How to use the tool
The Solar Pumps Tool has been developed by aggregating and analysing district-wise data for more than 600 districts across India. The tool uses 20 parameters affecting the deployment of solar for irrigation in varying scenarios. Based on objectives defined by the user, the tool helps to:
i. Prioritise target districts in India or within a state, based on the relative situation of districts across various parameters;
ii. Assess the overall suitability of various deployment approaches for each district of the country;
iii. Understand district specific impetus factors and bottlenecks affecting the suitability of solar for irrigation;
iv. Identify the government policy objectives, which could be furthered through deployment of solar for irrigation.
I. What is the Overall Score?
In order to conveniently analyse the relative standing of different districts in a given scenario, multiple parameters have been collapsed into one numeral, the overall score. In order to do so, the parameters were normalised, through unity-based normalisation, to make them dimensionless and align the range from 0 to 1 to eliminate range specific biases before applying a weighted sum average as shown below:
Composite score = n1*w1 + n2*w2 + …………………… + n10*w10
Where, ni = normalised score for a parameter = (x-xmin)/(xmax – xmin); [0,1]; wi = weight; and x = parameter value
II. Why is the analysis at the district-level?
The choice of basic unit of assessment was influenced by data availability, minimum heterogeneity within the selected unit of geographical area, and administrative ease of implementation based on insights from this tool. The parameters chosen for the assessment display wide intra-state variation and there are gaps in the availability of block-wise data. Hence, the district was preferred over the state and the block, as the basic unit of assessment for this tool.
III. What are 'parameters'?
This tool makes use of 20 parameters, which in varying configurations, affect the suitability of:
(i) various approaches to deploy solar for irrigation.
(ii) policy objectives, which could be furthered with use of solar-based irrigation.
The deployment of solar for irrigation should be governed by ensuring environmental sustainability, economic viability, and social equity. In this regard, five criteria, with 10 corresponding parameters (described below) were identified for this tool. These are applicable as ‘weights’ across all scenarios. The rest of the parameters pertain to specific deployment approaches and policy objectives and are covered under the respective headings.
A. Potential demand for solar pumps - Inadequate access to affordable and reliable irrigation
i. Number of cultivators reporting use of diesel pumps: Indicates absence of affordable irrigation options for farmers.
ii. Unirrigated net sown area: Indicates unmet demand and hence potential for expanding irrigation access through solar.
B. Economic viability of solar-based irrigation
i. Proportion of gross cropped area under horticulture crops: Indicates higher potential for capacity utilisation of solar pumps (through multiple cropping cycles per year), increasing returns for farmer.
ii. Score on Water Scarcity Index: Indicates the groundwater situation in the district. Higher the index value, better would be the availability of water. This index is derived from a combination of depth of the water table and long-term groundwater development.
C. Purchasing capacity of farmers:
i. Monthly per capita expenditure of rural households: Indicates affluence of agricultural households. It represents the ability of farmers to invest in solar-based irrigation.
ii. Crop revenue per holding: Indicates average revenue from farming in the district. Higher the revenue, higher is ability of farmers in the district to invest in solar-based irrigation.
D. Access and subscription to institutional credit
i. Number of rural and semi-urban bank branches per 10,000 farmers: Indicates the availability of adequate banking infrastructure for farmers to avail loans.
ii. Medium and long-term credit disbursed in a year: Indicates higher likelihood of farmers’ taking loans for solar-based irrigation.
E. Farmers’ attitude towards progressive farm technologies
i. Calls made by farmers at Kisan Call Centres (KCC): Indicates farmers’ attitudes towards learning about new technologies and government schemes.
ii. Level of farm mechanisation: Measured as no. of tractors, threshers, and harvesters per hectare. Indicates farmers’ attitudes towards adopting progressive technologies.
IV. Using the parameters through 'filters' and 'weights'
Parameters can be applied in two ways in the tool: as ‘filters’ to select/de-select districts, and as ‘weights’ contributing to the overall score of a district.
‘Filters’ are used in the tool to define a maximum or minimum cut-off point for a parameter or multiple parameters to help focus on only the districts meeting such criteria (say, districts appearing in the bottom 25th percentile under Number of cultivators reporting use of diesel pumps), based on the objectives of the user.
i. Parameters which affect the selected deployment approach or policy objective are categorised under ‘Affecting’ on the tool page. ‘All,’ as the name suggests, has every parameter that is being used in this tool. The naming does not affect anything in terms of usage.
ii. Certain parameters which are tagged as ‘Affecting,’ have a default criterion pre-applied to them (for example, for Score on Water Scarcity Index, the default selection will only show districts in the top 75th percentile).
iii. The configuration of all the ‘Affecting’ parameters together determines the suitability of districts for a specific deployment approach or policy objective.
iv. A user has an option to change these filtering criteria based on her discretion.
‘Weights’ are used in the tool to determine the contribution of a certain parameter towards the overall score of a district (explained below), being calculated for each district for every scenario.
i. The distribution of districts on the map is shown based on their respective overall scores, ranging from low (light blue) to high (dark blue).
ii. The parameters contributing to the overall score of a district have been selected based on the rationale outlined in the section on ’What are parameters?’.
iii. The default weights have been calculated based on the 'Delphi approach', which includes results gathered from a set of experts.
iv. A user is allowed to vary these weights as per her discretion after signing in.
v. For two parameters, namely, Unirrigated net sown area and Score on Water Scarcity Index, minimum weight restriction of 5 and 15 respectively have been mandated to ensure social equity and economic viability of solar pumps.
V. What are 'deployment approaches'?
This tool measures the suitability of four deployment approaches (mentioned below) for any given district. The district’s suitability is assessed based on the performance of its ‘Affecting’ parameters on their filtering criteria.
A. Individually owned off-grid solar pumps: Solar for irrigation has been largely promoted through this approach so far, i.e. farmers purchasing-stand-alone solar pumps of varying capacities with significant subsidy support from the government. Ownership of pumps provides easy and reliable access to irrigation.
i. Number of cultivators reporting use of diesel pumps [percentile>50%]: Most probable group to switch to solar power under this model.
ii. Score on Water Scarcity Index [value>0.75]: Groundwater availability for irrigation; determines long term economic viability.
iii. Crop revenue per holding (INR) [percentile>50%]: Higher the revenue, higher the appetite for investment.
iv. Medium and long-term credit disbursed in a year (INR) [percentile>50%]: Enhances the likelihood of farmers taking loans for purchasing solar pumps.
B. Solarisation of feeders: Changing the source of power at the feeder level will ensure a rapid and cost-effective transition to solar-based irrigation at a large scale.
i. Power purchase rate for DISCOM [value>INR 3.5/kWh]: Cost comparison of the current power source with solar.
ii. Extent of feeder segregation [value>50%]: Dedicated line for agriculture connections. Allows the line to be energised during day time (8 am to 5pm).
iii. Proportion of cultivators using electric pumps [percentile>50%]: Higher the proportion, higher the conversion to solar. Will require no additional cost for farmers to transition.
C. Water as a service: This model has the potential to improve irrigation equity as it avoids a prohibitively high upfront cost of technology for small and marginal farmers:
i. Score on Water Scarcity Index [value>0.75]: Groundwater availability for irrigation. Determines long-term economic viability.
ii. Proportion of small and marginal farmers [value>85%]: Likely to be the biggest takers and beneficiaries of this model.
iii. Unirrigated net sown area as a share of net sown area [value>50%]: Lack of access to irrigation and opportunity to expand irrigation cover.
D. Promote 1 HP & sub-HP pumps: 1 HP and sub-HP pumps could help marginal farmers meet their needs and could also be put to use for lift irrigation, provided there is access to surface water.
i. Area under horticulture crops as a share of gross cropped area [percentile>50%]: Ensures higher revenue for farmers and higher capacity utilisation of solar pumps.
ii. Score on Water Scarcity Index [value>0.75]: Groundwater availability for irrigation. Determines long term economic viability.
iii. Proportion of marginal farmers [value>50%]: Likely to be the biggest takers and beneficiaries of small-sized pumps.
iv. Medium and long-term credit disbursed to marginal farmers in a year (INR) [percentile>50%]: Higher access to credit enhances the likelihood of investment.
VI. What are 'policy objectives'?
This tool recommends a set of policies for each district, for the implementation of which solar could be leveraged as a potential source of irrigation, a capital investment, or a way to further climate resilience. The suitability of a policy for a district is evaluated based on the performance of a set of pre-identified ‘Affecting’ parameters.
A. Har Khet ko Pani – Pradhan Mantri Krishi Sinchayee Yojana: Solar-based irrigation could improve access to groundwater irrigation.
i. Unirrigated net sown area [value>50%]: Indicates lack of access to irrigation and opportunity to expand irrigation cover.
B. Per Drop More Crop – Pradhan Mantri Krishi Sinchayee Yojana: Solar pumps can be deployed along with precise water application devices such as drip irrigation to promote efficient irrigation practices.
i. Area under crops suitable for drip and sprinkler as a share of gross cropped area [percentile>50%]: Indicates the likelihood of adoption of such water saving technologies.
C. Doubling Farmers’ Income – Capital Investment: Encourages investment in farm technologies, such as solar pumps, by small and marginal farmers.
i. Proportion of small and marginal farmers [value>85%]: Should be the biggest takers and beneficiaries of the scheme.
ii. Medium and long-term credit disbursed to small and marginal farmers in a year (INR) [percentile>50%]: Higher access to credit enhances likelihood of investment.
D. Doubling Farmers’ Income – Crop Diversification: Solar pumps help achieve diversification towards high value crops; in turn enhancing the economic viability of solar pumps.
i. Area under horticulture crops as a share of gross cropped area [percentile<50%]: Ensures higher revenue for farmers and capacity utilisation of solar pumps.
E. Doubling Farmers’ Income – Crop Intensity: Solar pumps to ensure irrigation access to help grow crops beyond rabi and kharif.
i. Unirrigated net sown area [value>50%]: Indicates lack of access to irrigation and opportunity to expand irrigation cover.
F. National Mission on Oilseeds and Oil Palm (NMOOP): Solar pumps to help provide reliable irrigation for oil crops.
i. Area under oil seeds as a share of gross cropped area [percentile<50%]: indicates irrigation demand for these crops.
G. Sub-Mission on Agricultural Mechanisation – Farm Power Availability: Solar pumps to improve farm power availability.
i. Level of farm mechanisation [value<50%]: Lower the value, higher the opportunity to increase farm power availability.
ii. Proportion of cultivators using electric pump [value<50%]: Lower the number of users, higher the potential of increasing mechanisation through solar pumps.
H. Climate Resilient Farming for Small Farms: Solar pumps to advance the cause of low-carbon agriculture and improve climate resilience.
i. Proportion of small and marginal farmers [value>85%]: Most vulnerable group to climate change. Will benefit the most from climate resilient farming practices.
ii. Climate Change Vulnerability Index by Central Research Institute for Dryland Agriculture (CRIDA) [ value>0.459]: Captures the exposure, sensitivity and adaptive capacity of district to climate change.
VI. Limitations of the tool
i. The choice of filters and weights has been kept the same across states, while in reality the influence of parameters will vary with geographic locations and states.
ii. The default weights and filters have been decided based on CEEW research and consultation with a set of experts, which could reflect biases of the group. The tool tries to correct this by allowing the user to change weights and as per their discretion, with almost no restriction.
iii. The tool as of now only captures the potential of solar-based irrigation for groundwater sources. In future, it might incorporate variables corresponding to surface water availability to enhance its scope.
iv. Given water availability is an important criterion when it comes to the sustainable deployment of solar pumps, it would have been useful to integrate India’s aquifer (hard rock) map to its political map. But, this could not be done due to the unavailability of a usable format of such a map.
v. Certain deployment approaches, like the community ownership of solar pumps, and a few policy objectives could not be incorporated in the tool due to unavailability of data.