blog




  • Essay / Drought Early Prediction Models

    High climate variability has been observed in central India, with very hot summers, very cold winters and an intense monsoon. However, summer monsoon is important for the agriculture of central India and its agriculture is always affected by drought as MP receives most of the rainfall during the summer monsoon season (JJAS). Central India receives almost 95% of rainfall only during the JJAS season. However, this region is vulnerable to extreme events such as droughts and floods. It therefore experiences regular and long-term droughts which cause the most serious losses for the agricultural economy. Therefore, there is an urgent need for a model or system that can predict drought in advance with fewer resources. Among the many drought indicators such as SPI, SPEI, PDSI and aridity index used for monitoring, the most used are the standardized precipitation index (SPI), standardized precipitation index and d evapotranspiration (SPEI), Palmer Drought Severity Index (PDSI), soil moisture percentile, standardized runoff index and standardized soil moisture index. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get an original essay Based on the distinguished values ​​of the SPI, the impact of drought can be assessed to determine the appropriate repercussions to reduce the impacts. Additionally, the impact on agricultural production was seen due to lack of soil moisture even for a short time, during periods of maximum water use by crops. Several studies have discussed the importance of drought monitoring that takes into account some or all of the above factors such as SPI, SPEI, PDSI, etc. Based on multiple indicators, the Global Integrated Drought Monitoring and Forecasting System (GIDMaPS) provides real-time drought information. A probabilistic framework for drought forecasting based on accumulated precipitation to make 20-day forecasts. 'advance. There is a comparative study of the SPI and the SPEI. Their comparative study concludes with a few impotent points. First, the fluctuation value and continuity are slightly different in the SPI and SPEI as the time scale increases. Second, at different time scales, the characteristics of SPI and SPEI were found to be significantly different. Third and finally, the largest difference between SPI and SPEI was found for the shortest period. In conclusion, they also stated that SPEI is more suitable than SPI for drought monitoring, but it depends on its region. Meteorological drought variability in Indian region using SPEI examined the trends and behavior of meteorological drought episodes in India using SPEI indices and found that increasing drought in the eastern part of India was attributed to the decrease in precipitation, while to the decrease in PET. the frequency of droughts in the arid western region is decreasing, presented an application of a seasonal forecast model using SPEI as a drought indicator. Additionally, SPEI is also used in many studies to identify drought. By using traditional statistical or physical models (general circulation models) to predict drought at different time scales, the extraordinary developments observed in the past have been realized. Numerous data-driven machine learning algorithms for drought forecasting..