Robust and transparent planning and operation of water resource infrastructure

稳健、透明的水资源基础设施规划和运营

基本信息

批准号：
EP/R007330/1
负责人：
Francesca Pianosi
金额：
$ 92.13万
依托单位：
University of Bristol
依托单位国家：
英国
项目类别：
Fellowship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FR007330%2F1
关键词：
Robust transparent planning operation water

项目摘要

Ensuring a reliable and safe supply of water is essential for the socioeconomic and environmental sustainability of our society. In the UK, several water companies are responsible for supplying clean water to industrial and domestic users in different parts of the country. Water companies need to estimate what the water demand and the available resource will be in the future (typically over a 25-years ahead period) so to be able to plan infrastructure development (for example, building a new reservoir) or changes in their management (for example, reducing or increasing river abstractions that feed into an existing reservoir) wherever they anticipate a gap between demand and supply.Making decisions is becoming increasingly complex in the fast-changing world we live in. On the supply side, extreme events such as floods and droughts are becoming more frequent and unpredictable under the combined effect of climate and land-use change. On the demand side, water demand is also becoming more variable due to changes in population density and distribution, changing life-style and socioeconomic conditions, and technological developments (for example, the introduction of smart water meters), which all together may affect water consumption in different ways in different places.To tackle all these complexities, the water industry needs to adopt innovative, flexible and adaptive planning and management solutions, which will increase the efficiency and resilience of water systems while avoiding raising costs. Mathematical models can provide a vital contribution to this end. By reproducing the behavior of the main components of a water resource system (such as reservoirs, pumping stations, treatment plants, etc.) and their connections among each other and with the natural environment, mathematical models enable water practitioners to predict the key system variables (for example, the future storage levels in a reservoir, the amount of energy consumed for pumping, the supply rate of clean water to a group of domestic users) and to simulate the system response under different infrastructural/management scenarios.The use of mathematical models in the water industry has increased in recent years, however their adoption is still relatively limited with respect to their potential. A key challenge water resource practitioners face is in recognising the uncertainty and errors that unavoidably affect all model predictions while still extracting useful information from them. A great opportunity that they are offered today, is to extract more and more useful information from fast growing sensing and computing technology, for example satellite data, smart sensors and high-performance computers. In this research project, I aim to tackle the uncertainty challenge and take the IT opportunity to develop the next-generation modelling tools that will support more sustainable water resource management in the UK.This project will develop mathematical methods and software tools to assist water system managers in their day-to-day decisions (for example, how much water to abstract from a river or a reservoir, how much water to pump to a treatment plant, etc.) as well as long-term decisions (for example, whether to build a new reservoir or connect existing ones) by finding "low-regret" solutions that would prove effective across a range of possible futures. All methods will be developed and tested on case study applications provided by water companies, so to ensure that they are actually valuable to address the most urgent issues they face, and they will be implemented in open-source software packages so that also other water practitioners besides those directly involved in the project will benefit from its findings and outputs.

确保可靠和安全的供水对于我们社会的社会经济和环境可持续性至关重要。在英国，多家自来水公司负责向全国不同地区的工业和家庭用户提供清洁水。自来水公司需要估计未来（通常是未来 25 年）的用水需求和可用资源，以便能够规划基础设施开发（例如，建造新水库）或管理变革（例如，减少或增加注入现有水库的河流取水量）无论何时他们预计需求和供应之间存在差距。在我们生活的快速变化的世界中，决策变得越来越复杂。在供应方面，诸如此类的极端事件随着洪水和干旱变得越来越频繁在气候和土地利用变化的综合影响下，这种变化是不可预测的。在需求方面，由于人口密度和分布的变化、生活方式和社会经济条件的变化以及技术的发展（例如智能水表的引入），水需求也变得更加多变，所有这些都可能影响水为了解决所有这些复杂问题，水务行业需要采用创新、灵活和适应性强的规划和管理解决方案，这将提高水系统的效率和弹性，同时避免成本上升。数学模型可以为此做出重要贡献。通过再现水资源系统主要组成部分（如水库、泵站、处理厂等）的行为及其相互之间以及与自然环境的联系，数学模型使水务从业者能够预测关键系统变量（例如，水库未来的蓄水量、抽水消耗的能量、向一组家庭用户提供清洁水的供应率）并模拟不同基础设施/管理场景下的系统响应。使用数学近年来水行业的型号有所增加然而，就其潜力而言，它们的采用仍然相对有限。水资源从业者面临的一个关键挑战是认识到不可避免地影响所有模型预测的不确定性和错误，同时仍从中提取有用的信息。如今，他们面临的一个绝佳机会是从快速发展的传感和计算技术（例如卫星数据、智能传感器和高性能计算机）中提取越来越多有用的信息。在这个研究项目中，我的目标是应对不确定性挑战，并利用 IT 机会开发下一代建模工具，以支持英国更可持续的水资源管理。该项目将开发数学方法和软件工具来协助水系统管理人员的日常决策（例如，从河流或水库抽取多少水、向处理厂抽多少水等）以及长期决策（例如，是否建造一个新的水库或连接现有的水库）通过寻找“低遗憾”的解决方案将在一系列可能的未来中证明是有效的。所有方法都将在水公司提供的案例研究应用程序上进行开发和测试，以确保它们对于解决他们面临的最紧迫的问题确实有价值，并且它们将在开源软件包中实施，以便其他水从业者此外，那些直接参与该项目的人也将从其研究结果和成果中受益。