Global Fully Distributed Parameter Regionalization Based on Observed Streamflow From 4,229 Headwater Catchments

Unit hydrograph characterization of flow regimes leading to streamflow estimation in ungauged catchments (regionalization)

The IHACRES rainfall–streamflow modelling approach provides a powerful set of techniques for assisting with parametrically efficient regionalization of streamflow response characteristics (unit hydrograph and loss module parameters) from inputs of rainfall, evaporation surrogates and physical catchment descriptor data. Recent work has indicated where further improvements can be made to the mode...

4 : Parameter Estimation in Fully Observed BNs

The goal of learning a graphical model is find the best (or most likely) Bayesian Network (both DAG and CPDs) given a set of independent samples (or assignments of random variables). To succeed in finding the best model first, we either learn the structure of the model or assume a structure of the model given by an expert. Structural leaning has multiple limitations and hence there is not too m...

Streamflow data assimilation: A study on nested catchments

2 Parameter estimation for fully observed Undirected Graphical

Calibration of global hydrological models based on streamflow characteristics

Streamflow (Q) estimation in ungauged catchments is perhaps the most fundamental challenge faced by hydrologists. A promising approach to calibrate hydrological models in ungauged catchments is to use estimated Q characteristics to identify acceptable model parameter sets. This study is the first to test this approach at the global scale using a large, heterogeneous catchment set. First, observ...