The method for surface modelling of land cover scenarios (SMLCS) has been improved to simulate the scenarios of land cover in Eurasia. On the basis of the observation monthly climatic data observed from 2127 weather stations in Eurasia during 1981-2010, the climatic scenarios data of RCP26, RCP45 and RCP85 scenarios released by CMIP5, and the land cover current data of Eurasia in 2010, the land cover scenarios of Eurasia were respectively simulated. The results show that most land cover types would generally have similar changing trends in the future, but with some difference in different periods under the three scenarios of RCP26, RCP45 and RCP85. Deciduous needleleaf forest, mixed forest, shrub land, wetlands and snow and ice would generally decrease in Eurasia during 2010-2100. Snow and ice would have the fastest decreasing rate that would decrease by 37.42% on average. Shrub land would have the slowest decreasing rate that would decrease by 5.65% on average. Water bodies would have the fastest increasing rate that would increase by 28.78% on average. Barren or sparsely vegetated land would have the slowest increasing rate that would increase by 0.76%. Moreover, the simulated results show that climate change would directly impact on land cover change in Eurasia.

Based on the Beijing Climate Center’s land surface model BCC_AVIM (Beijing Climate Center Atmosphere-Vegetation Interaction Model), the ensemble Kalman filter (EnKF) algorithm has been used to perform an assimilation experiment on the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product to study the influence of satellite LST data frequencies on surface temperature data assimilations. The assimilation results have been independently tested and evaluated by Global Land Data Assimilation System (GLDAS) LST products. The results show that the assimilation scheme can effectively reduce the BCC_AVIM model simulation bias and the assimilation results reflect more reasonable spatial and temporal distributions. Diurnal variation information in the observation data has a significant effect on the assimilation results. Assimilating LST data that contain diurnal variation information can further improve the accuracy of the assimilation analysis. Overall, when assimilation is performed using observation data at 6-hour intervals, a relatively good assimilation result can be obtained, indicated by smaller bias (<2.2K) and root-mean-square-error (RMSE) (<3.7K) and correlation coefficients larger than 0.60. Conversely, the assimilation using 24-hour data generally showed larger bias (>2.2K) and RMSE (>4K). Further analysis showed that the sensitivity of assimilation effect to diurnal variations in LST varies with time and space. The assimilation using observations with a time interval of 3 hours has the smallest bias in Oceania and Africa (both<1K); the use of 24-hour interval observation data for assimilation produces the smallest bias (<2.2K) in March, April and July.

Aridity index reflects the exchanges of energy and water between the land surface and the atmosphere, and its variation can be used to forecast drought and flood patterns, which makes it of great significance for agricultural production. The ratio of potential evapotranspiration and precipitation is applied to analyse the spatial and temporal distributions of the aridity index in the Belt and Road region under the 1.5℃ and 2.0℃ global warming scenarios on the basis of outputs from four downscaled global climate models. The results show that: (1) Under the 1.5℃ warming scenario, the area-averaged aridity index will be similar to that in 1986-2005 (around 1.58), but the changes vary spatially. The aridity index will increase by more than 5% in Central-Eastern Europe, north of West Asia, the monsoon region of East Asia and northwest of Southeast Asia, while it is projected to decrease obviously in the southeast of West Asia. Regarding the seasonal scale, spring and winter will be more arid in South Asia, and the monsoon region of East Asia will be slightly drier in summer compared with the reference period. While, West Asia will be wetter in all seasons, except winter. (2) Relative to 1986-2005, both areal averaged annual potential evapotranspiration and precipitation are projected to increase, and the spatial variation of aridity index will become more obvious as well at the 2.0℃ warming level. Although the aridity index over the entire region will be maintained at approximately 1.57 as that in 1.5℃, the index in Central-Eastern Europe, north of West Asia and Central Asia will grow rapidly at a rate of more than 20%, while that in West Siberia, northwest of China, the southern part of South Asia and West Asia will show a declining trend. At the seasonal scale, the increase of the aridity index in Central-Eastern Europe, Central Asia, West Asia, South Asia and the northern part of Siberia in winter will be obvious, and the monsoon region in East Asia will be drier in both summer and autumn. (3) Under the scenario of an additional 0.5℃ increase in global temperature from 1.5℃ to 2.0℃, the aridity index will increase significantly in Central Asia and north of West Asia but decrease in Southeast Asia and Central Siberia. Seasonally, the aridity index in the Belt and Road region will slightly increase in all other seasons except spring. Central Asia will become drier annually at a rate of more than 20%. The aridity index in South Asia will increase in spring and winter, and that in East Asia will increase in autumn and winter. (4) To changes of the aridity index, the attribution of precipitation and potential evapotranspiration will vary regionally. Precipitation will be the major influencing factor over southern West Asia, southern South Asia, Central-Eastern Siberia, the non-monsoon region of East Asia and the border between West Asia and Central Asia, while potential evapotranspiration will exert greater effects over Central-Eastern Europe, West Siberia, Central Asia and the monsoon region of East Asia.

Drought is one of the most frequent and widespread natural disasters and has tremendous agricultural, ecological, societal, and economic impacts. Among the many drought indices, the standardized precipitation index (SPI) based on monthly precipitation data is simple to calculate and has multiscale characteristics. To evaluate the applicability of high spatiotemporal resolution satellite precipitation products for drought monitoring, based on the Tropical Rainfall Measuring Mission (TRMM) products and station-based meteorological data, the SPI values at different time scales (1, 3, 6, and 12 months) were calculated for the period of 1998-2016 in the middle and lower reaches of the Yangtze River Basin (MLRYRB). The temporal correlations show that there is a high degree of consistency between calculations at the different time scales (1, 3, 6 and 12 months) based on the two data sources and that the amplitude of fluctuations decreases with increasing time scale. In addition, the Mann-Kendall (MK) test method was applied to analyze the trends from 1998 to 2016, and the results suggest that wetting trends clearly prevailed over drying trends. Moreover, a correlation analysis of the two data sources based on 60 meteorological stations was performed with the SPI values at different time scales. The correlation coefficients at the short time scales (1, 3, and 6 months) are all greater than 0.7, and the correlation coefficient at the long time scale (12 months) is greater than 0.5. In summary, the results demonstrate that the TRMM 3B43 precipitation product provides a new data source that can be used for reliable drought monitoring in the MLRYRB.

The countries throughout the Belt and Road region account for more than 60% of the world’s population and half of the global economy. Future changes in this area will have significant influences on the global economic growth, industrial structure and resource allocation. In this study, the proportion of the urban population to the total population and the gross domestic product were used to represent the levels of urbanization and economic development, respectively. The population, urbanization and economic levels of the Belt and Road countries for 2020-2050 were projected under the framework of the IPCC's shared socioeconomic pathways (SSPs), and the following conclusions are drawn. (1) The population, urbanization and economic levels in the Belt and Road region will likely increase under all five pathways. The population will increase by 2%-8%/10a during 2020-2050 and reach 5.0-6.0 billion in 2050. Meanwhile, the urbanization rate will increase by 1.4%-7.5%/10a and reach 49%-75%. The GDP will increase by 17%-34%/10a and reach 134-243 trillion USD. (2) Large differences will appear under different scenarios. The SSP1 and SSP5 pathways demonstrate relatively high urbanization and economic levels, but the population size is comparatively smaller; SSP3 shows the opposite trend. Meanwhile, the economy develops slowly under SSP4, but it has a relatively high urbanization level, while SSP2 exhibits an intermediate trend. (3) In 2050, the population will increase relative to 2016 in most countries, and population size in the fastest growing country in Central Asia and the Middle East countries will be more than double. Urbanization will develop rapidly in South Asia, West Asia and Central Asia, and will increase by more than 150% in the fastest growing countries. The economy will grow fastest in South Asia, Southeast Asia and West Asia, and increase by more than 10 times in some counties with rapid economic development.

The climate change and Land Use/Land Cover (LULC) change both have an important impact on the rainfall-runoff processes. How to quantitatively distinguish and predict the impacts of the above two factors has been a hot spot and frontier issue in the field of hydrology and water resources. In this research, the SWAT (Soil and Water Assessment Tool) model was established for the Jinsha River Basin, and the method of scenarios simulation was used to study the runoff response to climate change and LULC change. Furthermore, the climate variables exported from 7 typical General Circulation Models (GCMs) under RCP4.5 and RCP8.5 emission scenarios were bias corrected and input into the SWAT model to predict runoff in 2017-2050. Results showed that: (1) During the past 57 years, the annual average precipitation and temperature in the Jinsha River Basin both increased significantly while the rising trend of runoff was far from obvious. (2) Compared with the significant increase of temperature in the Jinsha River Basin, the LULC change was very small. (3) During the historical period, the LULC change had little effect on the hydrological processes in the basin, and climate change was one of the main factors affecting runoff. (4) In the context of global climate change, the precipitation, temperature and runoff in the Jinsha River Basin will rise in 2017-2050 compared with the historical period. This study provides significant references to the planning and management of large-scale hydroelectric bases at the source of the Yangtze River.

ENSO is an interannual mode which may be affected by external forcing, such as volcanic eruptions. Based on the reconstructed volcanic eruptions chronology and ENSO sequences, both 195 large volcanic eruptions (VEI≥4) and 398 ENSO (El Ni?o and La Ni?a) events were extracted from 1525 to 2000. An analysis of the correspondence between the large volcanic eruptions and ENSO events was performed by matching the large volcanic eruptions with the types and magnitudes of ENSO events present in the 0–2 years after the eruptions. The results show the following: (1) The percentages of ENSO events within the 3 years after the large eruptions had increased to 68.3% from 31.7% compared with those with no-eruptions in the previous 0–2 years. In addition, the ratio of El Ni?o to La Ni?a events turned from 2:3 to 1:1, and more El Ni?o events occurred in the 0 year after eruptions in the low-latitudes of the Northern Hemisphere and in the tropics but more La Ni?a events occurred in the 0 year after in the high-latitudes of the Northern Hemisphere and the Southern Hemisphere. (2) After the eruptions, the weak (W) El Ni?o events had increased by 8 percentage points and the very strong (VS) El Ni?o events had decreased by 10 percentage points; conversely, there was a decrease by 15 percentage points of the weak La Ni?a events and an increase by 11.4 percentage points of the very strong La Ni?a events. Specifically, the percentages of strong La Ni?a events increased to a peak at 1 (+1) year after the eruptions. (3) The percentage of eruptions followed by single-year ENSO was the greatest. The percentage of ENSO events that occurred in the consecutive 2 years following an eruption was approximately equal to the percentage of events that occurred consecutively 3 years following an eruption, and both sets of ENSO magnitudes showed a decreasing trend.

The Medieval Climate Anomaly (MCA, AD950-1250) is the most recent warm period lasting for several hundred years and is regarded as a reference scenario when studying the impact of and adaptation to global and regional warming. In this study, we investigated the characteristics of temperature variations on decadal-centennial scales during the MCA for four regions (Northeast, Northwest, Central-east, and Tibetan Plateau) in China, based on high-resolution temperature reconstructions and related warm-cold records from historical documents. The ensemble empirical mode decomposition method is used to analyze the time series. The results showed that for China as a whole, the longest warm period during the last 2000 years occurred in the 10th-13th centuries, although there were multi-decadal cold intervals in the middle to late 12th century. However, in the beginning and ending decades, warm peaks and phases on the decadal scale of the MCA for different regions were not consistent with each other. On the inter-decadal scale, regional temperature variations were similar from 950 to 1130; moreover, their amplitudes became smaller, and the phases did not agree well from 1130 to 1250. On the multi-decadal to centennial scale, all four regions began to warm in the early 10th century and experienced two cold intervals during the MCA. However, the Northwest and Central-east China were in step with each other while the warm periods in the Northeast China and Tibetan Plateau ended about 40-50 years earlier. On the multi-centennial scale, the mean temperature difference between the MCA and Little Ice Age was significant in Northeast and Central-east China but not in the Northwest China and Tibetan Plateau. Compared to the mean temperature of the 20th century, a comparable warmth in the MCA was found in the Central-east China, but there was a little cooling in Northeast China; meanwhile, there were significantly lower temperatures in Northwest China and Tibetan Plateau.

Based on the revised First Chinese Glacier Inventory (FCGI), the Second Chinese Glacier Inventory (SCGI) and Landsat OLI images for 2015-2016, we analyzed the spatial-temporal variation characteristics of glaciers in the Gangdisê Mountains from 1970 to 2016. The results showed that there were 3953 glaciers with a total area of 1306.45 km ² and ice volume of ~58.16 km ³ in the Gangdisê Mountains in 2015-2016. Glaciers with sizes of 0.1-5 km ² and <0.5 km ² accounted for the largest area and the most amounts of glaciers in the Gangdisê Mountains, respectively. Over the past five decades, the area of glaciers in the Gangdisê Mountains decreased by 854.05 km ² (-1.09%·a ^-1), accounting for 39.53% of the total glacier area in 1970. The increase in temperature during the ablation period was the most important cause for glacier retreat. Compared to other mountains in western China, the Gangdisê Mountains have experienced the strongest glacial retreat, and the rate of recession has increased in recent years. The decrease of glacier area was mainly concentrated at elevations of 5600-6100 m, and no change in glacier area was observed at elevations above 6500 m. The number and area of glaciers decreased in all orientations in the Gangdisê Mountains except for south- and southeast-oriented glaciers. Among them, north-oriented glaciers suffered the largest loss of glacier area, while glacier retreat saw the fastest in northwest-oriented glaciers. The rate of glacier retreat increased from west to east in the Gangdisê Mountains. The relative rate of glacier area change was the highest in the eastern section of the Gangdisê Mountains (-1.72%·a ^-1), followed by the middle section (-1.67%·a ^-1) and the western section (-0.83%·a ^-1).

The morphological changing trend of the Yangtze Estuary, the largest estuary of Asia, has become a focus of research in recent years. Based on a long series of topographic data from 1950 to 2015, this paper studied the erosion-deposition pattern of the entire Yangtze Estuary. An alternation between erosion and deposition was found during the past 65 years, which was in correspondence to the alternation between flood and dry periods identified by multi-year average duration days of high-level water flow (defined as discharge ≥ 60,000 m ³/s, namely, D_≥60,000) from the Yangtze River Basin. A quantitative relationship was further developed between the erosional/depositional rate of the Yangtze Estuary and the interpreting variables of yearly water discharge, D_≥60,000 and yearly river sediment load, with contributing rates of 1%, 59% and 40%, respectively. Mechanism behind the alternate erosion and deposition pattern was analyzed by examining residual water surface slope and the corresponding capacity of sediment transport in flood and dry periods. In flood periods, a larger discharge results in steeper slope of residual water level which permits a greater capacity of sediment transport. Therefore, more bed materials can be washed to the sea, leading to erosion of the estuary. In contrast, flatter slope of residual water level occurs in dry periods, and deposition dominates the estuarine area due to the decreased capacity of sediment transport and the increased backwater effect of flood-tide. Coastal dynamics and estuarine engineering projects alter the local morphological changes, but slightly affect the total erosional/depositional rate of the whole estuarine region. Heavy sedimentation within the Yangtze Estuary after the impoundment of the Three Gorges Dam can be attributed to the reduced occurrence frequency of flood years due to water regulation by the dam, and largely (at least 36%-52%) sourced from the sea. Deposition is still possible to occur in the Yangtze Estuary in the future, because the multi-year average D_≥60,000 is unlikely to exceed the critical value of 14 days/yr which corresponds to the future equilibrium state of the Yangtze Estuary, under the water regulation of the large cascade dams in the upper Yangtze. Nevertheless, the mean depositional rate will not surpass the peak value of the past years, since the total sediment load entering the Yangtze Estuary has presented a decreasing trend.

In the context of climate change and over-exploitation of water resources, water shortage and water pollution in arid regions have become major constraints to local sustainable development. In this study, we established a Soil and Water Assessment Tool (SWAT) model for simulating non-point source (NPS) pollution in the irrigation area of the lower reaches of the Kaidu River Basin, based on spatial and attribute data (2010-2014). Four climate change scenarios (2040-2044) and two agricultural management scenarios were input into the SWAT model to quantify the effects of climate change and agricultural management on solvents and solutes of pollutants in the study area. The simulation results show that compared to the reference period (2010-2014), with a decline in streamflow from the Kaidu River, the average annual irrigation water consumption is expected to decrease by 3.84×10 ⁸ m ³ or 8.87% during the period of 2040-2044. Meanwhile, the average annual total nitrogen (TN) and total phosphorus (TP) in agricultural drainage canals will also increase by 10.50% and 30.06%, respectively. Through the implementation of agricultural management measures, the TN and TP in farmland drainage can be reduced by 14.49% and 16.03%, respectively, reaching 661.56 t and 12.99 t, accordingly, and the increasing water efficiency can save irrigation water consumption by 4.41×10 ⁸ m ³ or 4.77%. The results indicate that although the water environment in the irrigation area in the lower reaches of the Kaidu River Basin is deteriorating, the situation can be improved by implementing appropriate agricultural production methods. The quantitative analysis results of NPS pollutants in the irrigation area under different scenarios provide a scientific basis for water environmental management in the Kaidu River Basin.

Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems. As a process-oriented modelling approach, agent based model (ABM) plays an important role in revealing the driving forces of land change and understanding the process of land change. This paper starts from three aspects: The theory, application and modeling framework of ABM. First, we summarize the theoretical basis of ABM and introduce some related concepts. Then we expound the application and development of ABM in both urban land systems and agricultural land systems, and further introduce the case study of a model on Grain for Green Program in Hengduan Mountainous region, China. On the basis of combing the ABM modeling protocol, we propose the land system ABM modeling framework and process from the perspective of agents. In terms of urban land use, ABM research initially focused on the study of urban expansion based on landscape, then expanded to issues like urban residential separation, planning and zoning, ecological functions, etc. In terms of agricultural land use, ABM application presents more diverse and individualized features. Research topics include farmers’ behavior, farmers’ decision-making, planting systems, agricultural policy, etc. Compared to traditional models, ABM is more complex and difficult to generalize beyond specific context since it relies on local knowledge and data. However, due to its unique bottom-up model structure, ABM has an indispensable role in exploring the driving forces of land change and also the impact of human behavior on the environment.

Systematically revealing the impact of cultivated land fragmentation (CLF) on the geographical agglomeration pattern of agricultural specialization (AS) has positive significance for national agricultural production management. Based on the data of the second national land survey and agricultural production, this study has explored the impact of CLF on spatial heterogeneity of agricultural agglomeration in China by comprehensively using the Theil index, ordinary least square model and geographically weighted regression. Results showed that: (1) the regional differentiation of the CLF in China is obvious, and the cultivated land fragmentation index is generally characterized by increasing pattern from northwest to southeast. (2) Spatially, the development level of AS in China has formed three high-value clusters in the Northeast China Plain, the Qinghai-Tibet Plateau, and the middle of the Middle-lower Yangtze Plain; and the low-value contiguous areas centered on the Yunnan-Guizhou Plateau and the Sichuan Basin and surrounding regions, with significant spatial differences. The contribution of grain crops, economic crops, and vegetables and melon to the level of AS was 74.63%, 9.09%, and 16.28%, respectively, and the pattern of agricultural geographical aggregation dominated by grain crops has primarily taken in shape. (3) CLF is significantly negatively correlated with AS, and every 1% increase in the degree of CLF will result in a decrease of about 0.2% in AS. However, the impact of CLF on the geographic agglomeration of different crop categories or groups varies significantly. Among them, CLF has a prominent impact on the specialization level of grain crops and vegetables and melon. Each 1% increase in the CLF will reduce the specialization level of grain crops by 0.38%, and increase the level of vegetables and melon by about 0.22%. (4) According to the landscape characteristics of cultivated land, the degree of spatial division and agglomeration of cultivated land patches have a significant impact on the formation of geographical agglomeration pattern of AS, and the intensity and direction of influence show significant regional differentiation, while the patch size has no significant impact.

Capacity for grain self-sufficiency on the Tibetan Plateau (TP) is an important basis for ensuring social stability and regional sustainability. Thus, based on county-level statistical data for population, grain production and consumption, we analyzed patterns and trends in grain supply and demand at regional, provincial, and county levels on the TP between 1985 and 2016. We applied two indices to evaluate capacity for grain self-sufficiency and found that the regional average self-sufficiency rate increased quickly by 1.97%/a since 1989, reaching 173.03% on the plateau over the period between 2010 and 2016. This indicates that grain supply in this region is able to fully meet demand. In addition, all provinces apart from Xinjiang exhibited similar increasing trends, attaining grain self-sufficiency during 2010-2016. Furthermore, 59% of counties attained grain self-sufficiency over this period, mainly distributed in southern Tibet, in the Sichuan-Tibet junction area, and in eastern Qinghai Province. A number of gaps in grain supply and demand occurred within the headwater regions of the Yangtze and Yellow rivers as well as on the Qiangtang Plateau. Grain self-sufficiency significantly increased over the study period in 36% of counties, mainly distributed in the agricultural areas of southeastern Tibet and in eastern Qinghai. Across the whole plateau, capacity for grain self-sufficiency substantially increased between 1985 and 2016, although serious spatial imbalances remain.

Uneven urban and rural development is one of the main reasons for the decline of the countryside. This imbalance could be measured by the urban-rural difference index (URDI). Existing studies on urban-rural differences have focused on single dimension between urban and rural areas, and lack a systematic multi-dimensional measurement. Based on the construction of an index system and model for measuring urban-rural differences, this study took the Huang-Huai-Hai Plain (HHHP) as the study area, explores the spatial pattern of urban-rural differences in the area, and used geographical weighted regression models to identify the factors affecting urban-rural development differences. Results show that the mean value of URDI in the HHHP was 0.295, and the URDI in its western region was higher than that in the east. The average URDI was relatively high in the western counties along the Beijing-Guangzhou Railway. The low level of urban-rural “population-land-industry” development in the HHHP is an important reason for the small differences between urban and rural areas. Improvements in road transportation infrastructure have led to an increase in the urban-rural development gap. However, the driving force of the road network on urban development is greater than that on rural areas. The role of county economic agglomeration is gaining strength. In the process of rapid economic development, more attention should be paid to the development of the rural economy and the overall revitalization of the countryside. The equivalent allocation of social service facilities is an effective way to solve the problem of urban-rural imbalance. Further analysis demonstrated that terrain factors have relatively little influence on the URDI. This study provides a new perspective and measurement method for understanding the integration of urban and rural development, and provides a useful reference for guiding the urban-rural integration development and the rural revitalization.

The Yangtze River floodplain is critical for migratory waterbirds along the East Asian-Australasian Flyway (EAAF). Greater awareness of its global importance is urgently needed to ensure waterbird populations remain in favourable conservation status, as well as the enhancement of wider wetland biodiversity within this region. The designation of protected wetland areas and building a green ecological corridor in the Yangtze floodplain is now becoming a critical issue of interest to the Chinese government. Priority sites in this area were identified based on the criteria used to identify sites that qualify as Wetlands of International Importance (Ramsar Sites) and Important Bird and Biodiversity Areas (IBAs) by using multi-source data. The results show that 140 of the sites surveyed are priority sites. The Importance Index (I) for the whole floodplain decreased slightly from 2001-2005 and an unbalanced distribution pattern is evident with Jiangxi and Hunan provinces significantly higher than the other provinces in the floodplain. Although more than 60% of the priority sites are currently located outside protected areas, the average Conservation Effectiveness Index (C) of the whole floodplain is 75.6%, which suggests the coverage of protected areas for most wintering waterbird population is reasonable. Conservation of the Yangtze River floodplain needs to be further strengthened due to declining waterbird abundances and the mismatch between the distribution of protected areas and their importance for wintering waterbirds. A comprehensive system for priority site identification and protection and scientific review is needed. Multi-sourced data from regular, systematic and coordinated monitoring of waterbird distribution and abundance across the EAAF, as well as national scale citizen science programmes are also critically important.

The operation of large-scale reservoirs have modified water and sediment transport processes, resulting in adjustments to the river topography and water levels. The polynomial fitting method was applied to analyze the variation characteristics of water levels under different water discharge values in the Jingjiang reach of the Yangtze River from 1991-2016. The segregation variable method was used to estimate the contributions of the varied riverbed evaluation, the downstream-controlled water level, and the comprehensive roughness on the altered water level at an identical flow. We find that low water levels in the Jingjiang reach of the Yangtze River from 1991-2016 are characterized by a significant downward trend, which has intensified since 2009. Riverbed scouring has been the dominate factor causing the reduced low water level while increased roughness alleviated this reduction. From 1991-2016, there was first a decrease followed by an increase in the high water level. The variation characteristic in terms of the “high flood discharge at a high water level” before 2003 transformed into a “middle flood discharge at a high water level” since 2009. The increased comprehensive roughness was the main reason for the increased high water level, where river scouring alleviated this rise. For navigation conditions and flood control, intensified riverbed scouring of the sandy reaches downstream from dams enhanced the effects that the downstream water level has on the upstream water level. This has led to an insufficient water depth in the reaches below the dams, which should receive immediate attention. The altered variation characteristics of the high water level have also increased the flood pressure in the middle reaches of the Yangtze River.

Mapping floods is important for policy makers to make timely decisions in regards to emergency responses and future planning. It is therefore crucial to develop a rapid inundation modelling framework to map flood inundation. This study develops an airborne scanning laser altimetry (LiDAR) digital elevation model (DEM) based Rapid flood Inundation Modelling framework (LiDAR-RIM) for assessment of inundation extent, depth, volume and duration for flood events. The modelling framework has been applied to the mid-Murrumbidgee region in the southeast Murray-Darling Basin, Australia for two flood events occurred in December 2010 and March 2012. The inundation extents estimated using this methodology compared well to those obtained from two Landsat ETM+ images, demonstrating suitability and applicability of this method. For testing possibility of larger area application, the framework also uses 30-m resolution shuttle radar topography mission (SRTM)-DEM to replace LiDAR-DEM for the same modelling. The inundation extents obtained by using the SRTM-DEM are smaller than those obtained using the LiDAR-DEM, especially for large flood events. A possible reason is that the river cross sections obtained from the SRTM-DEM are not accurate enough for inundation modelling. The LiDAR-RIM has an advantage for process modelling and scenario modelling under future climatic conditions.

We collected and verified documentary records of the latest spring snowing dates (LSSD) in Hangzhou during Southern Song Dynasty. Furtherly, the statistical correlation between this proxy and February-April mean temperature in Hangzhou was examined, and samples later than the perennial mean of the LSSD during Southern Song Dynasty were transformed into the decadal mean of LSSD by means of Boltzmann function. General characteristics of this reconstructed LSSD series with a 10-year temporal resolution was analyzed, and it was also compared with other documentary evidences and reconstructed climate series in China for the period 1131-1270. The results and discussion suggested that: (1) Records of the LSSD in Hangzhou during Southern Song Dynasty did not refer to ice pellets and graupels, which had an explicit climate significance (-0.34oC/10d, R ²=0.37, p<0.001). However, when this proxy is used to reconstruct temperature changes, all dates should be converted into proleptic Gregorian style and meet the same criterion of “true Qi” as the Chinese traditional calendar after 1929. (2) The decadal mean of LSSD can be effectively estimated by using the forefront of LSSD in the decade on the basis of Boltzmann function, whose extrapolation has a lesser uncertainty than those on the basis of linear models or polynomial models. (3) The spring climate in Hangzhou during 1131-1270 was almost as warm as the period 1951-1980. At the centennial scale, this period can be divided into two phases: the cold 1131-1170 and the warm 1171-1270. In the latter, 1181-1200 and 1221-1240 were two cold intervals at the multi-decadal scale. (4) The reconstructed LSSD series was consistent well with other documentary evidences and reconstructed climate series in China for 1131-1270, which may reflect the influence on the climate over most regions of China imposed by the Pacific Decadal Oscillation (PDO).

Especially since 2012 Chinese companies have acquired stakes as investors and constructors of overseas ports in both high-income and emerging economies. These initiatives play an important role in the construction of a Maritime Silk Road and China’s Belt and Road Initiative (BRI). Although a result of many factors, of which Chinese port investments are only one, macro-geographical gravity methods show that distance impedance and increases in the export market potential, export supply capacity and access to imports of these countries drove increases in income per capita. Export supply capacity rose particularly in Southeast Asia and more recently in Sub-Saharan Africa. In difficult times for the world economy, countries in which China invested in overseas port infrastructure saw increases in national export market potential and income per capita, due to reduction in the impedance of distance, while in the case of developing economies export market supply capacity and access to imported capital equipment and intermediate goods improved.

The United States, Russia and China are militarily and economically among the most powerful countries in the post-Cold War period, and the interactions between the three powers heavily influence the international system. However, different conclusions about this question are generally made by researchers through qualitative analysis, and it is necessary to objectively and quantitatively investigate their interactions. Monthly-aggregated event data from the Global Data on Events, Location and Tone (GDELT) to measure cooperative and conflictual interactions between the three powers, and the complementary cumulative distribution function (CCDF) and the vector autoregression (VAR) method are utilized to investigate their interactions in two periods: January, 1991 to September, 2001, and October, 2001 to December, 2016. The results of frequencies and strengths analysis showed that: the frequencies and strengths of USA-China interactions slightly exceeded those of USA-Russia interactions and became the dominant interactions in the second period. Although that cooperation prevailed in the three dyads in two periods, the conflictual interactions between the USA and Russia tended to be more intense in the second period, mainly related to the strategic contradiction between the USA and Russia, especially in Georgia, Ukraine and Syria. The results of CCDF indicated that similar probabilities in the cooperative behaviors between the three dyads, but the differences in the probabilities of conflictual behaviors in the USA-Russia dyad showed complicated characteristic, and those between Russia and China indicated that Russia had been consistently giving China a hard time in both periods when dealing with conflict. The USA was always an essential factor in affecting the interactions between Russia and China in both periods, but China’s behavior only played a limited role in influencing the interactions between the USA-Russia dyad. Our study provides quantitative insight into the direct cooperative and conflictual interactions between the three dyads since the end of the Cold War and helps to understand their interactions better.

Central Asia features an arid and semi-arid climate, and the region is undergoing urbanization in the context of a fragile eco-environment. The influence of specific historical events in this region also persists on this ongoing urbanization. This study examines the mechanism of interaction between urbanization and the resource environment in Central Asia. The following results were obtained. (1) In different periods—Russian colonization, the era of the Soviet Union, and Central Asian countries as independent—the interactions between urbanization and the resource environment varied. (2) Variations in land use within 50 km of major cities of the region reflect both the trend of urbanization and that of variations in the eco-environment. In Kyrgyzstan and Tajikistan, where urbanization has been slow, the supportive effect of the eco-environment for urbanization was clear. In Uzbekistan and Turkmenistan, where freshwater resources are scarce, a close relationship was noted between urbanization and variations in the eco-environment. In Kazakhstan, fast urbanization has had a significant impact on the availability of water, grassland, and woodland in the relevant areas. (3) The efficiency of utilization of land and water resources is generally low. The compactness of the urban land of 47 major cities in Central Asia decreased from 0.44 in 1990 to 0.31 in 2015. Of them, 31 cities decreased in compactness, including all national capitals. Regardless of the level of urbanization, water consumption was high across the region. (4) The mechanisms of interaction between urbanization and the resource environment in Central Asia in the three stages were formulated to illustrate their specific temporal conductivity and spatial relevance.

Due to the unique geographical location and historical background of Central Asia, the region’s geo-relation networks are complex and changeable. A social network analysis was conducted in this study to visualize the 20-year evolutionary process of bilateral (diplomatic relations) and multilateral (intergovernmental organization (IGO) connections) networks in Central Asia since 1993. Additionally, a further empirical study determined the significant driving forces of the construction of the geo-relation networks. The results showed that since the independence of the five Central Asian countries, their degree centrality (C’_D(n_i)) values have been increasing, with the index values being the highest for Kazakhstan, followed by Uzbekistan, while the other three countries had relatively low values. The Central Asian countries maintain bilateral relations with post-Soviet nations, neighboring countries, and Western powers, and have gradually deepened and expanded their diplomatic networks. From each state’s perspective, the geostrategic approaches adopted by the five countries were different. Kazakhstan has focused on expanding its bilateral and multilateral relations, while the other Central Asian countries have attempted to increase their influence by joining influential IGOs. Various driving forces, including economic, political, cultural, and geographical factors, have played significant roles in the construction of geo-relation networks in Central Asia. The importance of these factors has changed over time, from political and cultural factors (before 1995) to relations with neighboring countries (1996-2001), and finally to economic power and cultural and religious proximity (after 2002).

In the context of accelerated development of the Silk Road Economic Belt, it is necessary to conduct in-depth research on urbanization of Central Asian countries. This paper analyzes the spatial and temporal patterns and evolution dynamics of urbanization during the period 1991-2017 from the perspective of internal-external forces. The results are as follows. (1) The urbanization process of the five Central Asian countries studied is significantly influenced by their political and economic situations and displays periodic characteristics. All five countries experienced a stagnation development stage at the beginning of independence, and then a rapid growth stage since the year 2000. The average annual growth rates of the two stages were 0.19% and 1.45%, respectively. (2) Differences in the urbanization of the studied countries are obvious, and the evolutionary characteristics of each subsystem of urbanization are different. It is therefore necessary to distinguish and clearly understand the urbanization process of each country. (3) Internal and external factors play a role in the urbanization processes of Central Asian countries. External railway transportation facilities are particularly important for the development of urbanization in these countries. The regression coefficients of railway construction length, total merchandise trade and actually utilized foreign capital are 0.5665, 0.0937 and 0.0806, respectively. (4) Countries with smaller populations and economic scales need to engage in international cooperation to promote healthy development of urbanization. The results of the study indicate that internal and external factors work together in the urbanization process of Central Asian countries, and external forces are particularly important for the development of such urbanization.

This study undertakes a systematic examination of characteristics of the spatio-temporal evolution of industrial economies in Central Asia from the perspectives of industrial scale, structural rationality, industrial competitiveness, and industrial isomorphism. The results show that industrial structures in Central Asian countries are becoming increasingly advanced, with certain differences among them in the characteristics of this evolution. Kazakhstan has long had a tertiary-secondary-primary industrial pattern, and productive services have played an increasingly prominent role in the development of its tertiary industry. The transformation of the industrial structure in Uzbekistan, from a secondary-tertiary- primary pattern at its independence from the Soviet Union to a tertiary-secondary-primary pattern, is apparent. Tajikistan’s industrial structure has also changed significantly in recent times. Its secondary industries shrunk while tertiary industries developed rapidly. In Kyrgyzstan, the ratios of secondary and tertiary industries to total industrial output have fluctuated significantly while considerable progress has been made in the service sector. The industrial structure of Turkmenistan is significantly lower than the other countries, and Turkmenistan is the only country in the Central Asian region which still shows a tertiary-secondary-primary industrial pattern. The feasibility and competitiveness of the industrial structures of these five Central Asian countries have different characteristics. Kazakhstan has structural advantages but lags in competitiveness, Uzbekistan is driven by both structural and competitive advantages, Tajikistan enjoys structural advantages while Kyrgyzstan lags behind in competitiveness, and Turkmenistan has a competitiveness-driven economy. Furthermore, values of the similar coefficient index of the three industrial structures in these countries were mostly above 0.95, the coefficients of the secondary industrial subdivisions in some countries were below 0.85, and those of tertiary industrial subdivisions among most countries were above 0.89, indicating considerable similarities in industrial structure among them. These findings are important in the context of establishing an effective industrial development strategy for the Silk Road Economic Belt, improving international cooperation, and upgrading industrial structures to achieve economic prosperity.

When viewed against the backdrop of globalization and the Belt and Road Initiative (BRI), Central Asia has ushered in new development opportunities. However, problems of ecological environment as a consequence of urbanization have begun to act as a constraint on the economic development of the region. the coupling coordination degree between the urbanization and ecological environment in Kazakhstan was analyzed by the coupling coordination degree model. The main controlling factors affecting its development were explored using a geographical detector. Several main conclusions can be drawn. (1) Kazakhstan's urbanization level, ecological environment level, and the coupling coordination degree between urbanization and ecological environment are all on the rise. (2) In terms of the comprehensive urbanization index, the western and eastern states have higher values than the southern and northern states. The spatial distribution pattern of the ecological environment index revealed high values in the eastern and western regions and low values in the central region. (3) The coupling coordination degree among the states of Kazakhstan is mostly at a low-moderate level. The spatial distribution shows that the coordination level of the east, middle, and west of the country is higher than that of south and north. (4) Indicators such as GDP per capita, social fixed asset investment per capita, employment in industry and services (% of total employment), and the number of college students per 10,000 people are important urbanization factors that affect the coupling coordination degree of urbanization and ecological environment. Indicators of farmland areas per capita, availability of water resources per capita, ecological land per capita and forest coverage in the ecological environment subsystem are important ecological environmental factors that affect the degree of coordination between urbanization and ecological environment in Kazakhstan. The interaction of the main elements in the two subsystems has a strong synergy.

Energy development has a significant impact on urbanization. This study employs the entropy method to evaluate the level of urbanization in Central Asia and further analyzes the possible dynamic transition mechanisms of the impact of energy development (characterized by energy development scale, energy trade, energy consumption, and energy endowment) on urbanization using the Panel Smooth Transition Regression model (PSTR). The results demonstrate that energy development in this region is characterized by “three highs and one low”, namely, high production volume, high export volume, high endowment, and low self-consumption, and plays a crucial role in the progress of urbanization. A nonlinear relationship is found to exist between energy development and comprehensive urbanization in the transition economies of Central Asia. Generally speaking, as energy development continues to expand, its impact on urbanization in this region has shifted from constraint to promotion, with the latter gradually tending to flatten out. Energy development characterized by energy development scale, energy consumption, and energy trade can prove the point, whose threshold is 1.47 million tons oil equivalent (Mtoe), 0.29 tons oil equivalent (toe) per capita, and 20.95 Mtoe, respectively. However, not all energy development models exhibit this behavior. Energy development characterized by energy endowment is such a case where the positive effect of it on comprehensive urbanization will be restrained when it exceeds 3.18. These findings can aid decision makers in seeking a better energy development model to promote the sustainable development of urbanization in Central Asia, avoiding energy resources waste and disorderly development.

Central Asia is emerging as an important pole of global economic and political power, thanks to its unique location at the heart of Eurasia and its abundance in energy reserves. This study explores the social power change in Central Asia from the perspective of cross-border mergers and acquisitions (M&A) by using the social network method. The main results are as follows: (1) The complexity of the energy M&A network has significantly decreased after the financial crisis in 2008. In the meantime, energy M&A became an important way to enhance energy power for buyer countries. Betweenness centrality is becoming the most significant factor affecting energy power, yet the effect of out-degree is weakening. (2) The community underwent multifaceted restructuring, which reflected the shift of energy power in Central Asia. Kazakhstan is the most powerful country in the energy sector in Central Asia. In addition, East Asian countries/regions, represented by China, are actively enhancing their energy power. (3) Different M&A modes reflect various M&A motivations of countries in the energy sector. In the future, more efforts should be made to promote the establishment of a pragmatic and efficient multilateral energy cooperation mechanism and strength the cooperation of the economy and energy finance when China participates in the energy market in Central Asia.

To ensure adequate oil supply and mitigate geopolitical uncertainties, China has diversified its sources of crude oil imports in recent years. Central Asia is a neighbor region of China, rich in oil and natural gas reserves, which can play an important role in China’s strategy to reduce its dependence on energy supplies from the Middle East. The geopolitical attributes of energy and the geopolitical situation in Central Asia determine that Central Asia’s energy development and cooperation are disturbed by domestic and foreign factors, and also face the risks of complex energy structural evolution and geopolitical games, which create a unique energy geopolitical pattern in Central Asia. This study proposes an analysis framework for energy geopolitics in Central Asia, arguing that the complexity of energy geopolitics in Central Asia can be demonstrated from the perspectives of both the main countries of energy development (game actors) and the whole-industry-chain of energy development (game themes). The most obvious feature of Central Asian energy geopolitics is the fierce game that is played between key countries and regions, Russia, the United States, China, the European Union (EU), Japan, India, Iran, and Turkey. Strategic geopolitical considerations and resource requirements necessitate the active participation of these players in Central Asian energy development and mean that the foreign policy agendas of states in this region are likely to become ever more crowded. Therefore, the energy cooperation between China and Central Asia faces the geopolitical risks of the great power games. It is necessary to develop reasonable and effective policies to establish guarantee mechanisms to minimize the risks of energy cooperation. This study characterizes the energy geopolitical strategies of Russia, the United States, China, and other related powers in Central Asia. It also assesses the country risks faced by energy cooperation between China and Central Asian countries. To withstand possible geopolitical and country risks, this study develops a series of policy frameworks which can be used to fortify the stability of the energy cooperation between China and Central Asian countries, and can also be effective in responding to the array of risks that might be encountered in the coming years.

Based on methods such as stochastic frontier production function, this paper analyses the changes of single factor productivity (SFP) and total factor productivity (TFP) of agriculture in the five Central Asian countries, during the period of 1992 to 2017. The research results show that the agricultural output in most of the five Central Asian countries has increased steadily, while agricultural labor productivity has shown a growth trend. With the exception of Kazakhstan, the land productivity of the other four countries shows a growth trend. In terms of factor input, the number of agricultural workers in the five Central Asian countries mainly shows a trend of decrease, with the input of chemical fertilizer increasing, and the amount of agricultural machinery increasing or decreasing within a small range. The total factor productivity in the five Central Asian countries has improved, but it is still at a low level. The policy suggestions contained in the research conclusions are as follows: (1) Promote the growth of agricultural TFP in the five Central Asian countries, and strengthen the emphasis on the input and allocation of agricultural factors; (2) be aware of the innovation of agricultural technology, as well as the promotion and diffusion of existing agricultural technologies, and improve the overall technical efficiency of agriculture; and (3) accelerate the effective flow of capital and other elements to the agricultural sector, improve infrastructure, better release the “dividend” of science and technology, and enhance the output efficiency.

In recent years, flows of many rivers and lakes have become reduced in arid and semi-arid regions around the world. The most typical examples of this phenomenon occur in Central Asia, and the reduction of the Aral Sea area is closely related to agricultural water use. However, due to a lack of continuous data in Central Asia spanning many years, “virtual water” is used to evaluate changes in agricultural water use. Based on virtual water theory, 325 kinds of agricultural products in eight categories are selected as the research object, and changes in virtual water are calculated for Central Asia from 1992 to 2016. Results indicate that: (1) The average annual net export of agricultural virtual water (TVWNE) in Central Asia is about 9 billion m3, concentrated in Kazakhstan, whose annual TVWNE reaches 8.1 billion m ³. (2) Since 2007, the TVWNE in Central Asia has dropped significantly, with a drop rate of 86%, while the total volume of agricultural virtual water has gradually increased since 1998. (3) The upstream and downstream countries in Central Asia have different characteristics in the change of virtual water quantity.

The urban-rural transformation from dichotomy to integration is a gradual process. Like rural areas in many countries, Chinese rural society is experiencing a decline in all spheres due to depopulation, aging, lack of economic opportunity, and so on. Aiming at solving the serious rural issues, China proposed the implementation of a rural revitalization strategy and the promotion of an integrated urban-rural development for the first time in 2017. This proposal marks the transformation of the urban-rural relationship, and the integrated urban-rural development reflects a significant conceptual change. Researches on issues of rural decline are urgently needed to determine the most effective method for rural revitalization and development from the perspective of the urban-rural dynamics. In this context, this paper focuses on studying the theory, technology and management of rural revitalization and development. We construct a theoretical framework for urban-rural integration based on population-land-industry-right between the urban and rural systems, regarding land engineering for land capacity building as the technical support and the rural land system reform and reconstruction as the policy support for management. This research will provide theoretical support for the implementation of China’s rural revitalization strategy.

A largely unexplored application of “Big Data” in urban contexts is using human mobility data to study temporal heterogeneity in intercity travel networks. Hence, this paper explores China’s intercity travel patterns and their dynamics, with a comparison between weekdays and holidays, to contribute to our understanding of these phenomena. Using passenger travel data inferred from Tencent Location Big Data during weekdays (April 11-15, 2016) and National Golden Week (October 1-7, 2016), we compare the spatial patterns of Chinese intercity travel on weekdays and during Golden Week. The results show that the average daily intercity travel during Golden Week is significantly higher than that during weekdays, but the travel distance and degree of network clustering are significantly lower. This indicates temporal heterogeneity in mapping the intercity travel network. On weekdays, the three major cities of Beijing, Shanghai, and Guangzhou take prominent core positions, while cities that are tourism destinations or transportation hubs are more attractive during Golden Week. The reasons behind these findings can be explained by geographical proximity, administrative division (proximity of cultural and policy systems), travel distance, and travel purposes.

Investigating the spatio-temporal transmission features and process of novel coronavirus disease 2019 (COVID-19) mitigation strategies are of great practical significance to understand the development of COVID-19 and establish international cooperation for prevention and control. In this paper, the cumulative number of confirmed cases, number of confirmed cases per day and cumulative number of deaths, were used to compare transmission paths, outbreaks timelines, and coping strategies of COVID-19 in China and the US. The results revealed that: first, the COVID-19 outbreaks in both China and the US exhibited a 6-week initiation stage. In China, the COVID-19 erupted in late January. It lasted only a short period of time and was almost completely contained within 6-8 weeks. But the COVID-19 erupted in early March in the US and was still in the peak or post-peak stage. Second, in China, the COVID-19 emerged in Wuhan and spread to other regions of Hubei Province and then nationwide, exhibiting a cross(“+”)-shaped of spread with Wuhan city as the center. Importantly, the COVID-19 in China had a large concentration and there were no national outbreaks. In contrast, the COVID-19 in the US first spread through New York and the western and eastern coasts but has since emerged throughout the entire country. Third, the lack of emergency response planning in both countries in the early stage (about 6-week) hampered COVID-19 prevention. However, actively high-pressure prevention and control measures were used to basically control COVID-19 in early March in China. And then China has gradually resumed business and production activities. Unfortunately, the US government missed the best opportunity to contain the epidemic. Faced with the choice between economic recovery and coronavirus containment, the US removed the quarantine and restriction measures too early. The COVID-19 is continuing to spread in the country and blossom everywhere, still showing no signs of receding.

Population migration, especially population inflow from epidemic areas, is a key source of the risk related to the coronavirus disease 2019 (COVID-19) epidemic. This paper selects Guangdong Province, China, for a case study. It utilizes big data on population migration and the geospatial analysis technique to develop a model to achieve spatiotemporal analysis of COVID-19 risk. The model takes into consideration the risk differential between the source cities of population migration as well as the heterogeneity in the socioeconomic characteristics of the destination cities of population migration. It further incorporates a time-lag process based on the time distribution of the onset of the imported cases. In theory, the model will be able to predict the evolutional trend and spatial distribution of the COVID-19 risk for a certain time period in the future and provide support for advanced planning and targeted prevention measures. The research findings indicate the following: (1) The COVID-19 epidemic in Guangdong Province reached a turning point on January 29, 2020, after which it showed a gradual decreasing trend. (2) Based on the time-lag analysis of the onset of the imported cases, it is common for a time interval to exist between case importation and illness onset, and the proportion of the cases with an interval of 1-14 days is relatively high. (3) There is evident spatial heterogeneity in the epidemic risk; the risk varies significantly between different areas based on their imported risk, susceptibility risk, and ability to prevent the spread. (4) The degree of connectedness and the scale of population migration between Guangdong’s prefecture-level cities and their counterparts in the source regions of the epidemic, as well as the transportation and location factors of the cities in Guangdong, have a significant impact on the risk classification of the cities in Guangdong. The first-tier cities - Shenzhen and Guangzhou - are high-risk regions. The cities in the Pearl River Delta that are adjacent to Shenzhen and Guangzhou, including Dongguan, Foshan, Huizhou, Zhuhai, Zhongshan, are medium-risk cities. The eastern, northern, and western parts of Guangdong, which are outside of the metropolitan areas of the Pearl River Delta, are considered to have low risks. Therefore, the government should develop prevention and control measures that are specific to different regions based on their risk classification to enable targeted prevention and ensure the smooth operation of society.

Widespread aeolian deposits on the Tibetan Plateau (TP) have provided valuable palaeoclimatic information. However, the primary factors (e.g., climate factors, human activity, and vegetation cover) controlling aeolian deposition remain elusive. In this paper, we use a dataset that comprises new and published ages of Holocene aeolian sand and loess in the middle reaches of the Yarlung Zangbo River to identify the primary controlling factors and palaeoclimatic implications of aeolian deposition. Several intervals of enhanced aeolian accumulation centered at 8.5-7.8, 6.4-5.8, 4.5-4.0, 3.1-1.8, and 0.9 ka are identified, generally consistent with regional low rainfall events and weak Indian summer monsoon (ISM). This suggests that regional wetness, dominated by the ISM, may play a key role in modulating dust emissions and aeolian deposition on centennial timescales. Our results show that on centennial- to millennial-scales, ISM activity can be reconstructed by non-continuous aeolian deposits in the monsoon dominated TP.

Land use and land cover (LULC) alteration has changed original energy balance and heat fluxes between land and atmosphere, and thus affects the structure characteristics of temperature and humidity fields over urban heterogeneous surfaces in different spatio-temporal scales. Lanzhou is the most typical river valley city of China, it is chosen as the case study. Typical river valley terrain, rapid urbanization and severe air pollution have caused unique urban climate and urban heat island (UHI) effects in Lanzhou. Firstly, the spatial structure characteristics and dynamic evolution of temperature and humidity fields in autumn are simulated by mobile measurement experiment and GIS spatial analysis method. The results show that temperature and humidity fields have significant dynamic change within a day, and have multiple center and multiple intensity level characteristics. Then, LULC and normalized difference vegetation index (NDVI) are extracted from remote sensing images, the distribution patterns of temperature and humidity fields have close relationships with LULC and NDVI. Moreover, there is a significant positive correlation between impervious surface area and thermal field intensity. A positive correlation between NDVI value and humidity field intensity has been found as well as a negative correlation between NDVI value and thermal field intensity. Finally, heat fluxes and energy balance characteristics between ground and atmosphere are analyzed based on the Bowen-ratio System experiments. This study could provide theoretical support and practical guidance for urban planning, urban eco-environment construction and air pollution prevention of river valley city.

To understand the non-equilibrium morphological adjustment of a river in response to environmental changes, it is essential to (i) accurately identify how past conditions of water and sediment have impacted current morphological adjustment of the river, and (ii) establish a corresponding simulation for non-equilibrium conditions. Based on discharge and suspended sediment concentration (SSC) as well as 82 cross-sectional data items for the Huayuankou-Lijin reach of the Lower Yellow River in the period 1965-2015, the process of adjustment of the geometry of the main channel (area, width, depth, and geomorphic coefficient), and its responses to changes in discharge and SSC for different reaches are statistically analyzed. Following this, a delayed response model (DRM) of the geometry of the main channel subjected to variations in discharge and SSC is established using a multi-step analytical model, with the discharge and SSC as the main controlling factors. The results show that the area, width, and depth of the main channel decreased initially, then increased, decreased again, and finally increased again. These features of the geometry of the channel were positively correlated with the 4-year moving average discharge and negatively with the 4-year moving average SSC. The geomorphic coefficient for the Huayuankou-Sunkou reach exhibited a trend of decrease, whereas that of the Sunkou-Lijin reach decreased initially, then increased, decreased again, and finally increased again. Except for the Huayuankou-Gaocun reach in 1965-1999, the coefficient was negatively correlated with the 4-year moving average discharge and positively with SSC. The simulated values of the morphological parameters of the main channel for all sub-reaches obtained using the DRM agreed well with the measured values. This indicates that the DRM can be used to simulate the process of response of the cross-sectional geometry of the main channel to variations in the water and sediment. The results of the model show that the adjustment of the geometry of the main channel was affected by the discharge and the SSC at present (30%) as well as for the previous 7 years (70%). The proposed model offers insights into the mechanism whereby past water and sediment influence the current morphological adjustment of the river, and provides an effective method for predicting the magnitude and trend of the geometry of the main channel under different flow conditions.

Flood is one of the severest natural disasters in the world and has caused enormous causalities and property losses. Previous studies usually focus on flood magnitude and occurrence time at event scale, which are insufficient to contain entire behavior characteristics of flood events. In our study, nine behavior metrics in five categories (e.g., magnitude, duration, timing, rates of changes and variability) are adopted to fully describe a flood event. Regional and interannual variations of representative flood classes are investigated based on behavior similarity classification of numerous events. Contributions of geography, land use, hydrometeorology and human regulation on these variations are explored by rank analysis method. Results show that: five representative classes are identified, namely, conventional events (Class 1, 61.7% of the total), low discharge events with multiple peaks (Class 2, 5.3%), low discharge events with low rates of changes (Class 3, 18.1%), low discharge events with high rates of changes (Class 4, 10.8%) and high discharge events with long durations (Class 5, 4.1%). Classes 1 and 3 are the major flood events and distributed across the whole region. Class 4 is mainly distributed in river sources, while Classes 2 and 5 are in the middle and down streams. Moreover, the flood class is most diverse in normal precipitation years (2006, 2008-2010 and 2015), followed by wet years (2007, 2013-2014), and dry years (2011 and 2012). All the impact factor categories explain 34.0%-84.1% of individual flood class variations. The hydrometeorological category (7.2%-56.9%) is the most important, followed by geographical (1.0%-6.3%), regulation (1.7%-5.1%) and land use (0.9%-2.2%) categories. This study could provide new insights into flood event variations in a comprehensive manner, and provide decision-making basis for flood control and resource utilization at basin scale.

Since 2007, the Chinese government has initiated the building of national eco-cultural protection areas (NECPAs), thereby embarking on a signi?cant transformation of the model of intangible cultural heritage (ICH) protection in China. To understand the origin and outputs of this policy, this paper demonstrates the context of China’s NECPAs. It proposes a conceptual NECPA framework that mainly features regional overall ICH protection. This is followed by an examination of the case of Xiangxi in Western Hunan as a pilot zone for China’s eco-cultural protection. Xiangxi has performed much related work to promote NECPAs and made great progress in regional overall ICH protection. This insight suggests that there are bene?ts and costs associated with promotion of China’s NECPAs and regional overall ICH protection. Despite the advantages of institutional innovation, the unexpected side effects actually undermine the success of plan implementation.