 0.27 0.26 0.26 0.26 0.27  
Average temperature Tmean (oC) 29.55 28.00 26.00 24.80 24.60 25.80  
Potential evapotranspiration, ETo (mm/day)  5.64 5.19 4.95 5.02 5.27  
Crop coefficient, Kc  1.10 1.10 1.20 1.30 1.00  
Crop water requirement ETcrop (mm/day)  6.20 5.71 5.94 6.53 5.27  
ETcrop (mm/month)  192.24 171.26 184.10 202.39 147.42  
SAT, mm 200.00       
PSL, mm/month @4 mm/day  124.00 120.00 124.00 124.00 112.00  
WL, mm  100.00      
Pe, mm 78.20 178.20 402.20 42.20 0.00 0.00  
Irrigation demand, mm 121.80 238.04 0.00 265.90 326.51 259.42 1,211.67 
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Table 4

Irrigation demand for paddy crop in the tank ayacuts

Sl. No.MonthIrrigation demand in mm
Kayarambedu tank ayacutNandhivaram tank ayacut
1 September 174.00 _ 
2 October 340.06 31.14 
3 November 0.00 0.00 
4 December 379.86 357.94 
5 January 466.28 444.03 
6 February 370.60 433.78 
7 March _ 425.71 
Sl. No.MonthIrrigation demand in mm
Kayarambedu tank ayacutNandhivaram tank ayacut
1 September 174.00 _ 
2 October 340.06 31.14 
3 November 0.00 0.00 
4 December 379.86 357.94 
5 January 466.28 444.03 
6 February 370.60 433.78 
7 March _ 425.71 
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Simulation of tanks

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The simulation was carried out for all four tanks namely Kayarambedu, Kannivakkam, Perumattunallur, and Nandhivaram tanks, for a period of 14 years from 2000–2001 to 2013–2014 using VENSIM. The output from VENSIM includes the monthly tank storage, release to meet the agriculture demand, if any, and the spill if any for the known inflow for the entire period of simulation. From these data, the period for which the tank contains water, the total release, the total net losses, and the maximum storage reached in the tank can be obtained. The simulation results in essence will be used to look at the adequacy of the inflow to the tank for meeting the irrigation requirements of the tank ayacut and the amount of water available for further utilization. The simulation model runs on a monthly time step. To start with the live storage in the tank was taken as zero as on 1 July 2000. The inflow for simulation was arrived at by aggregating the daily runoff from the NRCS model. Demand for irrigation is present for Kayarambedu and Nandhivaram tanks only. Figure 7 shows the end month storage obtained from VENSIM for all four tanks.
Figure 7
The end month storage for the tanks.
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The end month storage for the tanks.

Figure 7
The end month storage for the tanks.
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The end month storage for the tanks.

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Irrigation release made from Kayarambedu tank and the spill from each tank and year-wise spill quantity are shown in Figure 8. Simulation findings revealed that the Kayarambedu tank, with an ayacut size of 136.07 ha, could not supply the irrigation requirement for a paddy crop cultivated between September and February for 13 years out of 14 years of study. Even though the area presently under irrigation is assessed to be only around 80 ha, the farmers are growing 2–3 crops in a year, so the tank water is fully utilized by the farmers. There is no scope to utilize Kayarambedu tank water for other purposes.
Figure 8
Irrigation release made from the Kayarambedu tank and the spill from each tank.
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Irrigation release made from the Kayarambedu tank and the spill from each tank.

Figure 8
Irrigation release made from the Kayarambedu tank and the spill from each tank.
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Irrigation release made from the Kayarambedu tank and the spill from each tank.

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Kannivakkam tank presently has no ayacut and hence the tank water is fully available for utilization. The full tank capacity is 0.39 MCM. Simulation results indicate that the tank gets filled up for 9 years out of 14 years and there is a spill. The spill reaches the Perumattunallur tank and Figure 8 shows the quantities of annual spill. As the tank gets filled up for more than 50% of the time, the entire storage of 0.39 MCM of water per annum on an average is available for utilization.

Perumattunallur tank has no ayacut and the tank water is fully available for utilization. The full tank capacity is 1.07 MCM. Simulation results indicate that the tank gets filled up for 7 years out of 14 years and there is spill. The spill reaches the Nandhivaram tank and Figure 8 shows the quantities of the annual spill. As the tank gets filled up 50% of the time, the entire storage of 1.07 MCM of water per annum on an average is available for utilization.

With an ayacut area of 136.50 ha, the Nandhivaram tank can provide the irrigation needs of a single crop of paddy cultivated from October to March. The full tank capacity is 1.69 MCM. Table 5 gives summary of simulation results year wise. Simulation results indicate that the tank gets filled up for 12 years out of 14 years and there is a considerable spill. The percentage of Nandhivaram tank's irrigation demand that was satisfied each year is shown in Figure 9. It can be seen that more than 50% of the demand is met for 12 years and more than 75% of the demand is met for 9 years. Figure 10 shows the annual spill from the tank in a semi log plot. Also, the area presently under irrigation is assessed to be only around 70 ha. On average, there is scope to utilize 4.0 MCM of water per annum.
Table 5

Summary of simulation of the Nandhivaram tank

YearaInflow, m3Release for irrigation
Net losses, m3Spill, m3Maximum storage reached, m3
m3% of demand
Tank capacity = 1,690,000 m3 Irrigation demand = 2,310,415 m3 
2000–2001 3,025,214 1,729,324 74.85 764,102 531,787 1,690,000 
2001–2002 4,268,663 1,925,960 83.36 1,153,476 1,189,227 1,690,000 
2002–2003 1,046,845 738,187 31.95 308,658 0 988,549 
2003–2004 4,860,385 1,348,051 58.35 1,089,824 2,422,510 1,690,000 
2004–2005 7,960,945 1,566,936 67.82 806,296 5,587,714 1,690,000 
2005–2006 35,960,665 2,062,617 89.27 1,123,235 32,774,812 1,690,000 
2006–2007 9,453,985 1,893,995 81.98 783,690 6,776,300 1,690,000 
2007–2008 10,110,472 2,310,415 100.00 1,305,440 6,107,384 1,690,000 
2008–2009 7,004,030 1,856,896 80.37 918,707 4,451,351 1,690,000 
2009–2010 6,963,809 2,062,617 89.27 841,097 309,298 1,690,000 
2010–2011 6,071,919 1,920,836 83.14 1,052,757 3,098,326 1,690,000 
2011–2012 9,004,315 1,985,914 85.95 1,197,938 5,820,463 1,690,000 
2012–2013 5,900,009 1,917,366 82.99 1,072,682 2,909,960 1,690,000 
2013–2014 1,659,397 1,037,890 44.92 621,507 0 1,198,087 
YearaInflow, m3Release for irrigation
Net losses, m3Spill, m3Maximum storage reached, m3
m3% of demand
Tank capacity = 1,690,000 m3 Irrigation demand = 2,310,415 m3 
2000–2001 3,025,214 1,729,324 74.85 764,102 531,787 1,690,000 
2001–2002 4,268,663 1,925,960 83.36 1,153,476 1,189,227 1,690,000 
2002–2003 1,046,845 738,187 31.95 308,658 0 988,549 
2003–2004 4,860,385 1,348,051 58.35 1,089,824 2,422,510 1,690,000 
2004–2005 7,960,945 1,566,936 67.82 806,296 5,587,714 1,690,000 
2005–2006 35,960,665 2,062,617 89.27 1,123,235 32,774,812 1,690,000 
2006–2007 9,453,985 1,893,995 81.98 783,690 6,776,300 1,690,000 
2007–2008 10,110,472 2,310,415 100.00 1,305,440 6,107,384 1,690,000 
2008–2009 7,004,030 1,856,896 80.37 918,707 4,451,351 1,690,000 
2009–2010 6,963,809 2,062,617 89.27 841,097 309,298 1,690,000 
2010–2011 6,071,919 1,920,836 83.14 1,052,757 3,098,326 1,690,000 
2011–2012 9,004,315 1,985,914 85.95 1,197,938 5,820,463 1,690,000 
2012–2013 5,900,009 1,917,366 82.99 1,072,682 2,909,960 1,690,000 
2013–2014 1,659,397 1,037,890 44.92 621,507 0 1,198,087 

Note: aJuly–June of ensuing year.

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Figure 9
Irrigation demand met from the Nandhivaram tank.
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Irrigation demand met from the Nandhivaram tank.

Figure 9
Irrigation demand met from the Nandhivaram tank.
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Irrigation demand met from the Nandhivaram tank.

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Figure 10
A semi log plot of spill from the Nandhivaram tank.
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A semi log plot of spill from the Nandhivaram tank.

Figure 10
A semi log plot of spill from the Nandhivaram tank.
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A semi log plot of spill from the Nandhivaram tank.

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Surface water budgeting of chain of tanks

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Water budgeting for the watershed of a chain of tanks for 50% dependable year, 2008–2009 indicates that the total quantum of water available is 10.77 MCM. The available water is from three components, namely (i) the free catchment inflow into each of the tanks put together comes to 10.16 MCM (94.3%), (ii) irrigation return flow from Kayarambedu tank ayacut reaching Nandhivaram tank comes to 0.35 MCM (3.2%), and (iii) the net water available from carryover storage from the previous year namely 2007–2008 and carryover storage to the ensuing year namely 2009–10 for both Kannivakkam and Perumattunallur tanks comes to 0.26 MCM (2.5%).

The total utilization which comes to 10.77 MCM is assessed under four components, namely (i) irrigation release from Kayarambedu and Nandhivaram tanks is 3.02 MCM (28.0%), (ii) the net losses from all the four tanks is 3.37 MCM (31.3%), (iii) the spill from Nandhivaram tank is 4.23 MCM (39.3%) as it is the terminal tank, the spill from which leaves the watershed; and (iv) the transmission loss from the spill of Kannivakkam and Perumattunallur tanks is 0.15 MCM (1.4%). The present water availability and utilization from the watershed are shown in Figure 11.
Figure 11
Water availability and water utilization in the watershed of chain of tanks.
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Water availability and water utilization in the watershed of chain of tanks.

Figure 11
Water availability and water utilization in the watershed of chain of tanks.
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Water availability and water utilization in the watershed of chain of tanks.

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Kancheepuram district's population density is 892/km2 (Census of India 2011). The domestic water consumption of the watershed with an aerial extent of 20.625 km2 is 1,840 m3/day or 0.672 MCM per year, assuming a per capita water requirement of 100 L/day.

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In the present study, a scientific methodology is developed to examine the adequacy of the inflow to the tank for meeting the irrigation requirements of the tank ayacut and the amount of water available for further utilization. Hydrologic modelling along with simulation modelling can effectively be utilized for irrigation scheduling of small watersheds for sustainable management of available water resources. The study indicates that in total there is scope to utilize around 5.46 MCM water after meeting the irrigation requirement of its ayacut area. Even if half of the available water can be effectively utilized, around 2.73 MCM is available for further use in the watershed. According to the study for the chain of tanks, only 28% of the total available water is used for irrigation, with the remainder wasted due to evaporation, transition loss, and spill from the tanks. As the minimum available water is estimated to be around 2.73 MCM, demand from future development and demand from neighbouring regions, in addition to the watershed's present domestic demand of 0.672 MCM, may also be met if the available water is adequately captured. It is suggested that the authorities have to take necessary initiatives for the frequent maintenance of the tank to avoid a reduction in storage due to silting. One of the advantages of system dynamic study is that the changes in the system can be simulated easily using the developed VENSIM model. Future research can be oriented to study the effect of land-use/land-cover change and climate change effect on water resources in these tanks catchment.

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The work was carried out with the fund provided by the Natural Resources Data Management System (NRDMS), Department of Science and Technology, Government of India.

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All relevant data are included in the paper or its Supplementary Information.

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The authors declare there is no conflict.

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