Preprints
Filtering by Subject: Environmental Engineering
An Ethical Decision-Making Framework with Serious Gaming: Smart Water Case Study on Flooding
Published: 2020-06-23
Subjects: Artificial Intelligence and Robotics, Civil and Environmental Engineering, Civil Engineering, Computer Sciences, Databases and Information Systems, Engineering, Engineering Education, Environmental Engineering, Hydraulic Engineering, Physical Sciences and Mathematics, Theory and Algorithms
Sensors and control technologies are being deployed extensively in both urban water networks and rural river systems, leading to unprecedented ability to sense and control our water environment. Because these sensor networks and control systems allow for higher resolution monitoring and decision making in both time and space, greater discretization of control will allow for an unprecedented [...]
A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources
Published: 2020-06-19
Subjects: Civil and Environmental Engineering, Computer Engineering, Engineering, Environmental Engineering
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety, and velocity of water-related data are increasing due to large-scale sensor networks and increased attention to topics such as disaster response, water resources management, and climate change. Combined with the growing availability of computational resources and popularity of deep learning, these [...]
The sustainability of beach nourishments: A review of nourishment and environmental monitoring practice
Published: 2020-06-10
Subjects: Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Monitoring, Environmental Sciences, Geomorphology, Physical Sciences and Mathematics, Sustainability
Beach nourishments are a widely used method to mitigate erosion along flood-prone sandy shorelines. In contrast to hard coastal protection structures, nourishments are considered as soft engineering, although little is known about the cumulative, long-term environmental effects of both marine sediment extraction and nourishment activities. Recent endeavours to sustain the marine ecosystem and [...]
Evaluating single and multi-date Landsat classifications of land-cover in a seasonally dry tropical forest
Published: 2020-05-29
Subjects: Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Monitoring, Environmental Sciences, Natural Resources and Conservation, Natural Resources Management and Policy, Other Civil and Environmental Engineering, Other Environmental Sciences, Physical Sciences and Mathematics
Accurate information on the land cover is crucial for efficient monitoring and development of environmental studies in the Brazilian Caatinga forest. It is the largest tropical seasonal forest in South America, presenting high biodiversity and is under intense anthropogenic disturbance. Caatingas land cover is heterogeneous, and rainfall is its primary phenological regulator, presenting mainly [...]
Using Bayesian Hierarchical Modelling to capture cyanobacteria dynamics in Northern European lakes
Published: 2020-05-21
Subjects: Civil and Environmental Engineering, Engineering, Environmental Engineering
Cyanobacteria blooms in lakes and reservoirs currently threaten water security and affect the ecosystem services provided by these freshwater ecosystems, such as drinking water and recreational use. Climate change is expected to further exacerbate the situation in the future because of higher temperatures, extended droughts and nutrient enrichment, due to urbanisation and intensified agriculture. [...]
Probabilistic soil moisture dynamics of water- and energy-limited ecosystems
Published: 2020-05-18
Subjects: Agriculture, Agronomy and Crop Sciences Life Sciences, Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Sciences, Forest Sciences, Hydrology, Life Sciences, Physical Sciences and Mathematics, Plant Sciences, Statistical Models, Statistics and Probability
This paper presents an extension of the stochastic ecohydrological model for soil moisture dynamics at a point of Rodriguez-Iturbe et al. (1999) and Laio et al. (2001). In the original model, evapotranspiration is a function of soil moisture and vegetation parameters, so that the model is suitable for water-limited environments. Our extension introduces a dependence on maximum evapotranspiration [...]
Evaluating Controller Performance and Placement on System-level Urban Flooding Reduction and Water Quality Improvement
Published: 2020-05-07
Subjects: Civil and Environmental Engineering, Civil Engineering, Engineering, Environmental Engineering
Increases in urbanization and climate change are forcing urban drainage engineers to more effectively leverage stormwater storage facilities to minimize flooding and water quality impacts. This process becomes increasingly challenging due to the operations of storage coordination across the system-level watershed. This study presents a system-level real-time control simulation for assessing [...]
A Data-driven Improved Fuzzy Logic Control Optimization-simulation Tool for Reducing Flooding Volume at Downstream Urban Drainage Systems
Published: 2020-04-30
Subjects: Civil and Environmental Engineering, Civil Engineering, Engineering, Environmental Engineering
The uncertainty of climate change and urbanization imposed additional stress for urban drainage systems (UDSs) by intensifying rainfall frequency and magnifying peak runoff rate. UDSs are among the stormwater infrastructures that can be controlled in real-time for mitigating downstream urban flooding. In this paper, a data-driven improved real-time control optimization-simulation tool called [...]
A Performance Comparison of Unsupervised Machine Learning Algorithms for Clustering Water Depth Datasets at Urban Drainage Systems
Published: 2020-04-30
Subjects: Civil and Environmental Engineering, Civil Engineering, Engineering, Environmental Engineering
As sensor measurements emerge in urban water systems, data-driven unsupervised machine learning algorithms have been drawn tremendous interest in infrastructure monitoring, flow prediction, and pollutant warning recently. However, most of them are applied in water distribution systems, and few studies consider using unsupervised clustering analysis to group the time-series hydraulic-hydrologic [...]
Protecting rivers by integrating supply-wastewater infrastructure planning and coordinating operational decisions
Published: 2020-04-30
Subjects: Civil and Environmental Engineering, Engineering, Environmental Engineering
Placing water quality in rivers at the centre of water infrastructure planning and management is an important objective. In response there has been a range of whole system analyses. Few studies, however, consider both abstraction (water removed from rivers) and discharge (water returned) to inform the future planning of water systems. In this work we present a systems approach to analysing future [...]
External control and automatic calibration of the HEC-RAS NSM-I water quality model
Published: 2020-03-22
Subjects: Civil and Environmental Engineering, Engineering, Environmental Engineering, Hydraulic Engineering
Calibration of models is a common procedure required to properly reproduce a system under analysis. In the present study, we developed a tool integrating the HEC-RAS NSM-I water quality model with the optimization algorithm SCE-UA in order to allow the automatic calibration. The tool’s performance was assessed in two experiments involving a theoretical situation, when it was used to approximate a [...]
Distributed long-term hourly streamflow predictions using deep learning – A case study for State of Iowa
Published: 2020-03-21
Subjects: Civil and Environmental Engineering, Civil Engineering, Engineering, Environmental Engineering
Accurate streamflow forecasting has always been a challenge. Although there were many novel approaches using deep learning models, accuracy of these models is often limited to a short lead time. This study proposes a new deep recurrent neural network approach, Neural Runoff Model (NRM), which has been applied on 125 USGS streamflow gages in the State of Iowa for predicting the next 120 hours. We [...]
A Serious Gaming Framework for Decision Support on Hydrological Hazards
Published: 2020-03-17
Subjects: Civil and Environmental Engineering, Computer Sciences, Databases and Information Systems, Engineering, Environmental Education, Environmental Engineering, Environmental Sciences, Physical Sciences and Mathematics, Software Engineering, Sustainability, Water Resource Management
In this study, a web-based decision support tool (DST) was developed for hydrological multi-hazard analysis while employing gamification techniques to introduce a competitive element. The serious gaming environment provides functionalities for intuitive management, visualization, and analysis of geospatial, hydrological, and economic data to help stakeholders in the decision-making process [...]
Power law scaling model predicts N2O emissions along the Upper Mississippi River basin
Published: 2020-03-03
Subjects: Civil and Environmental Engineering, Engineering, Environmental Engineering
Nitrous oxide, N2O, is widely recognized as one of the most important greenhouse gases, and responsible for stratospheric ozone destruction. A significant fraction of N2O emissions to the atmosphere is from rivers. Reliable catchment-scale estimates of these emissions require both high-resolution field data and suitable models able to capture the main processes controlling nitrogen transformation [...]
Tracking Flooding Phase Transitions and Establishing a Passive Hotline with AI-Enabled Social Media Data
Published: 2020-02-21
Subjects: Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Monitoring, Environmental Sciences, Hydrology, Physical Sciences and Mathematics, Water Resource Management
Flooding management requires collecting real-time onsite information widely and rapidly. As an emerging data source, social media demonstrates an advantage of providing in-time, rich data in the format of texts and photos and can be used to improve flooding situation awareness. The present study shows that social media data, with additional information processed by Artificial Intelligence (AI) [...]