Drought Assessment using Z-Score for Vidarbha Region, Maharashtra

Drought is an insidious hazard of nature. It is conceivably the most complex natural hazard.Its impact varies from region to region. It originates from lack of precipitation over an extended period of time. The opulence of drought mitigation largely depends upon timely information on drought onset, progress, and areal extent. These kinds of information are better linked with drought monitoring which is performed generally by using various indices. However the presence of multiple time steps in drought indices make it harder to decide the best time step to show the drought conditions.The present study evaluates the performance of four precipitation based drought indices likethe Standardized Precipitation index (SPI), China-Z index (CZI), Modified China-Z index (MCZI) and Z-score on 1, 3, 6, 9 and 12 month timescales using monthly precipitation data from 1902 to 2001 at eight locations to specify the drought conditions in Marathwada region of Maharashtra, India. Out of the eight locations taken two locations are selected for the regression analysis to find out the best possible correlation of drought indices with SPI. The study reveals that 1 month time step for all the drought indices taken yield fallacious result as they are weakly correlated with Standardized Precipitation Index. On the other hand at higher month time scales e.g. 3 months, 6 months, 9 months and 12 months, all the drought indices are found to be best correlated with the SPI at the correspondingly same time steps. Linear Regression (R2) values were very close to unity (up to 0.9839 for Osmanabad and 0.9929 for Prabhani).

MAUSAM

Drought is one of the adverse natural hazards especially in arid and semi-arid regions regarding water resources management. Under the conditions of global warming and climate change, the investigation of drought severity and its trend in arid and semi-arid regions is of primary importance. Therefore, in this study, drought severity assessment and trend detection were carried out using different meteorological drought indices like Standardized Precipitation Index (SPI) and Standardized Reconnaissance Drought Index (RDIstd) for a semi-arid area of Parbhani district of the Indian state of Maharashtra. The results showed that SPI and RDIstd behave similarly to detect drought severity except for some slight deviation in detecting moderate and normal drought severity. Out of 37 years (1983 to 2019), SPI showed 1 severe drought year, 6 moderate drought years, 22 normal years, 4 moderate wet years, 3 very wet years and 1 extremely wet year while RDIstd showed 1 severe drought year, 5 moderate drought years, 23 normal years, 4 moderate wet years, 3 very wet years and 1 extremely wet year. One severe drought year was observed on the basis of both SPI and RDIstd indices. On the basis of weekly data analysis, the frequency of drought, normal and wet week was found to be 70.58, 15.90 and 13.51 per cent, respectively. It is revealed that the short term weekly rainfall analysis provides clear picture of frequent occurrences of drought episodes at the study area as compared to longer (monthly or annual) time scale. For identifying a statistically significant trend, a non-parametric test (Mann-Kendall) and parametric test (Linear regression) were used. At an annual scale, no significant either increasing or decreasing trend was found in the case of precipitation, SPI, RDIstd except potential evapotranspiration (PET) and temperature. Both the tests showed a statistically significant decreasing trend of PET at 0.1 level of significance (α) which would reduce water loss through trend for June month in the case of SPI (i.e., increasing drought severity) at α = 0.01, 0.05 and 0.1 which indicated increment in shortage of precipitation at early monsoon period and hence, increase in delay of early sowing of Kharif seasonal crops. For November month, both the tests showed an increasing trend of SPI and RDIstd (i.e., decreasing drought severity) at α = 0.1. In the case of PET, both the tests did not show any statistically significant trend at any month.

ISH Journal of Hydraulic Engineering, 2019

Drought has been called a creeping disaster because of the way it develops slowly. It can be defined according to meteorological, hydrological and agriculture criteria. In the present study, meteorological data i.e., monthly rainfall data from different rain gauges stations were used for identification of drought. Standardized Precipitation Index (SPI) values were generated based on Gamma distribution of precipitation data for 32 years (from 1985 to 2016) for Ananthpur district of Andhra Pradesh in India. Comparison of SPI, with actual rainfall and rainfall deviation from the mean indicated that SPI values underestimate the intensity of dryness/wetness when the rainfall is very low/very high respectively. This shows that the range of SPI values of the high rainfall district indicated better stretching, compared to that of the low rainfall district. SPI indicated deviation from normal probability in the lower and upper ranges. Therefore, it is suggested that SPI as a stand-alone indicator needs to be interpreted with caution to assess the intensity of drought.

Drought is a destructive hazard of nature. It is conceivably the most complex natural hazard. It shows a creeping appearance in nature. The impact of drought varies from region to region. It is difficult to define it in the most generalized way. It originates and crawls due to lack of precipitation over an extended period of time. Worldwide prevalence and duration of drought increases due to climate change and increasing water demands. Thus, the opulence of drought mitigation largely depends upon timely information on drought beginning, operation, and areal extent of drought. These kinds of information are better linked with drought monitoring. Monitoring is performed generally by using various indices. Various drought indices have been developed so far but many of them are region specific and have limitations of applicability in other climatic conditions. Moreover, the presence of multiple time steps in drought indices make it harder to decide the best time step to show the drought conditions. The present study aims to evaluate the Standardized Precipitation index (SPI) at 12 and 24 months timescale using monthly data of precipitation from 1953 to 2002 at eleven districts for monitoring drought years, in the Vidarbha region of Maharashtra, India. The Present study unveils the fact that Vidarbha region is associated with larger number of drought spells. Almost seven to eight numbers of dry periods have been observed in the data set from 1953-2002. Among the 11 districts namely Akola, Amravati, Washim and Yavatmal, Nagpur is associated with severe drought in most of the years.

International Research Journal of Engineering and Technology (IRJET), 2018

Ahmednagar district of Maharashtra State in India has always been in the limelight in the recent years whenever India suffers a drought. The geographical location and the inadequacy of rainfall in Ahmednagar district over the past few years when compared to the average rainfall of the country make it one of the most vulnerable places to suffer a meteorological drought. The unpredictability and the unknown severity of drought to occur in the future years alleviates the possibility of the drought management and drought mitigation strategies to fail eventually since drought can either be meteorological, agricultural or hydrological in nature. This paper discusses a measure the severity of meteorological drought severity using the historical data of precipitation as the major indicator. The Standard Precipitation Index (SPI) is computed and is used as an index for the prediction of drought severity and frequency of drought occurrence. The result can be used as a way forward to be ready with the water management and drought mitigation strategies to reduce the socio-economic losses incurred.

Journal of Pharmacognosy and Phytochemistry, 2021

This paper discusses a method for calculating the severity of meteorological droughts based on historical precipitation data as the primary criterion Monthly precipitation data from 1970 to 2020 were used to obtain Standardized Precipitation Index (SPI) values for Prakasam district, Andhra Pradesh. SPI has the ability to analyse the drought at various time scales and for a variety of applications. SPI is calculated at various time scales (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 etc. months). Time scales of one, two, and three months are effective for agriculture, while time scales of six, nine, and twelve months are useful for hydrology. A drought event occurs any time the SPI is continuously negative and reaches an intensity of -1.0 or less. The event ends when the SPI becomes positive. Each drought event, therefore, has a duration defined by its beginning and end, and an intensity for each month that the event continues. The annual SPI for Prakasam district was calculated from 1970 to 2020 to show the frequency of occurrence of dry and wet conditions. Temporal SPI graphs show that the maximum SPI value (extreme drought) occurred in the year 2018 in that year, the SPI value was -2.6. Furthermore, in severe and extreme drought years, SPI values indicated only moderate dryness rather than extreme dryness, with SPI values never falling below -2.5.Severe and moderate drought occurred in 1984, 2002 and 2014. Drought patterns were evaluated, yielding many interesting results on the variability of drought occurrence in the region. The study's findings are relevant to climate change studies in order to understand historical patterns and build future scenarios of drought occurrences.

The Standard precipitation index expresses the actual rainfall as a standardized departure with respect to rainfall probability distribution function and hence the index has gained importance in recent years as a potential job indicator permitting comparison across space and time. The computation of SPI requires long term data on precipitation. Droughts are hydro metrological events affecting vast regions and causing significant structural and non structural damages. Drought predictions may prevent these type of adverse consequences to a significant extant. This work regarding the drought analysis by assessing the drought severity based on fluctuation in rainfall trend by standard precipitation index for Shivamogga district by 30years rainfall data from rain gauge reading of different station in different taluks of Shivamogga district.

Journal of Water and Climate Change

The effectual estimation of meteorological drought parameters such as severity, duration and frequency to plan suitable drought mitigation measures is challenging owing to the complex relationship among these parameters. The present study endeavored to assess the drought proneness of various districts of chronic drought prone Saurashtra region of Gujarat state (India). The district wise Drought Severity Duration Frequency (DSDF) curves were developed using Standardized Precipitation Evapotranspiration Index (SPEI) based on 40 years (1980 to 2019) data. The monthly drought severities of SPEI for various return periods ranging from 2 to 100 years were estimated by testing 10 probability distributions. The DSDF curves revealed that severe droughts were more prominent for shorter durations and identical severities were observed for 1 to 4 month drought duration for smaller rerun periods. As drought mitigation measures vary according to drought severity and duration, the study employed a...

Current World Environment

Drought is a natural hazard which is challenging to quantify in terms of severity, duration, areal extent and impact. The present study was aimed to assess the meteorological drought for Junagadh (Gujarat), India using Standardized Precipitation Index (SPI) and evaluate its correlation with the productivity of Groundnut and Cotton. The SPI was computed for eight durations including monthly (June to August each), 3 monthly (June to August and July to September) and 6 monthly (June to November) time scales for the year1988 to 2018. The results revealed that 54% to 67% of years suffered from drought for SPI-1. Drought years based on SPI-3 and SPI-6 were 48 % to 58%. Among all the eight durations, mild drought was the most dominant drought category. Years 1993, 1999, 2002 and 2012 experienced the most severe droughts for Junagadh. Severe droughts were observed only for SPI-1 (July), SPI-3 and SPI-6. No extreme drought was witnessed in Junagadh. Correlation of groundnut yield with SPI wa...

Methodology to characterize meteorological drought and drought frequency curves have been developed for the drought prone Hazaribagh district, Jharkhand, India. The annual and monsoon seasonal rainfall data for a period of 80 years (1913 – 1992) were analyzed to determine excess and deficit from normal. The annual and seasonal rainfall follows log normal and normal distribution respectively. Meteorological drought is investigated by various methods and using proposed methodology. Based on seasonal rainfall of 80 years the proposed methodology classified 45 years (56.25%) as drought years out of which incipient, large, severe, disastrous and extreme drought years were 12 (15.55%), 21(27.77%), 8 (10%), 3 (3.75%) and 1(1.25%) respectively. Drought indices were also developed and year 1966 was classified as the extreme drought year of the area. Multiyear drought characteristic reveals that as drought duration increased from 2 to 6 years the mean severity increased with increasing variability, though the mean drought intensity also increased gradually, but with decreasing variability.