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  - 
TY  - JOUR
A1  - Janssen, Annette B. G.
A1  - Arhonditsis, George B.
A1  - Beusen, Arthur
A1  - Bolding, Karsten
A1  - Bruce, Louise
A1  - Bruggeman, Jorn
A1  - Couture, Raoul-Marie
A1  - Downing, Andrea S.
A1  - Elliott, J. Alex
A1  - Frassl, Marieke A.
A1  - Gal, Gideon
A1  - Gerla, Daan J.
A1  - Hipsey, Matthew R.
A1  - Hu, Fenjuan
A1  - Ives, Stephen C.
A1  - Janse, Jan H.
A1  - Jeppesen, Erik
A1  - Joehnk, Klaus D.
A1  - Kneis, David
A1  - Kong, Xiangzhen
A1  - Kuiper, Jan J.
A1  - Lehmann, Moritz K.
A1  - Lemmen, Carsten
A1  - Oezkundakci, Deniz
A1  - Petzoldt, Thomas
A1  - Rinke, Karsten
A1  - Robson, Barbara J.
A1  - Sachse, Rene
A1  - Schep, Sebastiaan A.
A1  - Schmid, Martin
A1  - Scholten, Huub
A1  - Teurlincx, Sven
A1  - Trolle, Dennis
A1  - Troost, Tineke A.
A1  - Van Dam, Anne A.
A1  - Van Gerven, Luuk P. A.
A1  - Weijerman, Mariska
A1  - Wells, Scott A.
A1  - Mooij, Wolf M.
T1  - Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective
JF  - Aquatic ecology : the international forum covering research in freshwater and marine environments
N2  - Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5-10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary.
KW  - Water quality
KW  - Ecology
KW  - Geochemistry
KW  - Hydrology
KW  - Hydraulics
KW  - Hydrodynamics
KW  - Physical environment
KW  - Socio-economics
KW  - Model availability
KW  - Standardization
KW  - Linking
Y1  - 2015
U6  - https://doi.org/10.1007/s10452-015-9544-1
SN  - 1386-2588
SN  - 1573-5125
VL  - 49
IS  - 4
SP  - 513
EP  - 548
PB  - Springer
CY  - Dordrecht
ER  -