A GIS plug-in for Bayesian belief networks: Towards a transparent software framework to assess and visualise uncertainties in ecosystem service mapping

The complexity and spatial heterogeneity of ecosystem processes driving ecosystem service delivery require spatially explicit models that take into account the different parameters affecting those processes. Current attempts to model ecosystem service delivery on a broad, regional scale often depend on indicator-based approaches that are generally not able to fully capture the complexity of ecosystem processes. Moreover, they do not allow quantification of uncertainty on their predictions. In this paper, we discuss a QGIS plug-in which promotes the use of Bayesian belief networks for regional modelling and mapping of ecosystem service delivery and associated uncertainties. Different types of specific Bayesian belief network output maps, delivered by the plug-in, are discussed and their decision support capacities are evaluated. This plug-in, used in combination with firmly developed Bayesian belief networks, has the potential to add value to current spatial ecosystem service accounting methods. The plug-in can also be used in other research domains dealing with spatial data and uncertainty.     

Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.     

Hydrocarbon-based electrode ionomer for proton exchange membrane fuel cells

The electrode ionomer is a key factor that significantly affects the catalyst layer morphology and fuel cell performance. Herein, sulfonated poly(arylene ether sulfone)-based electrode ionomers with polymers of various molecular weights and alcohol/water mixtures were prepared, and those comprising the alcohol/water mixture showed a higher performance than the ones prepared using higher boiling solvents, such as dimethylacetamide; this is owing to the formation of the uniformly dispersed ionomer catalyst layer. The relation between ionomer molecular weight for the same polymer structure and the sulfonation degree was investigated. Because the chain length of polymer varies with molecular weight and chain entanglement degree, its molecular weight affects the electrode morphology. As the ionomer covered the catalyst, the agglomerates formed were of different morphologies according to their molecular weight, which could be deduced indirectly through dynamic light scattering and scanning electron microscopy. Additionally, the fuel cell performance was confirmed in the current-voltage curve.     

Applicability and toxicity evaluation of an adsorbent based on jujube for the removal of toxic heavy metals

The removal of heavy metals from industrial wastewater is important, owing to its eco-toxicity in aqueous environment. In this study, the mechanism and efficiency of the removal of toxic heavy metals by an eco-friendly adsorbent was investigated. Various types of adsorbents made from jujube were synthesized by varying the drying temperature of gel-type beads and elution method for jujube constituents. The maximum adsorption capacity for lead and copper ions was determined using the Langmuir isotherm model, with DJB-A-S-F (freeze-dried jujube bead made from a solution of squeezed autoclaved jujube) having the highest values at 60.44 mg/g (lead) and 20.33 mg/g (copper). In addition, the characteristics of the various adsorbents were determined by the Brunauer–Emmett–Teller (BET) method, scanning electron microscopy (SEM), and energy dispersive X-ray analysis (EDX). Gas chromatography–mass spectrometry (GC–MS) was used to identify the constituents of DJB-A-S-F before and after adsorption of heavy metals (Pb- and Cu-DJB-A-S-F). Furthermore, in vitro cytotoxicity assay was performed to investigate whether the binding of heavy metals to DJB-A-S-F increases cellular toxicity. As a result, no differences in cell viability between DJB-A-S-F and the ones coupled to heavy metals were observed, indicating that the developed adsorbents are non-cytotoxic with good compatibility. Thus, DJB-A-S-F is a promising adsorbent for the removal of toxic heavy metal cations from wastewater.     

Impact assessment of reservoir desiltation measures for downstream riverbed migration in climate change: A case study in northern Taiwan

Typhoon Aere in 2004 induced severe sedimentation and loss of storage capacity of the Shihmen Reservoir in northern Taiwan. The resulting dramatic increase in the turbidity of the water seriously affected the water supply. To effectively maintain the stability of the water supply and maintain the reservoir’s storage capacity, the government of Taiwan began to plan and construct a series of improvement measures, such as a sediment flushing tunnel, the JhongJhuang Bank-Side Reservoir, and the Amuping Desilting Tunnel. However, previous studies only focused on the impact of the sediment flushing tunnel and the Amuping Desilting Tunnel on the downstream riverbed, and did not consider the possibility of increasing sediment discharge after the completion of the JhongJhuang Bank-Side Reservoir. In addition, climate change will cause the intensity of extreme rainfall to increase enormously in the future. That rainfall and extra sediment flushing will challenge the existing flood prevention facilities. Therefore, this study considered that the JhongJhuang Bank-Side Reservoir will increase sediment discharge of the Shihmen Reservoir, and used dynamical downscaling extreme typhoon data of climate change under the RCP 8.5 scenario to explore the flood prevention and riverbed migration of the main channels of the Dahan and Tamsui Rivers in the future. We used the rainfall–runoff model of Hydrologic Modeling System to simulate rainfall and runoff, and used the hydraulic and sediment transport model of CCHE1D to holistically simulate flood events and consequent river scouring and deposition behaviors. Our results showed that the projected peak discharge during the late 21st century (2075 to 2099) will be at least 50% higher than that during the baseline (1979 to 2003) period. In terms of flood prevention, the potential of overbank flooding will increase in the downstream area, and the trend of long-term change in the riverbed will be dominated by degradation (-0.489 ± 0.743 m) in the future. The improvement measures will have a limited impact on riverbed migration (0.011 ± 0.094 m) in the Dahan and Tamsui Rivers. After the operation of the JhongJhuang Bank-Side Reservoir, the Shihmen Reservoir is expected to increase the sediment discharge ratio by 70% during floods, and it will not cause excessive water turbidity that may affect downstream water supply.     

Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville–Thermalito complex

This study demonstrates the application of an improved Evolutionary optimization Algorithm (EA), titled Multi-Objective Complex Evolution Global Optimization Method with Principal Component Analysis and Crowding Distance Operator (MOSPD), for the hydropower reservoir operation of the Oroville–Thermalito Complex (OTC) – a crucial head-water resource for the California State Water Project (SWP). In the OTC's water-hydropower joint management study, the nonlinearity of hydropower generation and the reservoir's water elevation–storage relationship are explicitly formulated by polynomial function in order to closely match realistic situations and reduce linearization approximation errors. Comparison among different curve-fitting methods is conducted to understand the impact of the simplification of reservoir topography. In the optimization algorithm development, techniques of crowding distance and principal component analysis are implemented to improve the diversity and convergence of the optimal solutions towards and along the Pareto optimal set in the objective space. A comparative evaluation among the new algorithm MOSPD, the original Multi-Objective Complex Evolution Global Optimization Method (MOCOM), the Multi-Objective Differential Evolution method (MODE), the Multi-Objective Genetic Algorithm (MOGA), the Multi-Objective Simulated Annealing approach (MOSA), and the Multi-Objective Particle Swarm Optimization scheme (MOPSO) is conducted using the benchmark functions. The results show that best the MOSPD algorithm demonstrated the best and most consistent performance when compared with other algorithms on the test problems. The newly developed algorithm (MOSPD) is further applied to the OTC reservoir releasing problem during the snow melting season in 1998 (wet year), 2000 (normal year) and 2001 (dry year), in which the more spreading and converged non-dominated solutions of MOSPD provide decision makers with better operational alternatives for effectively and efficiently managing the OTC reservoirs in response to the different climates, especially drought, which has become more and more severe and frequent in California.     

Enhancing cation exchange capacity of chars through ozonation

The use of ozone to increase the cation exchange capacity (CEC) of two chars produced from pyrolysis of Douglas fir (Pseudotsuga menziessii) and a control bituminous coal activated carbon (AC) is reported. Chars were produced from the wood fraction of Douglas fir (DFWC) and the bark (DFBC) at 500 °C using an auger driven reactor with a nitrogen sweep gas under mild vacuum. Five ozone treatment times, ranging from 5 min to 60 min, were investigated. The initial properties of each char were found to differ significantly from the other samples in terms of surface area, proximate composition, and elemental composition. DFWC did not show significant mass loss or temperature variation during ozone treatment; however, after 1 h of oxidation both DFBC and AC samples resulted in 20% and 30% mass loss, respectively, and reactor temperatures in excess of 60 °C. Analysis of the pore size distribution of each treatment shows that ozone treatment did not significantly affect small micropores after 30 min of treatment for any material, but did reduce the apparent surface area of mesopores. Increases in carboxylic groups were identified with ozone treatment and found to correlate strongly with changes in measured CEC. The formation of lactone was found to correlate positively with reactor temperature during oxidation. These results indicate that the properties of chars, including surface area, pore structure, and chemical composition, as well as reactor conditions strongly affect the ozone oxidation of chars.