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Changes in drought characteristics based on rainfall pattern drought index and the CMIP6 multi-model ensemble

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  • Samantaray, Alok Kumar
  • Ramadas, Meenu
  • Panda, Rabindra Kumar

Abstract

Drought monitoring and understanding of spatiotemporal patterns of drought characteristics are beneficial for sustainable agricultural water management at a regional scale. Changes in rainfall and drought patterns in future could impact decision-making in water resources allocation. The impacts of potential climate change on future meteorological droughts could be better analysed by utilizing an index that incorporates the number of rainy days information in addition to magnitude of rainfall to characterize the drought severity. In this study, we propose a bivariate copula-based multi-scalar rainfall pattern drought index (RPDI), a variant of the popular standardized precipitation index (SPI), and then the drought characteristics in India based on RPDI and SPI at different time scales (3-, 6- and 12-months) are analysed. When compared to RPDI, SPI underestimated drought severity and indicated low spatial heterogeneity of drought characteristics. The RPDI analysis identified changes in average drought severity and total number of drought events between two sample time slices (1920–1960 and 1961–2000) in the historical period. Future RPDI drought characteristics based on the coupled model intercomparison project phase 6 (CMIP6) multi-model ensemble under two emission scenarios known as shared socioeconomic pathways (SSPs): SSP126 and SSP245 are then computed. When drought characteristics in the near future (2020–2049) and far future (2070–2099) periods are compared with their baseline period (1985–2014) values, the results show that a significant declining trend is likely in the total number of drought events over the study region, while increases are projected in the maximum drought duration and maximum drought severity in future. Long-term drought characteristics extracted using 12-months scale RPDI, are likely to intensify in future under both scenarios. Considering the effects of erratic rainfall pattern on agricultural productivity, the RPDI drought monitoring framework could be utilized for efficient agricultural water management in future.

Suggested Citation

  • Samantaray, Alok Kumar & Ramadas, Meenu & Panda, Rabindra Kumar, 2022. "Changes in drought characteristics based on rainfall pattern drought index and the CMIP6 multi-model ensemble," Agricultural Water Management, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:agiwat:v:266:y:2022:i:c:s0378377422001159
    DOI: 10.1016/j.agwat.2022.107568
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    1. Kalisa, Wilson & Zhang, Jiahua & Igbawua, Tertsea & Ujoh, Fanan & Ebohon, Obas John & Namugize, Jean Nepomuscene & Yao, Fengmei, 2020. "Spatio-temporal analysis of drought and return periods over the East African region using Standardized Precipitation Index from 1920 to 2016," Agricultural Water Management, Elsevier, vol. 237(C).
    2. Han, Zhiming & Huang, Qiang & Huang, Shengzhi & Leng, Guoyong & Bai, Qingjun & Liang, Hao & Wang, Lu & Zhao, Jing & Fang, Wei, 2021. "Spatial-temporal dynamics of agricultural drought in the Loess Plateau under a changing environment: Characteristics and potential influencing factors," Agricultural Water Management, Elsevier, vol. 244(C).
    3. Kaustubh Salvi & Subimal Ghosh, 2016. "Projections of Extreme Dry and Wet Spells in the 21st Century India Using Stationary and Non-stationary Standardized Precipitation Indices," Climatic Change, Springer, vol. 139(3), pages 667-681, December.
    4. Xu, Yang & Zhang, Xuan & Hao, Zengchao & Hao, Fanghua & Li, Chong, 2021. "Projections of future meteorological droughts in China under CMIP6 from a three‐dimensional perspective," Agricultural Water Management, Elsevier, vol. 252(C).
    5. Vergni, L. & Todisco, F. & Di Lena, B. & Mannocchi, F., 2020. "Bivariate analysis of drought duration and severity for irrigation planning," Agricultural Water Management, Elsevier, vol. 229(C).
    6. García-León, David & Contreras, Sergio & Hunink, Johannes, 2019. "Comparison of meteorological and satellite-based drought indices as yield predictors of Spanish cereals," Agricultural Water Management, Elsevier, vol. 213(C), pages 388-396.
    7. Xiong-Fei Liu & Shi-Xin Wang & Yi Zhou & Fu-Tao Wang & Guang Yang & Wen-Liang Liu, 2016. "Spatial analysis of meteorological drought return periods in China using Copulas," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(1), pages 367-388, January.
    8. Javad Bazrafshan, 2017. "Effect of Air Temperature on Historical Trend of Long-Term Droughts in Different Climates of Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4683-4698, November.
    9. Dai, Meng & Huang, Shengzhi & Huang, Qiang & Leng, Guoyong & Guo, Yi & Wang, Lu & Fang, Wei & Li, Pei & Zheng, Xudong, 2020. "Assessing agricultural drought risk and its dynamic evolution characteristics," Agricultural Water Management, Elsevier, vol. 231(C).
    10. Zhang, Yu & Hao, Zengchao & Feng, Sifang & Zhang, Xuan & Xu, Yang & Hao, Fanghua, 2021. "Agricultural drought prediction in China based on drought propagation and large-scale drivers," Agricultural Water Management, Elsevier, vol. 255(C).
    11. Alen Shrestha & Md Mafuzur Rahaman & Ajay Kalra & Rohit Jogineedi & Pankaj Maheshwari, 2020. "Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India," Forecasting, MDPI, vol. 2(2), pages 1-26, April.
    12. Xiong-Fei Liu & Shi-Xin Wang & Yi Zhou & Fu-Tao Wang & Guang Yang & Wen-Liang Liu, 2016. "Spatial analysis of meteorological drought return periods in China using Copulas," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(1), pages 367-388, January.
    13. Huang, Shengzhi & Huang, Qiang & Chang, Jianxia & Leng, Guoyong & Xing, Li, 2015. "The response of agricultural drought to meteorological drought and the influencing factors: A case study in the Wei River Basin, China," Agricultural Water Management, Elsevier, vol. 159(C), pages 45-54.
    14. Cai, X.L. & Sharma, B.R., 2010. "Integrating remote sensing, census and weather data for an assessment of rice yield, water consumption and water productivity in the Indo-Gangetic river basin," Agricultural Water Management, Elsevier, vol. 97(2), pages 309-316, February.
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    2. Li, Mo & Chen, Yingshan & Liu, Dong & Xue, Min & Wang, Yijia & Fu, Qiang, 2024. "Synergetic management of the water-energy-food nexus for cropland ecosystems under climate change: Toward a multistakeholder-based systematic optimization approach," Renewable Energy, Elsevier, vol. 220(C).

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