Time series prediction of reservoir bank landslide failure probability considering the spatial variability of soil properties

Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.

Inverse reliability analysis and design for tunnel face stability considering soil spatial variability

The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.

Spatial-temporal heterogeneity and controlling factors of evapotranspiration in Nujiang River Basin based on Variable Infiltration Capacity(VIC)model

Land surface evapotranspiration(ET)is a critical component in the hydrological cycle but has not well been understood in data-scarce areas especially in river basins,like Nujiang River(NRB)which is characterized by large elevation gradient and different vegetation zones with complex processes of water and energy exchange.The quality of ET from optical remote sensing is constrained by cloud cover which is common in the NRB in the monsoon seasons.To understand factors controlling the spatial-temporal heterogeneity of ET in NRB,we employed the Variable Infiltration Capacity(VIC)hydrological model by parameter optimization with support of quality controlled remote sensing ET product and observed river runoff series in the river.The modeled ET has increased during 1984-2018,which might be one of the reasons for the runoff decrease but precipitation increase in the same period.ET increase and runoff decrease tended to be quicker within altitudinal band of 2000-4000 m than in other areas in NRB.We observed that ET variation in different climatic zones were controlled by different factors.ET is generally positively correlated with precipitation,temperature,and shortwave radiation but negatively with relative humidity.In the Tundra Climate(Et)zone in the upper reach of NRB,ET is controlled by precipitation,while it is controlled by shortwave radiation in the snow climate with dry winter(Dw)zone.ET increase is influenced by the increase of temperature,wind speed,and shortwave radiation in the middle and downstream of NRB with warm temperate climate,fully humid(Cf)and warm temperate climate with dry winter(Cw).

On Spatial Variability and Distribution of Soil Nutrients in Different Nitraria tangutorum Bobr.Populations in Tsaidam Basin

In this paper,six important distribution areas of Nitraria tangutorum Bobr.in Tsaidam Basin were selected as research objects,to study spatial variability and distribution of soil nutrients in different N.tangutorum populations and analyze the relationship between soil nutrient contents and geographical location,by measuring soil pH and the contents of organic matter（OM）,total nitrogen（N）,total phosphorus（P）,total potassium（K）,hydrolysis N,available P and available K in soils.Results showed that：（1） soil nutrient contents among different populations showed significant spatial variability,and soil depth had a significant effect on soil nutrients contents,but the variation rules were not obvious.（2）Average pH and average contents of OM,total N,total P,total K,hydrolysis N,available P and available K in soils with different depths（0-15,15-30,30-45 cm） varied in the range of 8.37-9.21,3.34-20.68,0.18-1.21,0.35-0.75,16.12-22.04,5.13-553.28,1.10-52.54 and 103.83-562.28 mg/kg,respectively.（3） The analysis results of correlation between average values of pH and contents of nutrient indexes in soils with different depths（0-15,15-30,30-45 cm） showed that the correlation of these indexes were different.（4）OM and total N contents in soils with different depths（0-15,15-30,30-45 cm） all had a significant positive correlation with latitude and negative correlation with longitude and altitude,and the correlation of available P and available K contents in surface soils（0-15 cm） with latitude,longitude and altitude were significant positive,significant negative and significant negative,respectively;moreover,longitude and latitude also showed a significant impact on soil available K contents with the depth of 30-45 cm.In addition,comprehensive analysis result of nutrient contents showed that N.tangutorum populations in Huaitou Tala Town had the highest fertility,and the fertility levels of N.tangutorum populations in Chaka Town and Wulan Keke Town were relatively lower.

Spatial variability of soil total nitrogen,phosphorus and potassium in Renshou County of Sichuan Basin,China

Understanding soil nutrient distributions and the factors affecting them are crucial for fertilizer management and environmental protection in vulnerable ecological regions.Based on 555 soil samples collected in 2012 in Renshou County,located in the purple soil hilly area of Sichuan Basin,China,the spatial variability of soil total nitrogen(TN),total phosphorus(TP)and total potassium(TK)was studied with geostatistical analysis and the relative roles of the affecting factors were quantified using regression analysis.The means of TN,TP and TK contents were 1.12,0.82 and 9.64 g kg^(–1),respectively.The coefficients of variation ranged from 30.56 to 38.75%and the nugget/sill ratios ranged from 0.45 to 0.61,indicating that the three soil nutrients had moderate variability and spatial dependence.Two distribution patterns were observed.TP and TK were associated with patterns of obvious spatial distribution trends while the spatial distribution of TN was characterized by higher variability.Soil group,land use type and topographic factors explained 26.5,35.6 and 8.4%of TN variability,respectively,with land use being the dominant factor.Parent material,soil group,land use type and topographic factors explained 17.5,10.7,12.0 and 5.0%of TP variability,respectively,and both parent material and land use type played important roles.Only parent material and soil type contributed to TK variability and could explain 25.1 and 13.7%of TK variability,respectively.More attention should focus on adopting reasonable land use types for the purposes of fertilizer management and consider the different roles of the affecting factors at the landscape scale in this purple soil hilly area.

Probabilistic assessment of tunnel convergence considering spatial variability in rock mass properties using interpolated autocorrelation and response surface method

This study aims at the probabilistic assessment of tunnel convergence considering the spatial variability in rock mass properties. The method of interpolated autocorrelation combined with finite difference analysis is adopted to model the spatial variability of rock mass properties. An iterative procedure using the first-order reliability method(FORM) and response surface method(RSM) is employed to compute the reliability index and its corresponding design point. The results indicate that the spatial variability considerably affects the computed reliability index. The probability of failure could be noticeably overestimated in the case where the spatial variability is neglected. The vertical scale of fluctuation has a much higher effect on the probabilistic result with respect to the tunnel convergence than the horizontal scale of fluctuation. And the influence of different spacing of control points on the computational accuracy is investigated.

Spatial Variability of Nutrient Properties in Black Soil of Northeast China

A total of 1400 soil samples from the plow layer （0-20 cm） at an approximate interval of 5 km were collected in the autumn of 2002 over the entire black soil arable crops region to determine the spatial variability of seven variables, such as total organic matter content （OMC）, total N, total P, total K, alkali-dissolvable N （AN）, available P （AP） and available K （AK）, with classical statistics and geostatistical analysis across the entire black soil area in Northeast China. In nonsampled areas ordinary kriging was utilized for interpolation of estimated nutrient determinations. Classical statistics revealed highly significant （P ≤ 0.01） correlations with all seven of the soil properties, except for OMC with AP and total K with AK. In addition, using coefficients of variation, all soil properties, except for total K, were moderately variable. A geostatistical analysis indicated that structural factors, such as parent material, terrain, and water table, were the main causes of the spatial correlations. Strong spatial correlations were noted with OMC, total N, total P, AN, and AP, while they were moderate for total K and AK. The effective spatial autocorrelation of OMC, total N, total P, and AN ranged from 1 037 to 1353 km, whereas the ranges of total K, AP, and AK were only from 6 to 138 km. The fit of the experimental scmi-variograms to the theoretical models indicated that except for AN, kriging could successfully interpolate other six variables. Thns, the geostatistical method used on a large scale could accurately evaluate the spatial variability of most black soil nutrient properties in Northeast China.

Effect of 2D spatial variability on slope reliability: A simplified FORM analysis

To meet the high demand for reliability based design of slopes, we present in this paper a simplified HLRF(Hasofere Linde Rackwitze Fiessler) iterative algorithm for first-order reliability method(FORM). It is simply formulated in x-space and requires neither transformation of correlated random variables nor optimization tools. The solution can be easily improved by iteratively adjusting the step length. The algorithm is particularly useful to practicing engineers for geotechnical reliability analysis where standalone(deterministic) numerical packages are used. Based on the proposed algorithm and through direct perturbation analysis of random variables, we conducted a case study of earth slope reliability with complete consideration of soil uncertainty and spatial variability.

Spatial variability of soil water content and related factors across the Hexi Corridor of China

Soil water content(SWC) is a key factor limiting ecosystem sustainability in arid and semi-arid areas of the Hexi Corridor of China, which is characterized by an ecological environment that is vulnerable to climate change. However, there is a knowledge gap regarding the large-scale spatial distribution of SWC in this region. The specific objectives of this study were to determine the spatial distribution patterns of SWC across the Hexi Corridor and identify the factors responsible for spatial variation of SWC at a regional scale. This study collected and analyzed SWC in the 0–100 cm soil profile from 109 field sampling sites(farmland, grassland and forestland) across the Hexi Corridor in 2017. We selected 17 factors, including land use, topography(latitude, longitude, elevation, slope gradient, and slope aspect), soil properties(soil clay content, soil silt content, soil bulk density, saturated hydraulic conductivity, field capacity, and soil organic carbon content), climate factors(mean annual precipitation, potential evaporation, and aridity index), plant characteristic(vegetation coverage) and planting pattern(irrigation or rain-fed), as possible environmental variables to analyze their effects on SWC. The results showed that SWC was 0.083(±0.067) g/g in the 0–100 cm soil profile and decreased in the order of farmland, grassland and forestland. The SWC in the upper soil layers(0–20, 20–40 and 40–60 cm) had obvious difference when the mean annual precipitation differed by 200 mm. The SWC decreased from southeast to northwest following the same pattern as precipitation, and had a moderate to strong spatial dependence in a large effective range(75–378 km). The SWC showed a similar distribution and had no significant difference between soil layers in the 0–100 cm soil profile. The principal component analysis showed that the mean annual precipitation, geographical position(longitude and latitude) and soil properties(soil bulk density and soil clay content) were the main factors dominating the variance of environmental variables. A stepwise linear regression equation showed that plant characteristic(vegetation coverage) and soil properties(soil organic carbon content, field capacity and soil clay content) were the optimal factors to predict the variation of SWC. Soil clay content could be better to explain the SWC variation in the deeper soil layers compared with the other factors.

Spatial variability and pattern analysis of soil properties in Dehui city, Jilin province

Based on regionalized variable theory, semivariograms of geo-statistics wereused to research the spatial variation of soil properties quantitatively. The results showed thatthe semivariogram of soil organic matter is best described by spherical model, the best model forsemivariograms of soil total N and available K is exponential models and that of available P belongsto linear with sill model. Those soil properties have different spatial correlations respectively,the lag of organic matter is the highest and that of available P is the lowest, the spatialcorrelation of N and available K belongs to moderate degree. Spatial heterogeneities are differenttoo, the degree of organic matter and total N are higher, the degree of available K is in the nextplace and that of available P is the lowest. Influenced by the shape, topography and soil of thestudy area, all isotropies of available P are obvious in all directions while anisotropies of othersare manifested. According to the analytical results, supported by GIS, Kriging and IDW methods areapplied to describe and analyze the spatial distribution of soil properties. The results indicatethat soil organic matter, total N and available K are distributed regularly from northeast tosouthwest, while available P is distributed randomly.

Spatial variability of soil organic carbon in the forestlands of northeast China

Soil organic carbon （SOC） is an effective indicator of soil fertility and productivity, and it varies spatially and temporally in relation to other soil properties. Spatial variability of SOC in the forestlands of northeast China was characterized using geostatistics. Soil samples at the depths of 0-20 era, 20-40 cm and 40-60 cm were collected from six- ty-three temporary plots to evaluate SOC concentration and density （SOCD） and other soil properties. We analyzed correlations between SOC and soil properties. Soil organic carbon concentrations were high. The total amount of C stored in soil （0-60 cm） was 16.23 kg·m-2 with the highest SOCD of 7.98 kg·m-2 in topsoil. Soil properties in most cases differed by horizon, suggesting different processes and effects in each horizon. Soil organic carbon had positive relationships with total N, P and K as well as readily available K, but did not show a significant posi- tive correlation with available P. Spatial factors including elevation, slope and aspect affected SOC distribution. Soil organic carbon at 0-60 cm had strong spatial autocorrelation with nugget/sill ratio of 5.7%, and moderate structured dependence was found at 0-20 cm, which indicated the existence of a highly developed spatial structure. Spatial distributionsof SOC concentration and SOCD were estimated using regres- sion-kriging, with higher prediction accuracy than ordinary kriging. The fractal dimension of SOC indicated the preferential pattern of SOC dis- tribution, with the greatest spatial heterogeneity and strongest spatial dependence in the northeast-southwest direction.

Spatial Variability of Soil Chemical Properties in the Reclaiming Marine Foreland to Yellow Sea of China

Precise information about the spatial variability of soil properties is essential in developing site-specific soil management, such as variable rate application of fertilizers. In this study the sampling grid of 100 m × 100 m was established to collect 1 703 soil samples at the depth of 0-20 cm, and examine spatial patterns including 13 soil chemical properties （pH, OM, NH4^＋, P, K, Ca, Mg, S, B, Cu, Fe, Mn, and Zn） in a 1 760 ha rice field in Haifeng farm, China, from 6th to 22nd of April, 2006, before fertilizer application and planting. Soil analysis was performed by ASI （Agro Services International） and data were analyzed both statistically and geostatistically. Results showed that the contents of soil OM, NH4^＋, and Zn in Haifeng farm were very low for rice production and those of others were enough to meet the need for rice cultivation. The spatial distribution model and spatial dependence level for 13 soil chemical properties varied in the field. Soil Mg and B showed strong spatial variability on both descriptive statistics and geostatistics, and other properties showed moderate spatial variability. The maximum ranges for K, Ca, Mg, S, Cu and Mn were all - 3 990.6 m and the minimum ranges for soil pH, OM, NH4^＋, P, Fe, and Zn ranged from 516.7 to 1 166.2 m. Clear patchy distribution of N, P, K, Mg, S, B, Mn, and Zn were found from their spatial distribution maps. This proved that sampling strategy for estimating variability should be adapted to the different soil chemical properties and field management. Therefore, the spatial variability of soil chemical properties with strong spatial dependence could be readily managed and a site-specific fertilization scheme for precision farming could be easily developed.

Spatial and Temporal Variability of N, P and K Balances for Agroecosystems in China

Nitrogen, phosphorus, and potassium balances for agroecosystems in China from 1993 to 2001 were calculated at national and provincial levels using statistical data and related parameters, and their spatial and temporal variabilities were analyzed with GIS to estimate the potential impacts of nutrient N, P and K surpluses or deficits to soil, water and air. At the national scale, the N and P balances from 1993 to 2001 showed a surplus, with the nitrogen surplus remaining relatively stable from 1997—2001. Although during this period the P surplus pattern was similar to N, it had smaller values and kept increasing as the use of phosphate fertilizer increased year by year. However, K was deficient from 1993 to 2001 even though from 1999 to 2001 the K deficit decreased. The spatial analysis revealed higher N surpluses in the more developed southeastern provinces and lowest in the western and northern provinces where there was less chemical fertilizer input. The serious K deficit mainly occurred in Shanghai and Beijing municipalities, Jiangsu, Zhejiang and Hubei provinces, and Xinjiang autonomous regions. For the years 1992, 1996 and 2001, N surpluses and K deficits had significant positive spatial correlations with per capita gross domestic product (GDP), per capita gross industrial output value, and per capita net income of rural households. This showed that the level of economic development played an important role on nutrient balances in the agroecosystems.

Spatial variability of soil bulk density and its controlling factors in an agricultural intensive area of Chengdu Plain,Southwest China

Soil bulk density is a basic but important physic soil property related to soil porosity,soil moisture and hydraulic conductivity,which is crucial to soil quality assessment and land use management.In this study,we evaluated the spatial variability of soil bulk density in the 0–20,20–40,40–60 and 60–100 cm layers as well as its affecting factors in Southwest China’s agricultural intensive area.Results indicated the mean value of surface soil bulk density(0–20 cm)was 1.26 g cm^(–3),significantly lower than that of subsoil(20–100 cm).No statistical difference existed among the subsoil with a mean soil bulk density of 1.54 g cm^(–3).Spatially,soil bulk density played a similar spatial pattern in soil profile,whereas obvious differences were found in details.The nugget effects for soil bulk density in the 0–20 and 20–40 cm layers were 27.22 and27.02%while 12.06 and 3.46%in the 40–60 and 60–100 cm layers,respectively,gradually decreasing in the soil profile,indicating that the spatial variability of soil bulk density above 40 cm was affected by structural and random factors while dominated by structural factors under 40 cm.Soil organic matter was the controlling factor on the spatial variability of soil bulk density in each layer.Land use and elevation were another two dominated factor controlling the spatial variability of soil bulk density in the 0–20 and 40–60 cm layers,respectively.Soil genus was one of the dominated factors controlling the spatial variability of soil bulk below 40 cm.

Spatial and temporal variability of daily precipitation in Haihe River basin, 1958-2007

The seasonal variability and spatial distribution of precipitation are the main cause of flood and drought events. The study of spatial distribution and temporal trend of precipitation in river basins has been paid more and more attention. However, in China, the precipitation data are measured by weather stations （WS） of China Meteorological Administration and hydrological rain gauges （RG） of national and local hydrology bureau. The WS data usually have long record with fewer stations, while the RG data usually have short record with more stations. The consistency and correlation of these two data sets have not been well understood. In this paper, the precipitation data from 30 weather stations for 1958-2007 and 248 rain gauges for 1995-2004 in the Haihe River basin are examined and compared using linear regression, 5-year moving average, Mann-Kendall trend analysis, Kolmogorov-Smirnov test, Z test and F test methods. The results show that the annual precipitation from both WS and RG records are normally distributed with minor difference in the mean value and variance. It is statistically feasible to extend the precipitation of RG by WS data sets. Using the extended precipitation data, the detailed spatial distribution of the annual and seasonal precipitation amounts as well as their temporal trends are calculated and mapped. The various distribution maps produced in the study show that for the whole basin the precipitation of 1958-2007 has been decreasing except for spring season. The decline trend is significant in summer, and this trend is stronger after the 1980s. The annual and seasonal precipitation amounts and changing trends are different in different regions and seasons. The precipitation is decreasing from south to north, from coastal zone to inland area.

Spatial variability of organochlorine pesticides (DDTs and HCHs) in surface soils from the alluvial region of Beijing,China

The spatial variability in the concentrations of 1,2,3,4,5,6-hexachlorocyclohexane （HCH） and 1,1,1-trichloro-2,2-bis-（p-chloro- phenyl） ethane （DDT） in surface soils was studied on the basis of the analysis of 131 soil samples collected from the surface layer （0-20 cm depth） of the alluvial region of Beijing, China. The concentrations of total HCHs （including α-,β-, γ-, and δ-isomers） and total DDTs （including p,p＇-DDT, p,p＇-DDD, p,p＇-DDE, and o,p＇-DDT） in the surface soils tested were in the range from nondetectable to 31.72 μg/kg dry soil, with a mean value of 0.91, and from nondetectable to 5910.83 μg/kg dry soil, with a mean value of 32.13, respectively. It was observed that concentrations of HCHs in all soil samples and concentrations of DDTs in 112 soil samples were much lower than the first grade （50 μg/kg） permitted in ＂Environment quality standard for soils in China （GB 15618-1995）＂. This suggests that the pollution due to organochlorine pesticides was generally not significant in the farmland soils in the Beijing alluvial region. In this study, the spatial distribution and trend of HCHs and DDTs were analyzed using Geostatistical Analyst and GS＋（513）. Spatial distribution indicated how these pesticides had been applied in the past. Trend analysis showed that the concentrations of HCHs, DDTs, and their related metabolites followed an obvious distribution trend in the surface soils from the alluvial region of Beijing.

Spatial Variability of Soil Cation Exchange Capacity in Hilly Tea Plantation Soils Under Different Sampling Scales

Studies on the spatial variability of the soil cation exchange capacity （CEC） were made to provide a theoretical basis for an ecological tea plantation and management of soil fertilizer in the tea plantation. Geostatistics were used to analyze the spatial variability of soil CEC in the tea plantation site on Mengding Mountain in Sichuan Province of China on two sampling scales. It was found that, （1） on the small scale, the soil CEC was intensively spatially correlative, the rate of nugget to sill was 18.84% and the spatially dependent range was 1 818 m, and structural factors were the main factors that affected the spatial variability of the soil CEC; （2） on the microscale, the soil CEC was also consumingly spatially dependent, and the rate of nugget to sill was 16.52%, the spatially dependent range was 311 m, and the main factors affecting the spatial variability were just the same as mentioned earlier. On the small scale, soil CEC had a stronger anisotropic structure on the slope aspect, and a weaker one on the lateral side. According to the ordinary Kriging method, the equivalence of soil CEC distributed along the lateral aspect of the slope from northeast to southwest, and the soil CEC reduced as the elevation went down. On the microscale, the anisotropic structure was different from that measured on the small scale. It had a stronger anisotropic structure on the aspect that was near the aspect of the slope, and a weaker one near the lateral aspect of the slope. The soil CEC distributed along the lateral aspect of the slope and some distributed in the form of plots. From the top to the bottom of the slope, the soil CEC increased initially, and then reduced, and finally increased.

Delineation of Site-Specific Management Zones Based on Temporal and Spatial Variability of Soil Electrical Conductivity

A coastal saline field of 10.5 ha was selected as the study site and 122 bulk electrical conductivity (ECb) measurements were performed thrice in situ in the topsoil (0-20 cm) across the field using a hand held device to assess the spatial variability and temporal stability of the distribution of soil electrical conductivity (EC), to identify the management zones using cluster analysis based on the spatiotemporal variability of soil EC, and to evaluate the probable potential for site-specific management in coastal regions with conventional statistics and geostatistical techniques. The results indicated high coefficients of variation for topsoil salinity over all the three samplings. The spatial structure of the salinity variability remained relatively stable with time. Kriged contour maps, drawn on the basis of spatial variance structure of the data, showed the spatial trend of the salinity distribution and revealed areas of consistently high or consistently low salinity, while a temporal stability map indicated stable and unstable regions. On the basis of the spatiotemporal characteristics, cluster analysis divided the site into three potential management zones, each with different characteristics that could have an impact on the way the field was managed. On the basis of the clearly defined management zones it was concluded that coastal saline land could be managed in a site-specific way.

SPATIAL AND TEMPORAL VARIABILITY OF NORTHWEST PACIFIC TROPICAL CYCLONE ACTIVITY IN A GLOBAL WARMING SCENARIO

Utilizing the Joint Typhoon Warning Center(JTWC) and Tokyo-Typhoon Center of the Japan Meteorological Agency(JMA RSMC TOKYO) best-track tropical cyclone(TC) data for the period 1951-2014,variations in spatial and temporal characteristics of Northwest Pacific TC activity for a global warming scenario are discussed.The results suggest that since the early 1960 s,there has been an overall decreasing trend in the frequency of occurrence,intensity,peak intensity,length of movement,and lifetime of TCs.However,global wanning has led to a linearly increasing trend in TC activity in eastern Asia,which indicates that Northwest Pacific TC activity decreases,but the frequency of landfalls and intensity are likely strengthened.Therefore,the threat of TCs towards eastern Asia is enhanced.The increase in TC activity in eastern Asia is likely the result of a strengthened Walker circulation due to an increasing temperature gradient between the northwest Pacific Ocean and the central and eastern Pacific Ocean.The strengthening Walker circulation could increase the magnitude of the vertical wind shear,relative vorticity,and meridional wind shear of low-level easterlies near the equator in the tropical Northwest Pacific,which affects the spatial and temporal variations of TC activity in the Northwest Pacific.

Spatial variability of soil organic carbon and total nitrogen in the hilly red soil region of Southern China

To obtain accurate spatial distribution maps of soil organic carbon(SOC)and total nitrogen(TN)in the Hetian Town in Fujian Province,China,soil samples from three depths(0–20,20–40,and 40–60 cm)at 59 sampling sites were sampled by using traditional analysis and geostatistical approach.The SOC and TN ranged from 2.26 to 47.54 g kg-1,and from 0.28 to 2.71 g kg-1,respectively.The coefficient of variation for SOC and TN was moderate at 49.02–55.87%for all depths.According to the nuggetto-sill ratio values,a moderate spatial dependence of SOC content and a strong spatial dependence of TN content were found in different soil depths,demonstrating that SOC content was affected by both extrinsic and intrinsic factors while TN content was mainly influenced by intrinsic factors.Indices of cross-validation,such as mean error,mean standardized error,were close to zero,indicating that ordinary kriging interpolation is a reliable method to predict the spatial distribution of SOC and TN in different soil depths.Interpolation using ordinary kriging indicated the spatial pattern of SOC and TN were characterized by higher in the periphery and lower in the middle.To improve the accuracy of spatial interpolation for soil properties,it is necessary and important to incorporate a probabilistic and machine learning methods in the future study.