Drought Forecasting Using Standard Precipitation Index Based on Rainfall of Western Region

Deepak Kumar Mishra

School of Agricultural Sciences and Engineering, IFTM University, Moradabad (UP) -244102, India.

Ram Kumar *

School of Agricultural Sciences and Engineering, IFTM University, Moradabad (UP) -244102, India.

B. R. Singh

College of Technology, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut-250110, India.

P. V. Singh

Department of Soil and Water Conservation Engineering, College of Technology, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar (Uttarakhand) -263145, India.

*Author to whom correspondence should be addressed.


Abstract

Drought has always been one of the most dangerous natural disasters for manhood. Due to the continuous global climate change, drought occurrences have become more frequent and severe, affecting human existence and long-term social progress.  PIStandard values are a measure of the probability of a given precipitation event occurring. They are calculated using a statistical distribution of precipitation data. The three statistical distributions that are most commonly used to model precipitation data are the gamma distribution, the normal distribution, and the log-normal distribution. Therefore, utilising all three of the above-mentioned theoretical probability distributions, the drought index PIStandard has been computed. PIStandard range more than 2 (extremely wet) to less than -2 (extremely dry), with 0.99 to - 0.99 considered the near-normal range. PIStandard is calculated at different time scales which can be 1, 3, 6, 12 and 24 months, time scales. The temporal trends of SPI at the stations were identified using the Mann-Kendall test. PIStandard were computation at 1, 3, 6, 9, 12 and 24-month time scales. PIStandard provides a better analysis of meteorological drought at multiple different timescales for short- and long-term planning because it uses the running sum of rainfall values at 1 to 24 months and more parameters for the statistical distribution used. For short-term drought monitoring and agricultural crop planning, a 1- to 3-month PIStandard can be utilized; however, long-term hydrological drought monitoring and water management planning require PIStandards of 6 to 9 months and 12 to 24 months, respectively. Drought analysis using PIStandard results can be used to design rainwater harvesting and storage structures in drought-affected areas for appropriate crop planning.

Keywords: Rainfall, standardized precipitation index (PIStandard), running sum


How to Cite

Mishra, D. K., Kumar, R., Singh , B. R., & Singh , P. V. (2023). Drought Forecasting Using Standard Precipitation Index Based on Rainfall of Western Region . International Journal of Environment and Climate Change, 13(11), 687–701. https://doi.org/10.9734/ijecc/2023/v13i113214

Downloads

Download data is not yet available.

References

Thomas J, Prasannakumar V. Temporal analysis of rainfall (1871–2012) and drought characteristics over a tropical monsoon-dominated State (Kerala) of India. J. Hydrol. 2016;534:266–280

Shekhar A, Shapiro CA. What do meteorological indices tell us about a long-term tillage study?. Soil Tillage Res. 2019;193:161–170.

Ramdas DA. Rainfall and Agriculture, Indian J. Met. and Geophys. Quoted from WMO (1975). 1950;1(4):262-274.

Beran MA, Redier JA. Hydrological aspects of drought. UNESCO-WMO. Studies and Reports in Hydrology. 1985;39:149.

Barker LJ, Hannaford J. Chiverton, A and Svensson, C 2016. From meteorological to hydrological drought using standardised indicators, Hydrol. Earth Syst. Sci. 2016;20:2483– 2505, Available:www.hydrol-earth-syst-sci.net/20/2483/2016/ DOI: 10.5194/hess-20-2483-2016

Palmer WC. Keeping track of crop moisture conditions, nationwide: The new crop Moisture Index. Weather Wise. 1968;21:156-161.

Chandra Kishor Kumar CK, Chandola VK, Kumar R. Meteorological drought characterization using effective drought index (EDI) for Banswara District (Rajasthan), India, International Journal of Current Microbiology and Applied Sciences. 2018;7(09).ISSN: 2319- 7706. DOI.org/10.20546/ijcmas.2018.709.423

Ntale HK, Gan TY. Drought indices and their application to east Africa. Int. J. Climatol. 2003;213:1335-1357.

Mckee TB, Doesken NJ, Kleist J. The relationship of drought frequency and duration of time scale. In: Proc. 8th Conference of Applied Climatology, Anaheim, California. 1993;179-184.

Gibbs WJ, Maher JV. Rainfall deciles as drought indicators. Bureau of Meteorology Bulletin No. 48, Commonwealth of Australia, Melbourne; 1967.

Dracup JA, Lee KS, Paulson EG Jr. On the definition of droughts. Water Resources Research. 1980;16(2):297-302.

Sen Z. Regional drought and flood frequency analysis: Theoretical consideration, J. Hydrology. 1980;46:265-279.

Kumar R, Kumar A, Shankhwar AK, Vishkarma DK, Sachan A, Singh PV, Jahangeer J, Verma A, Kumar V. Modelling of meteorological drought in the foothills of Central Himalayas: A case study in Uttarakhand State, India. Ain Shams Engineering Journal. 2022;3(1-14).

Guttam NH. Comparing the palmer Index and Standard Precipitation Index. J. Amer. Water Resources Association. 1998;35(2):113-121.

Guttam NH. Accepting the standard precipitation index: A calculation algorithm. J. Amer. Water Resources Association. 1999;35(2):311-312.

Kar G, James BK, Singh R, Mahapatra IC. Agroclimate and Extreme weather analysis for successful crop production in Orissa. Water Technology centre for Eastern Region, Bhubaneswar-Orissa, India. Research Bulletin 22/2004. 2004;1-76.

Wilhite DA, Svoboda MD, Hayes MJ. Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparedness. Water Resour. Manag. 2007;21:763–774.

Karlina 2016 meteorological drought assessment in Wonogiri District. Journal of the Civil Engineering Forum. 2016;2(2).

Salehnia N, Alizadeh A, Sanaeinejad H, Bannayan M, Zarrin Z, Hoogenboom G. Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data, J Arid Land. 2017; 9(6):797–809. DOI.org/10.1007/s40333-017-0070-y

Mc Mahan TA, Arenas AD. Methods of computation of low streamflow. Paris, UNESCO Studies and Reports in Hydrology. 1982;36:107.

Sharma HC, Chauhan HS, Sewa Ram. Probability analysis of rainfall for crop planning. J. Agricultural Engg. 1979; 16(3):87-97.