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2020
Tuesday, September 15th
10:40 AM

Smart Climate Hydropower Tool: A web-cloud-based climate service for supporting decision-making in hydropower production

Arthur Essenfelder, CMCC@Ca'Foscari, Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici e Università Ca' Foscari di Venezia

10:40 AM - 11:00 AM

Smart Climate Hydropower Tool (SCHT, part of the H2020 project "CLARA - Climate forecast enabled knowledge service") is an innovative web-cloud-based climate service that makes use of a set of machine learning methods for supporting decision-making in a context of hydropower production. Although highly flexible and with low costs to power ratio, estimates of future hydropower production are strictly linked with the ability to forecast meteorological conditions. Even if tangible results using physically-based (e.g. Collischonn, et al., 2007; Fan, et al., 2015) or machine learning (e.g. Callegari, et al., 2015; De Gregorio et. al 2017) have been achieved, challenges remain for seasonal lead-times and rainfall dominated catchments. Here, we propose a hybrid forecast system by using a combination of physically-based seasonal forecasts (provided by state-of-art seasonal forecasts of meteorological data from the Copernicus Climate Data Store), with a set of different machine learning algorithms (support vector regression – SVD, Gaussian processes – GP, long short-term memory – LSTM, and recursive neural networks – RNN). We test the application of the different machine learning techniques for forecasting seasonal river discharges up to six months in advance for two catchments in Colombia, South America. Seasonal forecasts are performed by making use of available state-of-art seasonal forecasts of meteorological data provided by the Copernicus Climate Data Store (CDS). Each algorithm is trained over past decades datasets of recorded data, and forecast performances are validated and evaluated using separate test sets with reference to benchmarks (historical average of discharge values and simpler multiparametric regressions). Final results are then presented to the users through a user-friendly web interface. The web interface is the result of a tied connection with end-users in an effective co-design process, adding value to energy forecasts and ideally paving the road for highly scalability and replicability (e.g. development of similar services worldwide).

12:20 PM

Complex Hydro-policy Modeling with RiverWare for Collaborative Multi-objective River System and Hydropower Planning and Operations

Mitch Clement, University of Colorado Boulder, Center for Advanced Decision Support for Water and Environmental Systems

12:20 PM - 12:40 PM

5:40 PM

A Simplified Approach to Automatically Build and Evaluate Urban Hydrology and Green Infrastructure at the Municipal Scale Using SWMM

Tyler Dell, Colorado State University, USA

5:40 PM - 6:00 PM

Using available urban stormwater management models can be a complicated task for untrained users or in municipalities without a robust GIS/modelling program. However, many municipalities are still faced with the task of evaluating how urbanization and current green infrastructure programs will impact urban drainage systems as well as the hydrologic water balance. As a result, there is a need to be able to build and evaluate a simple urban hydrology model at the municipal scale particularly for the evaluation of green infrastructure. In this study, to reduce the barriers of developing a complete stormwater management model (SWMM) model, a procedure for creating a simplified SWMM model was developed. The simplified model was corroborated with a complete SWMM model and National stormwater calculator for an urban area located in south-east of Fort Collins, Colorado. The modelling approach considered three scenarios with different amounts and types of green infrastructure consistent across all three models. The first scenario involved a baseline scenario of the current catchment condition and two additional scenarios simulated the implementation of combinations of green infrastructure. Continuous simulations were ran using local climate data for a 35-year period. The models also were tested against design storms. A probabilistic approach was used to determine the sensitivity and uncertainty of the simplified model in comparison to the complete SWMM model and National stormwater calculator results. Overall, results showed a strong agreement between the developed simplified version and the complete SWMM model. The approach was adopted into an online urban hydrology tool to automate the generation and evaluation of SWMM models for any area within the United States to improve decision making.

6:00 PM

Peddling Influence: Estimating the Impact of Lobbying on Congressional Voting Behavior and Environmental Policy

Gautam Sethi, Bard College, United States

6:00 PM - 6:20 PM

Recent congressional policy outcomes on fossil fuel regulation do not reflect any urgency to curb CO2 emissions. One reason why the United States Congress has failed to enact meaningful policy to address climate change is that the fossil fuel industry, through hefty campaign contributions, is able to influence legislators to vote against environmental interests. Building off existing econometric research, we estimate the influence of oil and gas contributions on voting behavior of House members on 157 bills between the 107th-114th Congresses. Our results show a significant relationship between oil and gas contributions and anti-environment voting behavior, indicating that the probability of a legislator to vote against the environment increases as the proportion of total amount raised from oil and gas interests increases. We also find that ideological moderates and legislators from competitive districts are more susceptible to influence from fossil fuels, and that moderate and vulnerable Democrats are more susceptible to fossil fuel influence than Republicans. These results suggest that basic campaign finance laws fail to sufficiently prevent oil and gas interests from influencing environmental policy outcomes. Based on these results, we propose a bold and comprehensive approach to disrupt and prevent the undue influence of special interests on our political system. We recommend scaling up existing municipal programs aimed at enhancing small-dollar donations, holding candidates who pledge to reject special interest money accountable through institutionalized enforcement mechanisms, and using community organizing to transform campaign finance systems at the local and state level.

Wednesday, September 16th
8:20 AM

Using Game Technology to Engage Citizens and Quantify the Public Acceptability of Air Quality Interventions

Enda Hayes, Uni of the West of England, UK

8:20 AM - 8:40 AM

Ambient air pollution has as significant impact on public health and was responsible for more than 4.2 million premature deaths annually worldwide. It is within our cities where this public health impact is most acute as high population densities and elevated ambient pollution concentrations result in an increased risk of exposure. This health impact is further exacerbated as air pollution interacts with other social determinants of health creating a disproportionate risk and burden especially for vulnerable communities. Traditional approaches to public engagement on this issue has resulted in a general apathy among citizens as they cannot connect the scale of the air pollution problem with their daily social behaviours, practices and activities and subsequently there is a public lack of ownership of the problem and solutions. The EU Horizon 2020 funded ClairCity Project (www.claircity.eu) developed the Skylines Game App which utilises game technology to engage citizens and create a shift in the public understanding towards the causes of poor air quality while ‘crowd-sourcing’ public perceptions and capturing the acceptability of air pollution and carbon reduction policies. The design and implementation of the Skyline Game is described and the case study data for >2500 players across six European cities is analysed to better understand what influences citizen decision-making (e.g. health, environment, economy, personal satisfaction) and enable a scenario creation process with citizen at the centre and empowered to visualise clean, low carbon, healthy futures for their city.

10:00 AM

End-of-life management of rooftop solar photovoltaic: A system dynamics approach

Hengky Salim, Griffith University, Australia, School of Engineering and Built Environment, Griffith University, Australia

10:00 AM - 6:20 PM

11:00 AM

Comprehensive Uncertainty Assessment in Modelling, Elicitation of Stakeholder Preferences, and Decision Support

Peter Reichert, Eawag, Switzerland

11:00 AM - 6:20 PM

The current practice of uncertainty quantification in environmental decision support is incomplete by not covering all sources of uncertainty. In particular, typically used parameterizations of value functions that quantify preferences of stakeholders are insufficiently flexible to describe stakeholder preferences, the uncertainty of stakeholder opinions and of aggregated “societal preferences” are usually not quantified, and the sensitivity regarding prior assumptions in modelling of the outcomes of decision alternatives as well as on elicited preferences is usually not investigated. In this presentation, the attempt will be made to demonstrate how uncertainty can be considered more comprehensively in environmental decision support. In particular, the points mentioned above will be addressed by showing how more flexible parameterizations can be fitted to elicitation data, how the uncertainty of elicited preferences can be estimated and considered in the decision support process, and how ambiguity about prior distributions can be considered. The methodological approach is based on “expected expected utility theory” that extends expected utility theory to the consideration of uncertain preferences, and on imprecise, intersubjective Bayesian probabilities. The theoretical considerations will be illustrated by examples from water management in Switzerland and recent methodological research.

Thursday, September 17th
11:00 AM

Towards identification of pathways to more transformative adaptation strategies for adoption of new innovative agricultural techniques: The case of Makanya catchment, Tanzania

Hellen Aluku, Vrije Universiteit Brussel, VUB

11:00 AM - 11:20 AM

11:20 AM

Coupling Models and Narrative in Support of Decision Making

Kristy Bryden, Iowa State University, United States

11:20 AM - 11:40 AM

1:20 PM

A multiscale geospatial decision support system for sustainable land management: the LANSUPPORT project

Fabio Terribile, University of Naples Federico II, Italy

1:20 PM - 1:40 PM

Geo-Spatial Decision Support Systems (S-DSSs) are becoming increasingly popular since they provide operational tools to a large community of end-users and policy-makers for multiscale land planning and management. Moreover, they promise to better connect scientists and end-users over landscapes management (e.g. farmers and planners). In this context, the H2020 LandSupport project (https://www.landsupport.eu) aims at i) supporting sustainable agriculture and forestry, ii) evaluating trade-off between different land uses and iii) contributing to the development and implementation of land use policies in Europe. More than 100 operational tools are going to be implemented in a Web-based Land S-DSS, built on a smart geospatial cyberinfrastructure, to pursue a set of innovative scientific, technical and land policy-oriented specific objectives. In particular, there will be included models for the simulation of agroecosystems management on crop productivity, land degradation, environment-related variables (e.g. land take and pollutants transport) under current and future climate scenarios. The integrated models will also allow for the evaluation of climate change resilience (e.g. LULUCF models), ecosystem services, and socio-economic aspects. These will rely on both the rasdaman datacube technology and COMPSs framework for parallel workflows of modelling units. EO maps and products from the Copernicus Sentinel satellites will be also delivered, enabling a continuous monitoring of highly dynamic land surface variables and providing vegetation biophysical variables. A data service platform, with integrated handling of raster, vector and meta data, including query APIs, will manage the data and will enable easy-to-use exploration and analysis capabilities. As all these are based on open standards, freely available clients can be employed for accessing the LandSupport service. The spatial scale spans from European level to national and regional/ local scale – in Italy, Hungary and Austria – with additional pilot sites (e.g. Tunisia), to evaluate LANDSUPPORT tools in very different physical, socio-economic and cultural settings.