From 3655eeafad39a6f9fa18d634a95064e5f695a0e4 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 16 Oct 2024 13:33:16 +0100 Subject: [PATCH 01/23] initial paper file --- .pre-commit-config.yaml | 2 +- paper/paper.bib | 14 +++++ paper/paper.md | 112 ++++++++++++++++++++++++++++++++++++++++ 3 files changed, 127 insertions(+), 1 deletion(-) create mode 100644 paper/paper.bib create mode 100644 paper/paper.md diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 2fa60002..951cef32 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -20,7 +20,7 @@ repos: rev: v0.42.0 hooks: - id: markdownlint - args: ["--disable", "MD013", "--"] + args: ["--disable", "MD013", "--disable", "MD025", "--"] - repo: https://github.com/codespell-project/codespell rev: v2.3.0 diff --git a/paper/paper.bib b/paper/paper.bib new file mode 100644 index 00000000..1c9b4c27 --- /dev/null +++ b/paper/paper.bib @@ -0,0 +1,14 @@ +@article{gaia, + author = {{Gaia Collaboration}}, + title = "{The Gaia mission}", + journal = {Astronomy and Astrophysics}, + archivePrefix = "arXiv", + eprint = {1609.04153}, + primaryClass = "astro-ph.IM", + keywords = {space vehicles: instruments, Galaxy: structure, astrometry, parallaxes, proper motions, telescopes}, + year = 2016, + month = nov, + volume = 595, + doi = {10.1051/0004-6361/201629272}, + url = {http://adsabs.harvard.edu/abs/2016A%26A...595A...1G}, +} diff --git a/paper/paper.md b/paper/paper.md new file mode 100644 index 00000000..d227b451 --- /dev/null +++ b/paper/paper.md @@ -0,0 +1,112 @@ +--- +title: 'SWMManywhere: Synthesise Urban Drainage Network Models Anywhere in the World' +tags: + - python + - stormwater + - hydrology-stormwater-analysis + - swmm5 + - swmm + - hydraulic-modelling +authors: + - family-names: "Dobson" + given-names: "Barnaby" + orcid: "https://orcid.org/0000-0002-0149-4124" + affiliation: 1 + - family-names: "Alonso-Álvarez" + given-names: "Diego" + orcid: "https://orcid.org/0000-0002-0060-9495" + affiliation: 1 + - family-names: "Chegini" + given-names: "Taher" + orcid: "https://orcid.org/0000-0002-5430-6000" + affiliation: 2 +affiliations: + - name: Imperial College London, UK + index: 1 + - name: Purdue University, US + index: 2 +date: 16 October 2024 +bibliography: paper.bib + +--- + +# Summary + +The forces on stars, galaxies, and dark matter under external gravitational +fields lead to the dynamical evolution of structures in the universe. The orbits +of these bodies are therefore key to understanding the formation, history, and +future state of galaxies. The field of "galactic dynamics," which aims to model +the gravitating components of galaxies to study their structure and evolution, +is now well-established, commonly taught, and frequently used in astronomy. +Aside from toy problems and demonstrations, the majority of problems require +efficient numerical tools, many of which require the same base code (e.g., for +performing numerical orbit integration). + +# Statement of need + +`Gala` is an Astropy-affiliated Python package for galactic dynamics. Python +enables wrapping low-level languages (e.g., C) for speed without losing +flexibility or ease-of-use in the user-interface. The API for `Gala` was +designed to provide a class-based and user-friendly interface to fast (C or +Cython-optimized) implementations of common operations such as gravitational +potential and force evaluation, orbit integration, dynamical transformations, +and chaos indicators for nonlinear dynamics. `Gala` also relies heavily on and +interfaces well with the implementations of physical units and astronomical +coordinate systems in the `Astropy` package [@astropy] (`astropy.units` and +`astropy.coordinates`). + +`Gala` was designed to be used by both astronomical researchers and by +students in courses on gravitational dynamics or astronomy. It has already been +used in a number of scientific publications [@Pearson:2017] and has also been +used in graduate courses on Galactic dynamics to, e.g., provide interactive +visualizations of textbook material [@Binney:2008]. The combination of speed, +design, and support for Astropy functionality in `Gala` will enable exciting +scientific explorations of forthcoming data releases from the *Gaia* mission +[@gaia] by students and experts alike. + +# Mathematics + +Single dollars ($) are required for inline mathematics e.g. $f(x) = e^{\pi/x}$ + +Double dollars make self-standing equations: + +$$\Theta(x) = \left\{\begin{array}{l} +0\textrm{ if } x < 0\cr +1\textrm{ else} +\end{array}\right.$$ + +You can also use plain \LaTeX for equations +\begin{equation}\label{eq:fourier} +\hat f(\omega) = \int_{-\infty}^{\infty} f(x) e^{i\omega x} dx +\end{equation} +and refer to \autoref{eq:fourier} from text. + +# Citations + +Citations to entries in paper.bib should be in +[rMarkdown](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html) +format. + +If you want to cite a software repository URL (e.g. something on GitHub without a preferred +citation) then you can do it with the example BibTeX entry below for @fidgit. + +For a quick reference, the following citation commands can be used: +- `@author:2001` -> "Author et al. (2001)" +- `[@author:2001]` -> "(Author et al., 2001)" +- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)" + +# Figures + +Figures can be included like this: +![Caption for example figure.\label{fig:example}](figure.png) +and referenced from text using \autoref{fig:example}. + +Figure sizes can be customized by adding an optional second parameter: +![Caption for example figure.](figure.png){ width=20% } + +# Acknowledgements + +We acknowledge contributions from Brigitta Sipocz, Syrtis Major, and Semyeong +Oh, and support from Kathryn Johnston during the genesis of this project. + +# References From e4ed747d67520a3d5079103a30a53f51887113bf Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 16 Oct 2024 13:38:34 +0100 Subject: [PATCH 02/23] paper to about --- docs/paper/apa.csl | 1586 +++++++++++++++++++++++++++++++ {paper => docs/paper}/paper.bib | 0 {paper => docs/paper}/paper.md | 0 mkdocs.yml | 6 +- pyproject.toml | 4 + 5 files changed, 1595 insertions(+), 1 deletion(-) create mode 100644 docs/paper/apa.csl rename {paper => docs/paper}/paper.bib (100%) rename {paper => docs/paper}/paper.md (100%) diff --git a/docs/paper/apa.csl b/docs/paper/apa.csl new file mode 100644 index 00000000..2c50d03d --- /dev/null +++ b/docs/paper/apa.csl @@ -0,0 +1,1586 @@ + + diff --git a/paper/paper.bib b/docs/paper/paper.bib similarity index 100% rename from paper/paper.bib rename to docs/paper/paper.bib diff --git a/paper/paper.md b/docs/paper/paper.md similarity index 100% rename from paper/paper.md rename to docs/paper/paper.md diff --git a/mkdocs.yml b/mkdocs.yml index 7d02f737..7ea95a73 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -18,7 +18,10 @@ plugins: execute: false - search - include-markdown - + - bibtex: + bib_file: "./docs/paper/paper.bib" + csl_file: "./docs/paper/apa.csl" + cite_inline: false repo_url: https://github.com/ImperialCollegeLondon/SWMManywhere site_url: https://imperialcollegelondon.github.io/SWMManywhere/ @@ -41,6 +44,7 @@ extra_javascript: nav: - Home: index.md + - About: ./paper/paper.md - Quickstart: quickstart.md - Guides: - Configuration guide: config_guide.md diff --git a/pyproject.toml b/pyproject.toml index 665f451b..dcb63d35 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -73,11 +73,15 @@ optional-dependencies.dev = [ ] optional-dependencies.doc = [ "mkdocs", + "mkdocs-autorefs", + "mkdocs-bibtex", + "mkdocs-coverage", "mkdocs-include-markdown-plugin", "mkdocs-jupyter", "mkdocs-material", "mkdocs-material-extensions", "mkdocstrings[python]", + "pypandoc", ] urls.Documentation = "https://imperialcollegelondon.github.io/SWMManywhere/" urls.Issues = "https://github.com/ImperialCollegeLondon/SWMManywhere/issues" From bafd4b6d44fd1c6b977160a1f932b8796d15ff34 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 16 Oct 2024 14:22:12 +0100 Subject: [PATCH 03/23] add some ai garbage --- docs/index.md | 1 + docs/paper/paper.md | 73 ++++----------------------------------------- 2 files changed, 7 insertions(+), 67 deletions(-) diff --git a/docs/index.md b/docs/index.md index dcdf0525..83d5c6fc 100644 --- a/docs/index.md +++ b/docs/index.md @@ -6,6 +6,7 @@ derive a synthetic urban drainage network anywhere in the world. ## Table of contents - [Home](index.md) +- [About](./paper/paper.md) - [Quickstart](quickstart.md) - Guides: - [Configuration file](config_guide.md) diff --git a/docs/paper/paper.md b/docs/paper/paper.md index d227b451..f02d98c1 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -32,81 +32,20 @@ bibliography: paper.bib # Summary -The forces on stars, galaxies, and dark matter under external gravitational -fields lead to the dynamical evolution of structures in the universe. The orbits -of these bodies are therefore key to understanding the formation, history, and -future state of galaxies. The field of "galactic dynamics," which aims to model -the gravitating components of galaxies to study their structure and evolution, -is now well-established, commonly taught, and frequently used in astronomy. -Aside from toy problems and demonstrations, the majority of problems require -efficient numerical tools, many of which require the same base code (e.g., for -performing numerical orbit integration). +Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive survey underground survey. A variety of literature exists to derive such UDMs from GIS data [refs]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. # Statement of need -`Gala` is an Astropy-affiliated Python package for galactic dynamics. Python -enables wrapping low-level languages (e.g., C) for speed without losing -flexibility or ease-of-use in the user-interface. The API for `Gala` was -designed to provide a class-based and user-friendly interface to fast (C or -Cython-optimized) implementations of common operations such as gravitational -potential and force evaluation, orbit integration, dynamical transformations, -and chaos indicators for nonlinear dynamics. `Gala` also relies heavily on and -interfaces well with the implementations of physical units and astronomical -coordinate systems in the `Astropy` package [@astropy] (`astropy.units` and -`astropy.coordinates`). +Existing methods for synthesizing urban drainage networks have advanced significantly, producing hydraulically feasible models that closely approximate real-world systems. However, these methods face three critical limitations. First, many are closed-source, restricting accessibility and limiting transparency for users and researchers. Second, they typically require users to source, preprocess, and input geospatial data manually, which creates a high technical barrier, especially in regions where data acquisition is challenging. Third, while the output of these methods is often sensitive to input parameters, they offer limited control over the generation process, making it difficult to adjust and refine models according to specific needs. This combination of complexity and lack of control can lead to significant uncertainty in outputs, which remains difficult to manage. -`Gala` was designed to be used by both astronomical researchers and by -students in courses on gravitational dynamics or astronomy. It has already been -used in a number of scientific publications [@Pearson:2017] and has also been -used in graduate courses on Galactic dynamics to, e.g., provide interactive -visualizations of textbook material [@Binney:2008]. The combination of speed, -design, and support for Astropy functionality in `Gala` will enable exciting -scientific explorations of forthcoming data releases from the *Gaia* mission -[@gaia] by students and experts alike. +SWMManywhere addresses these limitations by offering an open-source, globally applicable tool that automates data acquisition and preprocessing while providing users with a flexible, customizable workflow. Its parameterized design allows for detailed sensitivity analysis [ref], enabling users to better understand and manage uncertainties in urban drainage network synthesis. Unlike existing methods, SWMManywhere emphasizes user control, allowing for fine-tuning of outputs to meet specific project requirements. By integrating publicly available geospatial data, the tool minimizes the technical burden and ensures applicability in data-scarce regions, making it an ideal solution for both researchers and practitioners in urban water management. -# Mathematics +## Outlook -Single dollars ($) are required for inline mathematics e.g. $f(x) = e^{\pi/x}$ - -Double dollars make self-standing equations: - -$$\Theta(x) = \left\{\begin{array}{l} -0\textrm{ if } x < 0\cr -1\textrm{ else} -\end{array}\right.$$ - -You can also use plain \LaTeX for equations -\begin{equation}\label{eq:fourier} -\hat f(\omega) = \int_{-\infty}^{\infty} f(x) e^{i\omega x} dx -\end{equation} -and refer to \autoref{eq:fourier} from text. - -# Citations - -Citations to entries in paper.bib should be in -[rMarkdown](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html) -format. - -If you want to cite a software repository URL (e.g. something on GitHub without a preferred -citation) then you can do it with the example BibTeX entry below for @fidgit. - -For a quick reference, the following citation commands can be used: -- `@author:2001` -> "Author et al. (2001)" -- `[@author:2001]` -> "(Author et al., 2001)" -- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)" - -# Figures - -Figures can be included like this: -![Caption for example figure.\label{fig:example}](figure.png) -and referenced from text using \autoref{fig:example}. - -Figure sizes can be customized by adding an optional second parameter: -![Caption for example figure.](figure.png){ width=20% } +While we believe that SWMManywhere is a useful tool it has a variety of current limitations that present an exciting outlook for future research. Foremost, based on the findings of a sensitivity analysis [ref], better identification of manhole locations and outfalls will be critical to # Acknowledgements -We acknowledge contributions from Brigitta Sipocz, Syrtis Major, and Semyeong -Oh, and support from Kathryn Johnston during the genesis of this project. +BD is funded through the Imperial College Research Fellowship scheme, which also funded the software development. We acknowledge computational resources and support provided by the [Imperial College Research Computing Service](http://doi.org/10.14469/hpc/2232). # References From 95aa8f8875fc918efa1c166403af9d93ff1600e8 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 16 Oct 2024 14:45:53 +0100 Subject: [PATCH 04/23] first pass --- docs/index.md | 5 +- docs/paper/paper.bib | 299 +++++++++++++++++++++++++++++++++++++++++-- docs/paper/paper.md | 13 +- 3 files changed, 298 insertions(+), 19 deletions(-) diff --git a/docs/index.md b/docs/index.md index 83d5c6fc..22278ddd 100644 --- a/docs/index.md +++ b/docs/index.md @@ -6,7 +6,7 @@ derive a synthetic urban drainage network anywhere in the world. ## Table of contents - [Home](index.md) -- [About](./paper/paper.md) +- [About] - [Quickstart](quickstart.md) - Guides: - [Configuration file](config_guide.md) @@ -24,4 +24,5 @@ derive a synthetic urban drainage network anywhere in the world. - [Post processing](reference-post-processing.md) - [Preprocessing](reference-preprocessing.md) - [Config](reference-defs.md) - \ No newline at end of file +- [Coverage report](coverage.md) + \ No newline at end of file diff --git a/docs/paper/paper.bib b/docs/paper/paper.bib index 1c9b4c27..98c29591 100644 --- a/docs/paper/paper.bib +++ b/docs/paper/paper.bib @@ -1,14 +1,287 @@ -@article{gaia, - author = {{Gaia Collaboration}}, - title = "{The Gaia mission}", - journal = {Astronomy and Astrophysics}, - archivePrefix = "arXiv", - eprint = {1609.04153}, - primaryClass = "astro-ph.IM", - keywords = {space vehicles: instruments, Galaxy: structure, astrometry, parallaxes, proper motions, telescopes}, - year = 2016, - month = nov, - volume = 595, - doi = {10.1051/0004-6361/201629272}, - url = {http://adsabs.harvard.edu/abs/2016A%26A...595A...1G}, +@ARTICLE{Blumensaat2012-hd, + title = "Sewer model development under minimum data requirements", + author = "Blumensaat, Frank and Wolfram, Martin and Krebs, Peter", + journal = "Environ. Earth Sci.", + publisher = "Springer Science and Business Media LLC", + volume = 65, + number = 5, + pages = "1427--1437", + month = mar, + year = 2012, + language = "en" +} + +@ARTICLE{Chahinian2019-lg, + title = "Automatic mapping of urban wastewater networks based on manhole + cover locations", + author = "Chahinian, Nan{\'e}e and Delenne, Carole and Commandr{\'e}, + Benjamin and Derras, Mustapha and Deruelle, Laurent and Bailly, + Jean-St{\'e}phane", + journal = "Comput. Environ. Urban Syst.", + publisher = "Elsevier BV", + volume = 78, + number = 101370, + pages = "101370", + month = nov, + year = 2019, + language = "en" +} + +% The entry below contains non-ASCII chars that could not be converted +% to a LaTeX equivalent. +@ARTICLE{Dobson2022-wq, + title = "A reduced complexity model with graph partitioning for rapid + hydraulic assessment of sewer networks", + author = "Dobson, Barnaby and Watson-Hill, Hannah and Muhandes, Samer and + Borup, Morten and Mijic, Ana", + abstract = "AbstractExisting, high‐fidelity models for sewer network + modeling are accurate but too slow and inflexible for modern + applications such as optimization or scenario analysis. Reduced + complexity surrogate modeling has been applied in response to + this, however, current approaches are expensive to set up and + still require high‐fidelity simulations to derive parameters. In + this study, we compare and develop graph partitioning algorithms + to automatically group sections of sewer networks into + semi‐distributed compartments. These compartments can then be + simulated using sewer network information only in the integrated + modeling framework, CityWat‐SemiDistributed (CWSD), which has + been developed for application to sewer network modeling in this + study. We find that combining graph partitioning with CWSD can + produce accurate simulations 100--1,000$\times$ faster than + existing high‐fidelity modeling. Because we anticipate that many + CWSD users will not have high‐fidelity models available, we + demonstrate that the approach provides reasonable simulations + even under significant parametric uncertainty through a + sensitivity analysis. We compare multiple graph partitioning + techniques enabling users to specify the spatial aggregation of + the partitioned network, also enabling them to preserve key + locations for simulation. We test the impact of temporal + resolution, finding that accurate simulations can be produced + with timesteps up to one hour. Our experiments show a log‐log + relationship between temporal/spatial resolution and simulation + time, enabling users to pre‐specify the efficiency and accuracy + needed for their applications. We expect that the efficiency and + flexibility of our approach may facilitate novel applications of + sewer network models ranging from continuous simulations for + long‐term planning to spatially optimizing the placement of + network sensors.", + journal = "Water Resour. Res.", + publisher = "American Geophysical Union (AGU)", + volume = 58, + number = 1, + month = jan, + year = 2022, + copyright = "http://creativecommons.org/licenses/by/4.0/", + language = "en" +} + +@ARTICLE{Rauch2017-jz, + title = "Modelling transitions in urban water systems", + author = "Rauch, W and Urich, C and Bach, P M and Rogers, B C and de Haan, + F J and Brown, R R and Mair, M and McCarthy, D T and Kleidorfer, + M and Sitzenfrei, R and Deletic, A", + abstract = "Long term planning of urban water infrastructure requires + acknowledgement that transitions in the water system are driven + by changes in the urban environment, as well as societal + dynamics. Inherent to the complexity of these underlying + processes is that the dynamics of a system's evolution cannot be + explained by linear cause-effect relationships and cannot be + predicted under narrow sets of assumptions. Planning therefore + needs to consider the functional behaviour and performance of + integrated flexible infrastructure systems under a wide range of + future conditions. This paper presents the first step towards a + new generation of integrated planning tools that take such an + exploratory planning approach. The spatially explicit model, + denoted DAnCE4Water, integrates urban development patterns, + water infrastructure changes and the dynamics of + socio-institutional changes. While the individual components of + the DAnCE4Water model (i.e. modules for simulation of urban + development, societal dynamics and evolution/performance of + water infrastructure) have been developed elsewhere, this paper + presents their integration into a single model. We explain the + modelling framework of DAnCE4Water, its potential utility and + its software implementation. The integrated model is validated + for the case study of an urban catchment located in Melbourne, + Australia.", + journal = "Water Res.", + publisher = "Elsevier BV", + volume = 126, + pages = "501--514", + month = dec, + year = 2017, + language = "en" +} + + +@ARTICLE{Thrysoe2019-pi, + title = "Identifying fit-for-purpose lumped surrogate models for large + urban drainage systems using {GLUE}", + author = "Thrys{\o}e, Cecilie and Arnbjerg-Nielsen, Karsten and Borup, + Morten", + journal = "J. Hydrol. (Amst.)", + publisher = "Elsevier BV", + volume = 568, + pages = "517--533", + month = jan, + year = 2019, + language = "en" +} + +@ARTICLE{Chegini2022-oo, + title = "An algorithm for deriving the topology of belowground urban + stormwater networks", + author = "Chegini, Taher and Li, Hong-Yi", + abstract = "Abstract. Belowground urban stormwater networks (BUSNs) are + critical for removing excess rainfall from impervious urban + areas and preventing or mitigating urban flooding. However, + available BUSN data are sparse, preventing the modeling and + analysis of urban hydrologic processes at regional and larger + scales. We propose a novel algorithm for estimating BUSNs by + drawing on concepts from graph theory and existing, extensively + available land surface data, such as street network, topography, + and land use/land cover. First, we derive the causal + relationships between the topology of BUSNs and urban surface + features based on graph theory concepts. We then apply the + causal relationships and estimate BUSNs using web-service data + retrieval, spatial analysis, and high-performance computing + techniques. Finally, we validate the derived BUSNs in the + metropolitan areas of Los Angeles, Seattle, Houston, and + Baltimore in the US, where real BUSN data are partly available + to the public. Results show that our algorithm can effectively + capture 59 \%--76 \% of the topology of real BUSN data, + depending on the supporting data quality. This algorithm has + promising potential to support large-scale urban hydrologic + modeling and future urban drainage system planning.", + journal = "Hydrol. Earth Syst. Sci.", + publisher = "Copernicus GmbH", + volume = 26, + number = 16, + pages = "4279--4300", + month = aug, + year = 2022, + copyright = "https://creativecommons.org/licenses/by/4.0/", + language = "en" +} + +@ARTICLE{Reyes-Silva2022-pr, + title = "An evaluation framework for urban pluvial flooding based on + open-access data", + author = "Reyes-Silva, Julian D and Novoa, Diego and Helm, Bj{\"o}rn and + Krebs, Peter", + abstract = "Identifying the location and estimating the magnitude of urban + pluvial flooding events is essential to assess their impacts, + particularly in areas where data are unavailable. The present + work focused on developing and exemplifying a tool to evaluate + urban pluvial flooding based on open-access information. The + tool has three separate submodules: (1) sewer network generation + and design; (2) hydrodynamic model development; (3) urban + pluvial flood evaluation. Application of the first two modules + in two catchments and comparison of these results with real data + indicated that the tool was able to generate systems with + realistic layouts and hydraulic properties. Hydrodynamic models + derived from this data were able to simulate realistic flow + dynamics. The third module was evaluated for one of the study + cases. The results of this indicated that the current approach + could be used to identify flood areas and associated flood + depths during different rainfall scenarios. The outcomes of this + study could be used in a wide variety of contexts. For example, + it could provide information in areas with data scarcity or + uncertainty or serve as a tool for prospective planning, design, + and decision making.", + journal = "Water (Basel)", + publisher = "MDPI AG", + volume = 15, + number = 1, + pages = "46", + month = dec, + year = 2022, + copyright = "https://creativecommons.org/licenses/by/4.0/", + language = "en" +} + +@UNPUBLISHED{Dobson2024-dv, + title = "{SWMManywhere}: A global-scale workflow for generation and + sensitivity analysis of synthetic urban drainage models", + author = "Dobson, Barnaby and Jovanovic, Tijana and Alonso-{\'A}lvarez, + Diego and Chegini, Taher", + abstract = "Continual improvements in publicly available global geospatial + datasets provide an opportunity for deriving urban drainage + networks and simulation models of these networks (UDMs) + worldwide. We present SWMManywhere, which leverages such datasets + for generating synthetic UDMs and creating a Storm Water + Management Model for any urban area globally. SWMManywhere's + highly modular and parameterised approach enables significant + customisation to explore hydraulicly feasible network + configurations. Key novelties of our workflow are in network + topology derivation that accounts for combined effects of + impervious area and pipe slope. We assess SWMManywhere by + comparing pluvial flooding, drainage network outflows, and design + with known networks. The results demonstrate high quality + simulations are achievable with a synthetic approach even for + large networks. Our extensive sensitivity analysis shows that the + locations of manholes, outfalls, and underlying street network + are the most sensitive parameters. We find widespread sensitivity + across all parameters without clearly defined values that they + should take, thus, recommending an uncertainty driven approach to + synthetic drainage network modelling. This study showcases + significant potential of SWMManywhere for research and industry + applications to provide drainage network models in urban areas + where traditional approaches are impractical.", + journal = "EarthArXiv", + month = oct, + year = 2024 +} + +@ARTICLE{Khurelbaatar2021-sp, + title = "Data reduced method for cost comparison of wastewater management + scenarios--case study for two settlements in Jordan and Oman", + author = "Khurelbaatar, Ganbaatar and Al Marzuqi, Bishara and Van + Afferden, Manfred and M{\"u}ller, Roland A and Friesen, Jan", + abstract = "Safe access to sanitation is at the core of the United Nations + Sustainable Development Goal (SDG) \#6. Currently, it is + estimated that this goal cannot be met by 2030. Despite all + kinds of administrational hurdles, meeting SDG\#6 depends on + considerable investment. In order to get a chance at fulfilling + SGD\#6, the most cost-effective wastewater management has to be + identified. Wastewater can be managed in different ways ranging + from central treatment plants connected to individual households + through sewer networks down to tanker fleets servicing each + household. Depending on the geographical setting, investment + costs, operation and maintenance as well as social acceptance + there is no single best solution. Instead, identifying the + optimal wastewater management is highly localized and + country-specific or even settlement-specific. Within this study + we present a data-reduced scenario generation and assessment for + wastewater management based on the ALLOWS method that can be + applied to individual settlements. Results provide cost-ranked + wastewater management scenarios that enable decision makers to + select the most cost-effective and feasible scenario. Our study + starts with a detailed step-by-step methodology of a + data-reduced ALLOWS approach. The approach is applied to two + small settlements in Jordan and Oman with comparable population + size for which a set of five scenarios along a decentralization + gradient is defined and generated: centralized, + semi-centralized, decentralized, and on-site/tanker. Considering + spatial specificities and country-specific cost data, the five + scenarios are cost-ranked and discussed in view of the two + settlement settings. For Jordan specific treatment costs range + from 3.8 to 6.9 USD/m3of treated water and for Oman from 2.3 to + 10.1 USD/m3. Although the scenario ranking differs, for both + settlements the decentralized scenario is identified as the most + cost effective, where wastewater is treated on-site for + less-populated parts and by small cluster treatment plants for + higher density parts. Further, potential extensions providing + users with more functionality depending upon data availability + for the data-reduced ALLOWS method are discussed. Using globally + available data, the data-reduced can be applied worldwide. In + view of SDG\#6, we present a methodology that closes the gap + between country-scale investment estimates and the most + cost-effective wastewater management scenarios at settlement + level.", + journal = "Front. Environ. Sci.", + publisher = "Frontiers Media SA", + volume = 9, + month = may, + year = 2021, + copyright = "https://creativecommons.org/licenses/by/4.0/" } diff --git a/docs/paper/paper.md b/docs/paper/paper.md index f02d98c1..93273ef5 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -32,17 +32,22 @@ bibliography: paper.bib # Summary -Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive survey underground survey. A variety of literature exists to derive such UDMs from GIS data [refs]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. +Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive survey underground survey. A variety of literature exists to derive such UDMs from GIS data [@Chahinian2019-lg;@Reyes-Silva2022-pr]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. # Statement of need -Existing methods for synthesizing urban drainage networks have advanced significantly, producing hydraulically feasible models that closely approximate real-world systems. However, these methods face three critical limitations. First, many are closed-source, restricting accessibility and limiting transparency for users and researchers. Second, they typically require users to source, preprocess, and input geospatial data manually, which creates a high technical barrier, especially in regions where data acquisition is challenging. Third, while the output of these methods is often sensitive to input parameters, they offer limited control over the generation process, making it difficult to adjust and refine models according to specific needs. This combination of complexity and lack of control can lead to significant uncertainty in outputs, which remains difficult to manage. +Existing methods for synthesizing urban drainage networks have advanced significantly, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Reyes-Silva2022-pr]. However, these methods face three critical limitations. First, many are closed-source, restricting accessibility and limiting transparency for users and researchers. Second, they typically require users to source, preprocess, and input geospatial data manually, which creates a high technical barrier, especially in regions where data acquisition is challenging. Third, while the output of these methods is often sensitive to input parameters, they offer limited control over the generation process, making it difficult to adjust and refine models according to specific needs. This combination of complexity and lack of control can lead to significant uncertainty in outputs, which remains difficult to manage. -SWMManywhere addresses these limitations by offering an open-source, globally applicable tool that automates data acquisition and preprocessing while providing users with a flexible, customizable workflow. Its parameterized design allows for detailed sensitivity analysis [ref], enabling users to better understand and manage uncertainties in urban drainage network synthesis. Unlike existing methods, SWMManywhere emphasizes user control, allowing for fine-tuning of outputs to meet specific project requirements. By integrating publicly available geospatial data, the tool minimizes the technical burden and ensures applicability in data-scarce regions, making it an ideal solution for both researchers and practitioners in urban water management. +SWMManywhere addresses these limitations by offering an open-source, globally applicable tool that automates data acquisition and preprocessing while providing users with a flexible, customizable workflow. Its parameterized design allows for detailed sensitivity analysis [@Dobson2024-dv], enabling users to better understand and manage uncertainties in urban drainage network synthesis. Unlike existing methods, SWMManywhere emphasizes user control, allowing for fine-tuning of outputs to meet specific project requirements. By integrating publicly available geospatial data, the tool minimizes the technical burden and ensures applicability in data-scarce regions, making it an ideal solution for both researchers and practitioners in urban water management. ## Outlook -While we believe that SWMManywhere is a useful tool it has a variety of current limitations that present an exciting outlook for future research. Foremost, based on the findings of a sensitivity analysis [ref], better identification of manhole locations and outfalls will be critical to +While we believe that SWMManywhere is a useful tool it has a variety of current limitations that present an exciting outlook for future research. A variety of improvements to the overall realism of the approach may be made in the future. + +- Foremost, based on the findings of a sensitivity analysis [@Dobson2024-dv], better identification of manhole locations and outfalls will be critical to narrowing uncertainty in simulation outputs and improving realism. +- Implementation of local design regulations is common practice in UDM synthesis [@Chegini2022-oo], but not implemented in SWMManywhere owing to its global scope. Users may customise design parameters, but implementing a global database of design parameters tailored to different regions may also be possible. +- Capturing the gradual evolution of a network over time is known to be important in UDM synthesis [@Rauch2017-jz], and further illustrated by SWMManywhere results [@Dobson2024-dv]. We do not know of a global database that provides the information that would be necessary to capture this, but it may exist in the future or for local applications. +- Hydraulic structures often dominate the behaviour of a drainage network [@Dobson2022-wq;@Thrysoe2019-pi] but are not accounted for by SWMManywhere. We envisage that a machine learning approach may be able to improve identification of structures such as weirs, while elements such as pumps have been incorporated into network synthesis for sanitary networks [@Khurelbaatar2021-sp]. # Acknowledgements From c321ec7a3bbd2dd3a40264885b0c6907d8bbd190 Mon Sep 17 00:00:00 2001 From: Dobson Date: Wed, 16 Oct 2024 14:49:56 +0100 Subject: [PATCH 05/23] fix coverage link --- docs/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/index.md b/docs/index.md index 22278ddd..254522d6 100644 --- a/docs/index.md +++ b/docs/index.md @@ -24,5 +24,5 @@ derive a synthetic urban drainage network anywhere in the world. - [Post processing](reference-post-processing.md) - [Preprocessing](reference-preprocessing.md) - [Config](reference-defs.md) -- [Coverage report](coverage.md) +- [Coverage report](https://app.codecov.io/gh/ImperialCollegeLondon/SWMManywhere) \ No newline at end of file From c6e3754059504597560b46f519c1473d42dc5f1a Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 16 Oct 2024 14:59:05 +0100 Subject: [PATCH 06/23] quick read over --- docs/paper/paper.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 93273ef5..69366883 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -32,11 +32,11 @@ bibliography: paper.bib # Summary -Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive survey underground survey. A variety of literature exists to derive such UDMs from GIS data [@Chahinian2019-lg;@Reyes-Silva2022-pr]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. +Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive underground survey. A variety of literature exists to derive such UDMs from GIS data [@Chahinian2019-lg;@Reyes-Silva2022-pr]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. # Statement of need -Existing methods for synthesizing urban drainage networks have advanced significantly, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Reyes-Silva2022-pr]. However, these methods face three critical limitations. First, many are closed-source, restricting accessibility and limiting transparency for users and researchers. Second, they typically require users to source, preprocess, and input geospatial data manually, which creates a high technical barrier, especially in regions where data acquisition is challenging. Third, while the output of these methods is often sensitive to input parameters, they offer limited control over the generation process, making it difficult to adjust and refine models according to specific needs. This combination of complexity and lack of control can lead to significant uncertainty in outputs, which remains difficult to manage. +Existing methods for synthesizing urban drainage networks have advanced significantly, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Reyes-Silva2022-pr]. However, these methods face three critical limitations. First, all are closed-source, restricting accessibility and limiting transparency for users and researchers. Second, they typically require users to source, preprocess, and input geospatial data manually, which creates a high technical barrier, especially in regions where data acquisition is challenging. Third, while the output of these methods is often sensitive to input parameters, they offer limited control over the generation process, making it difficult to adjust and refine models according to specific needs. The combination of complexity and lack of control in a UDM synthesis approach can lead to significant uncertainty in outputs, which remains difficult to manage. SWMManywhere addresses these limitations by offering an open-source, globally applicable tool that automates data acquisition and preprocessing while providing users with a flexible, customizable workflow. Its parameterized design allows for detailed sensitivity analysis [@Dobson2024-dv], enabling users to better understand and manage uncertainties in urban drainage network synthesis. Unlike existing methods, SWMManywhere emphasizes user control, allowing for fine-tuning of outputs to meet specific project requirements. By integrating publicly available geospatial data, the tool minimizes the technical burden and ensures applicability in data-scarce regions, making it an ideal solution for both researchers and practitioners in urban water management. @@ -47,7 +47,7 @@ While we believe that SWMManywhere is a useful tool it has a variety of current - Foremost, based on the findings of a sensitivity analysis [@Dobson2024-dv], better identification of manhole locations and outfalls will be critical to narrowing uncertainty in simulation outputs and improving realism. - Implementation of local design regulations is common practice in UDM synthesis [@Chegini2022-oo], but not implemented in SWMManywhere owing to its global scope. Users may customise design parameters, but implementing a global database of design parameters tailored to different regions may also be possible. - Capturing the gradual evolution of a network over time is known to be important in UDM synthesis [@Rauch2017-jz], and further illustrated by SWMManywhere results [@Dobson2024-dv]. We do not know of a global database that provides the information that would be necessary to capture this, but it may exist in the future or for local applications. -- Hydraulic structures often dominate the behaviour of a drainage network [@Dobson2022-wq;@Thrysoe2019-pi] but are not accounted for by SWMManywhere. We envisage that a machine learning approach may be able to improve identification of structures such as weirs, while elements such as pumps have been incorporated into network synthesis for sanitary networks [@Khurelbaatar2021-sp]. +- Hydraulic structures often dominate the behaviour of a drainage network [@Dobson2022-wq;@Thrysoe2019-pi], but are not accounted for by SWMManywhere. We envisage that a machine learning approach may be able to improve identification of structures such as weirs, while elements such as pumps have been incorporated into network synthesis for sanitary networks [@Khurelbaatar2021-sp]. # Acknowledgements From 13e22e4b2db552c1d406f1dac6888766c49ddabd Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 16 Oct 2024 15:01:04 +0100 Subject: [PATCH 07/23] link paper in toc --- docs/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/index.md b/docs/index.md index 254522d6..080081f1 100644 --- a/docs/index.md +++ b/docs/index.md @@ -6,7 +6,7 @@ derive a synthetic urban drainage network anywhere in the world. ## Table of contents - [Home](index.md) -- [About] +- [About](./paper/paper.md) - [Quickstart](quickstart.md) - Guides: - [Configuration file](config_guide.md) From f63a6703b578bca1ad15fab2ae85178467cf9773 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Tue, 22 Oct 2024 17:06:48 +0100 Subject: [PATCH 08/23] readover --- docs/paper/paper.md | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 69366883..088759dd 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -32,13 +32,11 @@ bibliography: paper.bib # Summary -Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive underground survey. A variety of literature exists to derive such UDMs from GIS data [@Chahinian2019-lg;@Reyes-Silva2022-pr]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. +Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive underground survey. A variety of literature exists to derive such UDMs from GIS data, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Chahinian2019-lg;@Reyes-Silva2022-pr]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. # Statement of need -Existing methods for synthesizing urban drainage networks have advanced significantly, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Reyes-Silva2022-pr]. However, these methods face three critical limitations. First, all are closed-source, restricting accessibility and limiting transparency for users and researchers. Second, they typically require users to source, preprocess, and input geospatial data manually, which creates a high technical barrier, especially in regions where data acquisition is challenging. Third, while the output of these methods is often sensitive to input parameters, they offer limited control over the generation process, making it difficult to adjust and refine models according to specific needs. The combination of complexity and lack of control in a UDM synthesis approach can lead to significant uncertainty in outputs, which remains difficult to manage. - -SWMManywhere addresses these limitations by offering an open-source, globally applicable tool that automates data acquisition and preprocessing while providing users with a flexible, customizable workflow. Its parameterized design allows for detailed sensitivity analysis [@Dobson2024-dv], enabling users to better understand and manage uncertainties in urban drainage network synthesis. Unlike existing methods, SWMManywhere emphasizes user control, allowing for fine-tuning of outputs to meet specific project requirements. By integrating publicly available geospatial data, the tool minimizes the technical burden and ensures applicability in data-scarce regions, making it an ideal solution for both researchers and practitioners in urban water management. +`SWMManywhere` is an open-source Python package designed for the global synthesis of urban drainage networks. SWMManywhere integrates publicly available geospatial data and automates data acquisition and preprocessing, reducing the technical burden on users. The CLI offers a flexible workflow, providing an accessible entry point to using and customising synthesis. Its parameterized design enables detailed sensitivity analyses, allowing users to understand and manage uncertainties inherent in urban drainage modelling [@Dobson2024-dv]. By emphasizing user control, SWMManywhere allows tuning of outputs with parameters to meet local requirements, making it adaptable to a wide range of scenarios. Designed for both researchers and practitioners in urban water management, SWMManywhere responds to the limitations of existing methods by providing an end-to-end, open-source, and customisable solution. ## Outlook From dae86ca0baf4f8974ff533eacafbf5d80d366bca Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 08:38:17 +0000 Subject: [PATCH 09/23] fix graph warning --- src/swmmanywhere/graph_utilities.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/swmmanywhere/graph_utilities.py b/src/swmmanywhere/graph_utilities.py index 9e1f601e..f47f4f94 100644 --- a/src/swmmanywhere/graph_utilities.py +++ b/src/swmmanywhere/graph_utilities.py @@ -54,7 +54,7 @@ def save_graph(G: nx.Graph, fid: Path) -> None: G (nx.Graph): A graph fid (Path): The path to the file """ - json_data = nx.node_link_data(G) + json_data = nx.node_link_data(G, edges="edges") with fid.open("w") as file: json.dump(json_data, file, default=_serialize_line_string) From af6dd9f8a26e53cf0e95d22c8e0f785393c13c8d Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 10:58:30 +0000 Subject: [PATCH 10/23] update --- .github/workflows/ci_template.yml | 21 ++++++++++++++++ docs/index.md | 2 +- docs/paper/extended_demo.svg | 1 + docs/paper/paper.bib | 42 +++++++++++++++++++++++++++++++ docs/paper/paper.md | 27 +++++++++++++++++--- mkdocs.yml | 2 +- 6 files changed, 90 insertions(+), 5 deletions(-) create mode 100644 docs/paper/extended_demo.svg diff --git a/.github/workflows/ci_template.yml b/.github/workflows/ci_template.yml index a3c731c2..42287986 100644 --- a/.github/workflows/ci_template.yml +++ b/.github/workflows/ci_template.yml @@ -16,6 +16,27 @@ on: type: string jobs: + paper: + runs-on: ubuntu-latest + needs: publish-PyPI + steps: + - name: Checkout + uses: actions/checkout@v4 + - name: Build draft PDF + uses: openjournals/openjournals-draft-action@master + with: + journal: joss + # This should be the path to the paper within your repo. + paper-path: docs/paper/paper.md + - name: Upload + uses: actions/upload-artifact@v4 + with: + name: paper + # This is the output path where Pandoc will write the compiled + # PDF. Note, this should be the same directory as the input + # paper.md + path: docs/paper/paper.pdf + test: runs-on: ${{ matrix.os }} strategy: diff --git a/docs/index.md b/docs/index.md index dce6da3d..a65059ff 100644 --- a/docs/index.md +++ b/docs/index.md @@ -6,7 +6,7 @@ derive a synthetic urban drainage network anywhere in the world. ## Table of contents - [Home](index.md) -- [About](./paper/paper.md) +- [About](./paper/paper.pdf) - [Quickstart](quickstart.md) - Guides: - [Configuration file](config_guide.md) diff --git a/docs/paper/extended_demo.svg b/docs/paper/extended_demo.svg new file mode 100644 index 00000000..4219d181 --- /dev/null +++ b/docs/paper/extended_demo.svg @@ -0,0 +1 @@ +Initial guess:-Default parametersSingle iteration (change 4 parameter values):-Prevent pipes on pedestrian paths-Allow pipes along major roads-Increase availability of river outfalls-Prevent outfalls far from river \ No newline at end of file diff --git a/docs/paper/paper.bib b/docs/paper/paper.bib index 98c29591..b2f557a2 100644 --- a/docs/paper/paper.bib +++ b/docs/paper/paper.bib @@ -285,3 +285,45 @@ @ARTICLE{Khurelbaatar2021-sp year = 2021, copyright = "https://creativecommons.org/licenses/by/4.0/" } + +@misc{VIDA2023, +author = {VIDA}, +title = {{Google-Microsoft Open Buildings}}, +url = {https://beta.source.coop/repositories/vida/google-microsoft-open-buildings}, +urldate = {2024-07-30}, +year = {2023} +} + +@article{Crippen2016, +abstract = {Abstract. NASADEM is a near-global elevation model that is being produced primarily by completely reprocessing the Shuttle Radar Topography Mission (SRTM) radar data and then merging it with refined ASTER GDEM elevations. The new and improved SRTM elevations in NASADEM result from better vertical control of each SRTM data swath via reference to ICESat elevations and from SRTM void reductions using advanced interferometric unwrapping algorithms. Remnant voids will be filled primarily by GDEM3, but with reduction of GDEM glitches (mostly related to clouds) and therefore with only minor need for secondary sources of fill.}, +author = {Crippen, R. and Buckley, S. and Agram, P. and Belz, E. and Gurrola, E. and Hensley, S. and Kobrick, M. and Lavalle, M. and Martin, J. and Neumann, M. and Nguyen, Q. and Rosen, P. and Shimada, J. and Simard, M. and Tung, W.}, +doi = {10.5194/isprs-archives-XLI-B4-125-2016}, +issn = {2194-9034}, +journal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, +month = {jun}, +pages = {125--128}, +title = {{NASADEM GLOBAL ELEVATION MODEL: METHODS AND PROGRESS}}, +url = {https://isprs-archives.copernicus.org/articles/XLI-B4/125/2016/}, +volume = {XLI-B4}, +year = {2016} +} + +@article{Boeing2017, +author = {Boeing, Geoff}, +doi = {10.1016/j.compenvurbsys.2017.05.004}, +issn = {01989715}, +journal = {Computers, Environment and Urban Systems}, +month = {sep}, +pages = {126--139}, +title = {{OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks}}, +url = {https://linkinghub.elsevier.com/retrieve/pii/S0198971516303970}, +volume = {65}, +year = {2017} +} + + @misc{OpenStreetMap, + author = {{OpenStreetMap contributors}}, + title = {{Planet dump retrieved from https://planet.osm.org }}, + howpublished = "\url{ https://www.openstreetmap.org }", + year = {2017}, + } \ No newline at end of file diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 088759dd..e6a1ff29 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -30,13 +30,34 @@ bibliography: paper.bib --- -# Summary +## Summary Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive underground survey. A variety of literature exists to derive such UDMs from GIS data, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Chahinian2019-lg;@Reyes-Silva2022-pr]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. -# Statement of need +## Statement of need + +SWMManywhere is an open-source Python package designed for the global synthesis of urban drainage networks. SWMManywhere integrates publicly available geospatial data and automates data acquisition and preprocessing, reducing the technical burden on users. The CLI offers a flexible workflow, providing an accessible entry point to using and customising synthesis. Its parameterized design enables detailed sensitivity analyses, allowing users to understand and manage uncertainties inherent in urban drainage modelling [@Dobson2024-dv]. By emphasizing user control, SWMManywhere allows tuning of outputs with parameters to meet local requirements, making it adaptable to a wide range of scenarios. Designed for both researchers and practitioners in urban water management, SWMManywhere responds to the limitations of existing methods by providing an end-to-end, open-source, and customisable solution. + +### Data + +A variety of datasets were selected to enable SWMManywhere to be applied globally. + +| Data Source | Description | Reference | +|-------------|-------------| --------- | +| **OpenStreetMap (OSM)** | Provides global street and river data, used to define potential pipe locations and outfall points for drainage networks. | [@Boeing2017;@OpenStreetMap] | +| **Google-Microsoft Open Buildings** | A dataset of global building footprints, used for estimating impervious surfaces essential for runoff calculations. | [@VIDA2023] | +| **NASADEM** | Provides 30m resolution global digital elevation model (DEM) data to support sub-catchment delineation and slope calculation. | [@Crippen2016] | + +These datasets are global in their coverage, and we consider them of sufficient quality in locations that we have tested [@Dobson24-dv], however, we urge users to check data in their specific case study. + +### Approach and customisation + +The core task in SWMManywhere is to begin with a 'starting graph' (e.g., an OSM street graph), refine this graph first into manhole locations and potential pipe locations, eliminate pipes from unnecessary locations, and then dimension the resulting pipe network so that it can be simulated in a software such as [SWMM](https://www.epa.gov/sites/default/files/2019-02/documents/epaswmm5_1_manual_master_8-2-15.pdf). These operations take place in an iterative approach, where each function takes a graph, and returns the transformed graph, thus each operation is referred to as a 'graph function'. The use of graph functions in SWMManywhere enables modular packaging of functions, easy customisation of the approach (e.g., by adding/removing/reordering graph functions), and explicit definition of parameters for each graph function. Explanations for making these customisations are available in the [documentation](https://imperialcollegelondon.github.io/SWMManywhere/). Ultimately, this customisability facilitates exploring uncertainty in urban drainage modelling in a way that reflects not just the model itself but the model creation process, as is demonstrated in [@Dobson2024-dv]. + +We visualise the example from the [extended demonstration](https://imperialcollegelondon.github.io/SWMManywhere/notebooks/extended_demo/) in the documentation to illustrate how changing relatively few parameter values in a strategic way can dramatically change the nature of the synthesised network \autoref{fig:fig1}. + +![Figure 1: Example of output customisation with SWMManywhere. Black nodes are manholes, black lines are pipes, red nodes are outfalls.\label{fig:fig1}](extended_demo.svg) -`SWMManywhere` is an open-source Python package designed for the global synthesis of urban drainage networks. SWMManywhere integrates publicly available geospatial data and automates data acquisition and preprocessing, reducing the technical burden on users. The CLI offers a flexible workflow, providing an accessible entry point to using and customising synthesis. Its parameterized design enables detailed sensitivity analyses, allowing users to understand and manage uncertainties inherent in urban drainage modelling [@Dobson2024-dv]. By emphasizing user control, SWMManywhere allows tuning of outputs with parameters to meet local requirements, making it adaptable to a wide range of scenarios. Designed for both researchers and practitioners in urban water management, SWMManywhere responds to the limitations of existing methods by providing an end-to-end, open-source, and customisable solution. ## Outlook diff --git a/mkdocs.yml b/mkdocs.yml index e6a9ba60..0fecbca0 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -41,7 +41,7 @@ extra_javascript: nav: - Home: index.md - - About: ./paper/paper.md + - About: ./paper/paper.pdf - Quickstart: quickstart.md - Guides: - Configuration guide: config_guide.md From 9078b80999558e35b037d902b1d8e329f128440c Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 11:09:03 +0000 Subject: [PATCH 11/23] fix precommit --- docs/paper/paper.md | 5 +++-- pyproject.toml | 2 +- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/docs/paper/paper.md b/docs/paper/paper.md index e6a1ff29..0ab0a6b1 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -40,7 +40,9 @@ SWMManywhere is an open-source Python package designed for the global synthesis ### Data -A variety of datasets were selected to enable SWMManywhere to be applied globally. +A variety of datasets were selected to enable SWMManywhere to be applied globally, \autoref{table:table1}. + +: SWMManywhere data source. \label{table:table1} | Data Source | Description | Reference | |-------------|-------------| --------- | @@ -58,7 +60,6 @@ We visualise the example from the [extended demonstration](https://imperialcolle ![Figure 1: Example of output customisation with SWMManywhere. Black nodes are manholes, black lines are pipes, red nodes are outfalls.\label{fig:fig1}](extended_demo.svg) - ## Outlook While we believe that SWMManywhere is a useful tool it has a variety of current limitations that present an exciting outlook for future research. A variety of improvements to the overall realism of the approach may be made in the future. diff --git a/pyproject.toml b/pyproject.toml index 9d39b5f5..2f11a892 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -113,7 +113,7 @@ lint.isort.required-imports = [ "from __future__ import annotations" ] lint.pydocstyle.convention = "google" [tool.codespell] -skip = "src/swmmanywhere/defs/iso_converter.yml,*.inp" +skip = "src/swmmanywhere/defs/iso_converter.yml,*.inp,docs/paper/*" ignore-words-list = "gage,gages,Carrer" [tool.pytest.ini_options] From c845191aaafd056abe686d68963c789f8dd857a3 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 11:30:55 +0000 Subject: [PATCH 12/23] update link checker --- .github/workflows/check-links.yml | 1 + .markdown-link-check.json | 7 +++++++ 2 files changed, 8 insertions(+) create mode 100644 .markdown-link-check.json diff --git a/.github/workflows/check-links.yml b/.github/workflows/check-links.yml index 4bfc95de..bbb7474a 100644 --- a/.github/workflows/check-links.yml +++ b/.github/workflows/check-links.yml @@ -13,3 +13,4 @@ jobs: with: use-quiet-mode: 'yes' use-verbose-mode: 'yes' + config-file: .markdown-link-check.json diff --git a/.markdown-link-check.json b/.markdown-link-check.json new file mode 100644 index 00000000..43f99a85 --- /dev/null +++ b/.markdown-link-check.json @@ -0,0 +1,7 @@ +{ + "ignorePatterns": [ + { + "pattern": "docs/paper/paper.pdf" + } + ] +} From 42195b514233615dd185b3945df29957a50b9fbd Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 11:33:11 +0000 Subject: [PATCH 13/23] Update .markdown-link-check.json --- .markdown-link-check.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.markdown-link-check.json b/.markdown-link-check.json index 43f99a85..9eb00c81 100644 --- a/.markdown-link-check.json +++ b/.markdown-link-check.json @@ -1,7 +1,7 @@ { "ignorePatterns": [ { - "pattern": "docs/paper/paper.pdf" + "pattern": "^docs/paper/paper.pdf" } ] } From ebac5a2e71dfe74cf474fd9ce0aabd4fb0724fcf Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 11:35:12 +0000 Subject: [PATCH 14/23] Update .markdown-link-check.json --- .markdown-link-check.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.markdown-link-check.json b/.markdown-link-check.json index 9eb00c81..5656a228 100644 --- a/.markdown-link-check.json +++ b/.markdown-link-check.json @@ -1,7 +1,7 @@ { "ignorePatterns": [ { - "pattern": "^docs/paper/paper.pdf" + "pattern": "^paper.pdf" } ] } From 9d98a1928b16f797a517961fc8d0303f3f548ec2 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 11:36:39 +0000 Subject: [PATCH 15/23] Update .markdown-link-check.json --- .markdown-link-check.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.markdown-link-check.json b/.markdown-link-check.json index 5656a228..c0991d9c 100644 --- a/.markdown-link-check.json +++ b/.markdown-link-check.json @@ -1,7 +1,7 @@ { "ignorePatterns": [ { - "pattern": "^paper.pdf" + "pattern": ".*/paper.pdf" } ] } From 07df8233124995caf3d4e00f4152aa76fce21ed0 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 11:38:25 +0000 Subject: [PATCH 16/23] Update ci_template.yml --- .github/workflows/ci_template.yml | 1 - 1 file changed, 1 deletion(-) diff --git a/.github/workflows/ci_template.yml b/.github/workflows/ci_template.yml index 42287986..3c1871d0 100644 --- a/.github/workflows/ci_template.yml +++ b/.github/workflows/ci_template.yml @@ -18,7 +18,6 @@ on: jobs: paper: runs-on: ubuntu-latest - needs: publish-PyPI steps: - name: Checkout uses: actions/checkout@v4 From 5e72d021b9819837f10ce2c2b112789b7720024b Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 11:44:56 +0000 Subject: [PATCH 17/23] debug --- docs/paper/extended_demo.png | Bin 0 -> 3025424 bytes docs/paper/extended_demo.svg | 1 - docs/paper/paper.md | 12 ++++-------- src/swmmanywhere/graph_utilities.py | 2 +- 4 files changed, 5 insertions(+), 10 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ztS1zU3N%-+xdQ=d;5;2%q+H$+Rs>A#nd)9S5a7OXhdbQ#OzwH{%5iC)H;Lv)1Eo`3 zz&~29eE|{4AvXM{{8qDS?TKL?Y@_nt;!tucS9f)km0F;yKCkzvredz+gRUd51F8`C zgl}!~C8yFJSSTaXH%@IMz+B);YPTZYMQ23j5@v?fab#0gIWj+BP*Wn~+%_u=YVeG+ zUiKPQ38o1_u!l4$7(8!mbP3ahn;b^qt~{Hk*@2@y&2-*312X+HRgl#_0-qr(^1Y{v z0|+5{C^@koUmII7%uHbtFf9dcQN^e@K;exkH-xvMDB=ciIZvr%dU^+k#R_m>!46o0 zlP1T8#{3}jrQ+n9ZFLju0psSCAL8F@G@P~iX-$cC(seFX!Cem0mmB)u`|8zVyy?eL wpnw1K0q1-)k literal 0 HcmV?d00001 diff --git a/docs/paper/extended_demo.svg b/docs/paper/extended_demo.svg deleted file mode 100644 index 4219d181..00000000 --- a/docs/paper/extended_demo.svg +++ /dev/null @@ -1 +0,0 @@ -Initial guess:-Default parametersSingle iteration (change 4 parameter values):-Prevent pipes on pedestrian paths-Allow pipes along major roads-Increase availability of river outfalls-Prevent outfalls far from river \ No newline at end of file diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 0ab0a6b1..7cb1ba2a 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -8,16 +8,13 @@ tags: - swmm - hydraulic-modelling authors: - - family-names: "Dobson" - given-names: "Barnaby" + - name: "Barnaby Dobson" orcid: "https://orcid.org/0000-0002-0149-4124" affiliation: 1 - - family-names: "Alonso-Álvarez" - given-names: "Diego" + - name: "Diego Alonso-Álvarez" orcid: "https://orcid.org/0000-0002-0060-9495" affiliation: 1 - - family-names: "Chegini" - given-names: "Taher" + - name: "Taher Chegini" orcid: "https://orcid.org/0000-0002-5430-6000" affiliation: 2 affiliations: @@ -27,7 +24,6 @@ affiliations: index: 2 date: 16 October 2024 bibliography: paper.bib - --- ## Summary @@ -58,7 +54,7 @@ The core task in SWMManywhere is to begin with a 'starting graph' (e.g., an OSM We visualise the example from the [extended demonstration](https://imperialcollegelondon.github.io/SWMManywhere/notebooks/extended_demo/) in the documentation to illustrate how changing relatively few parameter values in a strategic way can dramatically change the nature of the synthesised network \autoref{fig:fig1}. -![Figure 1: Example of output customisation with SWMManywhere. Black nodes are manholes, black lines are pipes, red nodes are outfalls.\label{fig:fig1}](extended_demo.svg) +![Figure 1: Example of output customisation with SWMManywhere. Black nodes are manholes, black lines are pipes, red nodes are outfalls.\label{fig:fig1}](extended_demo.png) ## Outlook diff --git a/src/swmmanywhere/graph_utilities.py b/src/swmmanywhere/graph_utilities.py index f47f4f94..a203a6f8 100644 --- a/src/swmmanywhere/graph_utilities.py +++ b/src/swmmanywhere/graph_utilities.py @@ -54,7 +54,7 @@ def save_graph(G: nx.Graph, fid: Path) -> None: G (nx.Graph): A graph fid (Path): The path to the file """ - json_data = nx.node_link_data(G, edges="edges") + json_data = nx.node_link_data(G, edges="links") with fid.open("w") as file: json.dump(json_data, file, default=_serialize_line_string) From ae7ee40b40b68789f8935b45e68e6c974eaa2a02 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Fri, 1 Nov 2024 12:16:42 +0000 Subject: [PATCH 18/23] update publish --- .github/workflows/ci_template.yml | 20 -------------------- .github/workflows/publish.yml | 22 +++++++++++++++++++++- docs/paper/paper.md | 6 +++--- src/swmmanywhere/graph_utilities.py | 5 ++++- 4 files changed, 28 insertions(+), 25 deletions(-) diff --git a/.github/workflows/ci_template.yml b/.github/workflows/ci_template.yml index 3c1871d0..a3c731c2 100644 --- a/.github/workflows/ci_template.yml +++ b/.github/workflows/ci_template.yml @@ -16,26 +16,6 @@ on: type: string jobs: - paper: - runs-on: ubuntu-latest - steps: - - name: Checkout - uses: actions/checkout@v4 - - name: Build draft PDF - uses: openjournals/openjournals-draft-action@master - with: - journal: joss - # This should be the path to the paper within your repo. - paper-path: docs/paper/paper.md - - name: Upload - uses: actions/upload-artifact@v4 - with: - name: paper - # This is the output path where Pandoc will write the compiled - # PDF. Note, this should be the same directory as the input - # paper.md - path: docs/paper/paper.pdf - test: runs-on: ${{ matrix.os }} strategy: diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index d857d16d..0a871404 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -71,9 +71,29 @@ jobs: - name: Publish package distributions to PyPI uses: pypa/gh-action-pypi-publish@release/v1 + paper: + runs-on: ubuntu-latest + needs: publish-PyPI + steps: + - name: Checkout + uses: actions/checkout@v4 + - name: Build draft PDF + uses: openjournals/openjournals-draft-action@master + with: + journal: joss + # This should be the path to the paper within your repo. + paper-path: docs/paper/paper.md + - name: Upload + uses: actions/upload-artifact@v4 + with: + name: paper + # This is the output path where Pandoc will write the compiled + # PDF. Note, this should be the same directory as the input + # paper.md + path: docs/paper/paper.pdf publish-docs: - needs: publish-PyPI + needs: paper runs-on: ubuntu-latest steps: diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 7cb1ba2a..64781703 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -38,7 +38,7 @@ SWMManywhere is an open-source Python package designed for the global synthesis A variety of datasets were selected to enable SWMManywhere to be applied globally, \autoref{table:table1}. -: SWMManywhere data source. \label{table:table1} +: SWMManywhere data sources. \label{table:table1} | Data Source | Description | Reference | |-------------|-------------| --------- | @@ -46,7 +46,7 @@ A variety of datasets were selected to enable SWMManywhere to be applied globall | **Google-Microsoft Open Buildings** | A dataset of global building footprints, used for estimating impervious surfaces essential for runoff calculations. | [@VIDA2023] | | **NASADEM** | Provides 30m resolution global digital elevation model (DEM) data to support sub-catchment delineation and slope calculation. | [@Crippen2016] | -These datasets are global in their coverage, and we consider them of sufficient quality in locations that we have tested [@Dobson24-dv], however, we urge users to check data in their specific case study. +These datasets are global in their coverage, and we consider them of sufficient quality in locations that we have tested [@Dobson2024-dv], however, we urge users to check data in their specific case study. ### Approach and customisation @@ -54,7 +54,7 @@ The core task in SWMManywhere is to begin with a 'starting graph' (e.g., an OSM We visualise the example from the [extended demonstration](https://imperialcollegelondon.github.io/SWMManywhere/notebooks/extended_demo/) in the documentation to illustrate how changing relatively few parameter values in a strategic way can dramatically change the nature of the synthesised network \autoref{fig:fig1}. -![Figure 1: Example of output customisation with SWMManywhere. Black nodes are manholes, black lines are pipes, red nodes are outfalls.\label{fig:fig1}](extended_demo.png) +![Example of output customisation with SWMManywhere. Black nodes are manholes, black lines are pipes, red nodes are outfalls.\label{fig:fig1}](extended_demo.png) ## Outlook diff --git a/src/swmmanywhere/graph_utilities.py b/src/swmmanywhere/graph_utilities.py index a203a6f8..48306d01 100644 --- a/src/swmmanywhere/graph_utilities.py +++ b/src/swmmanywhere/graph_utilities.py @@ -8,6 +8,7 @@ import json import tempfile +import warnings from abc import ABC, abstractmethod from pathlib import Path from typing import Callable, List, Optional @@ -54,7 +55,9 @@ def save_graph(G: nx.Graph, fid: Path) -> None: G (nx.Graph): A graph fid (Path): The path to the file """ - json_data = nx.node_link_data(G, edges="links") + with warnings.catch_warnings(): + warnings.simplefilter("ignore", FutureWarning) + json_data = nx.node_link_data(G) with fid.open("w") as file: json.dump(json_data, file, default=_serialize_line_string) From a37953b17b394c726e5327ab74d921d75297f42d Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 6 Nov 2024 15:24:39 +0000 Subject: [PATCH 19/23] update to addres cheginit --- .github/workflows/ci_template.yml | 20 ++++++++++++++++++++ docs/paper/paper.bib | 15 +++++++++++---- docs/paper/paper.md | 16 ++++++++++------ 3 files changed, 41 insertions(+), 10 deletions(-) diff --git a/.github/workflows/ci_template.yml b/.github/workflows/ci_template.yml index a3c731c2..3c1871d0 100644 --- a/.github/workflows/ci_template.yml +++ b/.github/workflows/ci_template.yml @@ -16,6 +16,26 @@ on: type: string jobs: + paper: + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: actions/checkout@v4 + - name: Build draft PDF + uses: openjournals/openjournals-draft-action@master + with: + journal: joss + # This should be the path to the paper within your repo. + paper-path: docs/paper/paper.md + - name: Upload + uses: actions/upload-artifact@v4 + with: + name: paper + # This is the output path where Pandoc will write the compiled + # PDF. Note, this should be the same directory as the input + # paper.md + path: docs/paper/paper.pdf + test: runs-on: ${{ matrix.os }} strategy: diff --git a/docs/paper/paper.bib b/docs/paper/paper.bib index b2f557a2..2581b634 100644 --- a/docs/paper/paper.bib +++ b/docs/paper/paper.bib @@ -321,9 +321,16 @@ @article{Boeing2017 year = {2017} } - @misc{OpenStreetMap, +@misc{OpenStreetMap, + author = {{OpenStreetMap contributors}}, + title = {{Planet dump retrieved from https://planet.osm.org }}, + howpublished = "\url{ https://www.openstreetmap.org }", + year = {2017}, +} + + @misc{OpenStreetMap-overture, author = {{OpenStreetMap contributors}}, - title = {{Planet dump retrieved from https://planet.osm.org }}, - howpublished = "\url{ https://www.openstreetmap.org }", - year = {2017}, + title = {{Overture Maps Foundation}}, + howpublished = "\url{ https://overturemaps.org/ }", + year = {2024}, } \ No newline at end of file diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 64781703..b1edf32a 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -28,11 +28,17 @@ bibliography: paper.bib ## Summary -Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive underground survey. A variety of literature exists to derive such UDMs from GIS data, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Chahinian2019-lg;@Reyes-Silva2022-pr]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. +Urban drainage network models (UDMs) are useful for a variety of purposes, most notably simulating and alleviating pluvial flooding. Despite the clear usefulness of UDMs, they are often not used owing to the difficulty and expense of creating them. This creates a significant gap for users attempting to generate UDMs if they are not able to perform an expensive underground survey. ## Statement of need -SWMManywhere is an open-source Python package designed for the global synthesis of urban drainage networks. SWMManywhere integrates publicly available geospatial data and automates data acquisition and preprocessing, reducing the technical burden on users. The CLI offers a flexible workflow, providing an accessible entry point to using and customising synthesis. Its parameterized design enables detailed sensitivity analyses, allowing users to understand and manage uncertainties inherent in urban drainage modelling [@Dobson2024-dv]. By emphasizing user control, SWMManywhere allows tuning of outputs with parameters to meet local requirements, making it adaptable to a wide range of scenarios. Designed for both researchers and practitioners in urban water management, SWMManywhere responds to the limitations of existing methods by providing an end-to-end, open-source, and customisable solution. +A variety of literature exists to derive UDMs from GIS data, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Chahinian2019-lg;@Reyes-Silva2022-pr;@Chegini2022-oo]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. + +SWMManywhere is an open-source Python package designed for the global synthesis of urban drainage networks. SWMManywhere integrates publicly available geospatial data and automates data acquisition and preprocessing, reducing the technical burden on users. + +## Features + +SWMManywhere includes a variety of key features aimed to improve useability and usefulness. A command line interface (CLI) offers a flexible workflow, providing an accessible entry point to using and customising synthesis. Its parameterized design enables detailed sensitivity analyses, allowing users to understand and manage uncertainties inherent in urban drainage modelling [@Dobson2024-dv]. By emphasizing user control, SWMManywhere allows tuning of outputs with parameters to meet local requirements, making it adaptable to a wide range of scenarios. Designed for both researchers and practitioners in urban water management, SWMManywhere responds to the limitations of existing methods by providing an end-to-end, open-source, and customisable solution. ### Data @@ -43,7 +49,7 @@ A variety of datasets were selected to enable SWMManywhere to be applied globall | Data Source | Description | Reference | |-------------|-------------| --------- | | **OpenStreetMap (OSM)** | Provides global street and river data, used to define potential pipe locations and outfall points for drainage networks. | [@Boeing2017;@OpenStreetMap] | -| **Google-Microsoft Open Buildings** | A dataset of global building footprints, used for estimating impervious surfaces essential for runoff calculations. | [@VIDA2023] | +| **Google-Microsoft Open Buildings** | A dataset of global building footprints, used for estimating impervious surfaces essential for runoff calculations. | [@OpenStreetMap-overture] | | **NASADEM** | Provides 30m resolution global digital elevation model (DEM) data to support sub-catchment delineation and slope calculation. | [@Crippen2016] | These datasets are global in their coverage, and we consider them of sufficient quality in locations that we have tested [@Dobson2024-dv], however, we urge users to check data in their specific case study. @@ -58,12 +64,10 @@ We visualise the example from the [extended demonstration](https://imperialcolle ## Outlook -While we believe that SWMManywhere is a useful tool it has a variety of current limitations that present an exciting outlook for future research. A variety of improvements to the overall realism of the approach may be made in the future. +While we believe that SWMManywhere is a useful tool it has a variety of current limitations that present an exciting outlook for future research. A variety of improvements to the overall realism of the approach may be made in the future. For example, - Foremost, based on the findings of a sensitivity analysis [@Dobson2024-dv], better identification of manhole locations and outfalls will be critical to narrowing uncertainty in simulation outputs and improving realism. -- Implementation of local design regulations is common practice in UDM synthesis [@Chegini2022-oo], but not implemented in SWMManywhere owing to its global scope. Users may customise design parameters, but implementing a global database of design parameters tailored to different regions may also be possible. - Capturing the gradual evolution of a network over time is known to be important in UDM synthesis [@Rauch2017-jz], and further illustrated by SWMManywhere results [@Dobson2024-dv]. We do not know of a global database that provides the information that would be necessary to capture this, but it may exist in the future or for local applications. -- Hydraulic structures often dominate the behaviour of a drainage network [@Dobson2022-wq;@Thrysoe2019-pi], but are not accounted for by SWMManywhere. We envisage that a machine learning approach may be able to improve identification of structures such as weirs, while elements such as pumps have been incorporated into network synthesis for sanitary networks [@Khurelbaatar2021-sp]. # Acknowledgements From 54c582dad245d7a25e22c8eb50c7a8ba5f99f734 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 6 Nov 2024 15:25:51 +0000 Subject: [PATCH 20/23] Update paper.md --- docs/paper/paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/paper/paper.md b/docs/paper/paper.md index b1edf32a..2dda1a87 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -32,9 +32,9 @@ Urban drainage network models (UDMs) are useful for a variety of purposes, most ## Statement of need -A variety of literature exists to derive UDMs from GIS data, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Chahinian2019-lg;@Reyes-Silva2022-pr;@Chegini2022-oo]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. +A variety of literature exists to derive UDMs from GIS data, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Chahinian2019-lg;@Reyes-Silva2022-pr;@Chegini2022-oo]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. -SWMManywhere is an open-source Python package designed for the global synthesis of urban drainage networks. SWMManywhere integrates publicly available geospatial data and automates data acquisition and preprocessing, reducing the technical burden on users. +SWMManywhere is an open-source Python package designed for the global synthesis of urban drainage networks. SWMManywhere integrates publicly available geospatial data and automates data acquisition and preprocessing, reducing the technical burden on users. ## Features From fe274185479d865e209115341e2736398f43964a Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 6 Nov 2024 15:33:59 +0000 Subject: [PATCH 21/23] Update paper.md --- docs/paper/paper.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 2dda1a87..972ece49 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -34,11 +34,11 @@ Urban drainage network models (UDMs) are useful for a variety of purposes, most A variety of literature exists to derive UDMs from GIS data, producing hydraulically feasible models that closely approximate real-world systems [@Blumensaat2012-hd;@Chahinian2019-lg;@Reyes-Silva2022-pr;@Chegini2022-oo]. We identify some key limitations of these approaches, most notably the lack of automatic data acquisition and preprocessing, that all approaches are closed-source to date, and that a key feature of such an approach should be to facilitate extension and customisation. -SWMManywhere is an open-source Python package designed for the global synthesis of urban drainage networks. SWMManywhere integrates publicly available geospatial data and automates data acquisition and preprocessing, reducing the technical burden on users. +SWMManywhere is an open-source Python package designed for the global synthesis of urban drainage networks. SWMManywhere integrates publicly available geospatial data and automates data acquisition and preprocessing, reducing the technical burden on users. Designed for both researchers and practitioners in urban water management, SWMManywhere responds to the limitations of existing methods by providing an end-to-end, open-source, and customisable solution. ## Features -SWMManywhere includes a variety of key features aimed to improve useability and usefulness. A command line interface (CLI) offers a flexible workflow, providing an accessible entry point to using and customising synthesis. Its parameterized design enables detailed sensitivity analyses, allowing users to understand and manage uncertainties inherent in urban drainage modelling [@Dobson2024-dv]. By emphasizing user control, SWMManywhere allows tuning of outputs with parameters to meet local requirements, making it adaptable to a wide range of scenarios. Designed for both researchers and practitioners in urban water management, SWMManywhere responds to the limitations of existing methods by providing an end-to-end, open-source, and customisable solution. +SWMManywhere includes a variety of key features aimed to improve useability and usefulness. A command line interface (CLI) offers a flexible workflow, providing an accessible entry point to using and customising synthesis. Its parameterized design enables detailed sensitivity analyses, allowing users to understand and manage uncertainties inherent in urban drainage modelling [@Dobson2024-dv]. By emphasizing user control, SWMManywhere allows tuning of outputs with parameters to meet local requirements, making it adaptable to a wide range of scenarios. We provide further details on the data and general approach below. ### Data @@ -64,7 +64,7 @@ We visualise the example from the [extended demonstration](https://imperialcolle ## Outlook -While we believe that SWMManywhere is a useful tool it has a variety of current limitations that present an exciting outlook for future research. A variety of improvements to the overall realism of the approach may be made in the future. For example, +While we believe that SWMManywhere is a useful tool it has a variety of current limitations that present an exciting outlook for future research. Key improvements to the overall realism of the approach may be made in the future, in particular, - Foremost, based on the findings of a sensitivity analysis [@Dobson2024-dv], better identification of manhole locations and outfalls will be critical to narrowing uncertainty in simulation outputs and improving realism. - Capturing the gradual evolution of a network over time is known to be important in UDM synthesis [@Rauch2017-jz], and further illustrated by SWMManywhere results [@Dobson2024-dv]. We do not know of a global database that provides the information that would be necessary to capture this, but it may exist in the future or for local applications. From 2f7b6bcb6644b7a38ce353e72b1a2e2376a0be44 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 6 Nov 2024 15:58:45 +0000 Subject: [PATCH 22/23] Update paper.md --- docs/paper/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 972ece49..f938b7cc 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -66,7 +66,7 @@ We visualise the example from the [extended demonstration](https://imperialcolle While we believe that SWMManywhere is a useful tool it has a variety of current limitations that present an exciting outlook for future research. Key improvements to the overall realism of the approach may be made in the future, in particular, -- Foremost, based on the findings of a sensitivity analysis [@Dobson2024-dv], better identification of manhole locations and outfalls will be critical to narrowing uncertainty in simulation outputs and improving realism. +- Based on the findings of a sensitivity analysis [@Dobson2024-dv], better identification of manhole locations and outfalls will be critical to narrowing uncertainty in simulation outputs and improving realism. - Capturing the gradual evolution of a network over time is known to be important in UDM synthesis [@Rauch2017-jz], and further illustrated by SWMManywhere results [@Dobson2024-dv]. We do not know of a global database that provides the information that would be necessary to capture this, but it may exist in the future or for local applications. # Acknowledgements From 99167e813cfa8eeaa22cc4a3ab373da20a548c92 Mon Sep 17 00:00:00 2001 From: barneydobson Date: Wed, 6 Nov 2024 16:03:44 +0000 Subject: [PATCH 23/23] Update ci_template.yml --- .github/workflows/ci_template.yml | 20 -------------------- 1 file changed, 20 deletions(-) diff --git a/.github/workflows/ci_template.yml b/.github/workflows/ci_template.yml index 3c1871d0..a3c731c2 100644 --- a/.github/workflows/ci_template.yml +++ b/.github/workflows/ci_template.yml @@ -16,26 +16,6 @@ on: type: string jobs: - paper: - runs-on: ubuntu-latest - steps: - - name: Checkout - uses: actions/checkout@v4 - - name: Build draft PDF - uses: openjournals/openjournals-draft-action@master - with: - journal: joss - # This should be the path to the paper within your repo. - paper-path: docs/paper/paper.md - - name: Upload - uses: actions/upload-artifact@v4 - with: - name: paper - # This is the output path where Pandoc will write the compiled - # PDF. Note, this should be the same directory as the input - # paper.md - path: docs/paper/paper.pdf - test: runs-on: ${{ matrix.os }} strategy:

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