Application of standardized precipitation index for monitoring meteorological drought and wet conditions in Garhwal region (Uttarakhand)

2021 ◽  
Vol 14 (9) ◽  
Author(s):  
Anurag Malik ◽  
Anil Kumar
Climate ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 28
Author(s):  
Anurag Malik ◽  
Anil Kumar ◽  
Priya Rai ◽  
Alban Kuriqi

Accurate monitoring and forecasting of drought are crucial. They play a vital role in the optimal functioning of irrigation systems, risk management, drought readiness, and alleviation. In this work, Artificial Intelligence (AI) models, comprising Multi-layer Perceptron Neural Network (MLPNN) and Co-Active Neuro-Fuzzy Inference System (CANFIS), and regression, model including Multiple Linear Regression (MLR), were investigated for multi-scalar Standardized Precipitation Index (SPI) prediction in the Garhwal region of Uttarakhand State, India. The SPI was computed on six different scales, i.e., 1-, 3-, 6-, 9-, 12-, and 24-month, by deploying monthly rainfall information of available years. The significant lags as inputs for the MLPNN, CANFIS, and MLR models were obtained by utilizing Partial Autocorrelation Function (PACF) with a significant level equal to 5% for SPI-1, SPI-3, SPI-6, SPI-9, SPI-12, and SPI-24. The predicted multi-scalar SPI values utilizing the MLPNN, CANFIS, and MLR models were compared with calculated SPI of multi-time scales through different performance evaluation indicators and visual interpretation. The appraisals of results indicated that CANFIS performance was more reliable for drought prediction at Dehradun (3-, 6-, 9-, and 12-month scales), Chamoli and Tehri Garhwal (1-, 3-, 6-, 9-, and 12-month scales), Haridwar and Pauri Garhwal (1-, 3-, 6-, and 9-month scales), Rudraprayag (1-, 3-, and 6-month scales), and Uttarkashi (3-month scale) stations. The MLPNN model was best at Dehradun (1- and 24- month scales), Tehri Garhwal and Chamoli (24-month scale), Haridwar (12- and 24-month scales), Pauri Garhwal (12-month scale), Rudraprayag (9-, 12-, and 24-month), and Uttarkashi (1- and 6-month scales) stations, while the MLR model was found to be optimal at Pauri Garhwal (24-month scale) and Uttarkashi (9-, 12-, and 24-month scales) stations. Furthermore, the modeling approach can foster a straightforward and trustworthy expert intelligent mechanism for projecting multi-scalar SPI and decision making for remedial arrangements to tackle meteorological drought at the stations under study.


2016 ◽  
Vol 42 (1) ◽  
pp. 67 ◽  
Author(s):  
M. Peña-Gallardo ◽  
S. R. Gámiz-Fortís ◽  
Y. Castro-Diez ◽  
M. J. Esteban-Parra

The aim of this paper is the analysis of the detection and evolution of droughts occurred in Andalusia for the period 1901-2012, by applying three different drought indices: the Standardized Precipitation Index (SPI), the Standardized Precipitation and Evapotranspiration Index (SPEI) and the Standardized Drought-Precipitation Index (IESP), computed for three time windows from the initial period 1901-2012. This analysis has been carried out after a preliminary study of precipitation trends with the intention of understanding the precipitation behaviour, because this climatic variable is one of the most important in the study of extreme events. The specific objectives of this study are: (1) to investigate and characterize the meteorological drought events, mainly the most important episodes in Andalusia; (2) to provide a global evaluation of the capacities of the three different considered indices in order to characterize the drought in a heterogeneous climatically territory; and (3) to describe the temporal behaviour of precipitation and drought indices series in order to establish the general characteristics of their evolution in Andalusia. The results have shown that not all the indices respond similarly identifying the intensity and duration of dry periods in this kind of region where geographical and climatic variability is one of the main elements to be considered.


2014 ◽  
Vol 12 (3) ◽  
pp. 253-264 ◽  
Author(s):  
Mladen Milanovic ◽  
Milan Gocic ◽  
Slavisa Trajkovic

Drought represents a combined heat-precipitation extreme and has become an increasingly frequent phenomenon in recent years. In order to access the entire analysis of drought, it is necessary to include the analysis of several types of drought. In this paper, impacts of meteorological and agricultural drought were analyzed across the Standardized Precipitation Index (SPI) and Agricultural Rainfall Index (ARI) on the territory of Serbia for the period from 1980 to 2010. For both types of drought, year 2000 is notable as the year when most of the observed stations had the highest drought intensity. It was found that meteorological drought for year 2000 has a higher intensity in the central and southeastern parts of the country, as well as in the north. Of all the stations, the highest intensity of meteorological drought was observed at Loznica station in 1989. Agricultural drought in 2000 had the lowest intensity in western Serbia.


2018 ◽  
Vol 44 ◽  
pp. 00082
Author(s):  
Justyna Kubicz

The paper presents the initial studies with the aim to assess the possibility to apply of Standardized Precipitation Index SPI to monitor drought in surface and groundwaters. The fact that data about precipitation are highly available allows for precise monitoring of the periods of occurrence and intensification of meteorological drought by determining the standardized SPI index. The evaluation of current water deficits in surface water courses and groundwaters is very difficult due to the fact that the measurement network is relatively scarce. In order to apply SPI to monitor hydrological and hydrogeological drought, it is required to assess the significance and level of the correlation between drought indices in the test area and then to calculate the probability of correct determination of drought in surface and groundwaters with use of SPI.


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