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Water footprint analysis for the upper Baitarani River basin, India

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Abstract

The water footprints (WFs) or freshwater availability components such as blue water flow (water yield plus deep aquifer recharge), green water flow (actual evapotranspiration), and green water storage (soil moisture) at spatial (sub-basin) level with temporal (monthly) time-steps are assessed for the Upper Baitarani River Basin (UBRB) of India. This study uses the modeling framework of the Soil Water Assessment Tool (SWAT) and the Sequential Uncertainty Fitting version 2 (SUFI-2) in SWAT-Calibration and Uncertainty Programs (SWAT-CUP) for automatic calibration of the hydrological model. In addition, the climate change impacts on the monthly soil moisture levels in the (UBRB) were assessed using five general circulation models (GCMs) under representative concentration pathways (RCPs) 4.5 and 8.5 scenarios. Model performance was evaluated using several statistical parameters. For calibration (1991–2006), the coefficient of determination (R2) was obtained as 0.86, and for validation (2007–2011) was 0.94. The Nash–Sutcliffe (NS) efficiency in the calibration was 0.85 and was obtained as 0.93 in the validation. The percentage bias (PBIAS) for calibration was − 11 and for the validation, the period was − 10.40. A good agreement among the simulated and observed data was found in both calibration and validation of the models. The average annual amount of water resources in the UBRB was 4749.59 million m3, of which the blue water resources were 1691 million m3, and the green water resources were 3058 million m3. The results summarize the spatiotemporal distribution of blue and green water resources and provide comprehensive information on water availability status in the study region for better planning management.

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Data availability

The data presented in this study are available on request from the corresponding author.

References

  • Abbaspour KC, Vejdani M, Haghighat S (2007) SWAT-CUP: Calibration and uncertainty programs for SWAT. Proceedings of the International Congress on Modelling and Simulation (MODSIM 2007), Modelling and Simulation Society of Australia and New Zealand, New Zealand, pp 1596–1602

  • Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment, Part I: Model development. J Am Water Resour Assoc 34:73–89

    Article  Google Scholar 

  • Cosgrove WJ, Rijsberman FR (2000) World water vision: making water everybody’s business. Earthscan Publications Ltd., London

    Google Scholar 

  • Cunge JA (1969) On the subject of a flood propagation method (Muskingum method). J Hydraul Res IAHR 7(2):205–230

    Article  Google Scholar 

  • Falkenmark M (1995) Coping with water scarcity under rapid population growth. Conference of SADC Ministers, Pretoria

  • FAO (2009) Harmonized World Soil Database (Version 1.1). In Global Environmental Change-Human and Policy Dimensions. FAO: Rome, Italy and IIASA, Laxenburg, Austria

  • Faramarzi M, Abbaspour KC, Schulin R, Yang H (2009) Modeling blue and green water resources availability in Iran. Hydrol Process 23:486–501

    Article  Google Scholar 

  • Gao X, Zuo D, Xu Z, Cai S, Xianming H (2018) Evaluation of blue and green water resources in the upper Yellow River basin of China. Proc IAHS 379:159–167. https://doi.org/10.5194/piahs-379-159-2018

    Article  Google Scholar 

  • Golabi MR (2020) New approach to the allocation of the blue water footprint of reservoirs using fuzzy AHP model. Model Earth Syst Environ 6:793–797. https://doi.org/10.1007/s40808-019-00706-8

    Article  Google Scholar 

  • Hargreaves GL, Hargreaves GH, Riley JP (1985) Irrigation water requirements for Senegal River Basin. J Irrig Drain Eng ASCE 111(3):265–275

    Article  Google Scholar 

  • IITM (Indian Institute of Tropical Meteorology) (2016) Climate data portal-CCCR. http://cccr.tropmet.res.in/home/ftp_data.jsp

  • IPCC (2014) Climate change—mitigation of climate change. Working Group III Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, 2014

  • Kaviya B (2013) Runoff estimation using SWAT model in Brahmani-Baitarani river basin. Int J Biot Tren Tech 3(2)

  • Lathuillière MJ, Coe MT (2016) Johnson MS (2016) A review of green and blue-water resources and their trade-offs for future agricultural production in the Amazon Basin: what could irrigated agriculture mean for Amazonia. Hydrol Earth Syst Sci 20:2179

    Article  Google Scholar 

  • Madhusudana Rao C, Bardhan A, Patra JP (2020) Assessment of hydrological response in Subarnarekha river basin under anticipated climate change scenarios. Global NEST J 22(2):207–219. https://doi.org/10.30955/gnj.003191

  • Madhusudana Rao C, Bardhan A, Raj A, Kumar R, Ranjan R (2019) Comparative analysis of land use and land cover changes on stream discharges using LANDSAT Maps, HYDRO 2019, International conference, Vol. 2, pp. 1839–1842, ISBN: 978–93–8935–484–3, UCE, OU, Hyderabad, India. http://www.hydro2019.com/paper-search.php?paperid=112&submit=Search

  • Mekonnen MM, Hoekstra AY (2011) The green, blue, grey water footprint of crops and derived crop products. Hydrol Earth Syst Sci 15:1577–1600. https://doi.org/10.5194/hess-15-1577-2011

    Article  Google Scholar 

  • Moriasi DN, Arnold JG, VanLiew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900

    Article  Google Scholar 

  • Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models: Part I: A discussion of principles. J Hydrol 10(3):282–290

    Article  Google Scholar 

  • Oki T, Kanae S (2006) Global hydrological cycles and world water resources. Science 313:1068–1072

    Article  Google Scholar 

  • Padhiary J, Patra KC, Das SS, Kumar AU (2019) Climate change impact assessment on hydrological fluxes based on ensemble GCM outputs: a case study in eastern Indian River Basin. J Water Clim Change 11(4):1676–1694

    Article  Google Scholar 

  • Padhiary J, Swain JB, Patra KC (2020) Optimized irrigation scheduling using SWAT for improved crop water productivity. Irrig Drain. https://doi.org/10.1002/ird.2418

    Article  Google Scholar 

  • Patel J, Patel H, Bhatt C (2014) Generalized calibration of the Hargreaves equation for evapotranspiration under different climate conditions. Soil Water Res 9(2):83–89

  • Paul PK, Zhang Y, Mishra A, Panigrahy N, Singh R (2019) Comparative study of two state-of-the-art semi-distributed hydrological models. Water 11:871. https://doi.org/10.3390/w11050871

    Article  Google Scholar 

  • Postel SL, Daily GC, Ehrlich PR (1996) Human appropriation of renewable freshwater. Science 271:785–788

    Article  Google Scholar 

  • Rodrigues DBB, Gupta HV, Mendiondo EM (2014) A blue/green water-based accounting framework for assessment of water security. Water Resour Res 50:7187–7205. https://doi.org/10.1002/2013WR014274

    Article  Google Scholar 

  • Shahidian S, Serralheiro RP, Serrano J, Teixeira J, Haie N, Santos FL (2012) Hargreaves and other reduced-set methods for calculating evapotranspiration. Ed:Ayşe Irmak. Available at https://www.researchgate.net/publication/221922376.

  • Schuol J, Abbaspour KC, Yang H, Srinivasan R, Zehnder AJB (2008) Modeling blue and green water availability in Africa. Water Resour Res 44:W07406. https://doi.org/10.1029/2007WR006609

    Article  Google Scholar 

  • Uniyal B, Jha MK, Verma AK (2015) Parameter identification and uncertainty analysis for simulating streamflow in a river basin of eastern India. Hydrol Process 29(17):3744–3766. https://doi.org/10.1002/hyp.10446

    Article  Google Scholar 

  • USDA-SCS (1972) USDA Soil Conservation Services National Engineering Handbook. Section 4: Hydrology. U.S. Government printing office

  • Van Griensven A (2005) Sensitivity, auto-calibration, uncertainty and model evaluation in SWAT 2005. UNESCO-IHE 48

  • Verma K, Jha MK (2015) Evaluation of a GIS-based watershed model for streamflow and sediment-yield simulation in the Upper Baitarani river basin of Eastern India. J. Hydrol Eng 20(6):1. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001134

  • Zang C, Mao G (2019) A spatial and temporal study of the green and blue water flow distribution in typical ecosystems and its ecosystem services function in an arid basin. J. Water 11:97. https://doi.org/10.3390/w11010097

  • Zang CF, Liu JG, Vander VM (2012) Assessment of spatial and temporal patterns of green and blue water flow under natural conditions in inland river basins in Northwest China. Hydrol Earth Syst Sci 16:2859–2870

    Article  Google Scholar 

  • Zhao A, Zhu X, Liu X, Pan Y (2016) Impacts of land-use change and climate variability on green and blue water resources in the Weihe river basin of northwest China. CATENA 137:318–327

    Article  Google Scholar 

  • Zhu K, Xie Z, Zhao Y, Lu F, Song X, Li L, Song X (2018) The assessment of greenwater based on the SWAT model: a case study in the Hai River Basin, China. Water 10:798. https://doi.org/10.3390/w10060798

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Authors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology Jamshedpur, Jamshedpur, 831014, Jharkhand, India

    Madhusudana Rao Chintalacheruvu & Avijit Bardhan

  2. Hydrological Investigations Division, National Institute of Hydrology, Roorkee, Roorkee, 247667, Uttarakhand, India

    Santosh Murlidhar Pingale

  3. Surface Water Hydrology Division, National Institute of Hydrology, Roorkee, Roorkee, 247667, Uttarakhand, India

    Jagadish Prasad Patra

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  1. Madhusudana Rao Chintalacheruvu
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  2. Avijit Bardhan
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  3. Santosh Murlidhar Pingale
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  4. Jagadish Prasad Patra
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Correspondence to Madhusudana Rao Chintalacheruvu.

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Chintalacheruvu, M.R., Bardhan, A., Pingale, S.M. et al. Water footprint analysis for the upper Baitarani River basin, India. Sustain. Water Resour. Manag. 8, 181 (2022). https://doi.org/10.1007/s40899-022-00769-z

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