Diagnostics of the Theoretical Underpinning of the Socio-hydrological Model in "Water Effciency in Sustainable Cotton-based Production Systems" Project in Maharashtra, India: Evaluation of model performance and the quantication of errors using Monte Carlo sampling, GLUE, linear regressions, linear PCA, and kernel PCA

This research is part of the project "Water Efficiency in Sustainable Cotton-based Production Systems” between Solidaridad Asia and TU Delft. The project aims to increase the livelihood of smallholder farmers in the Maharashtra, India through. A socio-hydrological (SH) model is used extensively in this research as an evaluation tool. However,...

Do direct and inverse uncertainty assessment methods present the same results?

Hydrological models are simplified imitations of natural and man-made water systems, and because of this simplification, always deal with inherent uncertainty. To develop more rigorous modeling procedures and to provide more reliable results, it is inevitable to consider and estimate this uncertainty. Although there are different approaches...

On the calibration of hydrological models in ungauged basins: A framework for integrating hard and soft hydrological information

This paper presents a calibration framework based on the generalized likelihood uncertainty estimation (GLUE) that can be used to condition hydrological model parameter distributions in scarcely gauged river basins, where data is uncertain, intermittent or nonconcomitant. At the heart of this framework is the conditioning of the model parameters...