My work involved building up a product to be used by policy makers to bring in sustainable development. A brief description of the product:
End Product: GIS based web-service coupled with analytical and remote sensing applications./ End User: Policy Makers/ Programming Languages : (Java J2EE, C++, Fortran, Data-library, Google KML API)/ Third Party Software: (Eclipse, HMM Tool, DSSAT Crop Model, Google Earth)/ Development Platform : Unix based operating system
This is not a technology demonstration blog. I will try to tell you a human side of the software by telling the story of a life of a poor farmer Ram Singh (this might be the story of any farmer in any developing country) as a concept of using this product for providing him with better life.
This is a story of the life of a farmer named Ram Singh, who lives in a small village in a corner of India. Ram Singh and his family are dependent on agriculture for their livelihood, and he has dreams of educating his kids to go and work in the corporate sector in urban India. Ram Singh has been practicing traditional methods of agriculture, which had been developed by his ancestors. He was also happy with the pro-farmer government policies that provided subsidized electricity. This allowed Ram Singh to pump as much water required for the farming from the groundwater for free, and typically had good luck with the harvest. But Ram Singh is always worried about his brother, Hari Singh, who relies on rainwater. Hari Singh would report about unpredictable monsoon onset date and how his crops are affected. Also he would read newspaper reports about the plight of farmers in a region in Western Maharashtra. The reports would suggest that a total of 7000 farmers have committed suicide during the last 3 years, and that is an average of over six farmers committing suicide per day. This region is home for approximately 3.4 million cotton farmers, and 95% of them are struggling with massive debt. The growth of bio-tech cotton was encouraged by the government, and now the farmers are facing the brunt of the failed policy.
Ram Singh doubts his luck will continue that the government will be providing the same generosity in the future. He continues to wonder whether he will be able to save enough to send his children to work in the city.
Understanding the Ground Realities in India
Due to population growth, there has been a constant increase in demand for food and energy. The availability of energy sources has helped farmers to pump out ground water in order to meet the growing food demands. However, years of pumping have resulted in a drop in the average depth of ground water. This yielded an increase in demand for energy and more stress in agricultural output. By providing subsidies in electricity, the government is faced with budget constraints. Also, the drop in agricultural outputs due to groundwater stress and change in monsoon patterns did not help the government’s treasury. The only option the government has is to remove the subsidies, leaving lots of farmers starving.
Economic Models & Ram Singh’s Dream
The economic theories claim that models can suggest how development occurs. Using the learning’s from these models we need to see if the product could be designed based on this. In brief Solow model says that the capital accumulated in the agricultural sector could be used in urbanization and jobs. This means that, Ram Singh’s profitable output would mean more capital for the state for urbanization. Overlapping Generation model at any given point of time, two distinct generations exist, the young and the old. The young works and saves and the old consumes based on the wages they saved when they are young. The amount saved could also be used by the younger generation in this case Ram Singh’s son. Malthusian trap suggests that population growth could offset for the capital accumulation and poverty trap means that environment degradation can affect capital accumulation and lead to destruction of infrastructure. If poverty trap occurs one must insert outside capital as aid to the state to bring the state out of the trap and colapsing. Keeping this in mind is essential to keep Ram Singh’s dream in mind. Also one needs to see if Ram Singh and his government follow the social planner model so that he can protect them from the effect of climate change.
Understanding the impact of Climate Change and finding a solution.
Being in the tropics, the impact of climate change on India could be written in one line stating,
It rains less often, but when it rains it pours.
This has resulted in damaging of standing crops year after year. The questions that come to mind are: 1) Can we predict the monsoon onset date and tell the farmers when to sow their seeds; 2) Can we predict the spatial signal of the monsoon and provide the farmers with the information about crop practices?
Rainfall prediction is a tricky affair, particularly at the regional scale. Theoretically speaking, dynamical downscaling of General Circulation Models can help in capturing the signal of the monsoon onset date and mean intensity over the region. However, this depends on how good the General Circulation Models capture the circulation patterns over the region. Also, if one feeds the output of the dynamical down-scaling of the General Circulation Models into crop models (which also take into account soil conditions over the region), farmers can be informed of the best practices for the season. This will help the farmers produce the optimal output and help with the state budget crisis.
My research on GCM downscaling over the region suggests that there is too much noise that prevents the monsoon onset date to be predicted. However, inserting the non-homogenous Markoff model outputs, generated by the GCM downscaling, in the crop model helps in intensifying the signal component thereby reducing this noise. The following image shows the correlation between crop model outputs for Sorghum with various weather parameters.One can clearly see the signature of monsoon circulations and this means the crop output could be predicted.
Ram Singh can now stop relying on groundwater and can provide optimum outcome for the monsoon season. This would help him undertake savings. State will be benefited with the capital generated in agriculture and could be used for urbanization. But Ram Singh is still dependent on groundwater for the rest 8 months. He is worried about the increased energy use and decreasing productivity. In the next section we would discuss about the impact of decreasing groundwater.
Impact of decreasing Groundwater
Groundwater use cannot be neglected from agriculture because the monsoon only occurs for four months out of a year. Agricultural practices for the rest 8 months have to be based on groundwater reserves. The following map shows the energy in kwh/hectare used in the winter season (Rabi) to pump out groundwater to meet the water requirements of the crops grown in the region. One could see some areas badly affected.
The decrease in ground water has three major impacts. First, it increases the energy required to pump the water out, which might impact the profit from the farm. Secondly, the salinity increases as one goes down. Third, the increase in the release of CO2 to the atmosphere can lead to a larger greenhouse effect.
My calculations while using linear programming on yield based on climatologically averages of rainfall and integrating the cost of electricity in the field input suggested that the total profit from the agricultural farm would be negative in some regions. So to decrease the energy demand, one option is to change to other crops that are less dependent on water. The second option is to build artificial aquifers over the areas where groundwater experiences major stress. Remote Sensing images can be used to serve this purpose. The following images show where the agriculture is in stress for bad agricultural practices. This is an application based on remote sensing and the dark areas in left shows areas having bad crop practices. As cities won’t have a lot of vegetation variability, validating the image with night lights over the region helps to understand that this is a good tool. Using this tool, Agricultural policy makers could suggest Ram Singh techniques to recharge groundwater or change cropping pattern.
The solution to the second problem might be to switch to renewable to provide the energy to pump out water. The next step is to look into the economics of investing into renewable.
Understanding switching to Renewable and the challenges
Solar power is still too costly to be implemented on a large scale. Wind is very intermittent over the region and would require a high investment on storage. The state might not have enough capital to invest into solar or wind. Proffesor Lackner in his class on carbon sequestration suggested that coupling of air capture and wind could help reduce the cost of wind in the region. This theory suggests that if excess wind could be used to convert the CO2 captured into synthetic fuel, the same could be used as storage and burnt cleanly when there is no wind.
My calculations suggest for the district of Jaipur that a total of 1,214 air-capture devices would be enough to capture the CO2 emitted from the agriculture in the region. Also the synthetic fuel generated would be enough in combination with 1000 wind farms to generate enough energy to provide a continuous 14MW electricity supply in an off-grid scenario. The hitch today is, until the cost of CO2 capture is not below 20 cents/ton, the cost is still too high to be met by the capital of the state. If the state gets involved in trading the CO2 captured with Annex1 countries, or launches these projects as CDM, the projects might be feasible.
Planning Future Economic Development
Keeping all the economic, engineering, political, and international perspectives in mind, the next step would include building up plans for investment into sustainable infrastructure planning in the region. The state might not have enough resources to bring them out of the poverty trap. The investment planning might include foreign investor investment. The product involves integration of various remote sensing applications, population maps and census data to plan out infrastructure and urbanization. This would involve planning roads, electricity grid, schools, hospitals, industries, and so on. May be using this application policy makers could make real effective policy to help Ram Singh.
In the end, it seems if everything goes in the following pattern, Ram Singh will be able to save enough, and there will be jobs in the cities that he cam send his kids to work in the corporate sector. Yay for Ram! And his village.
arindam
