The influence of climate change on the natural environmental and socio-economic system leads to a series of adverse effects. With the development of socio-economy, climate change hazards interact with the environmental and socio-economic risk bearing body and form the spatial-temporal patterns of climate change risk. The systematic expression of the spatial-temporal patterns is the scientific foundation of climate changes adaptation. Based on the RCP8.5 climate scenario data from 2021 to 2050, we analyzed the variation trend and rate of temperature and precipitation, and assessed the hazard of extreme climate events including drought, heat wave and flood. Then, economy, population, food production and ecosystem were selected as the risk bearing bodies to assess the possible impacts of climate change as the indices qualifying the comprehensive climate change risk. Under the guidance of systematic principle, predominating factor principle, as well as the space consecution principle, we proposed a scheme of three-level regional division system for the comprehensive climate change risk regionalization in China. Finally, the Chinese mainland was divided into 8 climate change sensitive zones, 19 danger zones of extreme events and 46 comprehensive risk zones of bearing body. The result shows that the climate changes high risk zones in China under the RCP8.5 climate scenario from 2021 to 2050 include North China weak warming and precipitation increased sensitive zone, North China Plain heat wave danger zone, population-economy-food high risk zone, South China-Southwest China weak warming and precipitation increased sensitive zone, Yunnan-Guizhou mountain heat wave danger zone, ecosystem-economy-food-population high risk zone; coastal South China flood-heat wave danger zone, ecosystem-food-economy-population high risk zone. The comprehensive climate change risk regionalization of China covers the climate change scenarios, the extreme events, and the possible lost information of the socio-economy and ecosystem, which can provide scientific and technological support for national and local governments to cope with the climate change and risk management.
Changes in hydrological processes and water resources under climate change in the Tianshan Mountains of Central Asia have been investigated based on data analysis and paper review. Under the context of global warming hiatus, temperature of the Tianshan Mountains in Central Asia has been in a state of high variability, which has accelerated the melting of glacier and snow. Warming has resulted in a series of changes in water resources. Snowfall fraction decreased from 11%-24% in 1960-1998 to 9%-21% in 2000-2014, 97.25% of the glaciers retreated in the last 50 years; and water storage decreased at a rate of -3.72 mm/a during 2003-2014. Warming has led to changes in mountainous hydrological processes and water resources. The runoff in the Tianshan Mountains has increased due to the accelerated glacier/snow melt, however, the runoff will decrease in the long term under continuous warming and current precipitation conditions.
In this paper, the literatures about the drought and flood disasters in Baoji region during the Ming and Qing dynasties were collected and sorted. The drought and flood disaster chains were discussed, while the response to climate change in Baoji region during 1368-1911 years was analyzed by using the accumulative anomaly method, moving average method and wavelet analysis and so on. The results showed that 297 events of drought and flood disasters occurred in Baoji during 1368-1911, while drought occurred 191 times and flood 106 times, accounting for 64.31% and 35.69%, respectively. There were obvious stage characteristics for drought and flood disasters, with drought episodes mainly observed from 1368 to 1644, while during 1645-1804 a fluctuant phase emerged, and the period 1805-1911 experienced drought episodes, presenting the alternating drought-wet period on the whole. Meanwhile there were three periods (70a, 110a and 170a) of oscillation on time scale of drought and flood existence, which had relationship with sunspot activity cycle. Drought and flood disasters had obvious variations in space; the northern and eastern parts of the Weihe river basin were prone to drought and flood. The occurrence of drought and flood disaster chains was a response to global climate change during the Ming and Qing dynasties in Baoji. Since the 1760s, the global climate deterioration has led to frequent extreme drought and flood disaster events.
Using NDVI3g vegetation index, we defined 18 phenological metrics to investigate phenology change in the Tibetan Plateau (TP). Considering heterogeneity of vegetation phenology, we divided TP into 8 vegetation clusters according to 1:1000000 vegetation cluster map. Using partial least regression (PLS) method, we investigated impacts of climate variables such as temperature, precipitation and solar radiation on vegetation phenology. Results indicated that: (1) Turning points of the date of the start of growing season (SOS) metrics are mainly observed during 1997-2000, before which SOS advanced 2-3 d/a. Turning points of the date of the end of growing season (EOS) and length of growing season (LOS) metrics are found during 2005 and 2004-2007, respectively. Before the turning point, EOS has a delayed tendency of 1-2 d/10a, and LOS has a lengthening tendency of 1-2 d/10a. After the turning point, the tendency of SOS and EOS metrics is questionable. Meanwhile, lengthening of LOS is not statistically significant; (2) Alpine meadows and alpine shrub meadows are subject to the most remarkable changes. Lengthening LOS of alpine meadow is mainly due to advanced SOS and delayed EOS. Nevertheless, lengthening LOS of alpine shrub meadow is attributed mainly to advanced SOS; (3) Using PLS method, we quantified impacts of meteorological variables such as temperature, precipitation and solar radiation on phenology changes of alpine meadows and alpine shrub meadows, indicating that temperature is the dominant meteorological factor affecting vegetation phenology. In these two regions, autumn of last year and early winter temperature of last year have a positive effect on SOS. Firstly, increased temperature in this period would postpone last year's EOS, and hence indirectly delay SOS of the current year; Secondly, warming autumn and early winter have the potential to negatively impact fulfilment of chilling requirements, leading to delay of SOS. Except summer, minimum temperature has a similar effect on vegetation phenology, when compared to average and maximum temperature. Furthermore, precipitation effects on phenology fluctuate widely across different months. Precipitation of the autumn and winter/spring of the last year has a negative/positive effect on SOS. Besides, precipitation acts as the key driver constraining vegetation growth in August, during which precipitation has a positive impact on EOS. Therefore, solar radiation can exert impacts on vegetation phenology mainly during summer and early fall. Our research will provide a scientific support for the improvement of vegetation phenology model.
Flowering phenology is of great importance for flower tourism planning, landscape arrangement, and pollen allergy forecast. Previous studies mainly focused on the changes in the first flowering date of plants, but rarely examined the spatiotemporal changes in flowering duration. In this study, we systematically analyzed the changes in flowering durations for 23 woody plants at 42 sites from China Phenological Observation Network (CPON) during 1963-2012. Through investigations on the spatiotemporal patterns, interspecific difference, and the forms of change in flowering durations, the following conclusions are drawn. (1) Out of all the 259-time series, flowering durations have lengthened in 159-time series (61.39%), where 21.24% have lengthened significantly. The extending trends for shrub species are found to be more significant than those for tree species. (2) Most flowering durations in the south of Northeast China, East China, and Central China exhibited trends of shortening, but those in the north of Northeast China, North China, parts of Southwest China, and South China exhibited extending trends. The strongest trend (0.94 d/a) occurred at around 20°N. The mean trend of flowering duration (0.28 d/a) in western China (87°E-112°E) was larger than that in eastern China (0.05 d/a). (3) The overall changes in flowering duration could be identified into three stages: 1963-1980 (shorter), 1981-1997 (close to multi-year average) and 2001-2012 (longer), although evident difference existed among species. (4) As for the time series with extending flowering duration, 43.39% were induced by a much earlier first flowering date than the end of flowering date. For the time series with shortening flowering duration, 62% were caused by a more advanced trend at the end of flowering date than at the first flowering date.
Regional information on the spatial distribution of soil salinity can be used as guidance in avoiding the continued degradation of land and water resources. However, most regional soil salinity maps are produced through a conventional direct-linking method derived from historic observations. Such maps lack spatial details and are limited in describing the evolution of soil salinization in particular instances. In anthropogenic regions, soil change, and soil formation and degradation, have accelerated, jeopardizing soil quality and health. The need for up-to-date soil and environmental data that characterize the physicochemical, biological, and hydrological conditions of arid ecosystems across continents has intensified (e.g. soil salinization in arid land). Digital soil mapping (DSM) and modeling techniques have been widely used in the past few decades. To overcome these limitations, we employed a method that included an integrative hierarchical-sampling strategy (IHSS) and the Soil Land Inference Model (SoLIM) to map soil salinity over a regional area. This case study, the Xinjiang Uygur Autonomous Region of China, demonstrates that the employed method can produce soil salinity maps at a higher level of spatial detail and accuracy. Twenty-three representative points are determined. The results show that: (1) the prediction is accurate in Kuqa Oasis (R2=0.70, RPD=1.55, RMSE=12.86) and Keriya Oasis (R2=0.75, RPD=1.66, RMSE=10.92), and performed a little better than in Fukang Oasis (R2=0.77, RPD=2.01, RMSE=6.32), according to the evaluation criteria. (2) Based on all validation samples from three oases, accuracy estimation shows that the employed method (R2= 0.74, RPD=1.67, RMSE=11.18) performed better than the multiple linear regression model (R2=0.60, RPD= 1.47, RMSE=14.45). Finally, this study concludes that the employed method can serve as an alternative model for soil salinity mapping on a large scale.
Central Asia, which is an arid inland area, has the most severe water-resource problems in the world. This paper reviews the literature on water issues in Central Asia published in the last 15 years (i.e., since 2000), covering the quantity of literature, the research institutes involved, the research approaches, and the major issues in the subject. The following conclusions can be reached based on the literature: (1) Water issues in Central Asia are an important area of geographical research. Many studies from China, Germany, the USA, and other countries have focused on the responses of water cycling processes to climate change, and on the hydrological environment of the catchment. In addition, Chinese researchers have tended to focus their studies on trans-boundary river management. (2) Temperature rise and precipitation increase are the fundamental features of climate change in Central Asia. Terrestrial water storage and river runoff have an obvious decrease as a result of temperature rise. (3) Soil salinization, land degradation and water pollution have been worsened by irrational utilization of water resources, and all of these have increased the pressures on the environment of the catchment. (4) Complicated geopolitics makes it difficult for the international community to manage the trans-boundary rivers in Central Asia. The water utilization situation in Central Asian countries is getting worse, which causes a series of ecological problems and even endangers the stability of social and economic development. Important future directions for studies on water issues in Central Asia include the relationships between population, resources and environment; the interaction mechanism of hydrology, methodological, social and political aspects; as well as the collection of basic hydrological data.
Geomorphic evolution often presents a spatial pattern of a "young to old" distribution under certain natural environment condition, whereby sampling the geomorphic types and characteristics in spatial sequence can provide some evidence for the evolution of the individual geomorphologic object. This so-called space-for-time substitution has been a methodology in geomorphology research. This paper firstly introduced the basic concepts and background of space-for-time substitution, then a full review has been conducted of recent research progress in geomorphic evolution based on space-for-time substitution, such as fluvial landform, structural landform, estuarine landform and coastal landform. Finally, the explicit terms like suitable conditions, influencing factors and classifications have been summarized so that the research paradigm of space-for-time substitution was proposed. We argued that in the future, the researchers should focus on a full use of massive geographic data for geomorphic evolution research at multi-spatial scales, as well as an effective combination with physical mechanisms and statistical laws for a comprehensive geomorphic evolution modelling.
Due to its rapid economic development in recent years, China is becoming ever more urbanized. With this background of urbanization, land use and land cover change are complex in urban-rural continuum where the land is characterized by both town and country usages. The urban-rural continuum of Harbin City, Heilongjiang Province was chosen as the study area. Impervious surface from the Harbin urban-rural continuum was extracted by a linear spectral mixture analysis method based on the Landsat TM image acquired in the years of 1984, 1993, 2002 and 2010. The temporal and spatial variations of the urban impervious surface were examined. A boosted regression tree was employed to identify the most important factor that has been affecting the expansion of the impervious surface since 1984 from among eight factors, i.e. slope, aspect, DEM, distance to river, distance to expressway, distance to railway, distance to main road, and distance to the central city in 1984. The results indicate that the proportion of impervious surfaces in the Harbin rural-urban continuum was 3.9% in 1984, 6.6% in 1993, 9.0% in 2002, and 16.52% in 2010. The distribution patterns of impervious surface coverage from 1984 to 2010 showed obvious spatial variations. Traffic factors, including expressways, railways, and main roads, have been propelling the development of surrounding area, and inducing the rapid expansion of cities along the roads.
Spatial stratified heterogeneity is the spatial expression of natural and socio-economic process, which is an important approach for human to recognize nature since Aristotle. Geodetector is a new statistical method to detect spatial stratified heterogeneity and reveal the driving factors behind it. This method with no linear hypothesis has elegant form and definite physical meaning. Here is the basic idea behind Geodetector: assuming that the study area is divided into several subareas. The study area is characterized by spatial stratified heterogeneity if the sum of the variance of subareas is less than the regional total variance; and if the spatial distribution of the two variables tends to be consistent, there is statistical correlation between them. Q-statistic in Geodetector has already been applied in many fields of natural and social sciences which can be used to measure spatial stratified heterogeneity, detect explanatory factors and analyze the interactive relationship between variables. In this paper, the authors will illustrate the principle of Geodetector and summarize the characteristics and applications in order to facilitate the using of Geodetector and help readers to recognize, mine and utilize spatial stratified heterogeneity.
The northern border of the tropical zone of China has been the focus of studies on comprehensive physical regionalization. Based on different indexes and methods, the border was delineated by different scholars, but their results varied greatly. Based on the Geodetector model and regionalization thought of spatial stratified heterogeneity, the northern border of the tropical zone of China's mainland was investigated. Climatic elements were used as dominant demarcation partitioning indexes, combined with auxiliary indexes such as soil and multiple cropping types. The key results were as follows: (1) Using Geodetector, the northern border of the tropical zone was delineated. From west to east, the border goes through Lincang, Simao, Yuxi and Gejiu in Yunnan, Baise, Mashan, Guigang and Wuzhou in Guangxi, Zhaoqing, Guangzhou, Huizhou, Heyuan and Meizhou in Guangdong, and Zhangzhou, Quanzhou and Putian in Fujian. It generally agrees with the 12℃ isotherm of the coldest monthly mean temperature, soil border between lateritic red soil and red soil, and border of double cropping rice or its continuous thermophile dry framing and single (double) cropping rice or its continuous chimonophilous dry framing. (2) The q average value of all indexes for the border was 0.40. Using this model, regionalization principles—homogeneity of the within-strata value and heterogeneity of the between-strata value—were satisfied. The border meets the requirements of zonal heterogeneity between tropical and subtropical zones. Therefore, it is reasonable to use Geodetector in studies of comprehensive physical regionalization, and it can provide high-precision technical support.
Hu Line uncovers one of China's most important characteristics of population paper distribution: East is dense, while west is sparse. Different from most previous research, this paper examined the differentiation and changes of population distribution on both sides of Hu Line from a perspective of spatial stratified heterogeneity instead. Geodetector was employed based on the spatial database of China's census data of 1953, 1982, 1990, 2000 and 2010 to reconfirm spatial position of Hu Line and analyzed changes of spatial stratified heterogeneity of population between southeast and northwest sides of Hu Line in different periods. Changes of population distribution since the founding of New China were found and the reasons for these changes were discussed. Major findings include: (1) From the spatial stratified heterogeneity perspective, Hu Line could be improved and optimized, at least, in some periods. Although the ratio of total population on both sides of Hu Line has roughly been kept at 94:6 since 1953, spatial stratified heterogeneity of population between the two sides (the southeastern side: the northwestern side) increased when Hu Line moves to south slightly in 1953, 2000 and 2010, which means population distribution was more homogeneous within either southeastern or northwestern region and heterogeneity was more remarkable between the two regions. (2) Heterogeneity decreased gradually since the reform and opening up. We found characteristics of population distribution converged on the two sides, especially since the 1990s when convergence between the two sides became apparent. This finding is significantly different from the conclusion of "remain unchanged" from most literatures. The reasons why heterogeneity reduced were: pattern of population distribution on the southeastern side changed from relatively even distribution among cities before 1990 to agglomeration in a few huge cities after 2000, while the degree of spatial agglomeration of population decreased slightly after the reform on the northwestern side. These changes have been confirmed by the analysis from cumulative distribution function and Gini coefficient. (3) On the whole, the effect of economic factors on population distribution has become more and more important, while the effect of natural environment and institution reduced. Combined effect from economic development, natural environment and institution resulted in two opposite directions of changes of population spatial distribution on the two sides. It should be emphasized that although general effect of natural environment has decreased, some natural factors, such as Three Gradient Terrains, still have significantly influence on population distribution in China.
Rural poverty has long aroused attention from countries around the world, and eliminating poverty and achieving realize common prosperity is an important mission to build the well-off society in an all-round way. Scientifically revealing the regional differentiation mechanism of rural poverty has become an important issue of implementation of national poverty alleviation strategy. This paper, taking Fuping County of Hebei Province as a typical case, diagnoses the dominant factors of differentiation of rural poverty and reveals the dynamic mechanism of rural poverty differentiation by using the Geodetector model and multiple linear regressions, and puts forward the poverty alleviation policies and models for different poverty regions. The result shows that the dominant factors affecting rural poverty differentiation include slope, elevation, per capita arable land resources, distance to the main roads and distance to the center of county, and their power determinant value to poverty incidence differentiation are 0.14, 0.15, 0.15, and 0.17. These factors affect the occurrence of poverty from different aspects and their dynamic mechanism is also different. Among various factors, the slope and per capita arable land resources affect the structure and mode of agricultural production, while distance to the main roads and distance to the center of county have influence on the relationship between the interior and exterior of the region. There are significant differences in the four types identified of regional rural poverty, namely, environment constrained region mainly affected by slope (seven towns), resource oriented region mainly affected by per capita arable land (seven towns), area dominated by traffic location affected by distance to the main roads (three towns), and economic development leading area mainly affected by distance to the center of county (four towns). Then, Fuping County is divided into single core, dual core and multi-core area according to the number of core elements of the township. The county has shown a multi differentiation of rural poverty with a horizontal center of dual core area, and both sides have a single core and multi-core, which are affected by different dominant factors. Finally, this paper suggests that policy of targeted poverty alleviation should take science and technology as the foundation and form innovation of targeted poverty alleviation according to the core dominant factors of the differentiation mechanism of rural poverty. The county's poverty alleviation and development under different driving mechanisms need orderly promotion of poverty alleviation and integration of urban and rural development strategy with adjusting measures to local conditions, respecting for science, and stressing practical results.
