A water resource simulator in Python. (April 2020)

• Record Type: Journal Article
• Authors: Tomlinson, J.E.; Arnott, J.H.; Harou, J.J.
• Is Part Of: Environmental modelling & software. Volume 126(2020)
• Publication Date: 2020-04
• Subjects: Water resource simulation -- Network optimisation -- Open source -- Python -- Multi-reservoir operations -- Decision making under deep uncertainty; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104635
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: A new generalised water resource network modelling Python library, Pywr, is presented. Given hydrological inflows, Pywr simulates customisable water allocation and operation rules throughout complex multi-purpose managed water systems at each user-defined time-step. The model uses a low-level interface to existing linear programming solvers for fast priority-based optimisation-driven simulation. The library uses an object based system for users to provide input data and record simulation outputs. A novel multi-scenario simulation method provides an almost 4-fold improvement in model run-times and supports calculating robustness metrics across scenarios. A flexible interface to specify multi-objective optimisation formulations as part of a model's input file is included. These features enable analysts to apply advanced water planning approaches, such as robust decision making and robust optimisation, to real systems. The library is available under the GPLv3 open source licence, includes several examples and a regression test suite. Highlights: We present an open source water resources simulation library written in Python. Includes multi-scenario simulation for the application of robust decision making. Enables the use of multi-objective optimisation. Uses an extensible component based input–output system.