A framework for the quantitative assessment of climate change impacts on water-related activities at the basin scale

• Main Authors: D. Anghileri, F. Pianosi, R. Soncini-Sessa
• Format: Article
• Language: English
• Published: Copernicus Publications 2011-06-01
• Series: Hydrology and Earth System Sciences
• Online Access: http://www.hydrol-earth-syst-sci.net/15/2025/2011/hess-15-2025-2011.pdf

While quantitative assessment of the climate change impact on hydrology at the basin scale is quite addressed in the literature, extension of quantitative analysis to impact on the ecological, economic and social sphere is still limited, although well recognized as a key issue to support water resource planning and promote public participation. In this paper we propose a framework for assessing climate change impact on water-related activities at the basin scale. The specific features of our approach are that: (i) the impact quantification is based on a set of performance indicators defined together with the stakeholders, thus explicitly taking into account the water-users preferences; (ii) the management policies are obtained by optimal control techniques, linking stakeholder expectations and decision-making; (iii) the multi-objective nature of the management problem is fully preserved by simulating a set of Pareto-optimal management policies, which allows for evaluating not only variations in the indicator values but also tradeoffs among conflicting objectives. The framework is demonstrated by application to a real world case study, Lake Como basin (Italy). We show that the most conflicting water-related activities within the basin (i.e. hydropower production and agriculture) are likely to be negatively impacted by climate change. We discuss the robustness of the estimated impacts to the climate natural variability and the approximations in modeling the physical system and the socio-economic system, and perform an uncertainty analysis of several sources of uncertainty. We demonstrate that the contribution of natural climate uncertainty is rather remarkable and that, among different modelling uncertainty sources, the one from climate modeling is very significant.