In densely populated countries like China, clean water is one of the most challenging issues of prospective politics and environmental planning. Water pollution and eutrophication by excessive input of nitrogen and phosphorous from nonpoint sources is mostly linked to soil erosion from agricultural land. In order to prevent such water pollution by diffuse matter fluxes, knowledge about the extent of soil loss and the spatial distribution of hot spots of soil erosion is essential. In remote areas such as the mountainous regions of the upper and middle reaches of the Yangtze River, rainfall data are scarce. Since rainfall erosivity is one of the key factors in soil erosion modeling, e.g., expressed as R factor in the Revised Universal Soil Loss Equation model, a methodology is needed to spatially determine rainfall erosivity. Our study aims at the approximation and spatial regionalization of rainfall erosivity from sparse data in the large (3,200 km2) and strongly mountainous catchment of the Xiangxi River, a first order tributary to the Yangtze River close to the Three Gorges Dam. As data on rainfall were only obtainable in daily records for one climate station in the central part of the catchment and five stations in its surrounding area, we approximated rainfall erosivity as R factors using regression analysis combined with elevation bands derived from a digital elevation model. The mean annual R factor (Ra) amounts for approximately 5,222 MJ?mm?ha?1?h?1?a?1. With increasing altitudes, Ra rises up to maximum 7,547 MJ?mm ha?1?h?1 a?1 at an altitude of 3,078 m a.s.l. At the outlet of the Xiangxi catchment erosivity is at minimum with approximate Ra?=?1,986 MJ?mm?ha?1?h?1?a?1. The comparison of our results with R factors from high-resolution measurements at comparable study sites close to the Xiangxi catchment shows good consistance and allows us to calculate grid-based Ra as input for a spatially high-resolution and area-specific assessment of soil erosion risk. 相似文献
Increasing value is attributed to mangroves due to their considerable capacity to sequester carbon, known as ‘blue carbon’. Assessments of opportunities and challenges associated with estimating the significance of carbon sequestered by mangroves need to consider a range of disciplinary perspectives, including the bio-physical science mangroves, social and economic issues of land use, local and international law, and the role of public and private finance. We undertook an interdisciplinary review based on available literature and fieldwork focused on parts of the Mekong River Delta (MRD). Preliminary estimates indicate mangrove biomass may be 70–150 t ha?1, but considerably larger storage of carbon occurs in sediments beneath mangroves. These natural stores of carbon are compromised when mangroves are removed to accommodate anthropogenic activities. Mangroves are an important resource in the MRD that supplies multiple goods and services, and conservation or re-establishment of mangroves provides many benefits. International law and within-country environmental frameworks offer increasing scope to recognize the role that mangrove forests play through carbon sequestration, in order that these might lead to funding opportunities, both in public and private sectors. Such schemes need to have positive rather than negative impacts on the livelihoods of the many people living within and adjacent to these wetlands. Nevertheless, many challenges remain and it will require further targeted and coordinated scientific research, development of economic and social incentives to protect and restore mangroves, supportive law and policy mechanisms at global and national levels, and establishment of long-term financing for such endeavours. 相似文献
This study evaluated the individual and interactive effect of phenol and thiocyanate (SCN−) on partial nitritation (PN) activity using batch test and response surface methodology. The IC50 of phenol and SCN− on PN sludge were 5.6 and 351 mg L−1, respectively. The PN sludge was insensitive to phenol and SCN− at levels lower than 1.77 and 43.3 mg L−1, respectively. A regression model equation was developed and validated to predict the relative specific respiration rate (RSRR) of PN sludge exposed to different phenol and SCN− concentrations. In the range of independent variables, the most severe inhibition was observed with a valley value (17%) for RSRR, when the phenol and SCN− concentrations were 4.08 and 198 mg L−1, respectively. An isobole plot was used to judge the combined toxicity of phenol and SCN−, and the joint inhibitory effect was variable depending on the composition and concentration of the toxic components. Furthermore, the toxic compounds showed independent effects, which is the most common type of combined toxicity.