Impact of climate change on river water temperature and dissolved oxygen: indian riverine thermal regimes

HIGHLIGHTS

• who: M. Rajesh from the u00b0C). However, Stajkowski et_al, used AT values as input for hourly data in their analysis, Qiu et_al, used AT and discharge as input for daily data in RWT predictions, and the current study is dedicated to monthly timescales. Based on RSR, KGE, R u00ad, and NSE performance values (Fig., ), the kNN-LSTM model is the best performant model for all catchments. Overall, the kNN-LSTM model statistical metrics are reasonably within the range for all the catchment locations providing confidence that the developed model performs effectively. The following analyses concentrate on how . . .
  

   

  

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