Climate Change Impacts on Crop Water Balance of Cotton (Gossypium herbaceum) and Maize (Zea mays L.) in Telangana

Not AvailableRainfed agricultural production systems are primarily dependent on climate parameters including rainfall, temperature, wind velocity, sunshine hours/solar radiation etc among which rainfall is the critical input resource. It significantly varies over time and space with erratic distribution having coefficient of variation (CV) in the range of 30 to 80% in all the semi arid regions. The other crop water balance parameters effective rainfall, crop evapotranspiration, irrigation water requirement during crop seasons, have dynamic relationship with the quantity and distribution pattern of rainfall. IPCC AR5 report indicated the decrease in rainfall in southern part of the country with extreme events of drought, and its frequency, decrease in rainy days which are primarily concerns of rainfed agriculture. The two states of Andhra Pradesh and Telangana have maximum area (67%) under rainfed agriculture with major crops of maize, cotton, groundnut and pigeon pea grown in the 16 districts of two states. Therefore an attempt is made to analyze the decadal variation of crop water balance parameters in 16 districts of Telangana and Andhra Pradesh. The data and its variation are shown in the geospatial maps of Telangana and Andhra Pradesh for easy understanding to the readers in the form of atlas for each state. The atlas is the outcome of the work related to modeling of crop water balance for maize and cotton crops in rainfed districts of Telangana state. It was an important activity on potential of rainwater harvesting and utilization under NICRA project of ICAR-CRIDA. We thank Dr. S. Ayyappan , Director General, ICAR and Secretary, DARE and Dr. A.K. Sikka, DDG (NRM) for their keen interest, guidance and constant support. We also express our sincere thanks to Director, CRIDA and Principal Investigator, NICRA for extending necessary support and encouragement. We take this opportunity to thank “Climate Change, Agriculture and Food Security (CCAFS)” for providing base data (1961-1990) and ECHam5 data as open source from Marksim DSSAT. We are also thankful to FAO, Rome for providing CROPWAT V8.0 simulation software. We also extend thanks to Dr. Abdul Islam for critically evaluating the findings and suggestions to improve upon. We recognize the help rendered by students of College of Agricultural Engineering, Madakasira and SangareddyNot Availabl