祁连山讨赖河流域1957—2012年极端气候变化

全球气候变化背景下,极端气候事件发生的频率逐年增大,由此引发的气象灾害事件也随之增加。鉴此,本文利用祁连山讨赖河流域1957—2012年的气象观测资料,对该流域23个极端气候指数的时空变化特征做了研究。结果表明：（1）极端气温升高趋势明显,夜间和白天极端低温日数显著减少,极端气温昼指数显著增大;气温日较差变化幅度很小,霜冻日数显著减少,生长季长度明显加长,冰冻日数2000年后增加;夜指数增大幅度大于昼指数,秋、冬季极端气温升高幅度大于春、夏季。（2）极端降水指数增大趋势明显,雨日降水总量、连续五日降水总量和中雨天数均展现出增大态势,反映出连续降水事件的增加;极端降水量事件增大显著,但雨日降水强度变化不大;除最多连续无降水日数外,极端降水日数指数展现出增大趋势;降水日数夏、秋季节分配趋向均匀化;降水量的增加主要是单次降水时间持续加长和中雨日数增加的贡献;高海拔区极端降水事件发生的频次较大。     

东北振兴以来吉林省区域经济差异的时空演变研究

基于吉林省2003~2015年间地区生产总值和人均地区生产总值数据,以市域、县域两个尺度单元为研究对象,采用人口加权变异系数、基尼系数、泰尔指数等统计分析方法,对吉林省东北振兴战略实施以来的13 a内,区域经济差异的时空演变进行定量分析,并运用泰尔指数的分解方法,探讨了吉林省区域经济差异的空间格局。结果发现：① 吉林省区域经济总体差异、市域差异、县域差异均呈逐年下降趋势。② 通过差异贡献率显示：县域差异是区域总体差异变化的主导力量,长春市域的内部差异远高于其他市域,但有逐年减小的趋势,长吉两地的二元结构仍然突出,是全省区域经济差异产生的主要来源,主导着全省区域经济差异走向;③ 从2003~2015年来看,全省经济增长速度较快的地区主要还是集中在“三核一带”;④吉林省经济差异主要是由资源禀赋、产业结构、极化效应和政策导向等多种因素综合作用的结果。     

Calculation method for thickness of discontinuous boundary layer of engineering pavement

The boundary layer is a buffer layer of water and heat exchange between the atmosphere and permafrost.Based on the atmospheric boundary layer and heat transfer theory,we established a method for determining the boundary layer thickness of engineering pavement(asphalt and sand pavement)in permafrost region.The boundary layer can be divided into the Boundary Layer Above Surface(BLAS)and the Boundary Layer Below Surface(BLBS).From in-situ monitoring data,the thickness of BLAS was determined through the laminar thickness,and the thickness of BLBS was determined through ground temperature,the heat conduction function,and the mean attenuation function(α).For asphalt pavement,the BLAS thickness varied between 2.90 and 4.31 mm and that of BLBS varied between 28.00 and 45.38 cm.For sand pavement,the BLAS thickness varied between 2.55 and 3.29 mm and that of BLBS varied between 15.00 and 46.44 cm.The thickness varied with freezing and thawing processes.The boundary layer calculation method described in this paper can provide a relatively stable boundary for temperature field analysis.     

Capacity of soil loss control in the Loess Plateau based on soil erosion control degree

The capacity of soil and water conservation measures, defined as the maximum quantity of suitable soil and water conservation measures contained in a region, were determined for the Loess Plateau based on zones suitable for establishing terraced fields, forestland and grassland with the support of geographic information system (GIS) software. The minimum possible soil erosion modulus and actual soil erosion modulus in 2010 were calculated using the revised universal soil loss equation (RUSLE), and the ratio of the minimum possible soil erosion modulus under the capacity of soil and water conservation measures to the actual soil erosion modulus was defined as the soil erosion control degree. The control potential of soil erosion and water loss in the Loess Plateau was studied using this concept. Results showed that the actual soil erosion modulus was 3355 t?km^-2?a^-1, the minimum possible soil erosion modulus was 1921 t?km^-2?a^-1, and the soil erosion control degree was 0.57 (medium level) in the Loess Plateau in 2010. In terms of zoning, the control degree was relatively high in the river valley-plain area, soil-rocky mountainous area, and windy-sandy area, but relatively low in the soil-rocky hilly-forested area, hilly-gully area and plateau-gully area. The rate of erosion areas with a soil erosion modulus of less than 1000 t?km^-2?a^-1 increased from 50.48% to 57.71%, forest and grass coverage rose from 56.74% to 69.15%, rate of terraced fields increased from 4.36% to 19.03%, and per capita grain available rose from 418 kg?a^-1 to 459 kg?a^-1 under the capacity of soil and water conservation measures compared with actual conditions. These research results are of some guiding significance for soil and water loss control in the Loess Plateau.     

江南南部—华南北部前汛期严重旱涝诊断分析

利用江南南部—华南北部区域18个站45年（1951～1995年）4～6月降水资料计算了Z指数,确定出该区域严重涝年（1954、1962、1968、1973、1975年）和严重旱年（1958、1963、1967、1985、1991年）。分析了严重旱涝的频数分布和空间分布的特征,以及印度洋和太平洋整个赤道地区的SSTA、OLR距平场的分布。结果表明旱涝年SSTA、OLR距平场均有明显的差异。     

Grassland productivity in an alpine environment in response to climate change

Situated in a climatically stressful environment, alpine grassland is sensitive to subtle climate changes in its productivity. We remedy the current deficiency in studying grassland productivity by taking the integrated effect of all relevant factors into consideration. The relative importance of temperature, rainfall and evaporation to the alpine grassland productivity in western China was determined through analysis of their relationship with the normalized difference vegetation index (NDVI) between 1981 and 2000. Climate warming stimulated grassland productivity in the 1980s, but hampered it in the 1990s. Temperature is more important than rainfall to grassland productivity early in the growing season. However, their relative importance is reversed late in the growing season. Monthly summer month rainfall modified by maximum monthly temperature is a good predictor of alpine grassland productivity at 62.0 per cent. However, the best predictor is water deficiency, which is able to improve the estimation accuracy to 78.3 per cent. Hence, the impact of temperature on grassland productivity is better studied indirectly through evaporation.     

Simulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata

Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone.     

1983—2017年宁夏盐池县生态治理政策的类型与变化——基于政策工具视角

政策工具是政府实施政策的手段。结合盐池县1983-2017年出台的生态治理政策,运用内容分析法,从政策工具视角,对盐池县生态治理政策的类型与变化进行了分析,并深入探讨其原因。结果表明:强制型和混合型政策工具占主导地位,其中,规制、直接提供、信息与劝诫、补贴与奖励4种工具使用频率最高,自愿型工具的使用还很缺乏。政策工具的运用受到中央政策的显著影响。以后应当开发更多可利用的政策工具,并对不同政策工具进行优化组合。通过本研究可深入了解生态脆弱区地方政府生态政策的政策工具使用情况,为生态脆弱区生态保护的政策工具选择与优化组合提供参考。     

De(re)forestation and climate warming in subarctic China

Although tropical deforestation bears a close relationship with climate change, its exact contribution to climate warming and its threshold of exerting a noticeable influence remain unknown. This study attempts to bridge this knowledge gap by analyzing deforestation data of Heilongjiang Province, China in relation to climate data. It is found that forest cover was reduced from 238,335 km² in 1958 to 216,009 km² in 1980, and further to 207,629 km² in 2000. During this period the provincial annual temperature rose by 1.68 °C, against the nation-wide warming of 0.99 °C during the same period. At the provincial level the observed deforestation caused a warming in the vicinity of 0.69 °C. This warming does not bear any definite relationship with latitude and elevation. At the local scale, deforestation is related inversely to the rise in decadal temperature in the form of ΔT = −0.013ΔF + 0.4114 (R² = 0.30). There is a positive relationship between the accuracy (R² value) of predicting climate warming from deforestation and its severity. The critical threshold for deforestation to exert a noticeable impact on climate warming (e.g., R² = 50%) appears to be 5 km². The amount of forest cover at the beginning of a period can inhibit temperature rise, but its exact effect on climate warming is difficult to quantify.