Employing sensitivity analysis to catchments having scanty data.

Sensitivity analysis (SA) is generally desirable for parameter optimization, mapping, and calibration in hydrological models, yet the implementation of SA in data-sparse regions is usually avoided due to a lack of continuous data. The present study proposes the novel concept of "minimum continuous data period" to overcome this constraint. It analyses the sensitivity profile of two data-suffice sub-catchments of a data-sparse watershed using data at various timescales to determine the minimum data period required for the SA. The results suggest that the SA employing a minimum data period (2 years in this study) replicated the actual sensitivity profile by an average of 77.5% while replicating the most sensitive and insensitive parameters by 100%. The study encourages the use of the data from sub-catchments to determine the sensitivity profile of the data-sparse catchment. It would benefit in improving the use of SA for rainfall-runoff modelling in data-scanty regions.
(© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)