دانلود کتاب مدیریت ریسک آب و هوا در کشاورزی

In India, more than 50% of the population is engaged in agriculture and allied activities, contributing around 18% to the country’s Gross Value Added (census report 2021). Further, more than 50% of the total agricultural production comes from a rain-fed area covering ≈60% of total agricultural land and is highly vulner¬able to weather hazards. Seasonal weather variability in terms of droughts, flash floods, heavy rainfall, thunderstorms, cyclones, heat waves, etc. severely affect the agricultural production, particularly the rainfed agriculture and rural economy. To avoid such weather-related risks, weather-based crop planning is essential, thus, seamless accurate weather forecasting is one of the important inputs for agricul¬tural production management.
Although several improvements have been made in understanding the science of the atmosphere and the development in a physical and statistical model predic¬tion for weather and climate, yet, the monthly to seasonal scale prediction remains the most difficult, and challenging task for the research community. This is mainly because of the tropical region, where the interaction between small-scale physi¬cal processes with the large-scale flow is very complex, and land surface charac¬teristics are highly heterogeneous. For example, the 2002 Indian monsoon season (June-September) was a drought year (−19% of the long period average) due to a large rainfall departure in the month of July (−49% of normal), which turned out to be the severe in recorded history. Since July month is the most vital for sowing the Kharif crop, the food grain production dropped to 183 million tons as compared to 212 million tons in the previous year because of the unprecedented intra-seasonal variation of rainfall during that year. In addition, climate change is inevitable, and intensity, pattern, duration, and frequency of climate variability in association with climate extremes are being changed which greatly impacts agri¬culture and allied sectors.
In this context, a major number of earning people depend on agricultural pro¬duction and there is an urgent requirement to develop a better sustainable tech¬nique for advanced intimation of weather and climate information in extended range time scales (monthly to seasonal scale) for weather-based agricultural plan¬ning and management. Such kind of forecast will be helpful to mend a decision support system for sustainable agricultural production (and minimizing the losses) and the livelihood of a farming community. The mandated need stated above moti¬vated to direct concise pathways for the development of monthly and seasonal scale weather/climate forecasts.