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In the present study, an optimal rain gauge network has been derived for predicting runoff in the Middle Tapi Basin, India. This study employs a statistical approach by Hall and the recently developed BHARAT (Best Holistic Adaptable Ranking of Attributes Technique) method. BHARAT, primarily designed for industrial applications, has been adapted to address the hydrological challenge of selecting key rain gauges. The lumped conceptual NAM rainfall–runoff model has been developed for the evaluation of rain gauges ranked by each approach. The reliability of Hall's network is affirmed through its commendable performance in statistical assessments of simulated runoff. However, the outcome difference between BHARAT and Hall's method is not prominently pronounced. It's worth noting that Hall's method places primary emphasis on rain gauge stations based solely on measured rainfall, overlooking other hydrological parameters in the selection process. In contrast, BHARAT offers flexibility by considering all relevant attributes to identify optimal alternatives. Both Hall's method and BHARAT exhibit dependable applicability for hydrological applications, with each method presenting unique strengths in the design of rain gauge networks. The observations highlight that the newly developed BHARAT technique, characterized by its simplicity and user-friendly interface, exhibits robust applicability for hydrological applications comparable to Hall's method.

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  • The optimal rain gauge network has been designed for reliable hydrologic applications.

  • BHARAT, a recently innovated technique for industrial problem-solving and decision-making, is utilized to select key rain gauges and the results of designed rain gauges have been compared to that of the traditional Hall's approach.

  • The effectiveness of the networks designed by each approach is evaluated using a hydrologic model.

BHARAT, lumped conceptual hydrologic model, MADM technique, rain gauge network design, runoff prediction
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