BHARAT: a MADM approach to prioritizing the best performing EPS in a semi-arid river basin

The comparison of the discrete and finite set of predefined alternatives requires a simple, effective, and reliable Multi-Attribute Decision-Making (MADM) method. This paper shows an application of a simple and effective MADM technique named the Best Holistic Adaptable Ranking of Attributes Technique (BHARAT) to find the best-performing ensemble prediction system (EPS) in issuing flood warnings in the study area. The three well-behaved EPSs, European Centre for Medium-Range Weather Forecast (ECMWF), the National Centre for Medium-Range Weather Forecasting (NCMRWF), and the United Kingdom Meteorological Office (UKMO) for 1-day and 5-day leadtime were considered in the study. The EPSs are considered as the alternatives and the evaluation metrics of the precipitation forecasts and hydrologic forecasts are considered as the factors (attributes) in the BHARAT method. The evaluation is categorized into three factors, (1) performance metrics for the evaluation of precipitation forecasts, (2) evaluation metrics based on the hydrological model performance, and (3) threshold-based evaluation metrics of the hydrologic forecasts. These factors are further divided into eleven sub-factors. The BHARAT method includes assigning numerical weights by the decision maker, which are directly multiplied with the normalized values based on the “best” attribute value of an alternative and summed up to get the best-performing alternative. The results of the BHARAT method showed that the total scores of the alternative NCMRWF are 0.976 and 0.916 for 1-day and 5-day leadtime. Thus, the NCMRWF EPS is found to be the best performing in both the leadtime for issuing the flood warning in the Vishwamitri River basin. At the global scale, BHARAT can be applied in similar studies of decision-making with variable attributes in the fields of hydrology to find the best alternative.