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+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +4996 +10.21105/joss.04996 + +Water Systems Integrated Modelling framework, WSIMOD: A +Python package for integrated modelling of water quality and quantity +across the water cycle + + + +https://orcid.org/0000-0002-0149-4124 + +Dobson +Barnaby + + + + +https://orcid.org/0000-0001-7556-1134 + +Liu +Leyang + + + + +https://orcid.org/0000-0001-7096-9405 + +Mijic +Ana + + + + + +Department of Civil and Environmental Engineering, Imperial +College London, UK + + + + +4 +11 +2022 + +8 +83 +4996 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Python +water quality +hydrology +integrated modelling +pollution + + + + + + Summary +

The water cycle is highly interconnected; water fluxes in one part + depend on physical and human processes throughout. For example, rivers + are a water supply, a receiver of wastewater, and an aggregate of many + hydrological, biological, and chemical processes. Thus, simulations of + the water cycle that have highly constrained boundaries may miss key + interactions that create unanticipated impacts or unexpected + opportunities + (Dobson + & Mijic, 2020; + Liu, + Dobson, & Mijic, 2022). Integrated environmental models aim + to resolve the issue of boundary conditions, however they have some + key limitations + (Rauch + et al., 2017), and in particular we find a significant need for + a parsimonious, self-contained suite that is accessible and easy to + setup.

+ + + Statement of need +

Traditional approaches to water system modelling broadly fall into + highly numerical models that excel in representing individual + subsystems, or systems dynamics models that create broad + representations but that lack a physical basis. Early attempts at a + physical representation of the water cycle combined existing numerical + models through an integration framework + (Rauch + et al., 2017). While successful, this approach has an + incredibly high user burden because each subsystem model is so + detailed, and as a consequence is also difficult to customise. To + illustrate, SWAT is one of the most widespread models of the rural + water cycle + (Arnold + et al., 2012), while SWMM is the same but for the urban water + cycle + (Gironás, + Roesner, Rossman, & Davis, 2010). It has been demonstrated + that these two software can interface using the OpenMI integration + framework + (Shrestha, + Leta, De Fraine, Van Griensven, & Bauwens, 2013). Despite + this seemingly powerful combination of two near-ubiquitous models, + integrated applications have been limited, and we propose that this is + for the same reasons presented in + (Rauch + et al., 2017): user burden and customisation difficulty.

+

Because of this need, we provide a parsimonious and self-contained + suite for integrated water cycle modelling in the WSIMOD Python + package. It brings together a range of software developed over the + course of three years on the + CAMELLIA + project. Urban water processes are based on those presented + and validated in the CityWat model + (Dobson + et al., 2021; + Dobson + & Mijic, 2020; + Dobson, + Watson-Hill, Muhandes, Borup, & Mijic, 2022; + Muhandes, + Dobson, & Mijic, 2022), while hydrological and agricultural + processes are from the CatchWat model + (Liu + et al., 2022, + 2023). + WSIMOD also provides an interface for message passing between + different model components, enabling all parts of the water cycle to + interact with all other parts. The result is a simulation model that + is easy to set up, highly flexible and ideal for representing water + quality and quantity in ‘non-textbook’ water systems (which in our + experience is nearly all of them).

+

The package provides a variety of tutorials and examples to help + modellers create nodes (i.e., representations of subsystems within the + water cycle), connect them together with arcs (i.e., representing the + fluxes between subsystems), and orchestrate them into a model that + creates simulations.

+ + Limitations +

We highlight that WSIMOD is not intended to be a substitute for + sophisticated physical models, nor for a system dynamics approach. + In applications where detailed hydraulic/hydrological process + representations are needed (e.g., informing the design of specific + pipes, cases where processes are hard to quantify such as + representing social drivers of population growth, etc.) there are + likely better tools available. Our case studies highlight that + WSIMOD is most useful in situations where physically representing + cross-sytem processes and thus capturing the impacts of cross-system + interactions are essential towards the questions you ask of your + model. Secondary benefits are that the parsimonious representations + utilised are computationally fast and flexible in capturing a wide + range of system interventions.

+ + + + Acknowledgements +

WSIMOD was developed by + Barnaby + Dobson and + Leyang + Liu. Theoretical support was provided by Ana Mijic. Testing + the WSIMOD over a variety of applications has been performed by + Fangjun Peng, Vladimir Krivstov and Samer Muhandes. Software + development support was provided by Imperial College’s Research + Software Engineering service, in particular from Diego Alonso and Dan + Davies.

+

We are incredibly grateful for the detailed software reviews + provided by + Taher + Chegini and + Joshua + Larsen and editing by + Chris + Vernon. Their suggestions have significantly improved + WSIMOD.

+

The design of WSIMOD was significantly influenced by + CityDrain3 + (Burger + et al., 2016), + OpenMI + (Gregersen, + Gijsbers, & Westen, 2007), + smif + (Usher + & Russell, 2019; + Usher + et al., 2018), and the following review + (Belete, + Voinov, & Laniak, 2017).

+

We acknowledge funding from the CAMELLIA project (Community Water + Management for a Liveable London), funded by the Natural Environment + Research Council (NERC) under grant NE/S003495/1.

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