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.

确保可靠且安全的水供应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，几家水公司负责向该国不同地区的工业和国内用户提供清洁的水。水公司需要估计未来的水需求和可用资源将是什么（通常是在25年的提前期间），以便能够计划基础设施的开发（例如，建立新的储层）或管理层的变化（例如，将河流抽象降低或增加河流抽象，以供应现有的储藏室，无论是在供应中都可以在何处进行供应。供应方面，在气候和土地利用变化的综合效果下，洪水和干旱等极端事件变得越来越频繁和不可预测。 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费用。数学模型可以为这一目标提供重要的贡献。通过重现水资源系统主要组成部分（例如储层，泵站，处理厂等）及其之间的连接及其与自然环境之间的连接，数学模型使水从业人员能够预测关键系统变量（例如，在供应量中，供应速率的供应速率，供应速率，供应速率，供应速率，泵送的量，泵送的量，供应量，供应量，供应量，供应量，供应量，供应量，供应量，泵送量的供应速率，一组供应速率，供应速率，泵送量的供应量基础设施/管理方案。近年来水产行业中数学模型的使用有所增加，但是在其潜力方面，其采用仍然相对有限。水资源从业人员面临的关键挑战是认识到不可避免地会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。他们今天提供的一个很好的机会是从快速增长的传感和计算技术中提取越来越多的有用信息，例如卫星数据，智能传感器和高性能计算机。在该研究项目中，我旨在应对不确定性挑战，并抓住IT机会来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，以帮助水系统管理人员在日常决策中协助水系统管理员（例如通过查找“低重新质量”解决方案，可以在许多可能的未来中有效，将现有的储层或连接现有的储层。所有方法都将在水公司提供的案例研究应用程序上开发和测试，以确保它们实际上是有价值的，可以解决他们面临的最紧急问题，并且它们将在开源软件包中实施，以便除了直接参与该项目的其他供水者还将从其发现和产出中受益。