Exploitation of rainfall data to optimize rural GDP in rain-dependent agriculture. Implementation in India

E. Kontarakis, Exploitation of rainfall data to optimize rural GDP in rain-dependent agriculture. Implementation in India, Diploma thesis, 196 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, June 2019.



According to international data from World Bank on developing countries and in the Southeast Asia, there is a strong relation of their Gross Domestic Product (GDP) to their agricultural output, suggesting that a large fraction of total income in the developing world derives from domestic agricultural value added. In addition, the significant lack of irrigation infrastructure (e.g. reservoirs and irrigation networks) forces these countries’ income into strong dependence from local hydroclimatic conditions such as precipitation and temperature; as the majority of crop output is -in turn- based on rain-fed agriculture. More and more countries, such as Ethiopia and India, where people face poverty and lack of food, participate, according to United Nations, in the Green Revolution initiative, which is a realistic target it the needs of food satisfaction until 2025. This is desired to be accomplished by the increase of the GDP in these countries through the improvement of the economy. Significant field of the economy in the developing countries is the agriculture, which in most cases is rainfed. Especially in India, GDP has a strong relation with agriculture and agricultural production, which is based in rainfed systems. So, study should be implemented in order the correlation of the rainfall and temperature with the Agriculture value added and agricultural production to be found. In the procedure of the study of the correlations between hydroclimatic (Precipitation and Temperature) and economic values (Agriculture value added and Crop production index), the Pearson correlation coefficient was calculated and equals ρ=0.78. We had to discriminate the year in the rainy and dry season, and it has been concluded that the rainy season of the year was the summer semester, due to the monsoon phenomenon. In order for the deductions for the Agriculture value added and CPI to be more precise, the rainfall in the period 1901-2015 has been studied. Since it was indicated through statistical analysis that the time series of rainfall in India has long term persistence, it was implemented a Hurst – Kolmogorov process 3AR (1) so as to be easier in the future, the management of water resources and precipitation in India. By this way, it could be predictable the change percentage of the economic values, that would lead to the improvement of economy. Basic part of the project was the study of the percentage of change of many variables and the statistical analysis of the growth of hydroclimatic and economic values. Lastly, endeavor has been conducted for the correlations between rainfall and agriculture value added to be analyzed, and it is assessed that the correlation of the 2 values does not change significantly from the first 3 months of the summer semester until the end of the semester. Agricultural output and agriculture value added is gathered at the end of the year, so the last conclusion offers indications for the variability of the agriculture value added 3 months earlier than the predicted and the appropriate movements of investments could be done earlier in order for the GDP to be increased. Further research could be done in the future for a model construction for rainfall- agriculture added in India or other countries with rainfed agriculture.

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