ALBERT

Description: Constructed ponds and wetlands are widely used in urban areas for stormwater management, ecological conservation, and pollution treatment. The treatment efficiency of these systems is strongly related to the hydrodynamics and hydraulic residence time. In this study, we developed a physical model and used rhodamine-WT as a tracer to conduct flume experiments. An equivalent Reynolds number was assumed, and the flume was a 1/25-scale model. Emergent obstructions (EOs), submerged obstructions (SOs), and high- and low-density emergent vegetation were placed along the sides of the flume, and 49 tracer tests were performed. We altered the density, spatial extent, aspect ratio, and configurations of the obstructions and emergent vegetation to observe changes in the hydraulic efficiency of a deep-water wetland. In the cases of low-aspect-ratio obstructions, the effects of the EOs on the hydraulic efficiency were significantly stronger than those of the SOs. In contrast, in the cases of high-aspect-ratio obstructions, the improvement effects of the EOs were weaker than those of the SOs. The high-aspect-ratio EOs altered the flow direction and constrained the water conveyance area, which apparently caused a short-circuited flow phenomenon, resulting in a decrease in hydraulic efficiency. Most cases revealed that the emergent vegetation improved the hydraulic efficiency more than the EOs. The high-density emergent vegetation (HEV) improved the hydraulic efficiency more than the low-density emergent vegetation (LEV). Three cases involving HEV, two cases involving LEV, and one case involving EOs attained a good hydraulic efficiency (λ > 0.75). To achieve greater water purification, aquatic planting in constructed wetlands should not be overly dense. The HEV configuration in case 3-1 achieved optimum hydraulic performance for compliance with applicable water treatment standards.

Description: The present study examined a mangrove ecosystem in northern Taiwan to determine how the various components of ecosystem function, ecosystem services and human wellbeing are connected. The overall contributions of mangrove services to specific components of human wellbeing were also assessed. A network was developed and evaluated by an expert panel consisting of hydrologists, ecologists, and experts in the field of culture, landscape or architecture. The results showed that supporting habitats was the most important function to human wellbeing, while water quality, habitable climate, air quality, recreational opportunities, and knowledge systems were services that were strongly linked to human welfare. Security of continuous supply of services appeared to be the key to a comfortable life. From a bottom-up and top-down perspective, knowledge systems (a service) were most supported by ecosystem functions, while the security of continuous supply of services (wellbeing) had affected the most services. In addition, the overall benefits of mangrove services to human prosperity concentrated on mental health, security of continuous supply of services, and physical health.

Description: Bird watching is one of many recreational activities popular in ecotourism. Its popularity, therefore, prompts the need for studies on energy conservation. One such environmentally friendly approach toward minimizing bird watching’s ecological impact is ensuring a reduced carbon footprint by using an economic travel itinerary comprising a series of connected routes between tourist attractions that minimizes transit time. This study used a travel-route planning approach using geographic information systems to detect the shortest path, thereby solving the problems associated with time-consuming transport. Based on the results of road network analyses, optimal travel-route planning can be determined. These methods include simulated annealing (SA) and genetic algorithms (GA). We applied two algorithms in our simulation research to detect which one is an appropriate algorithm for running carbon-routing algorithms at the regional scale. SA, which is superior to GA, is considered an excellent approach to search for the optimal path to reduce carbon dioxide and high gasoline fees, thereby controlling travel time by using the shortest travel routes.

Description: The treatment efficiency of a wetland constructed for nutrient removal depends strongly on the flow patterns and residence times of the wetland. In this study, a tracer experiment was performed to estimate the residence time distribution and the hydraulic efficiency of a treatment pond with shallow and deep‐water areas. Rhodamine WT experiments revealed a non‐uniform flow pattern in the deep‐water area and an overall poor hydraulic efficiency in the wetland. To improve flow uniformity and hydraulic efficiency, several design options for different inlet-outlet configurations, flow rates, water depths, and emergent baffle additions were considered. The effects on hydraulic performance were investigated through mathematical model simulations. The results revealed that increasing the flow rate and decreasing the water depth slightly improved the hydraulic performance, whereas changing the positions of the inlet and outlet produced inconsistent effects. The most effective improvement involved installing emergent baffles, with the number of baffles presenting the largest positive effect, followed by the width and length of the baffles. Long and thin baffles resulted in a uniform flow velocity field, a meandering flow path, and greater residence times and effective volume ratios. The installation of two baffles increased the hydraulic efficiency to 1.00, indicating excellent hydraulic performance. The thin baffles occupied approximately 3.7%-6.3% of the deep‐water area and 1.9%-3.2% of the entire pond, indicating the potential for their practical application in limited land use regions.

Description: Inundation forecast models with non-sequential regressors are advantageous in efficiency due to their rather fewer input variables required to be processed. This type of model is nevertheless rare mainly because of the difficulty in finding the proper combination of regressors for the model to perform accurate prediction. A novel methodology is proposed in this study to tackle the problem. The approach involves integrating a Multi-Objective Genetic Algorithm (MOGA) with forecast models based on ARX (Auto-Regressive model with eXogenous inputs) to transfer the search for the optimal combination of non-sequential regressors into an optimization problem. An innovative approach to codifying any combinations of model regressors into binary strings is developed and employed in MOGA. The Pareto optimal sets of three types of models including linear ARX (LARX), nonlinear ARX with Wavelet function (NLARX-W), and nonlinear ARX with Sigmoid function (NLARX-S) are searched for by the proposed methodology. The results show that the optimal models acquired through this approach have good inundation forecasting capabilities in every aspect in terms of accuracy, time shift error, and error distribution.