The rivers rejuvenate themselves by traveling over a distance thereby they assimilate the pollution load and cause their own self-cleansing, also termed ‘Self-purification capacity’. To ascertain such assimilative capacity of the river system, various water quality models (WQMs) were studied. Out of numerous WQMs, six models including QUAL2Kw, WASP, SWAT, SIMCAT, MIKE-11, and CE-QUAL-W2 were selected and studied on basis of their development, characteristics, capabilities and strengths, model input, governing equations, application, assumptions and limitations. A comparison based on such a study showing input variables and data, assumptions and limitations, strengths, and specific characteristics has been carried out and tabulated. While the selection of a model is based on the problem for which the decision-making is to be done. Of all the models, QUAL2Kw and WASP have been found to be advantageous over the rest. For a complex river system, a single model may not work and in such cases, a combination may be tried. A model finally selected for a problem must be calibrated so as to have minimum errors and maximum accuracy.

This research work aimed to project and analyse climatic variability in the Hathmati River Basin that happens to be one of the most important tributaries of Western India using GCMs and RCMs. The analysis included a baseline period from 1980 to 2014 and future scenario (2050 s) under a representative concentration pathway (RCP4.5). Following the evaluation of bias correction methods, the distribution mapping and power transformation were used for temperature and precipitation projection, respectively. The 2050 s RCP4.5 simulations showed an increase in precipitation to 1,015.54 mm from 936.91 mm giving around 8.45% of increase in average precipitation. For temperature, the maximum temperature shows around 7.05% increase taking the average temperature to 34.21 from 33.97. The minimum temperature goes to 20.24 from 20.41 showing positive change of around 8.4%. The future precipitation and temperature change projected might worsen the water stress and probability of the occurrence severe events, and hence mitigation strategies and management options to reduce this negative impact should be encouraged.

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