TY - JOUR A1 - Pilz, Tobias A1 - Francke, Till A1 - Baroni, Gabriele A1 - Bronstert, Axel T1 - How to Tailor my process-based hydrological model? BT - dynamic identifiability analysis of flexible model structures JF - Water resources research N2 - In the field of hydrological modeling, many alternative representations of natural processes exist. Choosing specific process formulations when building a hydrological model is therefore associated with a high degree of ambiguity and subjectivity. In addition, the numerical integration of the underlying differential equations and parametrization of model structures influence model performance. Identifiability analysis may provide guidance by constraining the a priori range of alternatives based on observations. In this work, a flexible simulation environment is used to build an ensemble of semidistributed, process-based hydrological model configurations with alternative process representations, numerical integration schemes, and model parametrizations in an integrated manner. The flexible simulation environment is coupled with an approach for dynamic identifiability analysis. The objective is to investigate the applicability of the framework to identify the most adequate model. While an optimal model configuration could not be clearly distinguished, interesting results were obtained when relating model identifiability with hydro-meteorological boundary conditions. For instance, we tested the Penman-Monteith and Shuttleworth & Wallace evapotranspiration models and found that the former performs better under wet and the latter under dry conditions. Parametrization of model structures plays a dominant role as it can compensate for inadequate process representations and poor numerical solvers. Therefore, it was found that numerical solvers of high order of accuracy do often, though not necessarily, lead to better model performance. The proposed coupled framework proved to be a straightforward diagnostic tool for model building and hypotheses testing and shows potential for more in-depth analysis of process implementations and catchment functioning. KW - identifiability analysis KW - flexible model KW - numerics KW - model structure KW - WASA-SED KW - ECHSE Y1 - 2020 U6 - https://doi.org/10.1029/2020WR028042 SN - 0043-1397 SN - 1944-7973 VL - 56 IS - 8 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Kneis, David T1 - A lightweight framework for rapid development of object-based hydrological model engines JF - Environmental modelling & software with environment data news N2 - Computer-based simulation models are frequently used in hydrological research and engineering but also in other fields of environmental sciences. New case studies often require existing model concepts to be adapted. Extensions may be necessary due to the peculiarities of the studied natural system or subtleties of anthropogenic control. In other cases, simplifications must be made in response to scarce data, incomplete knowledge, or restrictions set by the spatio-temporal scale of application. This paper introduces an open-source modeling framework called ECHSE designed to cope with the above-mentioned challenges. It provides a lightweight infrastructure for the rapid development of new, reusable simulation tools and, more importantly, the safe modification of existing formulations. ECHSE-based models treat the simulated system as a collection of interacting objects. Although feedbacks are generally supported, the majority of the objects' interactions is expected to be of the feed-forward type. Therefore, the ECHSE software is particularly useful in the context of hydrological catchment modeling. Conversely, it is unsuitable, e.g., for fully hydrodynamic simulations and groundwater flow modeling. The focus of the paper is put on a comprehensible outline of the ECHSE's fundamental concepts and limitations. For the purpose of illustration, a specific, ECHSE-based solution for hydrological catchment modeling is presented which has undergone testing in a number of river basins. (C) 2015 Elsevier Ltd. All rights reserved. KW - Modeling framework KW - Genetic model KW - Hydrology KW - ECHSE Y1 - 2015 U6 - https://doi.org/10.1016/j.envsoft.2015.02.009 SN - 1364-8152 SN - 1873-6726 VL - 68 SP - 110 EP - 121 PB - Elsevier CY - Oxford ER -