Donald H. Burn

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Metamodelling is an increasingly more popular approach for alleviating the computational burden associated with computationally intensive optimization/management problems in environmental and water resources systems. Some studies refer to the metamodelling approach as function approximation, surrogate modelling, response surface methodology or model(More)
A new technique is developed for identifying groups for regional flood frequency analysis. The technique uses a clustering algorithm as a starting point for partitioning the collection of catchments. The groups formed using the clustering algorithm are subsequently revised to improve the regional characteristics based on three requirements that are defined(More)
Reliability, resiliency, and vulnerability criteria are formulated as risk-based performance measures for the evaluation of a real-time reservoir operation model. The reservoir operation model includes a multi-objective compromise programming algorithm to select, in real time, an optimal operating horizon for the reservoir operation. The utility of the(More)
Understanding the hydro-climatological controls on floods is fundamental for estimating flood frequency. The river flood regime is a reflection of a complex catchment hydrological response to flood producing processes. Hence, the catchment similarity in a flood regime is a feasible basis for identifying flood frequency pooling groups used in regional(More)
This paper presents the development of a framework for data collection network design that considers sustainable development goals. The proposed framework adopts sustainable development principles and incorporates and revises traditional methodologies used in data collection network design. Important components of the framework include a focus on(More)
[1] Recent theoretical and empirical studies show that the generalization ability of artificial neural networks can be improved by combining several artificial neural networks in redundant ensembles. In this paper, a review is given of popular ensemble methods. Six approaches for creating artificial neural network ensembles are applied in pooled flood(More)
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