Water2015, 7(5), 2527-2541; doi:10.3390/w7052527 (registering DOI) - published 22 May 2015 Show/Hide Abstract
Abstract: Existing flocculation models for cohesive sediments are classified into two groups: population balance equation models (PBE) and floc growth models. An FGM ensures mass conservation in a closed system. However, an FGM determines only the average size of flocs, whereas a PBE has the capability to calculate a size distribution of flocs. A new stochastic approach to model the flocculation process is theoretically developed and incorporated into a deterministic FGM in this study in order to calculate a size distribution of flocs as well as the average size. A log-normal distribution is used to generate random numbers based on previous laboratory experiments. The new stochastic flocculation model is tested with three laboratory experiment results. It was found and validated with measured data that the new stochastic flocculation model has the capability to replicate a size distribution of flocs reasonably well under different sediment and carrier flow conditions. Three more distributions (normal; Pearson type 3; and generalized extreme value distributions) were also tested. From the comparison with results of different distribution functions, it is shown that a stochastic FGM using a log-normal distribution has a comparative advantage in terms of simplicity and accuracy.
Water2015, 7(5), 2516-2526; doi:10.3390/w7052516 (registering DOI) - published 22 May 2015 Show/Hide Abstract
Abstract: In a previous study, we showed that widespread adoption of water-saving equipment had the potential to reduce CO2 emissions by 1% in Japan. The usage of already diffused equipment was used as an evaluation baseline. This was an evaluation model of developed countries. In order to evaluate the potential benefits of water-saving in developing countries, it is necessary to set the baseline, as cities in developing countries are expected to have the necessary infrastructure in place in the near future. In this paper, the potential for reducing CO2 emissions by water saving in Vietnam was evaluated. Based on the development of water infrastructure, and envisioning a society in which the latest high-efficiency flush toilet bowls and showers installed in Hanoi and Ho Chi Minh City are used in all Vietnamese houses as a near future baseline, we evaluated the potential reduction when a water-saving project is implemented. Under these conditions, an 8.8% reduction in CO2 emissions in Vietnam would be achieved by the widespread adoption of water-saving equipment. Following the recognition of the large environmental contribution potential of water saving, a water-saving project has been planned for implementation in Vietnam in the near future.
Water2015, 7(5), 2494-2515; doi:10.3390/w7052494 (registering DOI) - published 22 May 2015 Show/Hide Abstract
Abstract: In this contribution we analyze the performance of a monthly river discharge forecasting model with a Support Vector Regression (SVR) technique in a European alpine area. We considered as predictors the discharges of the antecedent months, snow-covered area (SCA), and meteorological and climatic variables for 14 catchments in South Tyrol (Northern Italy), as well as the long-term average discharge of the month of prediction, also regarded as a benchmark. Forecasts at a six-month lead time tend to perform no better than the benchmark, with an average 33% relative root mean square error (RMSE%) on test samples. However, at one month lead time, RMSE% was 22%, a non-negligible improvement over the benchmark; moreover, the SVR model reduces the frequency of higher errors associated with anomalous months. Predictions with a lead time of three months show an intermediate performance between those at one and six months lead time. Among the considered predictors, SCA alone reduces RMSE% to 6% and 5% compared to using monthly discharges only, for a lead time equal to one and three months, respectively, whereas meteorological parameters bring only minor improvements. The model also outperformed a simpler linear autoregressive model, and yielded the lowest volume error in forecasting with one month lead time, while at longer lead times the differences compared to the benchmarks are negligible. Our results suggest that although an SVR model may deliver better forecasts than its simpler linear alternatives, long lead-time hydrological forecasting in Alpine catchments remains a challenge. Catchment state variables may play a bigger role than catchment input variables; hence a focus on characterizing seasonal catchment storage—Rather than seasonal weather forecasting—Could be key for improving our predictive capacity.
Water2015, 7(5), 2472-2493; doi:10.3390/w7052472 (registering DOI) - published 22 May 2015 Show/Hide Abstract
Abstract: In this paper we deal with the problem of missing data in environmental cost-benefit analysis. If government pursues the goal of maximizing social welfare, this implies that public funds should be allocated to those uses where they generate the highest net social benefit. This criterion makes it necessary to conduct cost-benefit analyses for public projects. While the assessment of project costs is typically rather straightforward, a comprehensive assessment of the project benefits is more complicated because one has to consider that also people living far away from the project site might benefit from that project. Neglecting these so-called passive use benefits would lead to a systematic undervaluation of environmental projects, thereby reducing their chances of being realized. A comprehensive cost-benefit analysis would, therefore, require benefit assessment studies in all areas where passive use values might occur. Obviously, this would be impossible. In this paper we show how the assessment of the social benefits from environmental projects can be enhanced even with an imperfect database by using benefit transfer techniques. This is also illustrated empirically using an example from Northwest China.
Water2015, 7(5), 2451-2471; doi:10.3390/w7052451 (registering DOI) - published 22 May 2015 Show/Hide Abstract
Abstract: The atmospheric chloride mass balance (CMB) method was used to estimate net aquifer recharge in Las Cañadas Caldera, an endorheic summit aquifer area about 2000 m a.s.l. with negligible surface runoff, which hosts the largest freshwater reserve in Tenerife Island, Canary Islands, Spain. The wet hydrological year 2005–2006 was selected to compare yearly atmospheric chloride bulk deposition and average chloride content in recharge water just above the water table, both deduced from periodical sampling. The potential contribution of chloride to groundwater from endogenous HCl gas may invalidate the CMB method. The chloride-to-bromide molar ratio was an efficient tracer used to select recharge water samples having atmospheric origin of chloride. Yearly net aquifer recharge was 631 mm year−1, i.e., 69% of yearly precipitation. This result is in agreement with potential aquifer recharge estimated through an independent lumped-parameter rainfall-runoff model operated by the Insular Water Council of Tenerife. This paper illustrates basic procedures and routines to use the CMB method for aquifer recharge in active volcanic oceanic islands having sparse-data coverage and groundwater receiving contribution of endogenous halides.
Water2015, 7(5), 2435-2450; doi:10.3390/w7052435 (registering DOI) - published 21 May 2015 Show/Hide Abstract
Abstract: Climate change information is essential for water resources management planning, and the majority of research available uses the global circulation model (GCM) data to project future water balance. Despite the fact that the results of various GCMs are still heterogeneous, it is common to utilize GCM values directly in climate change impact assessment models. To mitigate these limitations, this study provides an alternative methodology, which uses GCM-based data to assign weights on historical scenarios rather than to directly input their values into the assessment models, thereby reducing the uncertainty involved in the direct use of GCMs. Therefore, the real innovation of this study is placed on the use of a new probability weighting scheme with multiple GCMs rather than on the direct input of GCM-driven data. Applied to make future projections of the water shortage in the Han River basin of Korea, the proposed methodology produced conservative but realistic projection results (15% increase) compared to the existing methodologies, which projected a dramatic increase (144%) in water shortage over 10 years. As a result, it was anticipated that the amount of water shortages in the Han River basin would gradually increase in the next 90 years, including a 57% increase in the 2080s.