A coupled hydrologic-machine learning modelling framework to support hydrologic modelling in river basins under Interbasin Water Transfer regimes

Interbasin Water Transfer (IWT) is often a complex decision-making process that depends on factors ranging from hydro-meteorological conditions to socio-economic pressures. Hydrologic modelling is particularly challenging under these circumstances, requiring accurate quantitative information which may not always be available. This study proposes a methodological framework to simulate IWT flow contributions in the absence of observational data by introducing a coupled machine learning–hydrologic modelling approach. The proposed methodology employs a hydrologic model to simulate the rainfall-runoff process of a watershed, while a machine learning algorithm is used to simulate the decision-making process of IWTs. Methods are illustrated by simulating the hydrologic balance of the Dese-Zero River Basin (DZRB), a highly artificially modified catchment located in North-East Italy. Results suggest the proposed methodological framework can successfully simulate the complex water flow dynamics of the studied watershed and be a useful instrument to support complex scenario analysis under IWTs data scarce conditions.Interbasin Water Transfer (IWT) is often a complex decision-making process that depends on factors ranging from hydro-meteorological conditions to socio-economic pressures. Hydrologic modelling is particularly challenging under these circumstances, requiring accurate quantitative information which may not always be available. This study proposes a methodological framework to simulate IWT flow contributions in the absence of observational data by introducing a coupled machine learning–hydrologic modelling approach. The proposed methodology employs a hydrologic model to simulate the rainfall-runoff process of a watershed, while a machine learning algorithm is used to simulate the decision-making process of IWTs. Methods are illustrated by simulating the hydrologic balance of the Dese-Zero River Basin (DZRB), a highly artificially modified catchment located in North-East Italy. Results suggest the proposed methodological framework can successfully simulate the complex water flow dynamics of the studied watershed and be a useful instrument to support complex scenario analysis under IWTs data scarce conditions

Operationalizing Climate Proofing in Decision/Policy Making

The purpose of this work is to present an operational approach to include consideration of global change drivers (climatic, economic, social, etc.) in support to the design of local policies or investment plans. In both cases decision/policy makers typically have sets of plausible solutions and decisions to be taken in terms of choices among sets of plausible solutions with the best knowledge about the future dynamics of endogenous and exogenous system variables. The ambition is to identify the preferable solution(s) (in terms of technical performances, acceptance by stakeholders, cost–benefit ratio, etc.) in a medium term perspective, (e.g., 10–40 years), with current knowledge about the problem and under the effect of important sources of uncertainty (both aleatory and epistemic). Common to most decision contexts in a medium term perspective typical of both investment decisions and adaptation policies is the prevalence of economic signals in the shorter term and of climatic signals in the longer term. Models play a fundamental role in both cases, but they rarely cover the whole set of variables needed for decision making and the outcomes usually require integration of qualitative expert knowledge or simply subjective judgements. Multi-criteria analysis coupled with uncertainty analysis can contribute with methodologically sound and operational solutions. This paper elaborates on a series of recent cases with the ambition to extract common elements for a general methodological framework

Integration by identification of indicators

The objective of the BRAHMATWINN research component described in this chapter is to develop integrated indicators with relevance to Integrated Water Resources Management (IWRM) and climate change for the Upper Danube and the Upper Brahmaputra River Basins (UDRB and UBRB), and to foster the integration process amongst the different research activities of the project. Such integrated indicators aim at providing stakeholders, NGOs and GOs with an overview of the present state and trends of the river basins water resources, and at quantifying the impacts of possible scenarios and responses to driving forces, as well as pressures from likely climate change. In the process the relevant indicators have been identified by research partners to model and monitor issues relevant for IWRM in the case study areas. The selected indicators have been validated with the information gathered through the NetSyMoD approach (Giupponi et al., 2008) in workshops with local actors. In this way a strong link between the main issues affecting the basins as perceived by local actors and the BRAHMATWINN activities has been created, thus fostering integration between research outcomes and local needs

Reviewing agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability

Working Papers Department of Economics Ca’ Foscari University of Venic

Who is connected with whom? A Social network analysis of institutional interactions in the European CCA and DRR landscape

Communication and collaboration are critical for designing and implementing responses to climate change impacts and related disasters. This acknowledgement has increased interest in understanding social and institutional networks for climate change adaptation (CCA) and disaster risk reduction (DRR). In this study, we used Social Network Analysis (SNA) to explore institutional interactions within and across the communities of the aforementioned domains in Europe. Firstly, we investigated the type and intensity of interactions. We calculated SNA metrics to assess the roles of different actors and applied cluster analysis to identify actors with similar patterns of connections. SNA showed that communication is often more intensive within the two communities, while collaboration is frequent around topics related to both CCA and DRR. Cluster analysis revealed that actors tied with DRR were more closely connected, while actors tied with CCA and those with mixed connections showed no obvious clustering affnity. The European Climate Adaptation Platform, Climate-ADAPT, had the highest value for various SNA metrics, reflecting its popularity in the network and its potential for enhancing interactions among its actors. Finally, SNA was complemented by qualitative interviews, which emphasised the importance of connecting CCA and DRR in organisational mission and vision statements

Construction of a Bayesian Network for the Assessment of Agri-Environmental Measures – The Case Study of the Venice Lagoon Watershed

A methodological framework was designed to assess the effectiveness of agri-environmental policy measures adopted by the Veneto Region to reduce diffuse water pollution of agricultural origin. Two already existing methodologies were combined in a new flexible approach for policy assessment: Conceptual Modelling and Bayesian Networks (BNs). The former supported the development of a shared conceptual model (a cognitive map) of the agro-ecosystem of the study area; while the latter allowed the development of a probabilistic model coherent with the cognitive map. BNs were selected because they allow analyses with scarce data; they can be updated when further information becomes available, and are easily understandable by layperson. The paper reports the results obtained in the Venice Lagoon Watershed (VLW) case study, where the current agri-environmental measures were assessed in order to identify their effectiveness in terms of reduction of nitrogen releases in water bodies connected to the lagoon ecosystem. Preliminary results obtained by implementing expert opinions in the BN pointed out the likely limited effects of the measures on the declared objective o