Quantitative Analysis of Natural and Human Factors of Oasis Change in the Tail of Shiyang River over the Past 60 Years

The human and natural factors complicit in the driving forces of oasis change have always received considerable interest from the international research community. In this study, we used principal component analysis of natural and socio-economic statistical factors to quantitatively analyze the causal relationships and their contributions to the observed periodic expansion or shrinkage of the Minqin Oasis over almost 60 years. Our results show that human factors were the dominant factors governing expansion or shrinkage, with average contributions of 69.38% and 76.16%, respectively. Moreover, policy decisions have been the pivotal human factors. Under the influence of various policies, we have found that water resource utilization, land reclamation, population explosion, ecological protection and economic development have each played leading roles in different periods. This study provides a scientific basis for modelling the dynamics of an oasis for sustainable management.

A New Method to Predict Erythrocyte Sedimentation Rate with Natural Geographical Factors and Location by Case-based Reasoning: A Case Study of China

Reference values of erythrocyte sedimentation rate(ESR)are the key to interpret ESR blood test in clinic.The common local reference ESR values are more accuracy in blood test that are established with natural geographical factors by using the multiple linear regression(MLR)model and the artificial neural network(ANN).These knowledge-based methods have limitations since the knowledge domains of ESR and natural geographical factors are limited.This paper presents a new cases-depended model to establish reference ESR values with natural geographical factors and location using case-based reasoning(CBR)since knowledge domain of ESR and geographical factors is weak.Overall 224 local normal ESR values of China that calculated from 13623 samples were obtained,and the corresponding natural geographical factors and location that include altitude,sunshine hours,relative humidity,temperature,precipitation,annual temperature range and annual average wind speed were obtained from the National Geomatics Center of China.CBR was used to predict the unseen local reference ESR values with cases.The average absolute deviation(AAD),mean square error(MSE),prediction accuracy(PA),and Pearson correlation coefficient(r)between the observed and estimated data of proposed model is 33.07%,9.02,66.93% and 0.78,which are better than those of ANN and MLR model.The results show that the proposed model provides higher prediction accuracy than those of the artificial neural network and multiple linear regression models.The predicted values are very close to the observed values.Model results show significant agreement of cases data.Consequently,the model is used to predict the unseen local reference ESR with natural geographical factors and location.In spatial,the highest ESR reference areas are distributed in the southern-western district of China that includes Sichuan,Chongqing,Guangxi and Guizhou provinces,and the reference ESR values are greater than 23 mm/60 min.The higher ESR reference values are distributed in the middle part and northern-eastern of China which include Hubei,Henan,Shaanxi,Shanxi,Jilin and Heilongjiang provinces,and the reference ESR values are greater than 18 mm/60min.The lowest ESR reference values are distributed in the northern-western of China that includes Tibet and Xinjiang,and the reference ESR values are lower than 5 mm/60min.

2013 SCI Impact Factor being 1.788 for Journal of Natural Gas Chemistry

The SCI impact factor of Journal of Natural Gas Chemistry （JNGC） is 1.788, according to the ＂2013 Journal Citation Reports （JCR） Science Edition＂. This is the highest SCI impact factor for Journal of Natural Gas Chemistry since the journal was included in the Science Citation Index Expanded （SCIE） in 2007, and it ranks first among chemistry journals in China. Over the past decade, the Journal of Natural Gas Chemistry has become more and more international and has received large numbers of manuscripts concerning energy chemistry. In deed, nowadays enerzy chemistry is becoming one of the hot topics.

Investigating the Effect of Climatic Factors of Roshtkhar Town (Khorasan Razavi, Iran) on the Development and Cultivation of Pistachio Using GIS Software

The use of Geographic Information System (GIS) has significantly helped managers provide optimal models of sustainable agricultural development, identify local features related to agricultural production and their proper zoning, identify agricultural needs and constraints and finally provide the appropriate structure of land use. The main purpose of this study was to determine areas capable of cultivating Pistachio according to the parameters affecting the Pistachio cultivation in Roshtkhar town. Statistics of meteorological stations of the town were taken from Meteorology Organization of Khorasan Razavi for the period of 1989-2010 in order to determine climatic parameters required to cultivate Pistachio. For mapping surface elevation, slope, aspect, and TIN of the geographic organization of armed forces with a scale of 1:250,000 topographic maps were used. For mapping vegetation and land use in the area under study, land capability map of the area on a scale of 1:250,000 from the institute of soil and water was used. Also information on cultivation and annual production of agricultural statistics, published by Agriculture was used. Finally, it was concluded that the northeast and southwest of Roshtkhar town are the most prone areas to cultivate Pistachio.

2011 SCI Impact Factor being 1.348 for Journal of Natural Gas Chemistry

The SCI impact factor of Journal of Natural Gas Chemistry （JNGC） is 1.348, according to the ＂2011 Journal Citation Reports （JCR） Science Edition＂. This is the highest SCI impact factor for Journal of Natural Gas Chemistry since the journal was included in the Science Citation Index Expanded （SCIE） in 2007, and it ranks first among chemistry journals in China.

Assessing the vulnerability of changing coasts,Hainan Island,China

Knowledge of coastline changes and vulnerability is of great importance to local government departments that are responsible for the management and development of coastal zones.To study the nature of change and vulnerability along the coasts of the Hainan Island,we collected a large number of sediment samples through the last few years,and reconstructed the changes of the coastline by combining the data of sediment grain-size analysis and the nautical charts/TM RS imaginary.Contrary to being almost free from erosion（as expected from the findings that the coastlines are in a relatively stable state）,four major cities in Hainan（i.e.,Haikou,Wenchang,Sanya and Changjiang） turned out to be suffered from a moderate coastal vulnerability primarily because of the large populations that impose considerable pressure on the coastlines.Thus,the assessment methodology utilized in this study,including both anthropogenic and natural factors,serves as a useful tool to obtain a comprehensive understanding of coastline vulnerability for local government,in terms of coastal management and adaptation.

黄河流域径流变化

The driving factors of runoff changes can be divided into precipitationfactor and non-precipitation factor, and they can also be divided into natural factor and humanactivity factor. In this paper, the ways and methods of these driving factors impacting on runoffchanges are analyzed at first, and then according to the relationship between precipitation andrunoff, the analytical method about impacts of precipitation and non-precipitation factors onbasin's natural runoff is derived. The amount and contribution rates of the two factors impacting onnatural runoff between every two adjacent decades during 1956-1998 are calculated in the YellowRiver Basin (YRB). The results show that the amount and contribution rate of the two factorsimpacting on natural runoff are different in different periods and regions. For the YRB, thenon-precipitation impact is preponderant for natural runoff reduction after the 1970s. Finally, bychoosing main factors impacting on the natural runoff, one error back-propagation (BP) artificialneural network (ANN) model has been set up, and the impact of human activities on natural runoffreduction in the YRB is simulated. The result shows that the human activities could cause a 77 x10^8 m^3·a^(-1) reduction of runoff during 1980-1998 according to the climate background of1956-1979.

The spatial relationship between salt marsh vegetation patterns,soil elevation and tidal channels using remote sensing at Chongming Dongtan Nature Reserve, China

The analysis of vegetation-environment relationships has always been a study hotspot in ecology. A number of biotic, hydrologic and edaphic factors have great influence on the distribution of macrophytes within salt marsh.Since the exotic species Spartina alterniflora（S. alterniflora） was introduced in 1995, a rapid expansion has occurred at Chongming Dongtan Nature Reserve（CDNR） in the Changjiang（Yangtze） River Estuary, China.Several important vegetation-environment factors including soil elevation, tidal channels density（TCD）,vegetation classification and fractional vegetation cover（FVC） were extracted by remote sensing method combined with field measurement. To ignore the details in interaction between biological and physical process,the relationship between them was discussed at a large scale of the whole saltmarsh. The results showed that Scirpus mariqueter（S. mariqueter） can endure the greatest elevation variance with 0.33 m throughout the marsh in CDNR. But it is dominant in the area less than 2.5 m with the occurrence frequency reaching 98%. S. alterniflora has usually been found on the most elevated soils higher than 3.5 m but has a narrow spatial distribution. The rapid decrease of S. mariqueter can be explained by stronger competitive capacity of S. alterniflora on the high tidal flat. FVC increases with elevation which shows significant correlation with elevation（r=0.30, p〈0.001）. But the frequency distribution of FVC indicates that vegetation is not well developed on both elevated banks near tidal channels from the whole scale mainly due to tidal channel lateral swing and human activities. The significant negative correlation（r=–0.20, p〈0.001） was found between FVC and TCD, which shows vegetation is restricted to grow in higher TCD area corresponding to lower elevation mainly occupied by S. mariqueter communities. The maximum occurrence frequency of this species reaches to 97% at the salt marsh with TCD more than 8 m/m2.

Contents and spatial distribution patterns of heavy metals in the hinterland of the Tengger Desert,China

The desert in northern China is one of important sources of loess and one significant source of material for sandstorms in Asia.The sand/dust that is transported from desert when sandstorms occur can destroy the growth of crops,cause serious losses and great harm to the economic construction and life safety,and cause natural environment pollution.Hence,it is very important to deepen the research into heavy metals in surface deposits at vulnerable ecological region of arid land of northern China to guide local industrial and agricultural development and improve environmental protection.In this research,10 heavy metal elements(Cr,Mn,Fe,Co,Ni,Cu,Zn,Cd,Pb,and Th)were tested and analyzed in 33 soil sample sites collected from the hinterland of the Tengger Desert,northern China.The results showed that the average abundance of Th exceeded its background soil value of China by more than 5.2 times,which suggests that the Tengger Desert is polluted by Th.In addition,based on principal component analysis,spatial differentiation,and correlation analysis,we identified the source of element with a coefficient of variation in abundance of greater than 0.5 or exceeding the background soil value of China.Principal component analysis and correlation analysis showed that the sources of heavy metals of Cr,Mn,Fe,Co,Ni,Cu,and Cd were similar,while those of Th and Zn were different.Moreover,based on the contents and spatial distribution characteristics of those heavy metal elements,we found that the formation of heavy metal elements enrichment areas is caused by industrial pollution,development of irrigated agricultural,geological,and geomorphic conditions,and the sedimentary environment in the study area.Our result can provide information on the environmental background values of soils in the hinterland of the Tengger Desert.

Modeling groundwater nitrate concentrations using spatial and non-spatial regression models in a semi-arid environment

Nitrate nitrogen(NO_(3)^(-)N)from agricultural activities and in industrial wastewater has become the main source of groundwater pollution,which has raised widespread concerns,particularly in arid and semi-arid river basins with little water that meets relevant standards.This study aimed to investigate the performance of spatial and non-spatial regression models in modeling nitrate pollution in a semi-intensive farming region of Iran.To perform the modeling of the groundwater's NO_(3)^(-)N concentration,both natural and anthropogenic factors affecting groundwater NO_(3)^(-)N were selected.The results of Moran's I test showed that groundwater nitrate concentration had a significant spatial dependence on the density of wells,distance from streams,total annual precipitation,and distance from roads in the study area.This study provided a way to estimate nitrate pollution using both natural and anthropogenic factors in arid and semi-arid areas where only a few factors are available.Spatial regression methods with spatial correlation structures are effective tools to support spatial decision-making in water pollution control.

1958-2017年长江流域气候变化的时空特征与热点区域

The Yangtze River Watershed in China is a climate change hotspot featuring strong spatial and temporal variability;hence, it poses a certain threat to social development. Identifying the characteristics of and regions vulnerable to climate change is significantly important for formulating adaptive countermeasures. However, with regard to the Yangtze River Watershed, there is currently a lack of research on these aspects from the perspective of natural and anthropogenic factors. To address this issue, in this study, based on the temperature and precipitation records from 717 meteorological stations, the RClim Dex and random forest models were used to assess the spatiotemporal characteristics of climate change and identify mainly the natural and anthropogenic factors influencing climate change hotspots in the Yangtze River Watershed for the period 1958-2017. The results indicated a significant increasing trend in temperature, a trend of wet and dry polarization in the annual precipitation, and that the number of temperature indices with significant variations was 2.8 times greater than that of precipitation indices. Significant differences were also noted in the responses of the climate change characteristics of the sub-basins to anthropogenic and natural factors;the delta plain of the Yangtze River estuary exhibited the most significant climate changes, where 88.89% of the extreme climate indices varied considerably. Furthermore, the characteristics that were similar among the identified hotpots, including human activities(higher Gross Domestic Product and construction land proportions) and natural factors(high altitudes and large proportions of grassland and water bodies), were positively correlated with the rapid climate warming.