With the socio-economic development associated with urbanization, the urban-rural relationship has changed across the world. In China, due to the urban-rural dual structure, these changes turn out to be more complicated. Spatial restructuring are suggested as the main strategies and spatial supporting platforms for urban-rural development. However, the theory still lacks solid methodology and support from systematic empirical studies. This study seeks an adequate scientific methodology and discusses the difference of urban-rural transformation in plains and mountainous areas. A case in Shanghang County, China, demonstrates: 1) The compound ecological niche model can be a suitable approach in urban-rural restructuring, especially in mountainous areas. 2) The urban-rural development area with highly inappropriate, slightly appropriate, moderately appropriate, and highly appropriate areas are 1273.2 km2 (44.69%); 906.1 km2 (31.80%); 509.4 km2 (17.88%); and 160.1 km2 (5.62%), respectively. 3) The “deserting villages” in mountainous areas play positive synergistic roles in urbanization, in contrast to the “hollowing villages” common in plain areas. 4) The central town-village will become the most important settlement in mountainous areas. Therefore, we suggest more attention should be paid to environmental capacity in the construction of central town-villages. This study significantly extends the understanding of “hollowing village” theory and regional planning.
Taking the semi-arid area of Yulin City as an example, this study improves the vulnerability assessment methods and techniques at the county scale using the VSD (Vulnerability Scoping Diagram) assessment framework, integrates the VSD framework and the SERV (Spatially Explicit Resilience-Vulnerability) model, and decomposes the system vulnerability into three dimensions, i.e., exposure, sensitivity and adaptive capacity. Firstly, with the full understanding of the background and exposure risk source of the research area, the vulnerability indexes were screened by the SERV model, and the index system was constructed to assess the characteristics of the local eco-environment. Secondly, with the aid of RS and GIS, this study measured the spatial differentiation and evolution of the social-ecological systems in Yulin City during 2000-2015 and explored intrinsic reasons for the spatial-temporal evolution of vulnerability. The results are as follows: (1) The spatial pattern of Yulin City’s SESs vulnerability is “high in northwest and southeast and low along the Great Wall”. Although the degree of system vulnerability decreased significantly during the study period and the system development trend improved, there is a sharp spatial difference between the system vulnerability and exposure risk. (2) The evolution of system vulnerability is influenced by the risk factors of exposure, and the regional vulnerability and the spatial heterogeneity of exposure risk are affected by the social sensitivity, economic adaptive capacity and other factors. Finally, according to the uncertainty of decision makers, the future scenarios of regional vulnerability are simulated under different decision risks by taking advantage of the OWA multi-criteria algorithm, and the vulnerability of the regional system under different development directions was predicted based on the decision makers' rational risk interval.
Soil erosion has become a significant environmental problem that threatens ecosystems globally. The risks posed by soil erosion, the trends in the spatial distribution in soil erosion, and the status, intensity, and conservation priority level in the middle reaches of the Yellow River Basin were identified from 1978 to 2010. This study employed a multi-criteria evaluation method integrated with GIS and multi-source remote sensing data including land use, slope gradient and vegetation fractional coverage (VFC). The erosion status in the study region improved from 1978 to 2010; areas of extremely severe, more severe, and severe soil erosion decreased from 0.05%, 0.94%, and 11.25% in 1978 to 0.04%, 0.81%, and 10.28% in 1998, respectively, and to 0.03%, 0.59%, and 6.87% in 2010, respectively. Compared to the period from 1978 to 1998, the area classed as improvement grade erosion increased by about 47,210.18 km2 from 1998 to 2010, while the area classed as deterioration grade erosion decreased by about 17,738.29 km2. Almost all severe erosion regions fall in the 1st and 2nd conservation priority levels, which areas accounted for 3.86% and 1.11% of the study area in the two periods, respectively. This study identified regions where soil erosion control is required and the results provide a reference for policymakers to implement soil conservation measures in the future.
Glacial lakes are not only the important refresh water resources in alpine region, but also act as a trigger of many glacial hazards such as glacial lake outburst flood (GLOF) and debris flow. Therefore, glacial lakes play an important role on the cryosphere, climate change and alpine hazards. In this paper, the issues of glacial lake were systematically discussed, then from the view of glacial lake inventory and glacial lake hazards study, the glacial lake was defined as natural water mainly supplied by modern glacial meltwater or formed in glacier moraine’s depression. Furthermore, a complete classification system of glacial lake was proposed based on its formation mechanism, topographic feature and geographical position. Glacial lakes were classified as 6 classes and 8 subclasses, i.e., glacial erosion lake (including cirque lake, glacial valley lake and other glacial erosion lake), moraine-dammed lake (including end moraine-dammed lake, lateral moraine-dammed lake and moraine thaw lake), ice-blocked lake (including advancing glacier-blocked lake and other glacier-blocked lake), supraglacial lake, subglacial lake and other glacial lake. Meanwhile, some corresponding features exhibiting on remote sensing image and quantitative indices for identifying different glacial lake types were proposed in order to build a universal and operational classification system of glacial lake.
Glaciers are the most important fresh-water resources in arid and semi-arid regions of western China. According to the Second Chinese Glacier Inventory (SCGI), primarily compiled from Landsat TM/ETM+ images, the Qilian Mountains had 2684 glaciers covering an area of 1597.81±70.30 km2 and an ice volume of ~84.48 km3 from 2005 to 2010. While most glaciers are small (85.66% are <1.0 km2), some larger ones (12.74% in the range 1.0-5.0 km2) cover 42.44% of the total glacier area. The Laohugou Glacier No.12 (20.42 km2) located on the north slope of the Daxue Range is the only glacier >20 km2 in the Qilian Mountains. Median glacier elevation was 4972.7 m and gradually increased from east to west. Glaciers in the Qilian Mountains are distributed in Gansu and Qinghai provinces, which have 1492 glaciers (760.96 km2) and 1192 glaciers (836.85 km2), respectively. The Shule River basin contains the most glaciers in both area and volume. However, the Heihe River, the second largest inland river in China, has the minimum average glacier area. A comparison of glaciers from the SCGI and revised glacier inventory based on topographic maps and aerial photos taken from 1956 to 1983 indicate that all glaciers have receded, which is consistent with other mountain and plateau areas in western China. In the past half-century, the area and volume of glaciers decreased by 420.81 km2 (-20.88%) and 21.63 km3 (-20.26%), respectively. Glaciers with areas <1.0 km2 decreased the most in number and area recession. Due to glacier shrinkage, glaciers below 4000 m completely disappeared. Glacier changes in the Qilian Mountains presented a clear longitudinal zonality, i.e., the glaciers rapidly shrank in the east but slowly in the central-west. The primary cause of glacier recession was warming temperatures, which was slightly mitigated with increased precipitation.
Coupled hydrological and atmospheric modeling is an efficient method for snowmelt runoff forecast in large basins. We use short-range precipitation forecasts of mesoscale atmospheric Weather Research and Forecasting (WRF) model combining them with ground-based and satellite observations for modeling snow accumulation and snowmelt processes in the Votkinsk reservoir basin (184,319 km2). The method is tested during three winter seasons (2012-2015). The MODIS-based vegetation map and leaf area index data are used to calculate the snowmelt intensity and snow evaporation in the studied basin. The GIS-based snow accumulation and snowmelt modeling provides a reliable and highly detailed spatial distribution for snow water equivalent (SWE) and snow-covered areas (SCA). The modelling results are validated by comparing actual and estimated SWE and SCA data. The actual SCA results are derived from MODIS satellite data. The algorithm for assessing the SCA by MODIS data (ATBD-MOD 10) has been adapted to a forest zone. In general, the proposed method provides satisfactory results for maximum SWE calculations. The calculation accuracy is slightly degraded during snowmelt periods. The SCA data is simulated with a higher reliability than the SWE data. The differences between the simulated and actual SWE may be explained by the overestimation of the WRF-simulated total precipitation and the unrepresentativeness of the SWE measurements (snow survey).
Coal is a basic resource and its use guarantees the development of national economies and human society. Thus, coal transportation is an important part of China’s overall transportation system. In this system, ports are the vital transit nodes. This study considered coastal ports in China and analysed the evolution of coal transportation from 1973 to 2013. We focused on the spatial pattern of coal loading and unloading, and summarized the main characteristics and development of the processes. Then, we examined the volumes of coal transported and regional changes in these amounts using mathematical models and indicators. Finally, we analysed the specialized function and spatial differentiation of the ports involved in coal transportation to reveal their spatial relationship and temporal evolution. We found that the spatial pattern of coal transportation changed from “south input and north output” to “all input and north output”. However, the prominent ports used for coal unloading are still concentrated in areas south of the Yangtze River. Coal loading is concentrated on the west bank of Bohai Bay. In addition, some ports around Bohai Bay, such as Dandong, Dalian, Yantai, and Qingdao, changed from traditional coal loading ports to unloading ports. This study further developed the theory of transport geography, and improved our understanding of China’s coal transportation system.