Maria Elena Alfano

An Open-Source Python Platform for Integrated Water Resource Management: Exploring the W-E-L-L Nexus

The Integrated Water Resource Management (IWRM) represents a consolidated approach to water handling at basin scale. It allows a comprehensive assessment of the resource, providing detailed information on water availability and balancing it across all the possible uses, such as municipal, industrial, agriculture or energy. However, IWRM solely concentrates on water resources, failing to consider the interconnectedness with other resource systems like energy and agriculture beyond water demand. This narrow focus results in incomplete solutions within water management, overlooking crucial logistical and economic factors. Such oversight undermines the effectiveness of addressing challenges within a complex river basin context and hinders the exploration of more comprehensive and economically viable holistic approaches. An additional aspect commonly overlooked is how basin management is situated within the landscape, understood both as 'natural' and 'anthropogenic' elements. It's not just natural phenomena that shape the landscape mosaic, but also, in a structuring manner, anthropogenic factors, intertwined with complex processes of reciprocal influences.

The aim of my PhD thesis is to present a methodology to quantitatively perform an IWRM at the basin scale, using mathematical models, and to extend it with the Water-Energy-Land-Landscape (WELL) Nexus approach. Specifically, a virtual platform will be developed that will closely link models related to the water side, from hydrological assessment to river basin management, and models related to energy production and land-use (food production, energy use or agriculture). Attention will also be focused on the overall layout of the basin and on the interactions and changes that optimal management entails in the surrounding landscape. The Python-based, open-source platform will have a modular structure: each block represents a model that can be written in different programming languages. All modules will be tightly coupled to one or more blocks using a Python-implemented skeleton, ensuring efficient information flow and accurate representation of how different aspects of the water system interact. The modular approach will allow us to flexibly address specific needs and adapt to future developments. The overall development of the platform will result in a unique tool capable of assessing water resources, taking into account not only water availability, but also the energy and food markets. The platform, which is under continuous development, will be a useful tool for stakeholders and will enable a more optimal and sustainable use of water resources at the river basin level.