Abstract

This paper proposes scenarios to achieve more crop per drop and irrigation for all in water-scarce irrigation systems, with a particular reference to India. It uses economic water productivity (EWP) and water cost curve for EWP as tools to reallocate irrigation consumptive water use (CWU) and identify economically viable cropping patterns. Assessed in the water-scarce Sina irrigation system in Maharashtra, India, the method shows that drought-tolerant annual crops such as fruits and/or fodder should be the preferred option in irrigated cropping patterns. Cropping patterns with orchard or fodder as permanent fixtures will provide sustainable income in low rainfall years. Orchards in combination with other crops will increase EWP and value of output in moderate to good rainfall years. Governments should create an enabling environment for conjunctive water use and allocation of CWU to achieve a gradual shift to high-value annual/perennial crops as permanent fixtures in cropping patterns.

Highlights

  • Economic water productivity is a critical performance indicator when water has an opportunity cost.

  • Water cost curve assesses the financial trade-off of different cropping patterns.

  • Adapting to weather variability is imperative for water-scarce irrigation systems.

  • Drought-tolerant annual crops should be a permanent feature in cropping patterns.

  • Enabling a policy environment for conjunctive water use is necessary for change.

Introduction

Along with climate change, increasing population, changing lifestyles, and increasing sectoral water demand are expected to exacerbate the vulnerability to and risks of natural disasters (Scott et al., 2018; Rasul et al., 2019; Ray & Shaw, 2019; Shamsudduha & Panda, 2019). In South Asian countries, the agriculture sector uses about 80–90% of the water withdrawals and provides livelihoods for a large rural population. In India, agriculture's reliance on monsoon rainfall makes it highly vulnerable to climate variability and climate change. The projected implications of climate change for water and agriculture call for a much-needed focus on efficient water use in agriculture to build resilience and meet future water challenges (Mirza, 2011).

Efficiency and productivity of water use dominate the discourse on irrigation performance in general and canal irrigation systems in particular (Shah, 2013; Kumar, 2018). In India, low water-use efficiency (WUE) and water productivity (WP), and the widening gap between the irrigation potential created (IPC) and the irrigation potential utilized (IPU) are the major concerns in canal irrigation. Given the increasing incidence and magnitude of natural disasters (IPCC, 2014), more crop per drop or higher water productivity and access to irrigation are timelier solutions now than ever before to enhance resilience in the agriculture sector (Brauman et al., 2013; Kumar & van Dam, 2013). In India, the government's initiative for the agriculture sector, named Prime Minister's Krishi Sinchayee Yojana (PMKSY) (https://pmksy.gov.in), has twin goals: more crop per drop and ‘Har Kheth ko Pani’ or irrigation for all farms. How water-scarce canal irrigation systems can realize these two goals is the focus of this paper.

First, what do we mean by more crop per drop? The most commonly cited measure of this proposition is the quantity of production per unit of water use, i.e., physical water productivity (PWP), expressed in kg/m3 (Molden et al., 2003, 2010). The other popular measure is the value of production per unit of water use, i.e., economic water productivity (EWP), expressed in $/m3. However, with water scarcities and risks increasing, EWP also needs to consider the net value of output, i.e., profit per unit of water use (Fernández et al., 2020). The water use in the denominator of PWP and EWP can be total or irrigation water use. In irrigation systems, the water use measure frequently used is either irrigation supply, or irrigation, or full consumptive water use (CWU).

Water productivity in India varies substantially. Between states, rice PWP varies from 0.57 kg/m3 in Punjab, predominantly under groundwater irrigation, to 0.24 kg/m3 in Karnataka with mainly surface irrigation (Sharma et al., 2018). The wheat PWP between districts varies from 0.24 kg/m3 in the eastern and western regions to as high as 2.03 kg/m3 in the north-western region (Sharma et al., 2018). In the Indo-Gangetic basin, rice PWP varies from 0.5 to 1.32 kg/m3 from the north-western to eastern regions (Cai & Sharma, 2010). In Uttar Pradesh in the Ganges Basin, wheat PWP varies from 0.41 to 0.81 kg/m3 (Sharma et al., 2018). In the western region, in Maharashtra in the Bhima river basin, sugarcane PWP varies from 8 to 12 kg/m3, and sorghum and millet PWPs vary between 0.01 and 1.8 kg/m3 (Garg et al., 2012). These PWPs are significantly smaller in dry years. For example, the EWP of millet ranges from 0.026 to 0.047 $/m3. These variations in PWP and EWP show a substantial scope for improvement of PWP and EWP, and they can play a major role in water-scarce basins such as Bhima.

However, when water is plentiful and the opportunity cost of water use is low, WP has little role to play in water management. When water demand is high, water scarcities emerge, and the opportunity cost of water use is high, WP has a substantial role to play. In such cases, planning for interventions needs to shift focus, first to increasing PWP (the physical production of different crops per unit of water, kg/m3), and then to increasing EWP (the value of production per unit of water, $/m3) at the system level (Sharma et al., 2018; GOI, 2019). Ultimately, when the opportunity cost is too high, the economic productivity of water (value of production per value of water) will play a role, and water transfers from low-value to high-value production processes will emerge.

However, the more crop per drop principle can sometimes curtail access to irrigation for all. In water-scarce irrigation systems, the potential for increasing irrigation CWU or crop evapotranspiration is not high (Perry et al., 2009; Grafton et al., 2018), except where the non-beneficial evaporation part of the CWU is substantial (Kumar & van Dam, 2013). Better agronomic practices, including management of inputs, can reduce non-beneficial evaporation and increase yield, and hence PWP. Therefore, the potential for increasing beneficial CWU is low in highly water-scarce irrigation systems. Further, an increase in irrigation CWU in one location could be at the expense of beneficial CWU in other locations. Therefore, the next option for water-scarce irrigation systems is to increase EWP (value and profit/m3) (Fernández et al., 2020). With the focus on EWP, all stakeholders can potentially receive irrigation and income even under increased climatic variability and water scarcity.

Many irrigation systems in India face increasing climatic risks. The Sina irrigation system in Maharashtra is a typical water-scarce irrigation system in India. It had sufficient water for irrigation through canals in just 3 years in the past decade (Amarasinghe et al., 2020). Inadequate monsoon rainfall restricts water releases to the canal command area (CCA) and reduces groundwater irrigation in the water influence zone (WIZ). However, there is potential for more crop per drop and irrigation for all, even in dry years through reallocation of irrigation CWU.

This paper assesses strategies for reallocation of CWU and thereby increasing EWP in the Sina irrigation system. It develops scenarios of water allocation and a water cost curve (WCC) to assess the trade-off. The baseline for scenario development is a year with good rainfall and reservoir storage. The WCC assesses the hydro-economic trade-off of increasing EWP through different cropping patterns. The scenario analysis considers EWP of profit per unit of irrigation CWU as an instrument for water reallocation.

In the next section on methodology and data, we present the approach to developing these scenarios and the WCC for an assessment of the reallocation of CWU and the relevant trade-offs. Next, we present the results of our assessment and discuss the impacts of CWU reallocation. In the final section, we discuss policy recommendations.

Methodology and data

Data

The critical set of data for scenario analysis is a reliable estimate of the baseline cropping pattern. The primary source of data for cropping patterns is the land-use pattern derived from satellite data (Figure 1). Satellite-based data give an accurate picture of the land-use pattern in the Sina WIZ, including the CCA, a 1 km buffer zone outside the CCA, and the reservoir lift irrigated area (RLIA), the area of the catchment where farmers lift water for irrigation directly from the reservoir.

Fig. 1.

The land-use pattern in the Sina water influence zone (WIZ) in 2010–11 post-monsoon season. Source:Amarasinghe et al. (2020).

Fig. 1.

The land-use pattern in the Sina water influence zone (WIZ) in 2010–11 post-monsoon season. Source:Amarasinghe et al. (2020).

Sina irrigation scheme is in the Pune irrigation circle of Ahmednagar district in Maharashtra, India (Figure 1). Sina is a water-scarce medium irrigation system, and the reservoir has gross and live storage capacities of 67.95 million cubic meters (Mm3) and 52.30 Mm3, respectively. Amarasinghe et al. (2020) show that groundwater irrigation is widespread in Sina WIZ, which mainly lies in the hard-rock region of Maharashtra. Basalt is the aquifer system underneath. The basalts usually have medium to low permeability. The soil in the Sina command area is medium to fine-textured with some clay and sand content. The depth of soil in 85% of Sina project command falls under moderately deep to very deep.

Natural groundwater recharge from rainfall is estimated as 10% of total available water through rainfall (GoI, 2017) in the Sina command area. In the year 2016–17, the total available water through rainfall in the command area is estimated as 70.8 Mm3, in which 7.08 Mm3 contribute to groundwater recharge. The other major source for groundwater recharge is the unlined right bank canal, which runs in 73 km length with variable water depth in the head, middle, and tail region and having an average running of 35 days per year. The recharge of 2.5 cumecs per million square meters of the wetted area through the canal is taken based on GEC-2015 guidelines. Sina left bank canal is a closed conduit, and hence, the total groundwater recharge through Sina right bank canal is estimated as 4.63 Mm3. Overall, the total groundwater recharge obtained through rainfall and unlined canal is 11.71 Mm3.

The Sina WIZ experiences substantial water scarcities due to variation of rainfall (Figure 2). Due to low monsoon rainfall (from June to September), the primary water source for Sina reservoir storage, there was little or no water supply in 4 years (2011–12, 2012–13, 2015–16, and 2016–17) since 2007. In 4 years (2008–09, 2009–10, 2010–11, and 2017–18), reservoir storage was full due to high monsoon rainfall, but the irrigation supply still has substantial variation. In fact, the rainfall, irrigation supply, and cropped area in 2010–11 were among the highest in the past two decades. Moreover, the cropping pattern was diverse too. Therefore, we use the 2010–11 cropping pattern as the baseline data for the scenario–trade-off analysis (Table 1).

Table 1.

Remote sensing/GIS estimates of cropping patterns in the Sina irrigation system in Maharashtra, India, in 2010–11 (post-monsoon seasons and annual crops).

SeasonLand-use patternRecommended cropping pattern for CCA (% of the total area)Cropped area (ha)
CCA% of total1 km buffer% of totalRLIA% of total
Post-monsoona Sorghum 47 2,799 33 2,114 34 1,251 23 
Wheat 27 186 123 165 
Fodder 45 26 30 
Other cropsb – 2,828 34 2,165 35 1,641 30 
Oilseeds 100 – – 313 
Vegetables 390 – – 1,024 19 
Annual crops Sugarcane 544 344 483 
Orchardsc 102 171 59 
Cotton 1,442 17 1,190 19 545 10 
Total Post-monsoon 95 6,348 75 4,428 72 4,424 80 
Annual crops 2,088 25 1,705 28 1,087 20 
Total 100 8,436 100 6,133 100 5,511 100 
Other land use 
  • Fallow or harvested

 
– 1,850 – 2,292 – 1,526 – 
  • Non-agricultural lands

 
– 1,544 – 2,479 – 1,402 – 
  • Settlements

 
– 92 – 60 – 86 – 
  • Area of surface water bodies

 
– – 45 – 693 – 
Total area – 11,435 – 11,010 – 8,195 – 
SeasonLand-use patternRecommended cropping pattern for CCA (% of the total area)Cropped area (ha)
CCA% of total1 km buffer% of totalRLIA% of total
Post-monsoona Sorghum 47 2,799 33 2,114 34 1,251 23 
Wheat 27 186 123 165 
Fodder 45 26 30 
Other cropsb – 2,828 34 2,165 35 1,641 30 
Oilseeds 100 – – 313 
Vegetables 390 – – 1,024 19 
Annual crops Sugarcane 544 344 483 
Orchardsc 102 171 59 
Cotton 1,442 17 1,190 19 545 10 
Total Post-monsoon 95 6,348 75 4,428 72 4,424 80 
Annual crops 2,088 25 1,705 28 1,087 20 
Total 100 8,436 100 6,133 100 5,511 100 
Other land use 
  • Fallow or harvested

 
– 1,850 – 2,292 – 1,526 – 
  • Non-agricultural lands

 
– 1,544 – 2,479 – 1,402 – 
  • Settlements

 
– 92 – 60 – 86 – 
  • Area of surface water bodies

 
– – 45 – 693 – 
Total area – 11,435 – 11,010 – 8,195 – 

Source: Recommended cropping patterns are from the irrigation department, and the areas are the authors' estimates.

aPost-monsoon season includes both Rabi (October to March) and summer season (March to June) crops. Oilseeds (groundnuts or soybeans) and vegetable area are based on the cropped area in the summer season.

bOther crops include pulses and oilseeds.

cOrchards include pomegranate, orange, lime, etc.

Notes: Post-monsoon season includes both Rabi and summer season crops. Oilseeds and vegetables IRCWU are based on the cropped area in the summer season.

Fig. 2.

Rainfall, reservoir storage, and irrigation supply of Sina. Source: Authors.

Fig. 2.

Rainfall, reservoir storage, and irrigation supply of Sina. Source: Authors.

The design command area of the Sina irrigation system is 8,444 hectares (ha). The recommended cropping pattern included 41% of the command area (about 3,460 ha) sown to seasonal crops in the Kharif season (monsoon season, June to September), another 56% (4,728 ha) is sown in rabi (post-monsoon season, October to March) and the hot-weather season (summer season, March to June). Annual crops account for 3% of the command area. Normally, the monsoon season crops use only rainfall. Irrigation starts in mid-October for the rabi season.

However, the total irrigated area in the Sina CCA in the 2010–11 post-monsoon season alone was about 8,400 ha, twice the area under the recommended cropping pattern. The total irrigated area in the WIZ in the post-monsoon season was about 20,000 ha, including 5,500 and 6,100 ha of cropped area in the RLIA and 1 km buffer zone.

The consumptive fraction of the Sina WIZ, even in high rainfall years such as 2010–11, was almost 100% (Amarasinghe et al., 2020). The consumptive fraction is the ratio of crop evapotranspiration from (intended and unintended processes) irrigation to total irrigation water withdrawals. Thus, Sina is a physically water-scarce system, in which not much water is available for further increase in irrigation CWU (IRCWU). The IRCWU is the evapotranspiration (from intended and unintended processes) of crops from the irrigation withdrawals (surface and groundwater). The total CWU is the sum of IRCWU and effective rainfall from cropped areas (see Amarasinghe et al. (2020) for details). Therefore, the strategy for Sina should be to increase the value (and the profit) of crop production with available CWU. For that, it is necessary to reallocate the available irrigation CWU.

Scenarios of CWU reallocation

The goal of the reallocation of CWU is to generate net income for farmers even in water-scarce years. Scenario analysis explores potential cropping patterns that increase EWP in non-water-scarce years and provide a profit even in water-scarce years. Interventions to increase EWP include crop or agricultural diversification, technological interventions such as micro or solar irrigation, or institutional innovations in water management (Cameira & Pereira, 2019). In Sina, high-value, less water-intensive annual/perennial crops should be an integral part of the cropping patterns.

The EWP (at constant 2010 prices) and irrigation CWU per ha of different crops in 2010–11 (Table 2) provide us with the baseline or business-as-usual scenario (BAU) information. This analysis considers only the post-monsoon and summer seasons and the annual crops since the irrigation CWU only pertains to these crops.

Table 2.

Yield, market price, EWP, and irrigation CWU (IRCWU) of different crops in 2010–11.

SeasonCropYieldPriceIRCWUEWP
(t/ha)(USD/t)(m3/ha)(USD/m3 unit of IRCWU)
Post-monsoona Sorghum 0.6 500 3,226 0.10 
Wheat 2.1 317 3,769 0.18 
Fodder (Lucerne) 40.0 69 4,206 0.56 
Other crops (pulses) 1.2 636 2,669 0.28 
Oilseeds 1.1 411 4,279 0.10 
Vegetables (onion) 13.2 308 5,090 0.81 
Annual/perennial crops Sugarcane 134.9 27 9,209 0.40 
Orchards (pomegranate) 7.2 939 6,326 1.07 
Cotton 0.4 895 2,732 0.12 
SeasonCropYieldPriceIRCWUEWP
(t/ha)(USD/t)(m3/ha)(USD/m3 unit of IRCWU)
Post-monsoona Sorghum 0.6 500 3,226 0.10 
Wheat 2.1 317 3,769 0.18 
Fodder (Lucerne) 40.0 69 4,206 0.56 
Other crops (pulses) 1.2 636 2,669 0.28 
Oilseeds 1.1 411 4,279 0.10 
Vegetables (onion) 13.2 308 5,090 0.81 
Annual/perennial crops Sugarcane 134.9 27 9,209 0.40 
Orchards (pomegranate) 7.2 939 6,326 1.07 
Cotton 0.4 895 2,732 0.12 

Source: Yield and prices are from the cost of cultivation survey database of the Maharashtra Government maintained by the Mahatma Phule Krishi Vidyapeeth (MPKV). The EWP and IRCWU are the authors' estimates (Amarasinghe et al., 2020).

Notes:aPost-monsoon season include both Rabi and summer season crops. Oilseeds and vegetables IRCWU are based on the cropped area in the summer season.

The analysis generated the following scenarios, assuming available irrigation CWU as the primary constraint.

  • Scenario A: Generate the same value of output as in good rainfall years such as 2010–11, with smaller irrigation CWU.

  • Scenario B: Generate some output under water-scarce conditions with no water supply from the reservoir and assuming only groundwater irrigation. Generally, with no irrigation supply, it is not possible to grow seasonal crops in the post-monsoon seasons. In such a scenario, farmers are left with virtually no income. Scenario B assesses the value of drought-tolerant annual crops – the cropping patterns that can generate some output under extremely dry weather conditions corresponding to a low rainfall year (once-in-10-years rainfall of about 250 mm/year). We estimate natural groundwater recharge as per the guidelines issued by the GoI (2017). For the semi-arid region in Sina, the natural recharge is 10% of the rainfall.

  • Scenario C: Generate more output than Scenario B under moderate rainfall conditions (3-in-4 years, or 75% dependable rainfall of about 450 mm/year. This amount of rainfall allows both canal and groundwater irrigation, although the reservoir has no full storage level by October 15.

  • Scenario D: Generate more output than 2010–11 under high rainfall conditions of more than 650 mm/year, which is the median rainfall in the Sina WIZ. Under high rainfall conditions, the reservoir has full storage by October 15 and allows full irrigation potential under both canal and groundwater irrigation.

WCC for EWP

The WCC for EWP assesses the trade-off of CWU reallocation. It assesses the annual cost of cultivation and the net value of the production (the value of production − the cost of cultivation) of different crops per unit of irrigation CWU. The cost of cultivation includes the cost of conventional methods as well as the annualized cost of various technologies used for cultivation or irrigation. The technologies and practices include the system of rice intensification (SRI), direct seeding of rice (DSR), alternate wetting and drying (AWD), alternate furrow irrigation (AFI), etc. (see Table 6 in the cost curve section for more details).

The cost of technology/practices is the direct cost associated with implementing them in the field. For practices such as SRI, it is the additional cost of inputs and resources required to implement key components of the technology and included as a variable cost. For technologies such as drip or sprinkler irrigation and subsurface irrigation, the annualized cost of the technology is the capital investment, which is estimated using
formula
where i is the interest rate (at 12.5% per annum) and n is the lifetime of the technology in years, here assumed to be 10 years.

Data for developing the cost curve are available from various studies conducted by research stations and irrigation agencies in India. They include the cost of technologies, cost of cultivation, delivery of irrigation water, crop yield, and farm harvest prices.

Results

Cropping patterns for the CCA

The actual cropping pattern in the 2010–11 BAU scenario is substantially different from those recommended at the design stage of the irrigation project (Table 3). Crops with low EWP, such as sorghum, cotton, and pulses, occupy a large irrigated area. Scenarios SA1, SA2, and SA3 cropping patterns under scenario A, showing the percentage of area under fodder, orchard (pomegranate), and vegetables (onion) that can generate the same output as of BAU.

Table 3.

Scenario A cropping patterns in the CCA.

SeasonCropCropping patterns (%) of post-monsoon and annual/perennial crops
Scenario A
Recommended for Sina2010–11 (BAU)SA1SA2SA3
Post-monsoona Sorghum 47 33    
Wheat 27    
Fodder 40.1   
Pulses 34    
Oilseeds    
Vegetables   23.1 
Annual/perennial crops Sugarcane    
Orchard  14.4  
Cotton 17    
Total percentage 100 100 40.1 14.4 23.1 
Total area (ha) 4,982 8,432 3,381 1,181 1,948 
Total IRCWU (Mm320 29.50 14.22 7.47 9.91 
Total output (M USD) 5.23 8.01 8.01 8.01 8.01 
Total output (% of BAU output) 65 100 100 100 100 
SeasonCropCropping patterns (%) of post-monsoon and annual/perennial crops
Scenario A
Recommended for Sina2010–11 (BAU)SA1SA2SA3
Post-monsoona Sorghum 47 33    
Wheat 27    
Fodder 40.1   
Pulses 34    
Oilseeds    
Vegetables   23.1 
Annual/perennial crops Sugarcane    
Orchard  14.4  
Cotton 17    
Total percentage 100 100 40.1 14.4 23.1 
Total area (ha) 4,982 8,432 3,381 1,181 1,948 
Total IRCWU (Mm320 29.50 14.22 7.47 9.91 
Total output (M USD) 5.23 8.01 8.01 8.01 8.01 
Total output (% of BAU output) 65 100 100 100 100 

Source: Authors' estimation.

Notes:aPost-monsoon season include both Rabi and summer season crops. Oilseeds and vegetables IRCWU are based on the cropped area in the summer season.

Bold values indicate that SA1–SA3 provide the same output.

The total irrigation CWU under the BAU scenario was 29.5 Mm3 and generated only USD 8.01 million value, with an overall EWP of 0.28 USD/m3 of irrigation CWU. Under a similar water supply regime, Scenario A cropping patterns SA1–SA3 can match the BAU output in a much smaller area. For example:

Scenario SA2 shows that pomegranate orchards, an annual crop, require only 14.4% of the BAU cropped area (i.e., only 1,181 ha of the 8,432 ha of the BAU area), and only 25% of the irrigation CWU.

Scenarios SA3 and SA1 show that seasonal crops such as vegetables (tomatoes) and fodder (Lucerne) require a little more area and CWU to generate the same output; tomatoes need only 1,948 ha, and fodder requires only 3,381 ha. Sugarcane has the fourth-highest EWP among the 2010–11 cropping patterns. Although sugarcane requires 26% of the area, it requires 67% of the irrigation CWU to generate the same output.

However, the SA1, SA2, and SA3 cropping patterns are not feasible under dry weather conditions when only groundwater irrigation is possible. The potential groundwater recharge in the CCA under conditions of once-in-10-years rainfall of 250 mm is about 2.8 Mm3. But the SA1–SA3 cropping patterns require more irrigation CWU than the available groundwater can supply under extremely dry weather conditions. The scenarios SB1 to SB3 show the fodder, orchards, or vegetable area that can grow with the available groundwater under extremely dry weather conditions.

Scenarios SB1SB3 show that groundwater irrigation CWU of about 2.8 Mm3 can support fodder, fruits, and vegetables in 8.0, 5.3, and 6.6% of the BAU area and generate about 20, 38, and 29% of the BAU output, respectively.

Some orchard crops (pomegranate, mango) and fodder (Lucerne) are drought-tolerant. These crops, grown in a slightly larger area than in Scenario SB1–SB3 with deficit irrigation, can still survive a severe drought period. In deficit irrigation, farmers meet water requirements only during critical periods of crop growth. That may result in a marginal loss of productivity compared with Scenario A but may still generate higher output than Scenario B. These are the cropping patterns that can provide a sustainable income when there are no canal water releases from the reservoir. Therefore, an ideal cropping pattern to withstand a severe drought in the Sina CCA could include fruits, such as pomegranate, as a permanent crop. Fodder can also be a suitable crop in the cropping pattern if it supports milk production in farm households. Vegetables are seasonal and hence have the flexibility to change the area quickly according to rainfall.

Therefore, the next few scenarios (SC1–SC3, SD1–SD3 in Table 4) assume cropping patterns that include fruits (pomegranate) as the base crop in 5.3% of the BAU area, which consumes 2.83 Mm3 of groundwater irrigation CWU and generates USD 3.03 million output. These scenarios then assess what other crops can be grown with the available CWU under different rainfall patterns (moderate and high rainfall).

Table 4.

Scenarios B, C, and D cropping patterns in the CCA.

SeasonCropCropping patterns (%) of the post-monsoon, summer season, and annual/perennial crops
Scenario B (low rainfall)
Scenario C (moderate rainfall)
Scenario D (high rainfall)
SB1SB2SB3SC1SC2SC3SD1SD2SD3
Post-monsoon Sorghum      3.3   20.0 
Wheat         8.0 
Fodder 8.0   8.0 8.0 8.0 8.0 8.0 8.0 
Pulses     7.2 3.3  76.3 20.0 
Oilseeds         7.0 
Vegetables   6.6 10.4 6.6 6.6 55.5 10.4 20.4 
Annual/perennial crops Sugarcane          
Orchard  5.3  5.3 5.3 5.3 5.3 5.3 5.3 
Cotton          
Total percentage 8.0 5.3 6.6 23.7 26.8 26.4 68.8 100.0 88.8 
Total area (ha) 672 447 555 1,991 2,281 2,223 5,798 8,432 7,488 
Total IRCWU (Mm32.83 2.83 2.83 10.10 10.10 10.10 29.50 27.29 29.50 
Total output (M USD) 1.59 3.03 2.28 8.21 7.36 7.20 23.87 13.07 14.90 
Total output (% of BAU output) 20 38 29 103 92 90 298 163 176 
SeasonCropCropping patterns (%) of the post-monsoon, summer season, and annual/perennial crops
Scenario B (low rainfall)
Scenario C (moderate rainfall)
Scenario D (high rainfall)
SB1SB2SB3SC1SC2SC3SD1SD2SD3
Post-monsoon Sorghum      3.3   20.0 
Wheat         8.0 
Fodder 8.0   8.0 8.0 8.0 8.0 8.0 8.0 
Pulses     7.2 3.3  76.3 20.0 
Oilseeds         7.0 
Vegetables   6.6 10.4 6.6 6.6 55.5 10.4 20.4 
Annual/perennial crops Sugarcane          
Orchard  5.3  5.3 5.3 5.3 5.3 5.3 5.3 
Cotton          
Total percentage 8.0 5.3 6.6 23.7 26.8 26.4 68.8 100.0 88.8 
Total area (ha) 672 447 555 1,991 2,281 2,223 5,798 8,432 7,488 
Total IRCWU (Mm32.83 2.83 2.83 10.10 10.10 10.10 29.50 27.29 29.50 
Total output (M USD) 1.59 3.03 2.28 8.21 7.36 7.20 23.87 13.07 14.90 
Total output (% of BAU output) 20 38 29 103 92 90 298 163 176 

Source: Authors' estimation.

Bold values indicate that SB1–SB2 and SC1–SC3 have same irrigation consumptive water use.

Scenarios SC1SC3 are based on 75% dependable rainfall of about 450 mm. This rainfall augments about 5.0 Mm3 of natural groundwater resources in the CCA and 5.0 Mm3 of additional canal irrigation CWU. The latter is estimated based on past rainfall and reservoir release patterns. The total irrigation CWU available under SC1–SC3 is 10.0 Mm3.

The cropping patterns SC1–SC3 have fruits as a permanent feature in 5.3% of the BAU area. These cropping patterns can survive under moderate rainfall conditions with an irrigation CWU of 10.1 Mm3 of canal and groundwater irrigation.

  • Cropping pattern SC1, which includes only fruits, fodder, and vegetables, takes up only 23.7% of the BAU cropped area but can generate even higher output than the BAU cropping pattern.

Scenarios SD1SD3 offer alternative cropping patterns to the BAU under high rainfall conditions. These cropping patterns too assume a fixed area for fruits (5.3% of the BAU area) and fodder (8%) as permanent crops, as in scenario C. Moreover, they assume that 29.5 Mm3 (same as under BAU conditions) is available for irrigation CWU.

  • SD1, which includes more vegetable area than SC1, occupies 68.8% of the BAU cropped area but generates three times the value of the BAU output.

  • SD2 and SD3 have more diversified cropping patterns and generate substantially more output than those in SC1. In addition to fruit, fodder, and vegetables (as in scenario SC1), SD2 scenario assumes an additional area with pulses – the crop with the next highest EWP. The SD2 scenario generates 66% more output than BAU.

The scenario analysis for the CCA shows that Sina can generate the same or much higher output with different cropping patterns. To achieve this target, all cropping patterns can include a permanent feature such as orchards or fodder for milk production. The seasonal crops can vary according to rainfall and water availability patterns.

Scenarios for RLIA and 1 km buffer

Following the same methodology, Table 5 shows potential cropping patterns for the RLIA and the 1 km buffer zone. It only shows cropping patterns that can provide some income even in low to moderate rainfall years, but substantially more income in high rainfall years.

Table 5.

Potential cropping patterns for RLIA and 1 km buffer.

SeasonCropReservoir lift irrigated area (RLIA)
1 km buffer zone
2010–11Same outputRainfall patterns
2010–11Same outputRainfall patterns
LowModeratehighLowModeratehigh
BAUSASB2SC3SD2SD3BAUSASB2SC3SD2SD3
Post-monsoon Sorghum 22.7     22.7 34.5   8.2  41.6 
 Wheat 3.0     3.0 2.0     2.0 
 Fodder 0.5   7.7 7.7 7.7 0.4   8.6 8.6 8.6 
 Pulses 29.8     29.8 35.3   7.7  41.6 
 Oilseeds 5.7     5.7 0.0      
 Vegetables 18.6   25.4 66.6 21.6 0.0    63.2  
Annual crops Sugarcane 8.8      5.6      
 Orchard 1.1 22.7 5.1 5.1 5.1 5.1 2.8 12.6 5.9 5.9 5.9 5.9 
 Cotton 9.9            
Total percentage 100 22.7 5.1 38.2 82.4 95.6 100 12.6 5.9 30.3 77.6 100 
Total area (ha) 5,512 1,249 281 2,105 4,373 5,269 6,134 770 362 1,858 4,763 5,291 
Total IRCWU (Mm322.23 7.91 1.78 10.69 22.23 22.23 25.21 5.83 2.74 8.91 25.21 23.99 
Total output (M USD) 8.47 8.47 1.90 8.67 18.00 9.67 5.22 5.22 2.45 6.08 19.64 6.49 
% of BAU total output 100 100 22 102 213 114 100 100 47 114 363 124 
SeasonCropReservoir lift irrigated area (RLIA)
1 km buffer zone
2010–11Same outputRainfall patterns
2010–11Same outputRainfall patterns
LowModeratehighLowModeratehigh
BAUSASB2SC3SD2SD3BAUSASB2SC3SD2SD3
Post-monsoon Sorghum 22.7     22.7 34.5   8.2  41.6 
 Wheat 3.0     3.0 2.0     2.0 
 Fodder 0.5   7.7 7.7 7.7 0.4   8.6 8.6 8.6 
 Pulses 29.8     29.8 35.3   7.7  41.6 
 Oilseeds 5.7     5.7 0.0      
 Vegetables 18.6   25.4 66.6 21.6 0.0    63.2  
Annual crops Sugarcane 8.8      5.6      
 Orchard 1.1 22.7 5.1 5.1 5.1 5.1 2.8 12.6 5.9 5.9 5.9 5.9 
 Cotton 9.9            
Total percentage 100 22.7 5.1 38.2 82.4 95.6 100 12.6 5.9 30.3 77.6 100 
Total area (ha) 5,512 1,249 281 2,105 4,373 5,269 6,134 770 362 1,858 4,763 5,291 
Total IRCWU (Mm322.23 7.91 1.78 10.69 22.23 22.23 25.21 5.83 2.74 8.91 25.21 23.99 
Total output (M USD) 8.47 8.47 1.90 8.67 18.00 9.67 5.22 5.22 2.45 6.08 19.64 6.49 
% of BAU total output 100 100 22 102 213 114 100 100 47 114 363 124 

Source: Authors' estimates.

Notes: Low, medium, and high rainfall years correspond to 10th, 25th, and 50th percentile rainfall of 250, 450, and 700 mm, respectively.

In the RLIA, which uses both groundwater irrigation and lift irrigation from the reservoir, the following cropping patterns hold potential:

  • SA2: Fruits in 22.7% of the BAU area can generate the same value of output, with about one-third of the irrigation CWU. However, this CWU is substantially more than the available groundwater in a low rainfall year.

  • SB2: RLIA can sustain 5.1% of the BAU area with fruits in a low rainfall year.

  • SC3: Fruits (5.1%), fodder (7.7%), and vegetables can generate more output than the BAU cropping pattern in a moderate rainfall year.

  • SD4: Fruits (5.1%), fodder (7.7%), and other crops with vegetables in at least 18.6% of the BAU area can generate more output than the BAU.

In the 1 km buffer zone, which primarily uses return flows of canal water supply in the CCA and natural recharge for groundwater irrigation, the following cropping patterns showed promise:

  • SA2: It requires only 12.6% of the BAU area with fruits to generate the same output.

  • SB2: In a low rainfall year, it can sustain only 5.9% of the BAU area with fruits.

  • SC3: In a moderate rainfall year, fruits (5.9%), fodder (8.6%), sorghum, and pulses in 30% of the BAU area can generate more output than the BAU scenario.

  • SD2–3: Fruits (5.9%), fodder (8.6%), and a combination of other crops in more than three-fourths of the BAU cropped area can generate substantially more output in a good rainfall year.

Scenario analyses show that SD3 type cropping patterns are more suitable for the Sina WIZ. It reallocates some of the BAU irrigation CWU from crops with low EWP such as sorghum and pulses to crops with high EWP such as fruits, fodder, and vegetables. In low rainfall years, such cropping patterns generate some income from fruits (and fodder) in a smaller area. Fruits, fodder, and vegetables as primary crops with a combination of other crops can generate even more output than BAU cropping patterns under moderate rainfall conditions and substantially higher output in high rainfall conditions.

The cost curve for EWP

Assuming that water is the major constraint in the irrigation system, and that crop area and inputs depend on availability of water, this study estimates the EWP and net value of output (i.e., output − cost) per m3 of irrigation CWU. The cost includes both annualized capital cost of technology and the cost of cultivation of the crop (Table 6).

Table 6.

Economic water productivity (EWP) of various crops in the Sina irrigation system in Maharashtra, India.

CropTechnology/practiceCrop-technology/practiceCost of cultivationCost of technologyYieldPrice of commodityIrrigation CWUValue of output per m3 of irrigation CWU
(1,000 INR/ha)(1,000 INR/ha)(kg/ha)(INR/m3)(m3/ha)Gross EWP (INR/m3)Net EWP (INR/m3)
Rice Conventional Rice – conv. 55 0.00 4,295 13.33 4,908 11.66 0.38 
Sorghum Conventional Sorghum – conv. 0.00 612 18.16 3,226 3.44 1.14 
Wheat Conventional Wheat – conv. 14 0.00 2,274 8.12 3,769 4.90 1.23 
Groundnut Conventional Groundnut – conv. 45 0.00 1,282 52.42 4,377 15.35 5.13 
Rice System of rice intensification Rice – SRI 44 0.92 5,468 13.33 4,908 14.85 5.91 
Rice Alternate wet and dry irrigation (AWD) Rice – AWD 51 1.60 6,580 13.33 4,908 17.87 7.44 
Rice Direct-sown seed Rice – DSS 46 0.22 6,280 13.33 4,908 17.06 7.74 
Groundnut IW/cumulative pan evaporation (CPE) = 0.4 Groundnut – IW/CPE0.4 43 0.60 1,477 52.42 4,377 17.69 7.93 
Groundnut Border strip method Groundnut – BSM 44 0.80 1,684 52.42 4,377 20.17 10.14 
Mango High-density plantation Mango – HDP 510 15.80 15,000 40.00 6,326 94.85 14.25 
Maize Conventional Maize – conv. 48 0.00 5,010 16.20 2,271 35.74 14.65 
Maize IW/CPE = 0.6 Maize – IW/CPE0.6 48 0.60 5,050 16.20 2,271 36.03 14.93 
Maize Alternate furrow irrigation Maize – AFI 47 0.60 5,010 16.20 2,271 35.74 15.00 
Lime Conventional Lime – conv. 110 0.00 8,614 24.03 6,326 32.72 15.33 
Mango Conventional Mango – conv. 200 0.00 7,500 40.00 6,326 47.42 15.81 
Sunflower Conventional Sunflower – conv. 26 0.00 1,890 33.00 2,301 27.10 15.89 
Sunflower Ridge and furrow irrigation Sunflower – RFI 23 0.60 2,104 33.00 2,301 30.17 20.40 
Sugarcane Conventional Sugarcane – conv. 118 0.00 110,000 2.85 9,209 34.04 21.24 
Chickpeas Conventional Chickpea – conv. 18 0.00 1,870 59.33 3,457 32.09 26.81 
Sugarcane Drip with conventional planting Sugarcane – DRIP 104 13.55 123,000 2.85 9,209 38.07 26.82 
Sugarcane Subsurface drip 100% PE and 100% RDF Sugarcane – SSDRIP100PE 102 12.10 123,000 2.85 9,209 38.07 26.98 
Sugarcane Drip with fertigation Sugarcane – DRIPFERT 104 14.45 126,000 2.85 9,209 39.00 27.65 
Sugarcane Subsurface drip 80 PE and75% RDF Sugarcane – SSDRIP80PE 102 12.10 126,000 2.85 9,209 39.00 27.91 
Sugarcane Drip with improved planting method Sugarcane – DRIPIPM 103 12.64 131,000 2.85 9,209 40.54 29.40 
Sugarcane Drip and fertigation with improved planting Sugarcane – DRIPFERTIPM 104 13.55 132,500 2.85 9,209 41.01 29.76 
Chickpea Integrated water management Chickpea – IWM 19 0.68 2,090 59.33 3,457 35.87 30.39 
Groundnut Sprinkler Groundnut – SPRINK 37 6.86 3,280 52.42 4,377 39.28 30.86 
Groundnut Integrated nutrient management Groundnut – INM 37 6.86 3,280 52.42 4,377 39.28 30.86 
Lucerne Sprinkler Lucerne – SPRINK 0.00 40,000 3.50 4,206 33.29 32.77 
Onion Conventional Onion – conv. 96 0.00 12,200 28.00 5,090 67.12 48.25 
Onion Sprinkler Onion – SPRINK 97 1.45 13,000 28.00 5,090 71.52 52.37 
Pomegranate Drip irrigation Pomegranate – DRIP 100 0.00 9,673 47.97 6,326 73.34 57.54 
Tomatoes Conventional Tomatoes – conv. 41 0.00 35,000 13.00 5,090 89.40 81.36 
Banana Conventional Banana – conventional 115 0.00 42,500 24.03 6,326 161.44 143.31 
Banana Drip irrigation Banana – DRIP 90 12.64 56,250 24.03 6,326 213.67 199.38 
Tomato Precision land leveling Tomato – PLL 42 40,000 28 5,090 220.00 212.00 
Banana Drip and fertigation Banana – DRIFERT 114 22 63,000 24 6,326 239.00 221.00 
Banana Tissue cultured Banana – TC 464 18 82,500 24 6,326 313.00 240.00 
CropTechnology/practiceCrop-technology/practiceCost of cultivationCost of technologyYieldPrice of commodityIrrigation CWUValue of output per m3 of irrigation CWU
(1,000 INR/ha)(1,000 INR/ha)(kg/ha)(INR/m3)(m3/ha)Gross EWP (INR/m3)Net EWP (INR/m3)
Rice Conventional Rice – conv. 55 0.00 4,295 13.33 4,908 11.66 0.38 
Sorghum Conventional Sorghum – conv. 0.00 612 18.16 3,226 3.44 1.14 
Wheat Conventional Wheat – conv. 14 0.00 2,274 8.12 3,769 4.90 1.23 
Groundnut Conventional Groundnut – conv. 45 0.00 1,282 52.42 4,377 15.35 5.13 
Rice System of rice intensification Rice – SRI 44 0.92 5,468 13.33 4,908 14.85 5.91 
Rice Alternate wet and dry irrigation (AWD) Rice – AWD 51 1.60 6,580 13.33 4,908 17.87 7.44 
Rice Direct-sown seed Rice – DSS 46 0.22 6,280 13.33 4,908 17.06 7.74 
Groundnut IW/cumulative pan evaporation (CPE) = 0.4 Groundnut – IW/CPE0.4 43 0.60 1,477 52.42 4,377 17.69 7.93 
Groundnut Border strip method Groundnut – BSM 44 0.80 1,684 52.42 4,377 20.17 10.14 
Mango High-density plantation Mango – HDP 510 15.80 15,000 40.00 6,326 94.85 14.25 
Maize Conventional Maize – conv. 48 0.00 5,010 16.20 2,271 35.74 14.65 
Maize IW/CPE = 0.6 Maize – IW/CPE0.6 48 0.60 5,050 16.20 2,271 36.03 14.93 
Maize Alternate furrow irrigation Maize – AFI 47 0.60 5,010 16.20 2,271 35.74 15.00 
Lime Conventional Lime – conv. 110 0.00 8,614 24.03 6,326 32.72 15.33 
Mango Conventional Mango – conv. 200 0.00 7,500 40.00 6,326 47.42 15.81 
Sunflower Conventional Sunflower – conv. 26 0.00 1,890 33.00 2,301 27.10 15.89 
Sunflower Ridge and furrow irrigation Sunflower – RFI 23 0.60 2,104 33.00 2,301 30.17 20.40 
Sugarcane Conventional Sugarcane – conv. 118 0.00 110,000 2.85 9,209 34.04 21.24 
Chickpeas Conventional Chickpea – conv. 18 0.00 1,870 59.33 3,457 32.09 26.81 
Sugarcane Drip with conventional planting Sugarcane – DRIP 104 13.55 123,000 2.85 9,209 38.07 26.82 
Sugarcane Subsurface drip 100% PE and 100% RDF Sugarcane – SSDRIP100PE 102 12.10 123,000 2.85 9,209 38.07 26.98 
Sugarcane Drip with fertigation Sugarcane – DRIPFERT 104 14.45 126,000 2.85 9,209 39.00 27.65 
Sugarcane Subsurface drip 80 PE and75% RDF Sugarcane – SSDRIP80PE 102 12.10 126,000 2.85 9,209 39.00 27.91 
Sugarcane Drip with improved planting method Sugarcane – DRIPIPM 103 12.64 131,000 2.85 9,209 40.54 29.40 
Sugarcane Drip and fertigation with improved planting Sugarcane – DRIPFERTIPM 104 13.55 132,500 2.85 9,209 41.01 29.76 
Chickpea Integrated water management Chickpea – IWM 19 0.68 2,090 59.33 3,457 35.87 30.39 
Groundnut Sprinkler Groundnut – SPRINK 37 6.86 3,280 52.42 4,377 39.28 30.86 
Groundnut Integrated nutrient management Groundnut – INM 37 6.86 3,280 52.42 4,377 39.28 30.86 
Lucerne Sprinkler Lucerne – SPRINK 0.00 40,000 3.50 4,206 33.29 32.77 
Onion Conventional Onion – conv. 96 0.00 12,200 28.00 5,090 67.12 48.25 
Onion Sprinkler Onion – SPRINK 97 1.45 13,000 28.00 5,090 71.52 52.37 
Pomegranate Drip irrigation Pomegranate – DRIP 100 0.00 9,673 47.97 6,326 73.34 57.54 
Tomatoes Conventional Tomatoes – conv. 41 0.00 35,000 13.00 5,090 89.40 81.36 
Banana Conventional Banana – conventional 115 0.00 42,500 24.03 6,326 161.44 143.31 
Banana Drip irrigation Banana – DRIP 90 12.64 56,250 24.03 6,326 213.67 199.38 
Tomato Precision land leveling Tomato – PLL 42 40,000 28 5,090 220.00 212.00 
Banana Drip and fertigation Banana – DRIFERT 114 22 63,000 24 6,326 239.00 221.00 
Banana Tissue cultured Banana – TC 464 18 82,500 24 6,326 313.00 240.00 

Notes: AWD, Alternative wet and dry irrigation; SRI, System of rice intensification; DSS, direct-sown seed; IWPCE, Irrigation water cumulative pan evaporation; HDP, High-density plantation; AFI, Alternative furrow irrigation; RFI, Ridge and furrow irrigation; SSDRIP100PE, Subsurface drip with 100% pan evaporation; DRIPFERT, drip with fertigation; DRIPIPM, drip irrigation with improved planting; IWM, Integrated Water Management; SPRINK, Sprinkler irrigation; PLL, Precision land leveling; TC, Tissue culture.

Figure 3 shows the cost curve for different crops and technologies. The Y-axis shows the net value of output (value of production − the cost of cultivation) per m3/ha of irrigation CWU. The X-axis shows the EWP (gross output per m3/ha of irrigation CWU). The bars indicate the crop and the technology used for cropping. The values within parentheses show the EWP per m3/ha of irrigation CWU. The bars are in increasing order of the net value of output per irrigation CWU.

Fig. 3.

The net value of output versus EWP per m3 of irrigation CWU. Source: Authors’ estimation. Notes: Prices were farm gate prices paid in 2015–16. In 2016, USD 1 = INR 67.2. The bars are in increasing order of the net value of output per irrigation CWU. The numbers within parentheses are the EWP of crops with technologies used for cropping.

Fig. 3.

The net value of output versus EWP per m3 of irrigation CWU. Source: Authors’ estimation. Notes: Prices were farm gate prices paid in 2015–16. In 2016, USD 1 = INR 67.2. The bars are in increasing order of the net value of output per irrigation CWU. The numbers within parentheses are the EWP of crops with technologies used for cropping.

The bars on the extreme right of the cost curve show that fruits (banana, pomegranate, etc.), vegetables (onion, tomatoes, etc.), and fodder (Lucerne) crops have relatively higher gross and the net value of output per m3 of irrigation CWU. Sugarcane and mango have higher EWP than Lucerne but have a lower net value of output per m3. Groundnut – INM and chickpea – IWM also have a higher net value of production than Lucerne, although the EWP is slightly smaller.

The cost curve also shows the differences in EWP between technology use and conventional methods. For example, banana with tissue culture has the highest EWP and the net value of output, more than twice the traditional methods. Tomatoes with precision land leveling have more than twice the production of conventional methods.

Financial trade-off analysis for different scenarios

The financial trade-off analysis of different cropping patterns uses the technologies or practices that generate the highest net value of output. The crops and technologies/practices considered are fruits (pomegranate with drip irrigation), fodder (Lucerne with sprinkler irrigation), vegetables (onion with sprinkler irrigation), sorghum and wheat with conventional irrigation, pulses (chickpea with integrated water management), oilseed (groundnut with integrated nutrient management), and sugarcane with drip, fertigation, and integrated pest management.

Figure 4 shows the benefit–cost ratio (BCR) of scenarios of potential cropping patterns under low (SB), moderate (SC), and high (SD) rainfall conditions over a 10-year period. The following assumptions hold for the BCR scenario analysis.

  • There are three low rainfall (less than 250 mm), four moderate (between 250 and 450 mm) rainfall, and three high rainfall years (more than 600 mm rainfall) over the 10-year spell.

  • In low rainfall conditions, no canal irrigation supply is available. Under these conditions, the BAU scenario assumes that perennial/annual crops (pomegranate and sugarcane) can be cropped with available groundwater CWU. The alternative scenario is assumed to have only fruit (pomegranate).

  • In moderate rainfall years, past trends show that only about 40–60% of the cropped area in high rainfall years can be irrigated. Under moderate rainfall conditions, the BAU scenario assumes that perennial/annual crops (pomegranate and sugarcane), and sorghum and pulses are cropped with the available irrigation CWU. The alternative scenario assumes the SC3 cropping patterns, as shown in Tables 4 and 5.

  • In high rainfall years, the BAU scenario assumes the cropping patterns as in 2010/11, and the alternative scenario assumes SD3, as shown in Tables 4 and 5.

Fig. 4.

(a) Irrigation CWU and (b) the trade-off of different cropping patterns in the WIZ regions. Source: Authors' estimation. Notes: The numbers within parentheses show the number of years under low (SB), moderate (SC), and high rainfall (SC) conditions in a 10-year period. The value of output is in 2010 prices.

Fig. 4.

(a) Irrigation CWU and (b) the trade-off of different cropping patterns in the WIZ regions. Source: Authors' estimation. Notes: The numbers within parentheses show the number of years under low (SB), moderate (SC), and high rainfall (SC) conditions in a 10-year period. The value of output is in 2010 prices.

The trade-off analysis shows that alternative cropping patterns to BAU can generate substantially higher outputs with the same quantity of irrigation CWU. In RLIA, a large part of the irrigation CWU in moderate to high rainfall years is from direct pumping from the reservoir. In the CCA, the majority of the irrigation CWU is from groundwater irrigation, and in the 1 km buffer zone, 100% of the CWU is from groundwater irrigation.

  • The BCR shows that the alternative cropping patterns are also financially viable in the WIZ with different rainfall scenarios.

Conclusions and policy implications

The Sina irrigation system is a physically water-scarce system. In spite of physical water scarcity, it still grows low-value, high water-consuming crops. As a result, it has low EWP. With increasing variability of weather, water-scarce irrigation systems such as Sina cannot sustain these practices. They should explore increasing EWP by adopting alternative cropping patterns. The cropping patterns not only should increase EWP in moderate to good rainfall years but should also generate some income in low rainfall years.

The CWU water allocation scenarios found that the Sina irrigation system can improve EWP from the present level in all parts of its WIZ. Cropping patterns that include annual crops as a core feature can generate higher outputs with the same CWU in good to moderate rainfall conditions. Such cropping patterns can generate substantial output even in dry weather conditions with groundwater irrigation.

The inclusion of annual crops as a core feature of profitable cropping patterns is based on groundwater irrigation. This analysis used the method proposed by the Central Ground Water Board of India for estimating groundwater recharge. However, this method may be a limitation in the accurate estimation of groundwater availability in the Sina WIZ. Under low rainfall conditions, although there are no canal irrigation supplies, the reservoir still has some water storage. Reservoir storage recharges groundwater in the CCA and the 1 km buffer zone. Accurate estimates of groundwater recharge are needed for finalizing alternative cropping patterns.

The study leads to the following policy recommendations pertinent to the Sina irrigation system in particular and water-scarce irrigation systems in general. These will enable not only more crop per drop but also irrigation for all as envisaged in the Indian government's agriculture initiative, PMKSY.

All water-scarce irrigation systems should assess the groundwater recharge zones and the volume of groundwater storage that can support crop production in the WIZ. Groundwater irrigation is a key component in increasing the consumptive fraction and attaining irrigation for all in the WIZ. It is imperative to know the groundwater availability under different rainfall conditions to enable all stakeholders to use an appropriate crop as a potential feature of crop/agricultural production pattern. The groundwater availability estimation is now supported under the National Aquifer Mapping and Management program (NAQUIM) of the Central Groundwater Board of India at the block and village level in India. This will be useful information for the future with appropriate cropping patterns.

Conjunctive irrigation of canal water and groundwater should be promoted by design and not by default to reduce risks due to variable weather patterns. Groundwater irrigation contributed to the high irrigated area and CWU in the CCA of the Sina irrigation system. It is imperative to enable conditions for conjunctive irrigation in the canal command are to distribute irrigation benefits to all stakeholders in the WIZ.

There should be a gradual shift to cropping patterns that include high-value water stress-tolerant crops in a small area. These crops can primarily use groundwater with micro-irrigation even in a low rainfall year. Perennial crops such as fruits (pomegranate) are already in place in some parts of the Sina WIZ. How these cropping patterns are accommodated within the CCA is a question that needs policy intervention.

Determine the proportion of annual/perennial crops in the cropping pattern based on the available groundwater CWU in low rainfall years. Shift to improved technologies that can decrease non-beneficial evaporation and increase EWP.

The government should create an enabling environment for farmers to access groundwater without over-extracting the resources and incentivizing them to practice water conservation. Groundwater irrigation is not possible at present within the command area when canal irrigation is not available.

Data availability statement

Data cannot be made publicly available; readers should contact the corresponding author for details.

References

Amarasinghe
U. A.
Sikka
A.
Mandave
V.
Panda
R. K.
Gorantiwar
S.
Chandrasekharan
K.
Ambast
S. K.
(
2020
).
A re-look at canal irrigation system performance: a pilot study of the Sina irrigation system in Maharashtra, India
.
Water Policy.
doi: 10.2166/wp.2020.291
.
Brauman
K. A.
Siebert
S.
Foley
J. A.
(
2013
).
Improvements in crop water productivity increase water sustainability and food security – a global analysis
.
Environmental Research Letters
8
(
2
),
024030
.
Cameira
M. D. R.
Pereira
L. S.
(
2019
).
Innovation issues in water, agriculture and food
Water
11
(
1230
),
1
7
.
doi:10.3390/w11061230
.
Fernández
J. E.
Alcon
F.
Diaz-Espejo
A.
Hernandez-Santana
V.
Cuevas
M. V.
(
2020
).
Water use indicators and economic analysis for on-farm irrigation decision: a case study of a super high-density olive tree orchard
.
Agricultural Water Management
237
,
106074
.
Garg
K. K.
Bharati
L.
Gaur
A.
George
B.
Acharya
S.
Jella
K.
Narasimhan
B.
(
2012
).
Spatial mapping of agricultural water productivity using the SWAT model in Upper Bhima Catchment, India
.
Irrigation and Drainage
61
(
1
),
60
79
.
GoI (Government of India)
(
2017
).
Report of the Groundwater Resources Estimation Committee 2015
Vol. 2
.
Ministry of Water Resources, Government of India
,
New Delhi, India
.
GOI (Government of India)
(
2019
).
Economic Survey 2018–19
Vol. 2
.
Ministry of Finance, Government of India
,
New Delhi, India
.
Grafton
R. Q.
Williams
J.
Perry
C. J.
Molle
F.
Ringler
C.
Steduto
P.
Udall
B.
Wheeler
S. A.
Wang
Y.
Garrick
D.
Allen
R. G.
(
2018
).
The paradox of irrigation efficiency
.
Science
361
(
6404
),
748
750
.
IPCC (Intergovernmental Panel on Climate Change)
(
2014
). In
Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II, and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
.
Team
C. W.
Pachauri
R. K.
Meyer
L. A.
(eds).
IPCC
,
Geneva
,
Switzerland
, p.
151
.
Kumar
D.
(
2018
).
Canal irrigation versus well irrigation: comparing the uncomparable
. In:
Water Policy Science and Politics: An Indian Perspective
.
M. Dinesh Kumar, ed.
Elsevier
,
Amsterdam
,
The Netherlands
.
Mirza
M. M. Q.
(
2011
).
Climate change, flooding in South Asia and implications
.
Regional Environmental Change
11
(
1
),
95
107
.
Molden
D.
Murray-Rust
H.
Sakthivadivel
R.
Makin
I.
(
2003
).
A water-productivity framework for understanding and action
. In:
Water Productivity in Agriculture: Limits and Opportunities for Improvement
.
Kijne
J.
Barker
R.
Molden
D.
(eds).
CAB International
,
Wallingford, Oxon
,
UK
.
Molden
D.
Oweis
T.
Steduto
P.
Bindraban
P.
Hanjra
M. A.
Kijne
J.
(
2010
).
Improving agricultural water productivity: between optimism and caution
.
Agricultural Water Management
97
(
4
),
528
535
.
Perry
C.
Steduto
P.
Allen
R. G.
Burt
C. M.
(
2009
).
Increasing productivity in irrigated agriculture: agronomic constraints and hydrological realities
.
Agricultural Water Management
96
,
1517
1524
.
Rasul
G.
Neupane
N.
Hussain
A.
Pasakhala
B.
(
2019
).
Beyond hydropower: towards an integrated solution for water, energy and food security in South Asia
.
International Journal of Water Resources Development
,
1
25
.
doi:10.1080/07900627.2019.1579705
.
Ray
B.
Shaw
R.
(eds) (
2019
).
Water insecurity in Asian cities
. In:
Urban Drought
.
Springer
,
Singapore
, pp.
17
32
.
Scott
C. A.
Albrecht
T. R.
De Grenade
R.
Zuniga-Teran
A.
Varady
R. G.
Thapa
B.
(
2018
).
Water security and the pursuit of food, energy, and earth systems resilience
.
Water International
43
(
8
),
1055
1074
.
Shah
M.
(
2013
).
Water: towards a paradigm shift in the twelfth plan
.
Economic and Political Weekly
48
,
40
52
.
Sharma
B. R.
Gulati
A.
Mohan
G.
Manchanda
S.
Ray
I.
Amarasinghe
U.
(
2018
).
Water Productivity Mapping of Major Indian Crops
.
NABARD and ICRIA
,
New Delhi
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).