Spatio-temporal Variation Characteristics of Extreme Climate Events and Their Teleconnections to Large-scale Ocean-atmospheric Circulation Patterns in Huaihe River Basin,China During 1959–2019

Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.

Spatio-temporal variation of trace elements distributed over surface water of Upper Ganga River Basin in Western Himalayan Region

The rivers draining from the Himalayan range distribute enormous amount of fresh water to the people living in downstream regions.Trace metals flowed with river water can lead to serious impact on ecological system and human health.Nevertheless,the documentation on trace elements of Himalayan rivers is inadequately documented.The current study deals with the spatial and temporal variability of the major and trace elements of Ganga river water in epirhithron,metarhithron and hyporhithron zone belonging to Himalayan segment.Water samples from nineteen monitoring locations were collected in pre-monsoon(May-June),monsoon(AugustSeptember)and post-monsoon(December)seasons and subjected to be assessed for 20 elements(Ag,Al,Ba,Cd,Ca,Cr,Cu,Fe,Ga,K,Mn,Mg,Na,Ni,Pb,Sr,Th,U,Zn,and Zr)using ICP-OES(Inductively Coupled Plasma-Optical Emission Spectrometer).Different water pollution indexes such as HPI(Heavy Metal Pollution Index),MI(Metal Index)and PI(Pollution Index)were used to describe current water quality status at each monitoring station under particular classified ecological zone.The studied stations in hyporhithron zone had the value of Metal Index(MI>1),indicating threshold of warning.Further,the highest values of HPI in hyporhithron zone correspond to poor water quality status.Sites with poor water quality were also found to be contaminated as per the Pollution Index(PI),exhibiting high concentrations for element(Fe).However,the epirhithron and metarhithron zone in Himalayan segment showed excellent water quality mainly contributed from natural sources.Cluster Analysis(CA)and Principal Component Analysis(PCA)were applied to identify the main influential sources for Ganga river water pollution.The Kriging interpolation method was also applied to prepare spatial distribution map of computed indexes(HPI,MI,and PI).With the help of index of local Moran’s I(LMI),identified spatial clusters and spatial outliers revealed the elevated concentration of most elements in hyporhithron zone.The dataset presented in this study would be convenient for government officials in developing more effective management policies and necessary steps to check and monitor the Ganga river water quality.It was also suggested that further investigations in terms of trace elemental sources and their role in self-purification properties of Ganga water can be addressed in future.

Estimation of ocean primary productivity and its spatio-temporal variation mechanism for East China Sea based on VGPM model

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for CaseⅠand CaseⅡwater bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K 490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m 2 /d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m 2 /a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area.

Spatio-temporal variation and propagation direction of coal fire in Jharia Coalfield,India by satellite-based multi-temporal night-time land surface temperature imaging

In this paper,the spatio-temporal variation and propagation direction of coal fire were studied in the Jharia Coalfield(JCF),India during 2006–2015 through satellite-based night-time land surface temperature(LST)imaging.The LST was retrieved from Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)night-time thermal-infrared data by a robust split-window algorithm based on scene-specific regression coefficients,band-specific hybrid emissivity,and night-time atmospheric transmittance.The LST-profile-based coal fire detection algorithm was formulated through statistical analysis of the LST values along multiple transects across diverse coal fire locations in the JCF in order to compute date-specific threshold temperatures for separating thermally-anomalous and background pixels.This algorithm efficiently separates surface fire,subsurface fire,and thermally-anomalous transitional pixels.During the observation period,it was noticed that the coal fire area increased significantly,which resulted from new coal fire at many places owing to extensive opencast-mining operations.It was observed that the fire propagation occurred primarily along the dip direction of the coal seams.At places,lateral-propagation of limited spatial extent was also observed along the strike direction possibly due to spatial continuity of the coal seams along strike.Moreover,the opencast-mining activities carried out during 2009–2015 and the structurally weak planes facilitated the fire propagation.

Spatio-temporal Variation of Soil Respiration and Its Driving Factors in Semi-arid Regions of North China

Soil respiration （SR） is the second-largest flux in ecosystem carbon cycling. Due to the large spatio-temporal variability of environmental factors, SR varied among different vegetation types, thereby impeding accurate estimation of CO2 emissions via SR. However, studies on spatio-temporal variation of SR are still scarce for semi-arid regions of North China. In this study, we conducted 12-month SR measurements in six land-use types, including two secondary forests （Populus tomentosa （PT） and Robinia pseudoacacia （RP））, three artificial plantations （Armeniaca sibirica （AS）, Punica granatum （PG） and Ziziphusjujuba （Z J）） and one natural grassland （GR）, to quantify spatio-temporal variation of SR and distinguish its controlling factors. Results indicated that SR exhibited distinct sea- sonal patterns for the six sites. Soil respiration peaked in August 2012 and bottomed in April 2013. The temporal coefficient of variation （CI0 of SR for the six sites ranged from 76.98% to 94.08%, while the spatial CV of SR ranged from 20.28% to 72.97% across the 12-month measurement. Soil temperature and soil moisture were the major controlling factors of temporal variation of SR in the six sites, while spatial variation in SR was mainly caused by the differences in soil total nitrogen （STN）, soil organic carbon （SOC）, net photosynthesis rate, and fine root biomass. Our results show that the annual average SR and Q10 （temperature sensitivity of soil respira- tion） values tended to decrease from secondary forests and grassland to plantations, indicating that the conversion of natural ecosystems to man-made ecosystems may reduce CO2 emissions and SR temperature sensitivity. Due to the high spatio-temporal variation of SR in our study area, care should be taken when converting secondary forests and grassland to plantations from the point view of accurately quantifying C02 emissions via SR at regional scales.

Spatio-temporal variation and focal mechanism of the Wenchuan M_S8.0 earthquake sequence

Based on abundant aftershock sequence data of the Wenchuan Ms8.0 earthquake on May 12, 2008, we studied the spatio-temporal variation process and segmentation rupture characteristic. Dense aftershocks distribute along Longmenshan central fault zone of NE direction and form a narrow strip with the length of 325 krn and the depth between several and 40 km. The depth profile （section of NW direction） vertical to the strike of aftershock zone （NE direction） shows anisomerous wedgy distribution characteristic of afiershock concentrated regions; it is related to the force form of the Longmenshan nappe tectonic belt. The stronger aftershocks could be divided into northern segment and southern segment apparently and the focal depths of strong aftershocks in the 50 km area between northern segment and southern segment are shallower. It seems like ＇to be going to rupture＇ segment. We also study focal mechanisms and segmentation of strong aftershocks. The principal compressive stress azimuth of aftershock area is WNW direction and the faulting types of aftershocks at southern and northern segment have the same proportion. Because afiershocks distribute on different secondary faults, their focal mechanisms present complex local tectonic stress field. The faulting of seven strong earthquakes on the Longmenshan central fault is mainly characterized by thrust with the component of right-lateral strike-slip. Meantime six strong aftershocks on the Longmenshan back-range fault and Qingchuan fault present strike-slip faulting. At last we discuss the complex segmentation rupture mechanism of the Wenchuan earthquake.

Spatio-temporal Variations of Temperature and Precipitation During 1951–2019 in Arid and Semiarid Region, China

Understanding the spatio-temporal variations of temperature and precipitation in the arid and semiarid region of China(ASRC)is of great significance for promoting regional eco-environmental protection and policy-making.In this study,the annual and seasonal spatio-temporal patterns of change in average temperature and precipitation and their influencing factors in the ASRC were analyzed using the Mann-Kendall test,linear tendency estimation,accumulative anomaly and the Pearson’s correlation coefficient.The results showed that both annual average temperature and average annual precipitation increased in the ASRC during 1951–2019.The temperature rose by about 1.93℃and precipitation increased by about 24 mm.The seasonal average temperature presented a significant increase trend,and the seasonal precipitation was conspicuous ascension in spring and winter.The spatio-temporal patterns of change in temperature and precipitation differed,with the southwest area showing the most obvious variation in each season.Abrupt changes in annual and seasonal average temperature and precipitation occurred mainly around the 1990 s and after 2000,respectively.Atmospheric circulation had an important effect on the trends and abrupt changes in temperature and precipitation.The East Asian summer monsoon had the largest impact on the trend of average annual temperature,as well as on the abrupt changes of annual average temperature and precipitation.Temperature and precipitation changes in the ASRC were influenced by long-term and short-term as well as direct and indirect anthropogenic and natural factors.This study identifies the characteristics of spatio-temporal variations in temperature and precipitation in the ASRC and provides a scientific reference for the formulation of climate change responses.

SPATIO-TEMPORAL VARIATION OF ACTUAL EVAPOTRANSPIRATION AND ITS RELATION WITH CLIMATE PARAMETERS IN THE PEARL RIVER BASIN,CHINA

Spatio-temporal variation of actual evapotranspiration(ETa) in the Pearl River basin from 1961 to 2010 are analyzed based on daily data from 60 national observed stations. ETa is calculated by the Advection-Aridity model(AA model) in the current study, and Mann-Kendall test(MK) and Inverse Distance Weighted interpolation method(IDW)were applied to detect the trends and spatial variation pattern. The relations of ETa with climate parameters and radiation/dynamic terms are analyzed by Person correlation method. Our findings are shown as follows: 1) Mean annual ETa in the Pearl River basin is about 665.6 mm/a. It has significantly decreased in 1961-2010 at a rate of-24.3mm/10 a. Seasonally, negative trends of summer and autumn ETa are higher than that of spring and winter. 2) The value of ETa is higher in the southeast coastal area than in the northwest region of the Pearl River basin, while the latter has shown the strongest negative trend. 3) Negative trends of ETa in the Pearl River basin are most probably due to decreasing radiation term and increasing dynamic term. The decrease of the radiation term is related with declining diurnal temperature range and sunshine duration, and rising atmospheric pressure as well. The contribution of dynamic term comes from increasing average temperature, maximum and minimum temperatures in the basin. Meanwhile, the decreasing average wind speed weakens dynamic term and finally, to a certain extent, it slows down the negative trend of the ETa.

Spatio-temporal variations in organic carbon density and carbon sequestration potential in the topsoil of Hebei Province, China

Reliable prediction of soil organic carbon（SOC） density and carbon sequestration potential（CSP） plays an important role in the atmospheric carbon dioxide budget. This study evaluated temporal and spatial variation of topsoil SOC density and CSP of 21 soil groups across Hebei Province, China, using data collected during the second national soil survey in the 1980 s and during the recent soil inventory in 2010. The CSP can be estimated by the method that the saturated SOC content subtracts the actual SOC associated with clay and silt. Overall, the SOC density and CSP of most soil groups increased from the 1980 s to 2010 and varied between different soil groups. Among all soil groups, Haplic phaeozems had the highest SOC density and Endogleyic solonchaks had the largest CSP. Areas of soil groups with the highest SOC density（90 to 120 t C ha^（–1）） and carbon sequestration（120 to 160 t C ha^（–1）） also increased over time. With regard to spatial distribution, the north of the province had higher SOC density but lower CSP than the south. With respect to land-use type, cultivated soils had lower SOC density but higher CSP than uncultivated soils. In addition, SOC density and CSP were influenced by soil physicochemical properties, climate and terrain and were most strongly correlated with soil humic acid concentration. The results suggest that soil groups（uncultivated soils） of higher SOC density have greater risk of carbon dioxide emission and that management should be aimed at maximizing carbon sequestration in soil groups（cultivated soils） with greater CSP. Furthermore, soils should be managed according to their spatial distributions of SOC density and carbon sequestration potential under different soil groups.

SPATIO-TEMPORAL VARIATION CHARACTERISTICS OF EXTREMELY HEAVY PRECIPITATION FREQUENCY OVER SOUTH CHINA IN THE LAST 50 YEARS

This paper comprehensively studies the spatio-temporal characteristics of the frequency of extremely heavy precipitation events over South China by using the daily precipitation data of 110 stations during 1961 to 2008 and the extremely heavy precipitation thresholds determined for different stations by REOF, trend coefficients, linear trend, Mann-Kendall test and variance analysis. The results are shown as follows. The frequency distribution of extremely heavy precipitation is high in the middle of South China and low in the Guangdong coast and western Guangxi. There are three spatial distribution types of extremely heavy precipitation in South China. The consistent anomaly distribution is the main type. Distribution reversed between the east and the west and between the south and the north is also an important type. Extremely heavy precipitation events in South China mainly occurred in the summer-half of the year. Their frequency during this time accounts for 83.7% of the total frequency. In the 1960 s and 1980 s, extremely heavy precipitation events were less frequent while having an increasing trend from the late 1980 s. Their climatological tendency rates decrease in the central and rise in the other areas of South China, and on average the mean series also shows an upward but insignificant trend at all of the stations. South China's frequency of extremely heavy precipitation events can be divided into six major areas and each of them shows a different inter-annual trend and three of the representative stations experience abrupt changes by showing remarkable increases in terms of Mann-Kendall tests.

Spatio-temporal variation of spring phenology in Tibetan Plateau and its linkage to climate change from 1982 to 2012

The influence of climate change on vegetation phenology is a heated issue in current climate change study.We used GIMMS-3g NDVI data to detect the spatio-temporal dynamics of the start of the growing season(SGS) over the Tibetan Plateau(TP) from 1982 to 2012 and to analyze its relationship with temperature and precipitation.No significant trend was observed in the SGS at the regional scale during the study period(R^2 = 0.03,P = 0.352).However,there were three time periods(1982-1999,1999-2008 and 2008-2012) with identifiable,distinctly different trends.Regions with a significant advancing trend were mainly scattered throughout the humid and semi-humid areas,whereas the regions with a significant delaying trend were mostly distributed throughout the semi-arid areas.Statistical analysis showed that the response of the SGS to climate change varies spatially.The SGS was significantly correlated with the spring temperature and the start of the thermal growth season(STGS) in the relatively humid area.With increasing aridity,theimportance of the spring temperature for the SGS gradually decreased.However,the influences of precipitation and winter temperature on the SGS were complicated across the plateau.

Assessment of Spatio-Temporal Variations in Water Quality of Shailmari River, Khulna (Bangladesh) Using Multivariate Statistical Techniques

Surface water has become one of the most vulnerable resources on the earth due to deterioration of its quality from diverse sources of pollution. Understanding of the spatiotemporal distribution of pollutants and identification of the sources in the river systems is a prerequisite for the protection and sustainable utilization of the water resources. Multivariate statistical techniques such as Principal Component Analysis (PCA) and Factor Analysis (FA) were applied in this study to investigate the temporal and spatial variations of water quality and appoint the major factors of pollution in the Shailmari River system. Water quality data for 14 physicochemical parameters from 11 monitoring sites over the year of 2014 in three sampling seasons were collected and analyzed for this study. Kruskal-Wallis test showed significant (p < 0.01) temporal and spatial variations in all of the water quality parameters of the river water. Principal component analysis (PCA) allowed extracting the contributing parameters affecting the seasonal water quality in the river system. Scatter plots of the PCs showed the tidal and spatial variation within river system and identified parameters controlling the behavior in each case. Factor analysis (FA) further reduced the data and extracted factors which are significantly responsible for water quality variation in the river. The results indicate that the parameters controlling the water quality in different seasons are related with salinity, anthropogenic pollution (sewage disposal, effluents) and agricultural runoff in pre-monsoon;precipitation induced surface runoff in monsoon;and erosion, oxidation or organic pollution (point and non-point sources) in post-monsoon. Therefore, the study reveals the applicability and usefulness of the multivariate statistical methods in assessing water quality of river by identifying the potential environmental factors controlling the water quality in different seasons which might help to better understand, monitor and manage the quality of the water resources.

SPATIO-TEMPORAL VARIATION OF SENSIBLE HEAT FLUX OVER SOUTHERN CHINA

The spatio-temporal variation of surface sensible heat flux(SHF) in southern China(SC) is studied based on the data evaluated from conventional observational meteorological data.There exist prominent increasing trends in all seasonal surface sensible heat fluxes in the western SC and decreasing trends in the central-eastern part of southern China.The variations of surface sensible heat flux in all seasons are dominant on interannual time-scales.The land-air temperature difference and the near-surface wind speed are two key factors for the interannual variations of SHF,but the former is more important.The first two major anomalous patterns of SHF are presented as the region-wide in-phase anomalies and the east-west dipole anomalies,respectively,based on the EOF analysis results.

Spatio-Temporal Variation of HIV Infection in Kenya

Disease mapping is the study of the distribution of disease relative risks or rates in space and time, and normally uses generalized linear mixed models (GLMMs) which includes fixed effects and spatial, temporal, and spatio-temporal random effects. Model fitting and statistical inference are commonly accomplished through the empirical Bayes (EB) and fully Bayes (FB) approaches. The EB approach usually relies on the penalized quasi-likelihood (PQL), while the FB approach, which has increasingly become more popular in the recent past, usually uses Markov chain Monte Carlo (McMC) techniques. However, there are many challenges in conventional use of posterior sampling via McMC for inference. This includes the need to evaluate convergence of posterior samples, which often requires extensive simulation and can be very time consuming. Spatio-temporal models used in disease mapping are often very complex and McMC methods may lead to large Monte Carlo errors if the dimension of the data at hand is large. To address these challenges, a new strategy based on integrated nested Laplace approximations (INLA) has recently been recently developed as a promising alternative to the McMC. This technique is now becoming more popular in disease mapping because of its ability to fit fairly complex space-time models much more quickly than the McMC. In this paper, we show how to fit different spatio-temporal models for disease mapping with INLA using the Leroux CAR prior for the spatial component, and we compare it with McMC using Kenya HIV incidence data during the period 2013-2016.

Wi-Fi Positioning Dataset with Multiusers and Multidevices Considering Spatio-Temporal Variations

Precise information on indoor positioning provides a foundation for position-related customer services.Despite the emergence of several indoor positioning technologies such as ultrawideband,infrared,radio frequency identification,Bluetooth beacons,pedestrian dead reckoning,and magnetic field,Wi-Fi is one of the most widely used technologies.Predominantly,Wi-Fi fingerprinting is the most popular method and has been researched over the past two decades.Wi-Fi positioning faces three core problems:device heterogeneity,robustness to signal changes caused by human mobility,and device attitude,i.e.,varying orientations.The existing methods do not cover these aspects owing to the unavailability of publicly available datasets.This study introduces a dataset that includes the Wi-Fi received signal strength(RSS)gathered using four different devices,namely Samsung Galaxy S8,S9,A8,LG G6,and LG G7,operated by three surveyors,including a female and two males.In addition,three orientations of the smartphones are used for the data collection and include multiple buildings with a multifloor environment.Various levels of human mobility have been considered in dynamic environments.To analyze the time-related impact on Wi-Fi RSS,data over 3 years have been considered.

Bird Species Diversity and Spatio-temporal Variation in the Sihong Hongze Lake Wetland National Nature Reserve in Eastern China

As an important hub on the East Asian-Australian Flyway(EAAF),Hongze Lake is an important migratory stopover and wintering site for hundreds of thousands of birds.However,research on bird community diversity in this area is still lacking.We conducted a bird survey from July 2020 to June 2021 using the line transect method on the terrestrial habitat,as well as the fixed-point method in the lake wetland at the Sihong Hongze Lake Wetland National Nature Reserve located in northwestern Hongze Lake,and analyzed the temporal-spatial variation in the bird community.The results showed that a total of 170432 detections of 215 bird species belonging to 18 orders and 55 families were recorded.In terms of species composition,the proportion of terrestrial birds was relatively high,followed by waterfowl richness,with high numbers of Anatidae species and shorebirds.For bird species abundance,waterfowl had the highest abundance of common coot(Fulica atra),belonging to the Rallidae family,followed by Anatidae and Ardeidae species.The abundance of shorebirds was extremely low,and that of non-waterfowl was also low.In terms of temporal patterns,the number of bird species and richness index were higher in spring and autumn but lower in winter and summer.The bird abundance was the highest in winter,and the remaining three seasons were similar in terms of bird abundance.The diversity index and evenness index were higher in spring,summer and autumn,and lowest in winter.For the spatial pattern,the open water in the western part of the reserve included the most densely distributed areas for birds,and the number of bird species and their abundance were both the highest in that part.There were significant differences in the bird community structures among the four habitats.The species number and richness index of birds in the reed habitat were the highest,and the bird abundance was also high,but the diversity index and evenness index were low.Although the bird abundance in the lake habitat was much higher than in the other habitats,the diversity index,evenness index and richness index were the lowest.The numbers of bird species and individuals in tourist attraction land and farmland were low,but the diversity index,evenness index and richness index were high.Our results reveal the spatial and temporal patterns of bird species diversity and abundance in Sihong Hongze Lake Wetland National Nature Reserve,and reflect the effects of different habitat types on bird diversity.

Accuracy and spatio-temporal variation of high resolution satellite rainfall estimate over the Ganjiang River Basin

Based on spatial interpolation rainfall of the ground gauge measurement,we proposed a method to comprehensively evaluate and compare the accuracy of satellite rainfall estimates (SREs) at three spatial scales:0.25°×0.25° grid scale,sub-catchment scale and the whole basin scale.Using this method,we evaluated the accuracy of six high-resolution monthly SREs (TRMM 3B42 V6,3B42RT V6,CMORPH,GSMaP MWR+,GSMaP MVK+ and PERSIANN) and revealed the spatio-temporal variation of the SRE accuracy based on spatial interpolated rainfall from a dense network of 325 gauges during 2003-2009 over the Ganjiang River Basin in the Southeast China.The results showed that ground gauge-calibrated 3B42 had the highest accuracy with slight overestimation,whereas the other five uncalibrated SREs had severe underestimation.The accuracy of the six SREs in wet seasons was remarkably higher than that in the dry seasons.When the time scale was expanded,the accuracy of SRE,particularly 3B42,increased.Furthermore,the accuracy of SREs was relatively low in the western mountains and northern piedmont areas,while it was relatively high in the central and southeastern hills and basins of the Ganjiang River Basin.When the space scale was expanded,the accuracy of the six SREs gradually increased.This study provided an example for of SRE accuracy validation in other regions,and a direct basis for further study of SRE-based hydrological process.

Spatio-temporal variation of precipitation in the Three-River Headwater Region from 1961 to 2010

Based on a monthly dataset of precipitation time series （1961-2010） from 12 me- teorological stations across the Three-River Headwater Region （THRHR） of Qinghai Province China, the spatio-temporal variation and abrupt change analysis of precipitation were exam- ined by using moving average, linear regression, spline interpolation, the Mann-Kendall test and so on. Major conclusions were as follows. （1） The long-term annual and seasonal pre- cipitation in the study area indicated an increasing trend with some oscillations during 1961-2010; however, the summer precipitation in the Lantsang （Lancang） River Headwater Region （LARHR）, and the autumn precipitation in the Yangtze River Headwater Region （YERHR） of the THRHR decreased in the same period. （2） The amount of annual precipita- tion in the THRHR and its three sub-headwater regions was greater in the 1980s and 2000s. The springs were fairly wet after the 1970s, while the summers were relatively wet in the 1960s, 1980s and 2000s. In addition, the amount of precipitation in the autumn was greater in the 1970s and 1980s, but it was relatively less for the winter precipitation, except in the 1990s （3） The normal values of spring, summer, winter and annual precipitation in the THRHR and its three sub-headwater regions all increased, but the normal value of summer precipitation in the LARHR had a negative trend and the normal value of winter precipitation declined in general. （4） The spring and winter precipitation increased in most of the THRHR. The summer autumn and annual precipitation increased mainly in the marginal area of the west and north and decreased in the regions of Yushu, Zaduo, Jiuzhi and Banma. （5） The spring and winter precipitation in the THRHR and its three sub-headwater regions showed an abrupt change, except for the spring precipitation in the YARHR. The abrupt changes of spring precipitation were mainly in the late 1980s and early 1990s, while the abrupt changes of winter precipita- tion were primary in the mid- to late 1970s. This research would be helpful for further under- standing the trends and periodicity of precipitation and for watershed-based water resource management in the THRHR.

Spatio-temporal variation and the driving forces of tea production in China over the last 30 years

As a daily necessity and an important cash crop in China and many other countries, tea has received increasing attention. Using production concentration index model and in- dustry＇ s barycenter theory, we analyzed the spatio-temporal distribution of tea production and barycenter movement trajectory of tea plantations and production in China between 1986 and 2015. Driving forces of the movement were also analyzed. From 1986 to 2000, tea production in China＇s Mainland of grew slowly （by 210x103 t）. The continuous increase in tea yield per unit area was the primary contributor （more than 60%） to the growth in tea production during this period. Since China joined the World Trade Organization （WTO） in 2001, tea production has grown rapidly, by 1.59x106 t between 2001 and 2015. The increase in the tea plantations area is the main contributor. Over the last 30 years, the barycenters of tea production in China have moved westward from the Dongting Lake Plain to the eastern fringe of the Yun- nan-Guizhou Plateau. Guizhou, Guangxi, and Sichuan in southwestern China have gradually become regions of new concentrated tea plantations and main tea production provinces. Lower cost of land and labor in southwestern China are the main drivers of the westward movement of China＇s tea industry. In addition, supportive policies and the favorable natural geographical environment contribute to the westward movement of tea industry. Our research highlights the spatio-temporal variation of China＇s tea production in the last three decades. The result indicates importance to make appropriate policies to promote the development of tea industry in China.

Spatio-temporal variations and influencing factors of energy-related carbon emissions for Xinjiang cities in China based on time-series nighttime light data

This essay combines the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS)nighttime light data and the Visible Infrared Imaging Radiometer Suite(VIIRS)nighttime light data into a“synthetic DMSP”dataset,from 1992 to 2020,to retrieve the spatio-temporal variations in energy-related carbon emissions in Xinjiang,China.Then,this paper analyzes several influencing factors for spatial differentiation of carbon emissions in Xinjiang with the application of geographical detector technique.Results reveal that(1)total carbon emissions continued to grow,while the growth rate slowed down in the past five years.(2)Large regional differences exist in total carbon emissions across various regions.Total carbon emissions of these regions in descending order are the northern slope of the Tianshan(Mountains)>the southern slope of the Tianshan>the three prefectures in southern Xinjiang>the northern part of Xinjiang.(3)Economic growth,population size,and energy consumption intensity are the most important factors of spatial differentiation of carbon emissions.The interaction between economic growth and population size as well as between economic growth and energy consumption intensity also enhances the explanatory power of carbon emissions’spatial differentiation.This paper aims to help formulate differentiated carbon reduction targets and strategies for cities in different economic development stages and those with different carbon intensities so as to achieve the carbon peak goals in different steps.