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. 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. The Artificial Neural Network-Multilayer Perceptron (ANN-MLP) was employed to forecast the upcoming 15 years rainfall across India. We mapped the rainfall trend pattern for whole country by using the geo-statistical technique like Kriging in ArcGIS environment. Results show that the most of the meteorological divisions exhibited significant negative trend of rainfall in annual and seasonal scales, except seven divisions during. 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 premonsoon seasons. Furthermore, the significant negative trend (−8.5) was recorded for overall annual rainfall. 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. The increasing rainfall trend had observed during the period 1901-1950, while a significant decline rainfall was detected after 1951. The rainfall forecast for upcoming 15 years for all the meteorological divisions' also exhibit a significant decline in the rainfall. 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. 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. Rainfall is a key part of hydrological cycle and alteration of its pattern directly affect the water resources 1. The changing pattern of rainfall in consequence of climate change is now concerning issues to water resource managers and hydrologists 2. Srivastava et al. 3 and Islam et al. 4 reported that the changes of rainfall quantities and frequencies directly changing the stream flow pattern and its demand, spatiotemporal allocation of runoff , ground water reserves and soil moisture. Consequently, these changes showed the widespread consequences on the water resource, environment, terrestrial ecosystem, ocean, biodiversity , agricultural and food security. The drought and flood like hazardous events can be occurred frequently because of the extreme changes of rainfall trend 5. Gupta et al. 6 documented that the amount of soil moisture for crop production is totally determined by the amount of rainfall. The monsoon rainfall plays a vital role for agriculture in India. 68% of cultivated land to the total cultivated land of India is occupying by the rain fed agriculture which...

This paper provides a comprehensive review of various reports, articles documents and papers literature related to the assessment of climate change impacts on crop productivity, and will focus on how climate change and affects agriculture productivity. Agricultural practice is affected by climate changes because of its direct dependence on climatic changes. There are two methods of relationships between agriculture and climate change and has huge significance especially for developing and underdeveloped or low‐income countries, who are largely dependent on agriculture for subsistence and their lack of infrastructure for adaptation as compared with developed countries. Geographically high‐latitude areas with already existence of low temperature, by virtue of increasing temperature due to climate changes, could allow for the longer growing season. Agricultural fields are affected by the emission of GHG such as carbon dioxide, nitrous oxide, and methane. Gasses have an effect on climate through the discharge of greenhouse gasses. Emissions mostly come from the tillage practices, fossil fuels, fertilized agricultural soils, and farm animal's manure in a huge amount and affected the agriculture sector. On the contrary, agriculture could be a solution for climate change by reducing emission and implementation of mitigation and adaptation actions widely. It will happen with the assistance of best management practices such as agroforestry practice, organic farming, rainwater harvesting, irrigation planning, and manure management.

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The aim of this paper is to examine the impact of tourism arrivals and tourist expenditure on economic growth in case of four developing countries (Brazil, Russia, India, and China) using annual data from 1995 to 2016. To achieve this objective, we apply Dumitrescu–Hurlin causality test and panel data models. The results indicate that tourist expenditure has a positive impact on economic growth. Further, the results show that tourist arrivals do not have any significant effect on economic growth. The direction of causality shows that tourist expenditure has bidirectional causality with economic growth. The policy suggests that the investment environment must be upgraded through appropriate measures such as deregulation in economic activity; developing the port facilities, road network, railways, and telecommunication facilities; achieving clarity in trade policy and flexibility in labor markets; and setting a suitable regulatory framework and tariff structure and the country must grow in terms of better facilities and infrastructure for tourists.