Search Results - "Solomatine, D."

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions by Maier, H.R., Kapelan, Z., Kasprzyk, J., Kollat, J., Matott, L.S., Cunha, M.C., Dandy, G.C., Gibbs, M.S., Keedwell, E., Marchi, A., Ostfeld, A., Savic, D., Solomatine, D.P., Vrugt, J.A., Zecchin, A.C., Minsker, B.S., Barbour, E.J., Kuczera, G., Pasha, F., Castelletti, A., Giuliani, M., Reed, P.M.

“…The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active…”
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River cross-section extraction from the ASTER global DEM for flood modeling by Gichamo, T.Z., Popescu, I., Jonoski, A., Solomatine, D.

“…An approach to generate river cross-sections from the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER…”
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Assessing the impact of different sources of topographic data on 1-D hydraulic modelling of floods by Md Ali, A, Solomatine, D. P, Di Baldassarre, G

“…Topographic data, such as digital elevation models (DEMs), are essential input in flood inundation modelling. DEMs can be derived from several sources either…”
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Estimation of predictive hydrologic uncertainty using the quantile regression and UNEEC methods and their comparison on contrasting catchments by Dogulu, N, López López, P, Solomatine, D. P, Weerts, A. H, Shrestha, D. L

“…In operational hydrology, estimation of the predictive uncertainty of hydrological models used for flood modelling is essential for risk-based decision making…”
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Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 1: Concepts and methodology by Elshorbagy, A, Corzo, G, Srinivasulu, S, Solomatine, D P

“…A comprehensive data driven modeling experiment is presented in a two-part paper. In this first part, an extensive data-driven modeling experiment is proposed…”
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Multiobjective Direct Policy Search Using Physically Based Operating Rules in Multireservoir Systems by Ritter, J, Corzo, G, Solomatine, D. P, Angarita, H

“…AbstractThis study explores the ways to introduce physical interpretability into the process of optimizing operating rules for multireservoir systems with…”
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Experiments with AdaBoost.RT, an improved boosting scheme for regression by Shrestha, D L, Solomatine, D P

“…The application of boosting technique to regression problems has received relatively little attention in contrast to research aimed at classification problems…”
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Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application by Elshorbagy, A., Corzo, G., Srinivasulu, S., Solomatine, D. P.

“…In this second part of the two-part paper, the data driven modeling (DDM) experiment, presented and explained in the first part, is implemented. Inputs for the…”
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A Spatially Enhanced Data‐Driven Multimodel to Improve Semiseasonal Groundwater Forecasts in the High Plains Aquifer, USA by Amaranto, A., Munoz‐Arriola, F., Solomatine, D. P., Corzo, G.

“…The aim of this paper is to improve semiseasonal forecast of groundwater availability in response to climate variables, surface water availability, groundwater…”
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Machine Learning Approach to Modeling Sediment Transport by Bhattacharya, B, Price, R. K, Solomatine, D. P

“…Inaccuracies of sediment transport models largely originate from our limitation to describe the process in precise mathematical terms. Machine learning (ML) is…”
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A study of the climate change impacts on fluvial flood propagation in the Vietnamese Mekong Delta by Van, P. D. T, Popescu, I, van Griensven, A, Solomatine, D. P, Trung, N. H, Green, A

“…The present paper investigated the extent of the flood propagation in the Vietnamese Mekong Delta under different projected flood hydrographs, considering the…”
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Neural networks and M5 model trees in modelling water level–discharge relationship by Bhattacharya, B., Solomatine, D.P.

“…Reliable estimation of discharge in a river is the crucial component of efficient flood management and surface water planning. Hydrologists use historical data…”
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Alternative configurations of quantile regression for estimating predictive uncertainty in water level forecasts for the upper Severn River: a comparison by López López, P, Verkade, J. S, Weerts, A. H, Solomatine, D. P

“…The present study comprises an intercomparison of different configurations of a statistical post-processor that is used to estimate predictive hydrological…”
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Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan by Mount, N.J., Maier, H.R., Toth, E., Elshorbagy, A., Solomatine, D., Chang, F.-J., Abrahart, R.J.

“…"Panta Rhei - Everything Flows" is the science plan for the International Association of Hydrological Sciences scientific decade 2013-2023. It is founded on…”
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Integrating Qualitative Flow Observations in a Lumped Hydrologic Routing Model by Mazzoleni, M., Amaranto, A., Solomatine, D.P.

“…This study aims at proposing novel approaches for integrating qualitative flow observations in a lumped hydrologic routing model and assessing their usefulness…”
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novel approach to parameter uncertainty analysis of hydrological models using neural networks by Shrestha, D.L, Kayastha, N, Solomatine, D.P

“…In this study, a methodology has been developed to emulate a time consuming Monte Carlo (MC) simulation by using an Artificial Neural Network (ANN) for the…”
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Assessing the Impact of Precipitation Change on Design Annual Runoff in the Headwater Region of Yellow River, China by Hu, Y. M., Liang, Z. M., Solomatine, D. P., Wang, H. M., Liu, T.

“…A significant decrease in annual runoff (AR) in the headwater region of Yellow River, China, has been observed during the past decades, which produces a…”
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Fuzzy committees of specialized rainfall-runoff models: further enhancements and tests by Kayastha, N, Ye, J, Fenicia, F, Kuzmin, V, Solomatine, D. P

“…Often a single hydrological model cannot capture the details of a complex rainfall–runoff relationship, and a possibility here is building specialized models…”
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Machine learning in soil classification by Bhattacharya, B., Solomatine, D.P.

“…In a number of engineering problems, e.g. in geotechnics, petroleum engineering, etc. intervals of measured series data (signals) are to be attributed a class…”
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Model-Based Optimization of Downstream Impact during Filling of a New Reservoir: Case Study of Mandaya/Roseires Reservoirs on the Blue Nile River by Hassaballah, K., Jonoski, A., Popescu, I., Solomatine, D. P.

“…The aim of this paper is to develop a methodology based on coupled simulation-optimization approach for determining filling rules for the proposed Mandaya…”
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