Abstract
Godavari basin, a rain-fed and the second largest river basin in India has witnessed numerous extreme events of droughts and floods in recent decades, having major implications on the water resource situation of the basin. The present study is an attempt to assess the near-future water stress zones of the basin by analysing seven variables under GIS-based multi-criteria decision analysis (GIS-MCDA): dryness intensity (DI), dry-episodes frequency (DF), wet-episodes frequency (WF), annual rainfall trend (RfT), dry days trend (DD), population growth rate (PGR) and groundwater fluctuation rate (GWR). The weight of the variables was assigned by analytical hierarchical process (AHP), and water stress regions were identified using weighted linear combination (WLC) under GIS-MCDA. DI, DF and WF for the last three decades of this basin were calculated using the 9-month Standardised Precipitation Evapotranspiration Index (SPEI-9). Mann–Kendall's test and Sen’s slope were used to examine the dry and wet trends in SPEI-9 and estimate the groundwater fluctuation rate. The analysis shows that if the current trends of the seven climatic, hydrologic and demographic variables persist, then the interior districts of the basin will be prone to high water stress risk in the near future. This study has identified the districts that need urgent structural and non-structural changes in the current water resource management practices to sustain the future climate change challenges.
Highlights:
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Examined the frequency and intensity of dry and wet episodes between 1990 and 2019 of the Godavari basin at the sub-basin level using Standardised Precipitation Evapotranspiration Index (SPEI–9 months).
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Mann–Kendall’s test shows that Manjra and Pranhita register strong dryness trend during most of the months of a year.
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The maximum decline (> 10 cm bgl y–1) of groundwater is recorded in Upper Godavari, Middle Godavari, Manjra and parts of Wardah and Pranhita.
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GIS-MCDA-based water stress risk assessment found that the interior districts of the basin are more prone to high water stress in near future.
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Identified the districts that need urgent structural and non-structural changes in the current water resource management practices.
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References
Abdullah M F, Siraj S and Hodgett R E 2021 An overview of multi-criteria decision analysis (MCDA) application in managing water-related disaster events: Analysing 20 years of literature for flood and drought events; Water 13 1358.
Agarwal R and Garg P K 2016 Remote sensing and GIS based groundwater potential & recharge zones mapping using multi-criteria decision making technique; Water Resour. Manag. 30 243–260.
Alam N M, Sharma G C, Moreira E, Jana C, Mishra P K, Sharma N K and Mandal D 2017 Evaluation of drought using SPEI drought class transitions and log-linear models for different agro-ecological regions of India; Phys. Chem. Earth Parts a/b/c 100 31–43, https://doi.org/10.1016/j.pce.2017.02.008.
Albuquerque M B, de Araújo A A, Martinez C E N M, Mauad F F and Okawa C M 2019 Sustainable urban drainage: A brief review of the compensatory techniques of structural and non-structural measures; Revista Eletrônica Em Gestão, Educação e Tecnologia Ambiental 23 35.
Araghi A, Mousavi-Baygi M and Adamowski J 2016 Detection of trends in days with extreme temperatures in Iran from 1961 to 2010; Theor. Appl. Climatol. 125 213–225.
Aruldoss M, Lakshmi T M and Venkatesan V P 2013 A survey on multi-criteria decision making methods and its applications; Am. J. Inf. Syst. 1 31–43.
Ayugi B O and Tan G 2019 Recent trends of surface air temperatures over Kenya from 1971 to 2010; Meteorol. Atmos. Phys. 131 1401–1413.
Begueria S, Vicente Serrano S M and Martínez M A 2010 A multiscalar global drought dataset: The SPEI base. A new gridded product for the analysis of drought variability and impacts; Bull. Am. Meteorol. Soc. 91 1351–1356.
Bryant E A 1991 Natural Hazards; Cambridge University Press, Cambridge.
Chenini I, Benmammou A and Elmay M 2010 Groundwater recharge zone mapping using GIS-based multi-criteria analysis: A case study in central Tunisia (Maknassy Basin); Int. J. Water Resour. Manag. 24 921–939.
Cook G D and Heerdegen R G 2001 Spatial variation in the duration of the rainy season in monsoonal Australia; Int. J. Climatol. 21 1723–1732.
CRED 2017 Annual disaster statistical review 2016: The numbers and trends; Centre for Research on the Epidemiology of Disasters.
Das S K, Gupta R K and Varma H K 2007 Flood and drought management through water resources development in India; WMO Bull. 56(3).
Dash S K, Kulkarni M A, Mohanty U C and Prasad K 2009 Changes in the characteristics of rain events in India; J. Geophys. Res. 114 D10109, https://doi.org/10.1029/2008JD010572.
Dhangar N, Vyas S, Guhathakurta P, Mukim S, Tidke N, Balasubramaian R and Chattopadhyay N 2019 Drought monitoring over India using multi-scalar standardised precipitation evapotranspiration index; Mausam 70(4) 833–840.
DoES 2016 State of Indian Agriculture 2015–2016; Directorate of Economics & Statistics, Ministry of Agriculture & Farmers Welfare.
EM-DAT (n.d.) The International Disaster Database; Centre for Research on the Epidemiology of Disasters CRED; https://public.emdat.be.
Estrela T and Vargas E 2012 Drought management plans in the European Union: The case of Spain; Water Resour. Manag. 26 1537–1553.
Fassio A, Giupponi C, Hiederer R and Simota C 2005 A decision support tool for simulating the effects of alternative policies affecting water resources: An application at the European scale; J. Hydrol. 304 462–476.
Gadgil S, Vinayachandran P N and Francis P A 2003 Droughts of the Indian summer monsoon: Role of clouds over the Indian Ocean; Curr. Sci. 85 1713–1719.
Giupponi C, Eiselt B and Ghetti P F 1999 A multi-criteria approach for mapping risks of agricultural pollution for water resources: The Venice Lagoon watershed case study; J. Environ. Manag. 56 259–269.
Gocic M and Trajkovic S 2013 Analysis of changes in meteorological variables using Mann–Kendall and Sen’s slope estimator statistical tests in Serbia; Global Planet. Change 100 172–182.
Goodchild M 1993 The state of GIS for environmental problem-solving; In: Environmental modeling with GIS (eds) Goodchild M, Parks B and Steyaert L, Oxford University Press, Oxford.
Gore P G and Sinha Ray K C 2002 Variability in drought incidence over districts of Maharashtra; Mausam 53(4) 533–542.
Guhathakurta P and Rajeevan M 2008 Trends in rainfall patterns over India; Int. J. Climatol. 28 1453–1469.
Guhathakurta P, Menon P, Inkane P M, Krishnan U and Sable S T 2017 Trends and variability of meteorological drought over the districts of India using standardised precipitation index; J. Earth Syst. Sci. 126(8) 1–8.
Gujja B, Dalai S, Shaik H and Goud V 2009 Adapting to climate change in the Godavari River basin of India by restoring traditional water storage systems; Clim. Dev. 1(3) 229–240.
Hengade N and Eldho T I 2019 Relative impact of recent climate and land cover changes in the Godavari river basin, India; J. Earth Syst. Sci. 128 94.
IMD 2020a Observed rainfall variability and changes over Andhra Pradesh State; Met Monograph No. ESSO/IMD/HS/Rainfall Variability/01(2020)/25.
IMD 2020b Observed Rainfall Variability and Changes Over Karnataka State; Met Monograph No.: ESSO/IMD/HS/Rainfall Variability/13(2020)/37.
IMD 2020c Observed Rainfall Variability and Changes Over Telangana State; Met Monograph No.: ESSO/IMD/HS/Rainfall Variability/25(2020)/49.
IMD 2020d Observed Rainfall Variability and Changes Over Chhattisgarh State; Met Monograph No.: ESSO/IMD/HS/Rainfall Variability/05(2020)/29.
IMD 2020e Observed Rainfall Variability and Changes Over Madhya Pradesh State; Met Monograph No.: ESSO/IMD/HS/Rainfall Variability/15(2020)/39.
IMD 2020f Observed Rainfall Variability and Changes Over Maharashtra State; Met Monograph No.: ESSO/IMD/HS/Rainfall Variability/16(2020)/40.
IMD 2020g Observed Rainfall Variability and Changes Over Odisha State; Met Monograph No.: ESSO/IMD/HS/Rainfall Variability/20(2020)/44.
India-WRIS 2014 Godavari Basin; Central Water Commission (CWC) and National Remote Sensing Centre (NRSC), Indian Space Research Organisation (ISRO), Ministry of Water Resources, Government of India.
Kendall M G 1975 Rank Correlation Methods; Griffin, London.
Kulkarni A, Deshpande N, Kothawale D R, Sabade S S, Rama Rao M V S, Sabin T P, Patwardhan S, Mujumdar M and Krishnan R 2017 Observed climate variability and change over India; In: Climate change over India – an interim report (eds) Krishnan R and Sanjay J, Centre for Climate Change Research, IITM, Pune.
Kundzewicz Z W and Döll P 2009 Will groundwater ease freshwater stress under climate change?; Hydrol. Sci. J. 54(4) 665–675.
Kundzewicz Z W, Hegger D L T, Matczak P and Driessen P P J 2018 Opinion: Flood-risk reduction: Structural measures and diverse strategies; Proc. Nat. Acad. Sci. 115 12,321–12,325.
Lettenmaier D P, Wood E F and Wallis J R 1994 Hydro-climatological trends in the continental United States, 1948–1988; J. Clim. 7 586–607.
Liu X, Wang S, Zhou Y, Wang F, Li W and Liu W 2015 Regionalization and spatiotemporal variation of drought in China based on standardised precipitation evapotranspiration index (1961–2013); Adv. Meteor. 950262 18.
Makropoulos C K, Natsis K, Liu S, Mittas K and Butler D 2008 Decision support for sustainable option selection in integrated urban water management; Environ. Model. Software 23 1448–1460.
Malczewski J 2004 GIS-based land-use suitability analysis: A critical overview; Prog. Plann. 62 3–65.
Malczewski J 2006 GIS-based multi-criteria decision analysis: A survey of the literature; Int. J. Geogr. Inf. Sci. 20(7) 703–726.
Mann H B 1945 Nonparametric tests against trend; Econometrica 13 245–259.
Martin N J, St-Onge B and Waaub J P 2003 An integrated decision aid system for the development of Saint Charles River alluvial plain, Quebec, Canada; Int. J. Environ. Pollut. 12 264–279.
McKee T B, Doesken N J and Kliest J 1993 The relationship of drought frequency and duration to time scales; Proceedings of the 8th Conference on Applied Climatology, American Meteorological Society, Boston, MA, pp. 179–184.
Mekonnen M M and Hoekstra A Y 2016 Four billion people facing severe water scarcity; Sci. Adv. 2 e1500323.
Meyer V, Haase D and Scheuer S 2007 GIS-based multi-criteria analysis as decision support in flood risk management; UFZ Discussion Paper No. 6/2007, Helmholtz-Zentrum für Umweltforschung (UFZ), Leipzig.
Mortazavi M, Kuczera G and Cui L 2012 Multiobjective optimisation of urban water resources: Moving toward more practical solutions; Water Resour. Res. 48 W03514.
Mujumdar M, Bhaskar P, Ramarao M V S, Uppara U, Goswami M, Borgaonkar H, Chakraborty S, Ram S, Mishra V, Rajeevan M and Niyogi D 2020 Droughts and floods; In: Assessment of Climate Change over the Indian Region (eds) Krishnan R, Sanjay J, Gnanaseelan C, Mujumdar M, Kulkarni A and Chakraborty S, Springer, Singapore, https://doi.org/10.1007/978-981-15-4327-2_6.
NATMO 1986 Water Resources Development Atlas; National Atlas Thematic Mapping Organization, DST, Government of India.
NIC 2009 India: The Impact of Climate Change to 2030; A Commissioned Research Report: NIC 2009-03D, Joint Global Change Research Institute and Battelle Memorial Institute, Pacific Northwest Division, National Intelligence Council.
Nicholson S 2000 Land surface processes and Sahel climate; Rev. Geophys. 38 117–139, https://doi.org/10.1029/1999RG900014.
NITI Aayog 2018 Composite Water Management Index: A tool for water management; Government of India.
Pai D S and Rajeevan M 2007 Indian summer monsoon onset: Variability and prediction Indian summer monsoon onset; National Climate Centre, India Meteorological Department, Pune.
Palmer W C 1965 Meteorological Drought; Research Paper No. 45, US Department of Commerce, Weather Bureau, Washington, DC 59.
Partal T and Kahya E 2006 Trend analysis in Turkish precipitation data; Hydrol. Process. 20 2011–2026.
Paul S, Ghosh S, Oglesby R, Pathak A, Chadrasekharan A and Ramasankaran R 2016 Weakening of Indian summer monsoon rainfall due to changes in land use land cover; Sci. Rep. 6 32177.
Paul S, Ghosh S, Rajendran K and Murtugudde R 2018 Moisture supply from the Western Ghats forests to water deficit East Coast of India; Geophys. Res. Lett. 45 4337–4344.
PIB Delhi 2022 Repair, renovation & restoration of water bodies; Ministry of Jal Shakti, https://pib.gov.in/PressReleasePage.aspx?PRID=1813258.
Qin X S, Huang G H, Chakma A, Nie X H and Lin Q G 2008 A MCDM-based expert system for climate change impact assessment and adaptation planning – A case study for the Georgia Basin, Canada; Expert Syst. Appl. 34 2164–2179.
Radhakrishnan A, Murthy J V R and Gupte K 2014 Water-use efficiency through a multi-stakeholder platform; In: Water Conservation and Saving in Agriculture – Initiatives, Achievements and Challenges in Maharashtra, Water Resources Department, Government of Maharashtra, India.
Raju K S, Duckstein L and Arondel C 2000 Multicriterion analysis for sustainable water resources planning: A case study in Spain; Water Resour. Manag. 14 435–456.
Richey A S, Thomas B F, Lo M H, Reager J T, Famiglietti J S, Voss K, Swenson S and Rodell M 2015 Quantifying renewable groundwater stress with GRACE; Water Resour. Res. 51(7) 5217–5238, https://doi.org/10.1002/2015WR017349.
Saaty T L 1977 A scaling method for priorities in hierarchical structures; J. Math. Psycho. 15 234–281.
Saaty T L 1980 The analytic hierarchy process; McGraw-Hill, New York.
Saaty T L 2008 Decision making with the analytical hierarchy process; IJS Sci. 1 83–98.
Satish Kumar K, Anand Raj P, Sreelatha K and Sridhar V 2021 Regional analysis of drought severity-duration-frequency and severity-area-frequency curves in the Godavari River Basin, India; Int. J. Climatol. 41(12) 5481–5501.
Sen P K 1968 Estimates of the regression coefficient based on Kendall’s tau; J. Am. Stat. Assoc. 63 1379–1389.
Shewale M P and Kumar S 2005 Climatological features of drought incidences in India; Meteorological Monograph, Climatology No. 21/2005, India Meteorological Department.
UNDRR 2021 GAR Special Report on Drought 2021; The UN Global Assessment Report on Disaster Risk Reduction (GAR), United Nations Office for Disaster Risk Reduction.
UN-Water 2021 Summary Progress Update 2021: SDG 6 – water and sanitation for all.
Van Beck L P H, Wada Y and Bierkens M F P 2011 Global monthly water stress: Water balance and water availability; Water Resour. Res. 47 W07517.
Vicente-Serrano S M, Beguería S and López-Moreno J I 2010a A multiscalar drought index sensitive to global warming: The standardised precipitation evapotranspiration index; J. Clim. 23 1696–1718.
Vicente-Serrano S M, Begueria S, Martínez M A, Angulo M and El Kenawy A 2010b A new global 0.5 gridded dataset (1901–2006) of a multiscalar drought index: Comparison with current drought index datasets based on the Palmer Drought Severity Index; J. Hydrometeorol. 11 1033–1043.
World Bank 2022 World Water Day 2022: How India is addressing its water needs; https://www.worldbank.org/en/country/india/brief/world-water-day-2022-how-india-is-addressing-its-water-needs.
World Economic Forum, Global Risks 2015, 10th edn, World Economic Forum, Geneva, Switzerland.
WRD 2017 Integrated state water plan for Godavari Basin in Maharashtra; Vol-I, Godavari Marathwada Irrigation Development Corporation & Vidarbha Irrigation Development Corporation, Water Resources Department, Government of Maharashtra.
WRS 2013 Water and Related Statistics 2013; Water Related Statistics Directorate, Information System Organisation, Water Planning & Projects Wing, Central Water Commission, Government of India.
WRS 2021 Water and Related Statistics 2021; Water Related Statistics Directorate, Information System Organisation, Water Planning & Projects Wing, Central Water Commission, Government of India.
Wu W, Geller M A and Dickinson R E 2002 The response of soil moisture to long-term variability of precipitation; J. Hydrometeorol. 3(5) 604–613, https://doi.org/10.1175/1525-7541(2002)003%3C0604:TROSMT%3E2.0.CO;2.
WWDR 2020 Water and Climate Change; The United Nations World Water Development Report 2020, UN Water.
Yaduvanshi A and Ranade A 2017 Long-term rainfall variability in the eastern Gangetic Plain in relation to global temperature change; Atmos. Ocean 55(2) 94–109.
Yaduvanshi A, Kulkarni A, Bendapudi R and Haldar K 2020 Observed changes in extreme rain indices in semiarid and humid regions of Godavari basin, India: Risks and opportunities; Nat. Hazards 103 685–711.
Yang T H and Liu W C 2020 A general overview of the risk-reduction strategies for floods and droughts; Sustainability 12 2687.
Yue S and Hashino M 2003 Temperature trends in Japan: 1900–1996; Theor. Appl. Climatol. 75 15–27.
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I am grateful to the assistant editor and anonymous reviewers of JESS for their constructive reviews and thoughtful comments, which helped in refining the manuscript.
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Soma Sarkar: conceptualising the problem, study plan, data collection, data modelling and analysis, interpretation of results and drafting the manuscript.
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Sarkar, S. Appraisal of water stress regions of Godavari basin for climate resilient water resource management: A GIS-MCDA based approach. J Earth Syst Sci 132, 182 (2023). https://doi.org/10.1007/s12040-023-02196-w
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DOI: https://doi.org/10.1007/s12040-023-02196-w