Therefore, the sustainable development of agriculture in India requires the noteworthy research on the identification and quantification of climate change 7. Hence, the research on the climate change or most specifically on the changes of rainfall occurrences and its allocation are the most significant way for sustainable water resource management. 68% of cultivated land to the total cultivated land of India is occupying by the rain fed agriculture which supports 60% of livestock population and 40% of human population 7.
The monsoon rainfall plays a vital role for agriculture in India. 6 documented that the amount of soil moisture for crop production is totally determined by the amount of rainfall. The drought and flood like hazardous events can be occurred frequently because of the extreme changes of rainfall trend 5. Consequently, these changes showed the widespread consequences on the water resource, environment, terrestrial ecosystem, ocean, bio-diversity, agricultural and food security. 4 reported that the changes of rainfall quantities and frequencies directly changing the stream flow pattern and its demand, spatiotemporal allocation of run-off, ground water reserves and soil moisture. The changing pattern of rainfall in consequence of climate change is now concerning issues to water resource managers and hydrologists 2. Rainfall is a key part of hydrological cycle and alteration of its pattern directly affect the water resources 1. Findings of the study have some implications in water resources management considering the limited availability of water resources and increase in the future water demand. The results derived from ECMWF ERA5 reanalysis data exhibit that increasing/decreasing precipitation convective rate, elevated low cloud cover and inadequate vertically integrated moisture divergence might have influenced on change of rainfall in India.
The rainfall forecast for upcoming 15 years for all the meteorological divisions’ also exhibit a significant decline in the rainfall. The increasing rainfall trend had observed during the period 1901–1950, while a significant decline rainfall was detected after 1951. Based on the findings of change detection, the most probable year of change detection was occurred primarily after 1960 for most of the meteorological stations. Furthermore, the significant negative trend (−8.5) was recorded for overall annual rainfall. Out of 17 divisions, 11 divisions recorded noteworthy rainfall declining trend for the monsoon season at 0.05% significance level, while the insignificant negative trend of rainfall was detected for the winter and pre-monsoon seasons. Results show that the most of the meteorological divisions exhibited significant negative trend of rainfall in annual and seasonal scales, except seven divisions during. We mapped the rainfall trend pattern for whole country by using the geo-statistical technique like Kriging in ArcGIS environment. The Artificial Neural Network-Multilayer Perceptron (ANN-MLP) was employed to forecast the upcoming 15 years rainfall across India. The Pettitt test was employed to detect the abrupt change point in time frame, while the Mann-Kendall (MK) test and Sen’s Innovative trend analysis were performed to analyze the rainfall trend. This study analyzes and forecasts the long-term Spatio-temporal changes in rainfall using the data from 1901 to 2015 across India at meteorological divisional level.
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