Two-thirds of Nepal’s farmland is still reliant on the monsoon rain for irrigation (The Kathmandu Post, 2019). This adversely impacts agricultural production over the years: a small fluctuation in rainfall can yield massive divergence in harvest size. Also, considering that agriculture contributes to more than a quarter of the national output, this substantially influences the government’s ability to stabilize growth over an extended period. Considering this fact, the Government of Nepal has launched various schemes to promote the installation of solar pumps. The schemes include decentralized, and renewable energy powered irrigation equipment to substitute monsoon rain for irrigation – worth NRs. 960 million through 2019/2020’s annual fiscal budget. This is expected to contribute favorably to the 5.1 percent annual growth rate target that the government has set this year.
Gham Power has been working actively to redefine the agricultural landscape in Nepal. We provide low-cost solar irrigation solutions to smallholder farmers and use innovative business models to increase the affordability of these solutions for smallholder farmers. These pumps directly reduce farming expenses and on the other hand, increase farm yield and income. We have built our initiative on the belief that farm inputs are one of the most critical components in the entire agricultural value chain. Likewise, increased availability of these inputs can drastically upend the landscape for smallholder farmers. We are currently scaling up solar-water pumps and subject to the success of these solutions, and we have plans to incorporate more products into our portfolio. As such, we conducted a survey to test the impact of our solar water pumps on the lives of smallholders.
We have so far installed 200+ Solar Water Pumps of sizes one horsepower and two horsepower. In our systematic survey, we identified a sample size of 30 end-customers in Bara, Rautahat, and Sarlahi districts of Nepal. These three districts account for a large proportion of the national agricultural output, and our solar water pumps are loosely clustered in these areas. We have summarized the findings of the survey below:
1. Land under cultivation expanded by 8.46 percent
2. Increase in production by 10.24 percent,
3. Gain in income by 16.32 percent,
4. Lowering of farm expenses by 6.76 percent
5. Adoption of high-value crops like vegetables and
6. A shift in cultivation practices from subsistence to commercial
We have summarized the satisfaction level of end-users in the adjacent pie chart. The primary learning from the satisfaction survey questionnaire is that none of our customers is discontent from the operation of the pumps.
The way forward: automation in impact tracking
Findings of surveys like these are only as accurate as the quality of statistics gathered. These data are primarily collected first-hand from farmers who are not always sure of what information is sought and often answer in vague terms. While steps are being undertaken to increase the accuracy of the data found, standardizing the process has so far been costly because of the extent manual process involved. To combat this, we have started adopting data-driven techniques and remote sensing technologies to automate impact tracking, eliminating most of the costs involved in the procedure.
One such innovative technique we are exploring is satellite imagery services. Using this technology, we can geo-locate individual farms in a map and retrieve farm images from the satellite’s database. It will help us use agronomic machine learning techniques to look at how individual farms are evolving. This technique is a low-cost alternative to manual statistics collection. At this current stage, remote satellite tracking is witnessing upending innovations. With higher iteration, we will be able to gather more accurate data on individual farms and increase confidence in these technologies.
In a nutshell, availability of solar water pumps has many benefits for farmers, most of which are hard to track in real-time. The increasing accuracy of satellite imagery services and agronomic machine learning techniques will, however, substantially lower the cost of real-time impact tracking and in turn, increase its usage.