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Spatio-temporal drought assessment of the Subarnarekha River basin, India, using CHIRPS-derived hydrometeorological indices

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Abstract

Precipitation studies have a crucial role in deciphering climate change and monitoring natural disasters such as droughts. Such studies lead to better assessment of rainfall amounts and spatial variabilities; and have a vital role in impact assessment, mitigation, and prediction of occurrence. Thus, this study has been undertaken in the Subarnarekha River basin using Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset. Precipitation datasets helped in deriving hydrometeorological indices such as the Rainfall Anomaly Index (RAI) and Standardized Precipitation Index (SPI) for the identification of drought occurrences. The core objective was to infer spatio-temporal drought scenarios and their trend characterization covering four decades over the years 1981 to 2020. Quantitative drought assessment was done using run theory for identifying the Drought Duration (DD), Drought Severity (DS), Drought Intensity (DI), and Drought Frequency (DF). Mann–Kendall (MK) test was performed to understand the precipitation and drought trends at annual and seasonal scales. Eight severe drought events were identified in the Subarnarekha River basin for the past 40 years and the average DI value of 0.8 was recorded. MK test results for the precipitation showed a significant positive trend (95% confidence level) for pre-monsoon periods. However, for SPI, a significant positive trend was observed over the intervals of 3 (SPI3), 6 (SPI6), and 12 (SPI12) months respectively at an annual timescale, suggesting wetter conditions within the study area. Moreover, there had been insignificant negative trends for SPI1 and SPI3 during winter. It indicates that during the short-term SPI scale, i.e., 1 month (SPI1) and 3 months (SPI3), the instances of negative SPI values inferred were high, which point to the increasing incidences of meteorological drought possibly due to deficient soil moisture. Thus, the results indicated that the CHIRPS precipitation product-derived hydrometeorological indices could act as a valuable tool for assessing the past spatio-temporal drought conditions of the Subarnarekha River basin. This may further be helpful in planning for sustainable water resource management of such river basins.

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References

  • Aadhar, S., & Mishra, V. (2017). Data descriptor: High-resolution near real-time drought monitoring in South Asia. Scientific Data, 4, 1–14. https://doi.org/10.1038/sdata.2017.145

    Article  Google Scholar 

  • Ajaz, A., Taghvaeian, S., Khand, K., Gowda, P. H., & Moorhead, J. E. (2019). Development and evaluation of an agricultural drought index by harnessing soil moisture and weather data. Water (Switzerland), 11(7). https://doi.org/10.3390/w11071375

  • Beguería, S., Vicente-Serrano, S. M., Reig, F., & Latorre, B. (2014). Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. International Journal of Climatology, 34(10), 3001–3023. https://doi.org/10.1002/joc.3887

    Article  Google Scholar 

  • Bisht, D. S., Chatterjee, C., Raghuwanshi, N. S., & Sridhar, V. (2018). Spatio-temporal trends of rainfall across Indian river basins. Theoretical and Applied Climatology, 132(1–2), 419–436. https://doi.org/10.1007/s00704-017-2095-8

    Article  Google Scholar 

  • Central Water Commission. (2017). Water Year Book: Baitarani,Subarnarekha and Burhabalang Basin (Vol. 3).

  • Chatterjee, S., Krishna, A. P., & Sharma, A. P. (2014). Geospatial assessment of soil erosion vulnerability at watershed level in some sections of the Upper Subarnarekha river basin, Jharkhand, India. Environmental Earth Sciences, 71(1), 357–374. https://doi.org/10.1007/s12665-013-2439-3

    Article  Google Scholar 

  • Chaudhary, S., & Pandey, A. C. (2021). PCA driven watershed prioritization based on runoff modeling and drought severity assessment in parts of Koel river basin, Jharkhand (India). Water Supply, 22(2), 2034–2054. https://doi.org/10.2166/ws.2021.297

    Article  Google Scholar 

  • DAC & FW. (2016). Drought Crisis Management Plan (National) 2016 - India. Department of Agriculture, Cooperation& Farmers Welfare, Government of India.

  • de Carvalho, M. Â. C. C., Uliana, E. M., da Silva, D. D., Aires, U. R. V., da Silva Martins, C. A., de Sousa Junior, M. F., da Cruz, I. F., & Mendes, M. A. D. S. A. (2020). Drought monitoring based on remote sensing in a grain-producing region in the cerrado–amazon transition, Brazil. Water (switzerland), 12(12), 1–16. https://doi.org/10.3390/w12123366

    Article  Google Scholar 

  • Dutta, D., Kundu, A., Patel, N. R., Saha, S. K., & Siddiqui, A. R. (2015). Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI). Egyptian Journal of Remote Sensing and Space Science, 18(1), 53–63. https://doi.org/10.1016/j.ejrs.2015.03.006

    Article  Google Scholar 

  • Edwards, D. C. (1997). Characteristics of 20th century drought in the United States at multiple time scales (vol. 298, issue 0704).

  • Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Rowland, J., Romero, B., Husak, G., Michaelsen, J., & Verdin, A. (2014). A quasi-global precipitation time series for drought monitoring. US Geological Survey Data Series, 832(January), 4. https://doi.org/10.3133/ds832

    Article  Google Scholar 

  • Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations—A new environmental record for monitoring extremes. Scientific Data, 2, 1–21. https://doi.org/10.1038/sdata.2015.66

    Article  Google Scholar 

  • Ganguli, P., Singh, B., Reddy, N. N., Raut, A., Mishra, D., & Das, B. S. (2022). Climate-catchment-soil control on hydrological droughts in peninsular India. Scientific Reports, 12(1), 1–14. https://doi.org/10.1038/s41598-022-11293-7

    Article  CAS  Google Scholar 

  • Gao, F., Zhang, Y., Ren, X., Yao, Y., Hao, Z., & Cai, W. (2018). Evaluation of CHIRPS and its application for drought monitoring over the Haihe River Basin, China. Natural Hazards, 92(1), 155–172. https://doi.org/10.1007/s11069-018-3196-0

    Article  Google Scholar 

  • Gidey, E., Dikinya, O., Sebego, R., Segosebe, E., & Zenebe, A. (2018). Modeling the spatio-temporal meteorological drought characteristics using the Standardized Precipitation Index (SPI) in Raya and its environs, Northern Ethiopia. Earth Systems and Environment, 2(2), 281–292. https://doi.org/10.1007/s41748-018-0057-7

    Article  Google Scholar 

  • Government of India. (2016). Manual for Drought Management.

  • Guha, S., & Patel, P. P. (2017). Evidence of topographic disequilibrium in the subarnarekha river basin, India: A digital elevation model based analysis. Journal of Earth System Science, 126(7), 1–20. https://doi.org/10.1007/s12040-017-0884-1

    Article  Google Scholar 

  • Guo, H., Bao, A., Liu, T., Ndayisaba, F., He, D., Kurban, A., & De Maeyer, P. (2017). Meteorological drought analysis in the Lower Mekong Basin using satellite-based long-term CHIRPS product. Sustainability (Switzerland), 9(6). https://doi.org/10.3390/su9060901

  • Gupta, D. B., & Mitra, S. (2004). Sustaining Subernarekha River basin. International Journal of Water Resources Development, 20(3), 431–444. https://doi.org/10.1080/0790062042000248529

    Article  Google Scholar 

  • Hänsel, S., Schucknecht, A., & Matschullat, J. (2016). The Modified Rainfall Anomaly Index (mRAI)—Is this an alternative to the Standardised Precipitation Index (SPI) in evaluating future extreme precipitation characteristics? Theoretical and Applied Climatology, 123(3–4), 827–844. https://doi.org/10.1007/s00704-015-1389-y

    Article  Google Scholar 

  • Hayes, M., Svoboda, M., Wall, N., & Widhalm, M. (2011). The lincoln declaration on drought indices: Universal meteorological drought index recommended. Bulletin of the American Meteorological Society, 92(4), 485–488. https://doi.org/10.1175/2010BAMS3103.1

    Article  Google Scholar 

  • Helsel, D. R., & Hirsch, R. M. (1992). Statistical methods in water resources. 522.

  • Jamro, S., Channa, F. N., Dars, G. H., Ansari, K., & Krakauer, N. (2020). Exploring the evolution of drought characteristics in Balochistan, Pakistan. Applied Sciences, 10(913). https://doi.org/10.3390/app10030913

  • Jha, V. B., Gujrati, A., & Singh, R. P. (2021). Copula based analysis of meteorological drought and catchment resilience across Indian river basins. International Journal of Climatology, 41(S1), E1137–E1151. https://doi.org/10.1002/joc.6758

    Article  Google Scholar 

  • Kendall, M. (1975). Rank Correlation Methods. (4th ed.). Griffin & Co.

  • Keyantash, J., & Dracup, J. A. (2002). The quantification of drought: An evaluation of a drought indices. American Meteorological Society, August, 1167–1180.

  • Konapala, G., Mishra, A. K., Wada, Y., & Mann, M. E. (2020). Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation. Nature Communications, 11(1), 1–10. https://doi.org/10.1038/s41467-020-16757-w

    Article  CAS  Google Scholar 

  • Koudahe, K., Kayode, A. J., Samson, A. O., Adebola, A. A., & Djaman, K. (2017). Trend analysis in Standardized Precipitation Index and Standardized Anomaly Index in the context of climate change in Southern Togo. Atmospheric and Climate Sciences, 07(04), 401–423. https://doi.org/10.4236/acs.2017.74030

    Article  Google Scholar 

  • Kumar, V., & Jain, S. K. (2011). Trends in rainfall amount and number of rainy days in river basins of India ( 1951 – 2004). Hydrlogy Research, 290–306. https://doi.org/10.2166/nh.2011.067

  • Kumar, P., & Joshi, V. (2015). Characterization of hydro geological behavior of the upper watershed of River Subarnarekha through morphometric analysis using remote sensing and GIS approach. International Journal on Environmental Sciences, 6(4), 429–447. https://doi.org/10.6088/ijes.6049

    Article  Google Scholar 

  • Kundu, A., Patel, N. R., Denis, D. M., & Dutta, D. (2020). An estimation of hydrometeorological drought stress over the central part of India using geo-information technology. Journal of the Indian Society of Remote Sensing, 48(1), 1–9. https://doi.org/10.1007/s12524-019-01048-9

    Article  Google Scholar 

  • Li, Y. J., Zheng, X. D., Lu, F., & Ma, J. (2012). Analysis of drought evolvement characteristics based on Standardized Precipitation Index in the Huaihe River Basin. Procedia Engineering, 28(2011), 434–437. https://doi.org/10.1016/j.proeng.2012.01.746

    Article  Google Scholar 

  • Liu, Y., & Chen, J. (2021). Future global socioeconomic risk to droughts based on estimates of hazard, exposure, and vulnerability in a changing climate. Science of the Total Environment, 751, 142159. https://doi.org/10.1016/j.scitotenv.2020.142159

    Article  CAS  Google Scholar 

  • Livada, I., & Assimakopoulos, V. D. (2007). Spatial and temporal analysis of drought in Greece using the Standardized Precipitation Index (SPI). Theoretical and Applied Climatology, 89(3–4), 143–153. https://doi.org/10.1007/s00704-005-0227-z

    Article  Google Scholar 

  • Loukas, A., & Vasiliades, L. (2004). Probabilistic analysis of drought spatiotemporal characteristics in Thessaly region, Greece. Natural Hazards and Earth System Science, 4(5–6), 719–731. https://doi.org/10.5194/nhess-4-719-2004

    Article  Google Scholar 

  • Mandal, U., Sena, D. R., Dhar, A., Panda, S. N., Adhikary, P. P., & Mishra, P. K. (2021). Assessment of climate change and its impact on hydrological regimes and biomass yield of a tropical river basin. Ecological Indicators, 126, 107646. https://doi.org/10.1016/j.ecolind.2021.107646

    Article  Google Scholar 

  • Mann, H. B. (1945). Non-Parametric test against trend. Econometrica, 13(3), 245–259.

    Article  Google Scholar 

  • McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, 179–183.

  • Mondal, A., & Lakshmi, V. (2021). Estimation of total water storage changes in India. International Journal of Digital Earth, 14(10), 1294–1315. https://doi.org/10.1080/17538947.2021.1914759

    Article  Google Scholar 

  • NRAA. (2013). Contingency and compensatory agriculture plans for droughts and floods in India 2012 - India.

  • Pandey, V., Srivastava, P. K., Mall, R. K., Munoz-Arriola, F., & Han, D. (2020). Multi-satellite precipitation products for meteorological drought assessment and forecasting in Central India. Geocarto International, 1–20. https://doi.org/10.1080/10106049.2020.1801862

  • Pandey, V., Srivastava, P. K., Singh, S. K., Petropoulos, G. P., & Mall, R. K. (2021). Drought identification and trend analysis using long-term chirps satellite precipitation product in Bundelkhand, India. Sustainability (Switzerland), 13(3), 1–20. https://doi.org/10.3390/su13031042

    Article  Google Scholar 

  • Poonia, V., Goyal, M. K., Gupta, B. B., Gupta, A. K., Jha, S., & Das, J. (2021). Drought occurrence in different river basins of India and blockchain technology based framework for disaster management. Journal of Cleaner Production, 312(April), 127737. https://doi.org/10.1016/j.jclepro.2021.127737

    Article  Google Scholar 

  • Rolbiecki, R., Yücel, A., Kocięcka, J., Atilgan, A., Marković, M., & Liberacki, D. (2022). Analysis of SPI as a drought indicator during the maize growing period in the Çukurova Region (Turkey). Sustainability (Switzerland), 14(6). https://doi.org/10.3390/su14063697

  • Rossi, G., Vega, T., & Bonaccorso, B. (2007). Methods and tools for drought analysis and management. In Water Science and Technology Library (vol. 62). Springer Netherlands.

  • Roy, A. K., & Hirway, I. (2007). Multiple impacts of droughts and assessment of drought policy in major drought prone states in India. Project Report Submitted to the Planning Commission, Government of India, New Delhi. http://dx.doi.org/10.13140/RG.2.2.20088.03843

  • Samra, J. S. (2004). Review and analysis of drought monitoring, declaration and management in India. Working Paper 84. Drought Series Paper 2. International Water Management Institute, Colombo. International Water Management Institute.

  • Saravi, M. M., Safdari, A. A., & Malekian, A. (2009). Intensity-duration-frequency and spatial analysis of droughts using the Standardized Precipitation Index. Hydrology and Earth System Sciences Discussions, 6(2), 1347–1383. https://doi.org/10.5194/hessd-6-1347-2009

    Article  Google Scholar 

  • Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s tau. Journal of the American Statistical Association, 63(324), 1379–1389. https://doi.org/10.1080/01621459.1968.10480934

    Article  Google Scholar 

  • Shah, D., & Mishra, V. (2020). Integrated Drought Index (IDI) for drought monitoring and assessment in India. Water Resources Research, 56(2), 1–22. https://doi.org/10.1029/2019WR026284

    Article  Google Scholar 

  • Sharma, A., & Goyal, M. K. (2020). Assessment of drought trend and variability in India using wavelet transform. Hydrological Sciences Journal, 65(9), 1539–1554. https://doi.org/10.1080/02626667.2020.1754422

    Article  Google Scholar 

  • Sharma, A., Sharma, D., & Panda, S. K. (2022). Assessment of spatiotemporal trend of precipitation indices and meteorological drought characteristics in the Mahi River basin. India. Journal of Hydrology, 605(December 2021), 127314. https://doi.org/10.1016/j.jhydrol.2021.127314

    Article  Google Scholar 

  • Shewale, M. P., & Kumar, S. (2005). Climatological features of drought incidences in India. Meteorological monograph (Climatology 21/2005). In National Climate Centre, India Meteorological Department.

  • Shiau, J. T., & Modarres, R. (2009). Copula-based drought severity-duration-frequency analysis in Iran. Meteorological Applications, 16(4), 481–489. https://doi.org/10.1002/met.145

    Article  Google Scholar 

  • Shrestha, N. K., Qamer, F. M., Pedreros, D., Murthy, M. S. R., Wahid, S. M., & Shrestha, M. (2017). Evaluating the accuracy of Climate Hazard Group (CHG) satellite rainfall estimates for precipitation based drought monitoring in Koshi basin, Nepal. Journal of Hydrology: Regional Studies, 13(September), 138–151. https://doi.org/10.1016/j.ejrh.2017.08.004

    Article  Google Scholar 

  • Svoboda, M., Hayes, M., & Wood, D. (2012). World Meteorological Organization, 2012: Standardized Precipitation Index User Guide. In WMO-No. 1090.

  • Tigga, A., & Malini, B. H. (2014). Impact assessment of environmental changes on droughts over Ranchi city, Jharkhand, India. International Journal of Multidisciplinary Educational Research, 3(9(4)).

  • Trenberth, K. E. (2005). The impact of climate change and variability on heavy precipitation, floods, and droughts. Encyclopedia of Hydrological Sciences. https://doi.org/10.1002/0470848944.hsa211

    Article  Google Scholar 

  • Trenberth, K. E. (2011). Changes in precipitation with climate change. Climate Research, 47(1–2), 123–138. https://doi.org/10.3354/cr00953

    Article  Google Scholar 

  • Van-rooy, M. P. (1965). A Rainfall Anomaly Index (RAI), independent of the time and space. Notos, 14, 43–48.

    Google Scholar 

  • Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. Journal of Climate, 23(7), 1696–1718. https://doi.org/10.1175/2009JCLI2909.1

    Article  Google Scholar 

  • Vogt, J.V., Naumann, G., Masante, D., Spinoni, J., Cammalleri, C., Erian, W., Pischke, F., Pulwarty, R., & Barbosa, P. (2018). Drought risk assessment and management. A conceptual framework. In Publications Office of the European Union, Luxembourg, 2018. https://doi.org/10.2760/057223, JRC113937.

  • Wang, L., Zhang, X., Wang, S., Salahou, M. K., & Fang, Y. (2020). Analysis and application of drought characteristics based on theory of runs and copulas in Yunnan, southwest China. International Journal of Environmental Research and Public Health, 17(13), 1–17. https://doi.org/10.3390/ijerph17134654

    Article  CAS  Google Scholar 

  • Wilhite, D. A. (2000). Drought as a natural hazard: Concepts and definitions. Drought: A Global Assessment, I, 3–18. https://doi.org/10.4324/9781315830896-24

  • Wu, W., Li, Y., Luo, X., Zhang, Y., Ji, X., & Li, X. (2019). Performance evaluation of the CHIRPS precipitation dataset and its utility in drought monitoring over Yunnan Province, China. Geomatics, Natural Hazards and Risk, 10(1), 2145–2162. https://doi.org/10.1080/19475705.2019.1683082

    Article  Google Scholar 

  • Yaduvanshi, A., Sinha, A. K., & Haldar, K. (2019). A century scale hydro-climatic variability and associated risk in Subarnarekha river basin of India. Modeling Earth Systems and Environment, 5(3), 937–949. https://doi.org/10.1007/s40808-019-00580-4

    Article  Google Scholar 

  • Yevjevich, V. (1967). An objective approach to definitions and investigations of continental hydrologic droughts. Journal of Hydrology, 7(3), 353. https://doi.org/10.1016/0022-1694(69)90110-3

    Article  Google Scholar 

  • Zhang, M., Luo, D., & Su, Y. (2021). Drought monitoring and agricultural drought loss risk assessment based on multisource information fusion. Natural Hazards, 0123456789. https://doi.org/10.1007/s11069-021-05078-w

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Acknowledgements

First author also wishes to acknowledge her fellowship support from DST-SERB. Freely available rainfall data from the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) are also acknowledged herewith.

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This work was facilitated through the grant support of the DST-SERB (CRG/2019/002351), Govt. of India.

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  1. Department of Remote Sensing, Birla Institute of Technology, Mesra, India, 835215

    Farhin Tabassum & Akhouri Pramod Krishna

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Tabassum, F., Krishna, A.P. Spatio-temporal drought assessment of the Subarnarekha River basin, India, using CHIRPS-derived hydrometeorological indices. Environ Monit Assess 194, 902 (2022). https://doi.org/10.1007/s10661-022-10547-1

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