Predicting Multiple Functions of Sustainable Flood Retention Basins under Uncertainty via Multi-Instance Multi-Label Learning

Abstract

Abstract:The ambiguity of diverse functions of sustainable flood retention basins (SFRBs) may lead to conflict and risk in water resources planning and management. How can someone provide an intuitive yet efficient strategy to uncover and distinguish the multiple potential functions of SFRBs under uncertainty? In this study, by exploiting both input and output uncertainties of SFRBs, the authors developed a new data-driven framework to automatically predict the multiple functions of SFRBs by using multi-instance multi-label (MIML) learning. A total of 372 sustainable flood retention basins, characterized by 40 variables associated with confidence levels, were surveyed in Scotland, UK. A Gaussian model with Monte Carlo sampling was used to capture the variability of variables (i.e., input OPEN ACCESSWater 2015, 7 1360 uncertainty), and the MIML-support vector machine (SVM) algorithm was subsequently applied to predict the potential functions of SFRBs that have not yet been assessed, allowing for one basin belonging to different types (i.e., output uncertainty). Experiments demonstrated that the proposed approach enables effective automatic prediction of the potential functions of SFRBs (e.g., accuracy >93%). The findings suggest that the functional uncertainty of SFRBs under investigation can be better assessed in a more comprehensive and cost-effective way, and the proposed data-driven approach provides a promising method of doing so for water resources management.

Chance-Constrained Dynamic Programming for Multiple Water Resources Allocation Management Associated with Risk-Aversion Analysis: A Case Study of Beijing, China

“…The amount of different water sources in different seasons can be expressed by Gaussian distribution S ti ∼ N µ ti , σ 2 ti ) . The total water amount is the state variable.…”

“…Simultaneously, water shortage has seriously hindered the sustainable development of the Primary, Secondary, and Tertiary industry, which would pose a threat to social security and stability. In addition, there are still a variety of uncertainties existing in the water resources management system, such as available water amount, water consumption, multiple water sources, water conflicted users, and technical-economic parameters [2]. These uncertain factors could be an obstacle to the formulation of rational water resources utilization, and lead to conflict-laden water allocation among multiple competing users [3].…”