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Creating extreme weather time series through a quantile regression ensemble ☆
10.1016/j.envsoft.2018.03.007 2018-03-21 Heat waves give rise to order of magnitude higher mortality rates than other weather-related natural disasters. Unfortunately both the severity and amplitude of heat waves are predicted to increase worldwide as a consequence of climate change. Hence, meteorol... |
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Hybrid SOM+k-Means clustering to improve planning, operation and management in water distribution systems
10.1016/j.envsoft.2018.02.013 2018-03-08 With the advance of new technologies and emergence of the concept of the smart city, there has been a dramatic increase in available information. Water distribution systems (WDSs) in which databases can be updated every few minutes are no exception. Suitable ... |
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Modelling background air pollution exposure in urban environments: Implications for epidemiological research
10.1016/j.envsoft.2018.02.011 2018-02-26 Background pollution represents the lowest levels of ambient air pollution to which the population is chronically exposed, but few studies have focused on thoroughly characterizing this regime. This study uses clustering statistical techniques as a modelling ... |
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Environmental data stream mining through a case-based stochastic learning approach
10.1016/j.envsoft.2018.01.017 2018-02-16 Environmental data stream mining is an open challenge for Data Science. Common methods used are static because they analyze a static set of data, and provide static data-driven models. Environmental systems are dynamic and generate a continuous data stream. D... |
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Inverse modelling of snow depths
10.1016/j.envsoft.2018.01.010 2018-02-09 Operational snow forecasting models contain parameters for which site-specific values are often unknown. As an improvement a Bayesian procedure is suggested that estimates, from past observations, site-specific parameters with confidence intervals. It turned ... |
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Multilevel mesh workflows towards CONUS scale watersheds: How small should triangles be to capture stream curvature for hydrological modeling?
10.1016/j.envsoft.2017.11.036 2018-01-10 Generating quality meshes for hydrological modeling is challenging. This article demonstrates using mesh workflows to incorporate national stream networks into very large dynamic meshes for distributed High Performance Computing (HPC). A multilevel quadtree i... |
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Imbalanced classification techniques for monsoon forecasting based on a new climatic time series
10.1016/j.envsoft.2017.11.024 2017-12-13 Monsoons have been widely studied in the literature due to their climatic impact related to precipitation and temperature over different regions around the world. In this work, data mining techniques, namely imbalanced classification techniques, are proposed ... |
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Transforming data into knowledge for improved wastewater treatment operation: A critical review of techniques
10.1016/j.envsoft.2017.11.023 2017-12-08 The aim of this paper is to describe the state-of-the art computer-based techniques for data analysis to improve operation of wastewater treatment plants. A comprehensive review of peer-reviewed papers shows that European researchers have led academic compute... |
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Model-based analysis of the relationship between macroinvertebrate traits and environmental river conditions
10.1016/j.envsoft.2017.11.025 2017-12-06 Aquatic macroinvertebrates, 18 physical-chemical water characteristics and 30 hydromorphological variables were assessed at 85 locations on Leyte island, Philippines. Biological traits derived from literature were linked to the biological samples based on fou... |
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Data-driven rainfall/runoff modelling based on a neuro-fuzzy inference system
10.1016/j.envsoft.2017.11.026 2017-12-06 The development of rainfall/runoff models involves extensive computation and the availability of different coexisting platforms, including numerical flow models and GIS for their physiographical characterization. In this paper we present a data-driven approac... |