Our researchers work together with researchers from ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale, i.e. the Italian Environmental Agency) and Durham University to develop methods and protocols for monitoring large river systems from remote sensing. We use drones and traditional field techniques (e.g. GPS) to survey local river features (e.g. topography, sediment size, vegetation) and use these data as ground truth for their further detection and monitoring at large scale from the recent Sentinel satellites from Copernicus. Last week we successfully realised the first campaign of data acquisition.
Balancing exploration, uncertainty and computational demands in many objective reservoir optimization: a new paper on Advances in Water Resources
In this paper led by Jazmin Zatarain Salazar and our colleaguea at Cornell, we contribute a diagnostic assessment of state-of-the-art parallel strategies for the auto-adaptive Borg Multi Objective Evolutionary Algorithm (MOEA) to support EMODPS. Our analysis focuses on the Lower Susquehanna River Basin (LSRB) system where multiple sectoral demands from hydropower production, urban water supply, recreation and environmental flows need to be balanced. Using EMODPS with different parallel configurations of the Borg MOEA, we optimize operating policies over different size ensembles of synthetic streamflows and evaporation rates. As we increase the ensemble size, we increase the statistical fidelity of our objective function evaluations at the cost of higher computational demands. This study demonstrates how to overcome the mathematical and computational barriers associated with capturing uncertainties in stochastic multiobjective reservoir control optimization, where parallel algorithmic search serves to reduce the wall-clock time in discovering high quality representations of key operational tradeoffs. Our results show that emerging self-adaptive parallelization schemes exploiting cooperative search populations are crucial. Such strategies provide a promising new set of tools for effectively balancing exploration, uncertainty, and computational demands when using EMODPS.
We just published a new paper on Hydrology and Earth System Science where we explore the operational value of different long term forecast to support farmer cropping decisions. Quantifying this value, however, might not be straightforward as better forecast quality does not necessarily imply better decisions by the end users, especially when forecasts do not reach their final users, when providers are not trusted, or when forecasts are not appropriately understood. In this study, we contribute an assessment framework to evaluate the operational value of W&C services for informing agricultural practices by complementing traditional forecast quality assessments with a coupled human–natural system behavioural model which reproduces farmers’ decisions. This allows a more critical assessment of the forecast value mediated by the end users’ perspective, including farmers’ risk attitudes and behavioural factors. The application to an agricultural area in northern Italy shows that the quality of state-of- the-art W&C services is still limited in predicting the weather and the crop yield of the incoming agricultural season, with ECMWF annual products simulated by the IFS/HOPE model resulting in the most skillful product in the study area. More HERE
A stakeholder meeting has taken place in Lusaka (Zambia) as part of the DAFNE project. We have been meeting with stakeholders from Zambia and Mozambique and developed interactive sessions to explore issues, best practice and pathways to sustainability in the whole Zambezi river basin and the two case studies of the Lunsemfwa and Luia sub-basins. This is the first step to building the DAFNE Negotiation Simulation Lab which will enable stakeholders and decision maker to explore the multidimensional space of water – energy and food nexus in the Zambezi basin. A field trip in the Lunsemfwa based has taken place after the meeting.