Economic evidence on sanitation supports decisions on resource allocation and selection of efficient and affordable sanitation interventions. This study presents the economic efficiency (costs versus benefits) of sanitation interventions to better manage human excreta, from 47 field sites, covering six countries of Southeast Asia (Cambodia, China, Indonesia, Lao PDR, the Philippines and Vietnam). Costs were estimated in each location, while benefits (improved health, avoided water pollution, reduced sanitation access time, resource recovery) were estimated using evidence from published studies and field sites. The economic return per currency unit invested, known as the benefit-cost ratio (BCR), and the cost per disability-adjusted life-year (DALY) averted were estimated. Across 25 rural field sites, pit latrines had a BCR of at least 5 in all countries, except Cambodia where the BCR was 2. In 22 urban field sites, septic tanks with wastewater management had a BCR of at least 2. Costs per DALY averted were found to be ‘cost-effective’ for most sanitation interventions in all countries. Economic performance declined significantly when considering non-use of facilities by households or unused infrastructural capacity. However, the economic net returns were positive under all pessimistic scenarios examined in one-way sensitivity analysis. This study demonstrates that sanitation is a highly profitable social and economic investment in six Asian countries.
Abstract:The spatial and temporal variations of precipitation in the desert region of China (DRC) from 1951 to 2005 were investigated using a rotated empirical orthogonal function (REOF), the precipitation concentration index (PCI) and the Mann-Kendall trend test method (M-K method). In addition, the association between variation patterns of precipitation and large-scale circulation were also explored using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. The results indicated that the spatial pattern of precipitation was primarily the local climate effect significant type, with the first three EOFs explaining a total of 55Ð3% of the variance, and the large-scale climate system effect type, which explained 9Ð8% of the variance. Prior to the 1970s, the East Asian summer monsoon was stronger, which resulted in abundant precipitation in the Inner Mongolia region. Conversely, the climate of the Xinjiang region was controlled by westerly circulation and had lower precipitation. However, this situation has been reversed since the 1980s. It is predicted that precipitation will decrease by 15-40 and 0-10 mm/year in the Inner Mongolia plateau and southern Xinjiang, respectively, whereas it will likely increase by 10-40 mm/year in northern Xinjiang. Additionally, 58-62% of the annual rainfall occurred during summer in the DRC, with precipitation increasing during spring and summer and decreasing in winter. The intra-annual precipitation is becoming uniform, but the inter-annual variability in precipitation has been increasing in the western portions of the DRC. The probability of precipitation during the study period increased by 30% and 22Ð2% in the extreme-arid zones and arid zones, respectively. Conversely, the probability of precipitation during the study period decreased by 18Ð5% and 37Ð5% in the semi-arid zones and semi-wet zones, respectively. It is predicted that the northwest portion of the DRC will become warmer and wetter, while the central portion will become warmer and drier and the northeast portion will be subjected to drought.
There is a great deal of geographic imbalance in global hydrologic data sets. Outside of the US and parts of Europe, there are many parts of the world that have only sparsely available streamflow gauge networks with only a few years' worth of data (Do et al., 2017;Fekete & Vörösmarty, 2007). Besides streamflow gauges, these regions also lack data on physiographic attributes such as geology and soil depth. Nevertheless, climate change is stressing these parts of the world, and accurate hydrologic simulations are needed for these regions just as much, or even more than for data-rich regions.Catchments across the world are often perceived as being unique from each other, requiring customized model development for each basin (Teutschbein & Seibert, 2012). As a rule of thumb, when we create process-based hydrologic models, our development effort scales roughly linearly to the modeled area, computational effort scales linearly at best, and accuracy is unrelated to the number of basins modeled. It is typically difficult to apply knowledge gained from one basin to another, as parameters or experiences do not transfer easily. As a result, although there have been calls for hydrologic studies to transcend the uniqueness
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