Products - Systems Analysis Tools
This package of systems analysis tools includes desktop applications for implementing simulation, optimization and multi-objective analisis. The package is developed as part of the "Managing Water Resources-Matehods and Applications for a Systems Approach" textbook. The state-of-the-art simulation software Vensim PLE (Personal Learning Edition) is enclosed for the implementation of system dynamics simulation. This program was developed by Ventana Systems, which has kindly given permission for its use in this context. It can be dowloaded directly from the Ventana web site. The Systems Analysis Tools package includes seven more original computer programs developed in the user-friendly Windows environment. They are:
- LINPRO - a linear programming optimization tool;
- FUZZYLINPRO - a program for the implementation of fuzzy linear programming optimization;
- EVOLPRO - for the implementation of evolutionary optimization;
- COMPRO - for the implementation of the deterministic multi-objective analysis tool of compromise programming;
- FUZZYCOMPRO - which implements fuzzy compromise programming, for multi-objective analysis under uncertainty;
- FUZZYCOMPROGDM - for the support of group decision making using fuzzy compromise programming under uncertainty;
- SUSTAINPRO - a package of four programs for the computation of fairness, risk, reversibility and consensus sustainability criteria. You can download all the programs from this web site - go to the book page and select software.
Each program is presented in the same way, with:
- a read.me file with installation instructions;
- a folder containing the main program files;
- a folder containing all the examples presented in the textbook.
Vensim PLE is accompanied with a short tutorial developed by Craig W. Kirkwood, of Arizona State University. I am grateful to the author for permission to provide it here. The other seven programs have very extensive help manuals, which are integrated into the Windows environment. These provide detailed instructions on program use, data preparation, data import and interpretation of the results.
Products - ANEMI
ANEMI, Greek word for winds of change, is an integrated society-biosphere-climate model. It represents an alternative approach to understanding, mitigating, and adapting to global change. It consists of nine individual sectors that reproduce the main characteristics of the climate, carbon cycle, economy, land use, population, surface water flow, and water demand and water quality.
The model operates on a global scale, and explores the manner in which interactions, or feedbacks, between different subsystems determine the behaviour of the whole Earth-system. Several of the sectors build on previous integrated assessment modelling work, but their manner of integration is novel, as are the water sectors in particular. The work is timely, as recognition grows of the importance of nonlinearity, delays, and feedbacks in determining long-term Earth-system behaviour.
ANEMI is composed of the following 11 sectors:
- Hydrologic Cycle
- Water Demand
- Water Supply Development
- Nutrient Cycles
- Food Production
- Greenhouse Gases
- Land Use
Details are available in Breach, P.A., and S.P. Simonovic, (2020) "ANEMI3 - Tool for Investigating Impacts of Global Change", the Water Resources Research Report no.108 Facility for Intelligent Decision Support, Department of Civil and Environmental Engineering, Western University, London, Ontario, Canada, 264 pages. ISBN:.
The ANEMI3 model is available in the "ANEMI" GitHub repository as a Vensim model file titled "ANEMI3.mdl". This file can be opened using the Vensim software in order to view the model structure. A free Vensim PLE licence can be used to view the stock and flow diagram that makes up the model structure. Due to the advanced features used in the ANEMI3 model, a Vensim DSS license is required to run the model.
Products - Climate Downscaling Tools
Climate downscaling is the process of translating coarse gridded global climate datasets to local and regional scales. These tools are used to downscale Global Climate Model (GCM) data for use in climate change impact analyses on water resources management. Examples include: (i) Floodplain mapping; (ii) Reservoir operation; (iii) Flow-frequency analysis; (iv) Urban infrastructure resilience; and others.
Three statistical downscaling tools have been developed by my research group. They are:
- KNN-CADv4 - non-parametric multi-site weather generator that is able to preserve spatial and temporal correlation through sampling all sites together using a "block-bootstrap" approach. Details are available in King, L., A. I. McLeod and S. P. Simonovic, (2015) "Improved weather generator algorithm for multisite simulation of precipitation and temperature", Journal of the American Water Resources Association, 51(5):1305-1320.
- Maximum Entropy Bootstrap - non-parametric weather generator that uses random sampling from empirical cumulative distribution functions while preserving the temporal dependence structure of the historical climate series. Details are available in Srivastav, R. and S.P. Simonovic, (2015) "Multi-site, multivariate weather generator using maximum entropy bootstrap", Climate Dynamics, 44(11):3431-3438.
- Beta Regression - regression-based multi-site downscaling model that builds relationships between local historical precipitation and global climate variables to estimate future precipitation. Details are available in Mandal, S., R. K. Srivastav, and S.P. Simonovic, (2016) "Use of Beta Regression for Statistical Downscaling of Precipitation in the Campbell River Basin, British Columbia, Canada", Journal of Hydrology, 538:49-62.
All tools (computer code, example data, and instructions) are available on the GitHub platform free of charge.
Products - IDF_CC
IDF_CC is a web-based intensity-duration-frequency tool to update and adapt local extreme rainfall statistics to climate change. Anyone can access and use the tool free of charge, including water managers, municipal infrastructure professionals, provincial and federal government agencies, researchers, consultants and non-profit groups. The IDF_CC tool is pre-loaded with approximately 700 Environment Canada rain stations. Users can select any rain station that has 10 or more years of data and develop IDF curves based on historical data and curves that are adjusted to reflect climate change. Results can be generated for a future time period up to the year 2100 based on 18 Global Climate Model datasets that simulate various climate conditions to local rainfall data and three future climate scenarios ranging from low to high severity (RCP2.6, RCP4.5 and RCP8.5). Users can generate results for either pre-loaded Environment Canada rain stations or for user-created rain stations.
Intensity-duration-frequency (IDF) curves provide information on how often extreme rainfall events of various durations and intensities occur. Water-related infrastructure in Canada relies on IDF curves for planning, design, operation and maintenance. Climate change will result in increasing frequency and intensity of extreme rainfall events, yet IDF curves currently in use across Canada do not account for these impacts. As a result, infrastructure built today will not be able to accommodate future extreme rainfall conditions, resulting in increased risk of failure.
The rainfall "Intensity-Duration-Frequency under Climate Change" (IDF_CC) tool has been designed to address this gap. The Tool assists water management professionals to easily and quickly assess potential impacts of climate change on IDF curves at a local level, because it uses data from almost any rain monitoring station in Canada.
After selecting a rain station of interest, users can view information on that rain station, including the length of the data record. To create IDF curves for future climate change conditions, users can select a n-year projection period for any time between 2006 to 2100, followed by one or multiple GCM or GCM ensemble options. After selecting these options, the tool will automatically downscale GCM results and apply GCM results to the local rain station data, providing future IDF curves in table or graphical format and allowing the user to compare the impacts of multiple RCP scenarios and rainfall return periods, and to compare historical IDF curves to these updated curves.
Version 3, which has been available from Septmeber 2018, introduces a new dataset of IDF curves for ungauged locations in Canada.Users are able to obtain IDF curves for any location in the country with the new module.The Technical and User Manuals (can be downloaded from the tool's website) provide details on changes and new features introduced in Version 3. In addition, version 3 of the tool includes a new set of climate models and utilizes GEV distribution in the development of IDF curves.
The tool is in public domain and can be accessed at www.idf-cc-uwo.ca. Details are available in multiple publications and are all available upon request as well as from this web site (visit publications page) and the website of the tool. Users are strongly encouraged to share their comments and questions with the development team. User feedback will directly contribute to the improvement of Version 3 of the tool.
Products - ResilSIM
ResilSIM is a web-based decision support tool that rapidly estimates the resilience (a modern disaster management measure that is dynamic in time and space) of an urban system to the consequences of natural disasters. The web-based tool (with mobile access) operates in near real-time. It is designed to assist decision makers in selecting the best options for integrating adaptive capacity into their communities to protect against the negative impacts of a hazard. ResilSIM is developed for application in Toronto and London, Ontario, Canada.
A key feature of the tool is its use of freely available datasets to calculate the resilience metric. To represent the physical component of the urban system, shape-files containing engineering infrastructure, critical facilities (hospitals, schools, ambulance, fire and police stations) and other buildings (commercial, industrial, and residential economic sectors) are used. This type of data is often provided by the local, municipal government. Socioeconomic data include the vulnerable population based on age, marital status, residency, language, education and income as well as certain physical datasets. In Canada, demographic information is available through a census program. It is ideal for datasets to be complete and consistently generated/collected across a large area (such as a country) so that the tool can be more easily transferrable between urban systems. The methodological framework together with the ResilSIM DSS architecture will remain the same for all applications.
ResilSIM operates by simulating a hydro-meteorological hazard in the urban system under investigation using flood inundation maps and subsequently calculates an initial value of resilience inresponse to the disturbance. The tool offers a sample list of measures for adaptive capacity that can be applied to improve system resilience. The user can select adaptation options to be implemented virtually and observe how the resilience is impacted. After the adaptation option(s) has/have been integrated into the urban system, resilience is rapidly re-calculated and compared to its initial value, serving as a basis for comparison for potential combinations of community upgrades.
Overall, ResilSIM enables users to quickly make decisions that can reduce the physical, socioeconomic consequences of a disturbance. These include damages to the built and natural environments as well as the danger posed to human welfare. Details are available in Irwin, S., A. Schardong, S.P. Simonovic, and N. Nirupama, (2016) "ResilSIM - A Decision Support Tool for Estimating Resilience of Urban Systems", Water - special issue Hydroinformatics and Urban Water Systems, 8(377):1-25.
The tool is in public domain and can be accessed at www.resilsim-uwo.ca.
Continuous research on the application of resilience criteria in urban disaster managment resulted in a new product ResilSIMt which offers much more general tool that can be applied with multiple disasters of different types and consider cascading effects of the disasters on the connected infrastructure systems. Users of the new tool can choose adaptation measures and in this way make very wide application of resilience concept in urban disaster management. The database of the tool includes City of Toronto infrastructure.
The tool is in public domain and can be accessed at www.resilsimt-uwo.ca.