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Hydroclimatic river discharge and seasonal trends assessment model using an advanced spatio-temporal model

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Abstract

Climatic changes have a significant impact on the hydrologic behavior of a river especially its discharge. Sustainable management of water resources necessitates an examination of spatiotemporal variation in climatic parameters such as precipitation and temperature to quantify their relationships with the river discharge. The present study develops both parametric and non-parametric models by modifying the tools of ‘R’ statistical software (version 3.2.2) to investigate variations in 11 climatic parameters for a 117-year dataset (1900–2017) in Ganges River basin of India. The novelty of the modified hydroclimatic spatiotemporal trend model is its ability to explore seasonal trends and Sen’s slopes of climatic parameters while avoiding trend-autocorrelation complications using an advanced Mann–Kendall test and Sen’s slope estimator. Furthermore, relationships among the Sen’s slopes of each climatic parameter are assessed to investigate the trend interdependencies. Parametric modeling has been performed to develop relationships among precipitation and remaining climatic parameters. Model validation results suggest non-parametric model to quantify relationships between precipitation and river discharge for a long-term data series. The results demonstrate that the forecasted precipitation exhibits a gradually decreasing trend leading to a significantly decreasing trend in river discharge (15–21%) for the next three decades (2030, 2040 and 2050). The model outcomes guide the water managers towards framing sustainable policies for managing water supplies, floods and droughts, hydropower development, barrage operation control, and environmental flows.

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Authors and Affiliations

  1. Department of Bioproducts and Biosystems Engineering, University of Minnesota, Minneapolis, 55108, USA

    R. Srinivas & Joe Magner

  2. Civil Engineering Department, Birla Institute of Technology and Science, Pilani, 333031, India

    Ajit Pratap Singh & Kunal Dhadse

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  1. R. Srinivas
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  2. Ajit Pratap Singh
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  3. Kunal Dhadse
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  4. Joe Magner
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Correspondence to Ajit Pratap Singh.

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Srinivas, R., Singh, A.P., Dhadse, K. et al. Hydroclimatic river discharge and seasonal trends assessment model using an advanced spatio-temporal model. Stoch Environ Res Risk Assess 34, 381–396 (2020). https://doi.org/10.1007/s00477-020-01780-6

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