The neoliberalization of ecosystem services: wetland mitigation banking and problems in environmental governance

Wetland mitigation banking is an American neoliberal environmental policy that has created a functioning market in `ecosystem services', commodities defined using the holistic measures of ecological science. The development of this market is discussed as a project of environmental governance, defined as the nation-state's regulation of ecological relations within its territory towards stabilizing capitalist relations of power and accumulation. I argue that the wetland banking industry serves as a bellwether that presages problems that other strategies of neoliberal environmental governance will experience. Ethnographic, economic and ecological data from the Chicago-area wetland banking industry inform a discussion of two major obstacles to neoliberal strategy: the problem of relying on ecological science to define the unit of trade, and the problem of aligning the somewhat independent relations of law, politics, markets and ecosystems across an array of spatial scales. Theoretical guidance is sought from recent work on `social natures' and from the Regulationist approach to institutional political economics.     

金沙江流域(云南境内)山地灾害危险性评价

云南境内的金沙江流域是斜坡不稳定的敏感区,根据1988-2000年的区域调查和统计,区内发育山地灾害点1697处,其中流域面积大于1km2的泥石流沟808条,体积大于1×104m3的滑坡580处,体积大于1000m3的崩塌309处。用于山地灾害危险性评价的主要敏感因子包括岩土体类型、山坡坡度、降雨、土地利用、地震烈度和人类活动。在对这些因子进行了敏感性评价的基础上,应用GIS对敏感因子集成评价而产生了云南金沙江流域山地灾害危险性评价图。评价结果表明:高危险区面积占全区面积6464km2的8 77%,中危险区占全区总面积的41 51%,低危险区占41 12%,无危险区占8 60%。山地灾害危险性评价图可以帮助规划者或工程师在土地发展规划中选择最佳建设场所,以减轻灾害的影响。     

A knowledge base model for evaluation of bio-physical tendency of dryland

The present study aims the evaluation of bio-physical characteristics towards soil-water-vegetation stress and a rule is envisaged to assess the degree of temporal changes. The digital rule for assessment is initialized through the index of land Instability (ILI) where the variance indicates the temporal instability of the pixel i.e., smallest land unit. It is assumed that the biophysical characteristic of land is in command of land-dynamics where there is no change in Land Use/Land Cover (LU&LC). The intensity map on tendency of albedo (IALB) assesses the intensity of soil erosion and water stress whereas intensity map on tendency of NDVI (INDVI) appraises the stress on vegetation. The carry-out study covers a part of semiarid Western India. Primarily remote sensing technique, which carries the digital information of land temporally and spatially, is adopted in this paper. A part of the study area is represented using two sets of IRS 1A/1B LISS-I data of March with a decadal time domain (1989-1998) as a test area. It is assumed that the soil-water-vegetation stress is maximum during summer(March-April-May) in any tropical belt and decadal data will stretch the possibility of climate as well as man-made activity over the land.     

Regional comprehensive assessment on environment-health of China

The aim of the study was to assess the environment-health development in different regions of China. 175 indicators, such as average life expectancy at birth, emission intensity of waste gas, GDP etc. were chosen to describe various aspects of the environment, health and development of China. Of all the indicators, life expectancy can sufficiently reflect health situation of population. Consequently, life expectancy was identified as key indicator, and 42 out of 175 indicators were selected for establishing the environment-health indicator framework with three grades of integrative indices to assess the development of environment-health of China. Based on the hierarchical relation between various grades of indices, the comprehensive environment-health index was calculated and contributed to classify the environment-health situation of 30 provinces, municipalities and autonomous regions in China which were divided into five grades by four predefined limits. Comprehensive assessment indicates that the environment-health situation of the eastern and coastal areas is superior to that of inland which is the western regions with underdeveloped economy and rigorous natural condition. Especially, the Qinghai-Tibet and Yunnan-Guizhou plateaus in southwestern China are most vulnerable in the environment and population health. These fit in with the pattern of national socio-economic development, which fully shows that socio-economic context plays a dominant role in the improvement of environment-health in China.     

Representing and communicating deep uncertainty in climate-change assessments

IPCC reports provide a synthesis of the state of the science in order to inform the international policy process. This task is made difficult by the presence of deep uncertainty in the climate problem that results from long time scales and complexity. This paper focuses on how deep uncertainty can be effectively communicated. We argue that existing schemes do an inadequate job of communicating deep uncertainty and propose a simple approach that distinguishes between various levels of subjective understanding in a systematic manner. We illustrate our approach with two examples. To cite this article: M. Kandlikar et al., C. R. Geoscience 337 (2005).     

青海省新型功能材料研究和产业的分析(续完)

介绍了部分新型功能材料的前沿领域发展情况;通过对青海省在能源、矿产资源方面的优势及青海省可持续发展能力的分析,对我省目前及未来可以发展的新型功能材料产业提出了意见和建议。     

Snow model sensitivity analysis to understand spatial and temporal snow dynamics in a high‐elevation catchment

In this paper, we addressed a sensitivity analysis of the snow module of the GEOtop2.0 model at point and catchment scale in a small high‐elevation catchment in the Eastern Italian Alps (catchment size: 61 km²). Simulated snow depth and snow water equivalent at the point scale were compared with measured data at four locations from 2009 to 2013. At the catchment scale, simulated snow‐covered area (SCA) was compared with binary snow cover maps derived from moderate‐resolution imaging spectroradiometer (MODIS) and Landsat satellite imagery. Sensitivity analyses were used to assess the effect of different model parameterizations on model performance at both scales and the effect of different thresholds of simulated snow depth on the agreement with MODIS data. Our results at point scale indicated that modifying only the “snow correction factor” resulted in substantial improvements of the snow model and effectively compensated inaccurate winter precipitation by enhancing snow accumulation. SCA inaccuracies at catchment scale during accumulation and melt period were affected little by different snow depth thresholds when using calibrated winter precipitation from point scale. However, inaccuracies were strongly controlled by topographic characteristics and model parameterizations driving snow albedo (“snow ageing coefficient” and “extinction of snow albedo”) during accumulation and melt period. Although highest accuracies (overall accuracy = 1 in 86% of the catchment area) were observed during winter, lower accuracies (overall accuracy < 0.7) occurred during the early accumulation and melt period (in 29% and 23%, respectively), mostly present in areas with grassland and forest, slopes of 20–40°, areas exposed NW or areas with a topographic roughness index of ?0.25 to 0 m. These findings may give recommendations for defining more effective model parameterization strategies and guide future work, in which simulated and MODIS SCA may be combined to generate improved products for SCA monitoring in Alpine catchments.     

Modelling atmospheric and hydrologic processes for assessment of meadow restoration impact on flow and sediment in a sparsely gauged California watershed

The restoration of meadowland using the pond and plug technique of gully elimination was performed in a 9‐mile segment along Last Chance Creek, Feather River Basin, California, in order to rehabilitate floodplain functions such as mitigating floods, retaining groundwater, and reducing sediment yield associated with bank erosion and to significantly alter the hydrologic regime. However, because the atmospheric and hydrological conditions have evolved over the restoration period, it was difficult to obtain a comprehensible evaluation of the impact of restoration activities by means of field measurements. In this paper, a new use of physically based models for environmental assessment is described. The atmospheric conditions over the sparsely gauged Last Chance Creek watershed (which does not have any precipitation or weather stations) during the combined historical critical dry and wet period (1982–1993) were reconstructed over the whole watershed using the atmospheric fifth‐generation mesoscale model driven with the US National Center for Atmospheric Research and US National Center for Environmental Prediction reanalysis data. Using the downscaled atmospheric data as its input, the watershed environmental hydrology (WEHY) model was applied to this watershed. All physical parameters of the WEHY model were derived from the existing geographic information system and satellite‐driven data sets. By comparing the prerestoration and postrestoration simulation results under the identical atmospheric conditions, a more complete environmental assessment of the restoration project was made. Model results indicate that the flood peak may be reduced by 10–20% during the wet year and the baseflow may be enhanced by 10–20% during the following dry seasons (summer to fall) in the postrestoration condition. The model results also showed that the hydrologic impact of the land management associated with the restoration mitigates bank erosion and sediment discharge during winter storm events. Copyright © 2013 John Wiley & Sons, Ltd.     

Revised runoff curve number for runoff prediction in the Loess Plateau of China

The soil conservation service (now Natural Resources Conservation Service) Curve Number (SCS-CN), one of the most commonly used methods for surface runoff prediction. The runoff calculated by this method was very sensitive to CN values. In this study, CN values were calculated by both arithmetic mean (CN_C) and least square fit method (CN_F) using observed rainfall-runoff data from 43 sites in the Loess Plateau region, which are considerably different from the CN₂ values obtained from the USDA-SCS handbook table (CN_T). The results showed that using CN_C instead of CN_T for each watershed produce little improvement, while replacing CN_T with CN_F improves the performance of the original SCS-CN method, but still performs poorly in most study sites. This is mainly due to the SCS-CN method using a constant CN value and discounting of the temporal variation in rainfall-runoff process. Therefore, three factors—soil moisture, rainfall depth and intensity—affecting the surface runoff variability are considered to reflect the variation of CN in each watershed, and a new CN value was developed. The reliability of the proposed method was tested with data from 38 watersheds, and then applied to the remaining five typical watersheds using the optimized parameters. The results indicated that the proposed method, which boosted the model efficiencies to 81.83% and 74.23% during calibration and validation cases, respectively, performed better than the original SCS-CN and the Shi and Wang (2020b) method, a modified SCS-CN method based on tabulated CN value. Thus, the proposed method incorporating the influence of the temporal variability of soil moisture, rainfall depth, and intensity factors suggests an accurate runoff prediction for general applications under different hydrological and climatic conditions on the Loess Plateau region.     

基于决策树分类的大屯矿区地物信息提取及矿区污染分析

本文在对国内外遥感图像分类方法充分研究分析的基础上,选择决策树分类法对大屯矿区的Landsat 8遥感图像进行分类研究。选取样本提取并分析研究区典型地类光谱特征曲线,依据光谱曲线特征和归一化植被指数建立了土地利用分类决策树模型,通过反复试验和修正,筛选出适宜大屯矿区地物分类的决策树最优阈值,对研究区进行分类和精度评价,最后通过分类结果对研究区的水体污染状况进行简要分析。