A simulation interface designed for improved user interaction and learning in water quality modelling software

Moeseneder, Christian H.; Dutra, Leo X.C.; Thébaud, Olivier; Ellis, Nick; Boschetti, Fabio; Tickell, Sharon; Dichmont, Cathy; Mare, William de la; Pascual, Ricardo; Cannard, Toni

doi:10.1016/j.envsoft.2015.04.006

Cited by 13 publications

(4 citation statements)

References 39 publications

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“…The characterization of environmental conditions and the response of fish populations to the change of these conditions can be approached using various methodologies and modelling techniques (qualitative, quantitative, discrete or continuous, physical, statistical, etc.) through which it is possible to establish and simulate statistical functional relationships between different variables (Silliman, 1967;King and Paulik, 1967;Paulik, 1969;Francis, 1974;Fonteneau, 1975;Takeuchi and Taneishi, 1976;Tillman and Stadelman, 1976;Hammond and Lackey, 1976;Sissenwine, 1977;Grant et al, 1981;Crutchfield, 1986;Hilborn and Walters, 1987;Kleiber and Baker, 1987;Castro and Erzini, 1988;Erzini, 1990;Erzini and Castro, 1998;Christensen and Pauly, 1992;Walters et al, 1997Walters et al, , 2000Moeseneder et al, 2015;Schiavina et al, 2015;Begley, 2005;Erzini et al, 2006;Taylor et al, 2007). This allows the comparison of the responses of the system analysed under different environmental conditions or management scenarios (Sterman et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Improving the interpretability of the effects of environmental factors on abundance of fish stocks

Gutiérrez‐Estrada

Sanz‐Fernández

Pulido‐Calvo

et al. 2020

Ecological Indicators

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Adequately assess the environmental effects on commercially exploited fish stocks is one of the main challenges faced by stock managers in their attempt to achieve ecosystemic management. In this study, we have developed a methodology which allows simulate the evolution of abundance or biomass of a fish population and calculate two indexes (the significant effect of the environmental parameter-EF-and the relative weight index-RW-) that improve the interpretability of the environmental effects on abundance of fish stocks. This methodology is based on the assumption that under the premise of environmental invariability the variation in the abundance of a population is linearly dependent on its abundance in the past. These indexes have been integrated into a decision support system namely SFish SubClass 1.1, specifically designed to disaggregate the effects of different environmental factors on a commercially exploited fish population. We have applied our model to the fishery of Pagellus bogaraveo in a complex environmental area (Strait of Gibraltar). The results show that the developed methodology provides plausible simulations. Finally, the RW and EF indexes indicated that the most influential variables were salinity, sea temperature and salinity flux.

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Section: Introductionmentioning

confidence: 99%

Improving the interpretability of the effects of environmental factors on abundance of fish stocks

Gutiérrez‐Estrada

Sanz‐Fernández

Pulido‐Calvo

et al. 2020

Ecological Indicators

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“…As much as the literature acknowledges the valuable contributions of such EDSS, it is also asserted that these tools are often not used beyond the development and pilot project phase (Dilling and Lemos 2011;McIntosh et al 2011;Lemos et al 2012;Meyer et al 2015;Moeseneder et al 2015;Sandink et al 2016;Merritt et al 2017;Rodela et al 2017;Zasada et al 2017;Zulkafli et al 2017). It has been suggested that a lack of continuity of staff may be detrimental to long-term relationship building and also results in a lack of in-depth subject knowledge that would support the ongoing use of the EDSS (Campbell et al 2015;Meyer et al 2015).…”

Section: Environmental Decision Support Systemsmentioning

confidence: 99%

Stakeholder engagement with environmental decision support systems: The perspective of end users

Reiter

Meyer

Parrott

2019

Canadian Geographies / Géographies canadiennes

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Environmental decision support systems (EDSS) are designed to assist natural resource managers and stakeholders to assess problems and select options for change. EDSS that combine community engagement in developing future scenarios with computer‐based land use planning and modelling tools are widely used internationally. However, these EDSS are often not used after the research and development phase. To best understand why the EDSS are not being used in the long term, the end users of the EDSS should be consulted—a perspective that is lacking in the literature. The research reported here presents the perspectives of stakeholders involved in a community climate change adaptation project in western Canada. Evidence from the community suggests that this project was successful in instigating change. However, the EDSS was not used after the project's end. Our findings indicate that, from the end users’ perspective, the project could have had much greater and sustained success had there been ongoing engagement and communication with them, particularly in the form of continued support for the use of EDSS after the development project.

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“…Sakar and Abbasi [14] proposed for the first time, a water quality index software (QUALIDEX) containing several water quality index modules that include two indices developed in the USA and three indices developed in India. Other software such as SWQAT [15], MTSI [16], IWQG V.1 [17], QUAL2K or the latest version QUAL2Kw developed by the United States Environment Protection Agency [18], are available in the literature. Nabizideh et al [5] have integrated Iran's water quality index into software to ease calculations and still be able to use the index if certain water quality parameters are missing.…”

Section: Introductionmentioning

confidence: 99%

Development of a Computer Application for the Calculation of Water Quality Index in Morocco

Soumaila*,

Mustapha,

Mohamed

et al. 2019

IJITEE

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Water quality indices are generally a combination of biological, chemical, physical parameters to form a numerical composite index that can be easily interpreted and shared. Their efficiency and usefulness in managing and monitoring water quality have been appreciated by management organizations around the world. The integration of these tools into computer applications can be a major asset. The main purpose of this article is to present a computer application that integrates a water quality index developed in Morocco to facilitate its use and avoid manual errors related to users. The application entirely developed in python language under PyCharm (Integrated Development Environment) is executable on a computer and is presented as a GUI (Graphical User Interface) containing two sub-interfaces to calculate the surface and groundwater quality index according to the type of water analyzed.

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A simulation interface designed for improved user interaction and learning in water quality modelling software

Cited by 13 publications

References 39 publications

Improving the interpretability of the effects of environmental factors on abundance of fish stocks

Improving the interpretability of the effects of environmental factors on abundance of fish stocks

Stakeholder engagement with environmental decision support systems: The perspective of end users

Development of a Computer Application for the Calculation of Water Quality Index in Morocco

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