Antecedent Precipitation Index to Estimate Soil Moisture and Correlate as a Triggering Process in the Occurrence of Landslides

Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process;thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems;hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.

Novel Hybrid X GBoost Model to Forecast Soil Shear Strength Based on Some Soil Index Tests

When building geotechnical constructions like retaining walls and dams is of interest,one of the most important factors to consider is the soil’s shear strength parameters.This study makes an effort to propose a novel predictive model of shear strength.The study implements an extreme gradient boosting(XGBoost)technique coupled with a powerful optimization algorithm,the salp swarm algorithm(SSA),to predict the shear strength of various soils.To do this,a database consisting of 152 sets of data is prepared where the shear strength(τ)of the soil is considered as the model output and some soil index tests(e.g.,dry unit weight,water content,and plasticity index)are set as model inputs.Themodel is designed and tuned using both effective parameters of XGBoost and SSA,and themost accuratemodel is introduced in this study.Thepredictionperformanceof theSSA-XGBoostmodel is assessedbased on the coefficient of determination(R2)and variance account for(VAF).Overall,the obtained values of R^(2) and VAF(0.977 and 0.849)and(97.714%and 84.936%)for training and testing sets,respectively,confirm the workability of the developed model in forecasting the soil shear strength.To investigate the model generalization,the prediction performance of the model is tested for another 30 sets of data(validation data).The validation results(e.g.,R^(2) of 0.805)suggest the workability of the proposed model.Overall,findings suggest that when the shear strength of the soil cannot be determined directly,the proposed hybrid XGBoost-SSA model can be utilized to assess this parameter.

Combining RUSLE model and the vegetation health index to unravel the relationship between soil erosion and droughts in southeastern Tunisia

Droughts and soil erosion are among the most prominent climatic driven hazards in drylands,leading to detrimental environmental impacts,such as degraded lands,deteriorated ecosystem services and biodiversity,and increased greenhouse gas emissions.In response to the current lack of studies combining drought conditions and soil erosion processes,in this study,we developed a comprehensive Geographic Information System(GIS)-based approach to assess soil erosion and droughts,thereby revealing the relationship between soil erosion and droughts under an arid climate.The vegetation condition index(VCI)and temperature condition index(TCI)derived respectively from the enhanced vegetation index(EVI)MOD13A2 and land surface temperature(LST)MOD11A2 products were combined to generate the vegetation health index(VHI).The VHI has been conceived as an efficient tool to monitor droughts in the Negueb watershed,southeastern Tunisia.The revised universal soil loss equation(RUSLE)model was applied to quantitatively estimate soil erosion.The relationship between soil erosion and droughts was investigated through Pearson correlation.Results exhibited that the Negueb watershed experienced recurrent mild to extreme drought during 2000–2016.The average soil erosion rate was determined to be 1.8 t/(hm2•a).The mountainous western part of the watershed was the most vulnerable not only to soil erosion but also to droughts.The slope length and steepness factor was shown to be the most significant controlling parameter driving soil erosion.The relationship between droughts and soil erosion had a positive correlation(r=0.3);however,the correlation was highly varied spatially across the watershed.Drought was linked to soil erosion in the Negueb watershed.The current study provides insight for natural disaster risk assessment,land managers,and stake-holders to apply appropriate management measures to promote sustainable development goals in fragile environments.

Contamination assessment,source apportionment and associated health risks of PTEs in agricultural soil under five land-use patterns in Sanya,China

To understand the levels of potentially toxic elements(PTEs)contamination in soils and their effects on human health from different agricultural land use in Sanya,China.128 soil samples(64 topsoil samples and corresponding subsoil samples)were collected from the five representative land-use patterns.Inductively coupled plasma mass spectrometry(ICP-MS),Atomic fluorescence spectrometry(AFS),and Inductively coupled plasma optical emission spectrometry(ICP-OES)were used to determine the content of PTEs(As,Cd,Hg,Cu,Cr,Ni,Pb,Zn,Co,Mo,Sb,and V).Correlation analysis and factor analysis were used to determine the source of PTEs.Geo-accumulation index(I_(geo)),hazard quotient(HQ),and total carcinogenic risk index(TR)were used to measure the PTEs contamination and its relative health impacts.Results showed that the average values of 12 PTEs in topsoil were higher than the Hainan soil geochemical baseline,showing different degrees of PTEs accumulation effect.The concentration of PTEs in the topsoil was lower than those in the subsoil except for Cd and Hg.The I_(geo)revealed that the major accumulated element in soils was As followed by Mo.Source apportionment suggested that parent materials and agricultural practices were the dominant factors for PTEs accumulation in the topsoil.Noncarcinogenic risks of soil samples from five land-use patterns presented a trend of paddy field>dry field>woodland>orchard>garden plot.However,the HQ values of 12 PTEs were less than the recommended limit of HQ=1,representing that there are no non-carcinogenic risks of PTEs for children and adults in the study area.The TR values are within 6.95×10^(-6)-1.38×10^(-5),which corresponds to the low level.Therefore the PTEs in the agricultural soil of the study area show little influence on the health status of the local population.

Evaluation of Soil Fertility Quality and Environmental Driving Factors in Different Soil Types of Artificial Forests

The aim was to clarify the environmental driving factors of soil fertility indicators in artificial forests of Guangxi and comprehensively evaluate the soil fertility level.By collecting data on the current status of soil in artificial forests,the spatial distribution of major soil fertility indicators was analyzed,and the distribution map of the fertility index of artificial forests in the entire region and the comprehensive fertility index of artificial forests of different soil types were obtained.Canonical correspondence analysis method was used to analyze soil fertility indicators and environmental factors,and the environmental driving factors of soil fertility indicators for artificial forests of the main soil types in Guangxi were obtained.The results showed that over 90%of the soil fertility index of artificial forests in the entire region was between 0.20 and 0.50.The order of soil fertility index of different soil types of artificial forests from high to low was yellow brown soil>yellow red soil>yellow soil>red soil>limestone soil>latosolic red soil>laterite.In artificial forests of latosolic red soil,the correlation between soil alkaline nitrogen and organic matter,annual average temperature was high,while the correlation between soil available phosphorus and organic matter,pH was high,and the correlation between soil available potassium and environmental factors such as slope,altitude,rainfall,accumulated temperature,and slope aspect was high.In artificial forests of red soil,the correlation between soil alkaline nitrogen and slope,altitude was high,while the correlation between soil available phosphorus and accumulated temperature,rainfall was high,and the correlation between soil available potassium and pH was high.In artificial forests of limestone soil,there was a high correlation between soil alkaline nitrogen and slope,organic matter,a high correlation between soil available phosphorus and accumulated temperature,rainfall,and a high correlation between soil available potassium and pH.

Assessment of Agricultural Soil Quality Indices Using Mechanistic Models

Assessing soil quality is a critical strategy for diagnosing soil status and anticipating concerns in land use systems for agricultural sustainability. In this study, two soil quality assessment indices, the Integrated Quality Index (IQI) and Nemoro Quality Index (NQI), were employed using two indicator selection methods: Total Data Set (TDS) and Minimum Data Set (MDS), focusing on agricultural fields in Golestan province, Iran. A total of 89 soil samples were collected and analyzed for particle size distribution, organic carbon, calcium carbonate equivalent (CCE), electrical conductivity (EC), pH, and plant-essential nutrients, including nitrogen, phosphorus, potassium, zinc, copper, manganese, and iron. Principal component analysis (PCA) was used to extract MDS from TDS, and geostatistical adaptation and correlation analyses were performed to determine the optimal soil quality evaluation index. Our results show that the exponential model better suits the spatial structure of soil quality indicators (IQIMDS: 0.955). Conformity and correlation analyses indicate that the IQI index outperformed the NQI index in estimating soil quality. The superiority of the TDS technique over the MDS technique in terms of accuracy (IQITDSs kappa: 0.155). Linear relationships between different methods showed a higher correlation coefficient (R2 = 0.43) through the application of IQI. This study suggests the use of IQIMDS to provide a reliable measurement that is particularly useful in assessing the quality of agricultural soil.

Using geoaccumulation index to study source profiles of soil dust in China

Source apportionment studies of TSP （atmospheric particulate matter with aerodynamic diameters ≤ 100 μm） and PM10 （atmospheric particulate matter with aerodynamic diameters ≤ 10 μm） have revealed that soil dust is an important source of these particulates in China. In this study, the contamination of soil dust was assessed through the use of a geoaccumulation index （Igeo）. The mass concentration profiles of 17 elements （Na, Mg, Al, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Br, Ba, and Pb） were established for urban soil dusts. Geochemical compositions of soils from 15 cities were used to represent background urban soil compositions. The results of this study indicated that a number of cities are severely polluted by particulates containing Ca, Cr, Ni, and Cu in both size fractions （TSP and PM10）. Contamination with Zn, Pb, Co, and Br was moderate to severe （Igeo 〉 2）. The Al and Fe concentrations were not high enough for them to be considered contaminants.

Changes in Organic Carbon Index of Grey Desert Soil in Northwest China After Long-Term Fertilization

Soil organic carbon （SOC）, soil microbial biomass carbon （SMBC） and SMBC quotient （SMBC/SOC, qSMBC） are key indexes of soil biological fertility because of the relationship to soil nutrition supply capacity. Yet it remains unknown how these three indexes change, which limits our understanding about how soil respond to different fertilization practices. Based on a 22-yr （1990-2011） long-term fertilization experiment in northwest China, we investigated the dynamics of SMBC and qSMBC during the growing period of winter wheat, the relationships between the SMBC, qSMBC, soil organic carbon （SOC） concentrations, the carbon input and grain yield of wheat as well. Fertilization treatments were 1） nonfertilization （control）; 2） chemical nitrogen plus phosphate plus potassium （NPK）; 3） NPK plus animal manure （NPKM）; 4） double NPKM （hNPKM） and 5） NPK plus straw （NPKS）. Results showed that the SMBC and qSMBC were significantly different among returning, jointing, flowering and harvest stages of wheat under long-term fertilization. And the largest values were observed in the flowering stage. Values for SMBC and qSMBC ranged from 37.5 to 106.0 mg kg1 and 0.41 to 0.61%, respectively. The mean value rank of SMBC during the whole growing period of wheat was hNPKM〉NPK_M〉NPKS〉CK〉NPK. But there were no statistically significant differences between hNPKM and NPKM, or between CK and NPK. The order for qSMBC was NPKS〉NPKM〉CK〉hNPKM〉NPK. These results indicated that NPKS significantly increased the ratio of SMBC to SOC, i.e., qSMBC, compared with NPK fertilizer or other two NPKM fertilizations. Significant linear relationships were observed between the annual carbon input and SOC （P〈0.01） or SMBC （P〈0.05）, and between the relative grain yield of wheat and the SOC content as well （P〈0.05）. But the qSMBC was not correlated with the annual carbon input. It is thus obvious that the combination of manure, straw with mineral fertilizer may be benefit to increase SOC and improve soil quality than using only mineral fertilizer.

Assessment of Soil Water Content in Field with Antecedent Precipitation Index and Groundwater Depth in the Yangtze River Estuary

To better understand soil moisture dynamics in the Yangtze River Estuary （YRE） and predict its variation in a simple way, a field monitoring experiment was carried out along the north branch of the Yangtze River, where seawater intrusion was strong and salt-water variation is one of the limiting factors of local agriculture. In present paper, relation between antecedent precipitation index （API） and soil water content is studied, and effects of groundwater depth on soil water content was analyzed. A relatively accurate prediction result of soil water content was reached using a neural network model. The impact analysis result showed that the variation of the API was consistent with soil water content and it displayed significant correlations with soil water content in both 20 and 50 cm soil layer, and higher correlation was observed in the layer of 20 cm. Groundwater impact analysis suggested that soil moisture was affected by the depth of groundwater, and was affected more greatly by groundwater at depth of 50 cm than that at 20 cm layer. By introducing API, groundwater depth and temperature together, a BP artificial network model was established to predict soil water content and an acceptable agreement was achieved. The model can be used for supplementing monitoring data of soil water content and predicting soil water content in shallow groundwater areas, and can provide favorable support for the research of water and salt transport in estuary area.

A soil quality index for evaluation of degradation under land use and soil erosion categories in a small mountainous catchment, Iran

Soil erosion and land use type have long been viewed as being particularly important drivers of soil degradation.The objectives of this study,therefore,were to select a new soil quality index(SQI)which varies significantly with land use/soil erosion,and to evaluate the new SQI using expert opinion.In total,18 soil physical,chemical,and biochemical properties(indicators)were measured on 56 soil samples collected from four land use/soil erosion categories(rangeland/surface erosion,rangeland/subsurface erosion,cultivated land/surface erosion and dry-farming land/surface erosion).Principal component and classification analysis(PCCA)identified five PCs that explained 77.7%of the variation in soil properties with the biochemical PC varying significantly with land use/soil erosion.General discriminant analysis(GDA)selected urease and clay as the most sensitive properties distinguishing the land use/soil erosion categories.The GDA canonical scores for the new SQI were significantly correlated with expert opinion soil surface summed scores(for soil movement,surface litter,pedestalling,rills and flow pattern)derived using the U.S.Department of the Interior Bureau of Land Management(BLM)method.A forward stepwise general regression model revealed that the new SQI values were explained by soil movement,surface litter,and the summed values of the soil surface factors.Overall,this study confirmed that soil quality in the study area in Iran is controlled by land use and corresponding soil erosion.

An Assessment of Heavy-Metal Contamination in Soils within Auto-Mechanic Workshops Using Enrichment and Contamination Factors with Geoaccumulation Indexes

Soil characterization and heavy metals in different layers (0 - 15 cm;15 - 30 cm and 30 - 45 cm depth) of automobile mechanic waste dumps were studied. The soils showed remarkably high levels of all the metals above background concentrations with most (Ni, Cu, Fe, Cr and Cd) decreasing with soil depth. The distribution pattern were in the following order Fe > Cu > Zn > Pb > Cr > Ni > Cd. Across all the sampling locations and profiles, Fe and Cd showed the highest (476.4 μg·g-1) and least (37.5 μg·g-1) mean concentrations respectively. Pollution load index (PLI) and index of geoaccumulation (Igeo) revealed overall high and moderate contamination respectively but the enrichment factors (EFs) for Pb Ni and Cd are severe. The inter-element relationship revealed the identical source of elements in the soils of the studied area. The accuracy of the results has been cheeked using the standard reference material;SRM (PACS-2). The mechanic waste dumps represent potential sources of heavy metal pollution to environment. The elevated levels of heavy metals in these soil profiles constitute a serious threat to both surface and groundwater.

Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India

Drought is a natural phenomenon posing severe implications for soil,groundwater and agricultural yield.It has been recognized as one of the most pervasive global change drivers to affect the soil.Soil being a weakly renewable resource takes a long time to form,but it takes no time to degrade.However,the response of soil to drought conditions as soil loss is not manifested in the existing literature.Thus,this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India.MODIS remote sensing data was utilized for driving drought indices during 2000-2019.Firstly,we constricted Temperature condition index(TCI)and Vegetation Condition Index(VCI)from Land Surface Temperature(LST)and Enhanced Vegetation Index(EVI)derived from MODIS data.TCI and VCI were then integrated to determine the Vegetation Health Index(VHI).Revised Universal Soil Loss Equation(RUSLE)was utilized for estimating soil loss.The relationship between drought condition and vegetation was ascertained using the Pearson correlation.Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during2000-2019.The mean frequency of the drought occurrence was 7.95 months.The average soil erosion in the sub-basin was estimated to be 9.88 t ha^(-1)year^(-1).A positive relationship was observed between drought indices and soil erosion values(r value being 0.35).However,wide variations were observed in the distribution of spatial correlation.Among various factors,the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin.Thus,the study calls for policy measures to lessen the impact of drought and soil erosion.

Modelling the Soil Loss in the Watershed of the Chaddad Wadi in Terms of Both Rockiness and Soil Slaking Indexes

Currently we are at a phase where morphogenesis is gaining more prominence and dimension regarding the pedogenesis. The numerous multidisciplinary studies on the soil showed that the erosive action as well as the various problems that result from it, bring out a very serious state of soil degradation in the semi-arid field [1]-[9]. Several attempts have established to set empirical and experimental methods for a quantitative estimation of soil loss caused by diffuse erosion. In this perspective, this research intends to track soil losses in the watershed of the Chaddad wadi, the average-flowing stream of the Nebhana wadi belonging to the lower semi-arid field. The main stream and its tributaries drain an area of 26.5 km2 from the eastern slopes of Ejhaf mountain (517 m) and Fartout mountain (476 m), as well as the southern slope of Ediour mountain (405 m). The dividing line of the waters with the Khalfallah wadi and Bel Assoued wadi is caused by rows of hills with an altitude ranging between 220 m and 306 m such as the hills of Sidi Salah and those of Es-Souida and Ain Fres. The Wischmeier Equation will be improved by two corrective parameters: the rockiness on the one hand and the soil slaking index on the other, aiming to develop and optimize the potential of this empirical model. This application allowed overcoming some of the limitations that came with the Wischmeier equation, which is primarily designed for an application within different physical conditions on the scale of a land plot. This research is an opportunity to make a detailed contribution to the potential sensitivity of the watershed to water erosion. A good demarcation of the physical anthropogenic framework of the erosive action will provide substantial support in terms of soil protection and the stabilization of watersheds emitting sediments.

Site index for Chinese fir plantations varies with climatic and soil factors in southern China

Chinese fir[Cunninghamia lanceolata(Lamb.)Hook.]has a large native distribution range in southern China.Here,we tested differences in productivity of Chinese fir plantations in different climatic regions and screened the main environmental factors affecting site productivity in each region.Relationships of a Chinese fir site index with climatic factors and the soil physiochemical properties of five soil layers were examined in a long-term positioning observation trial comprising a total of 45 permanent plots in Fujian(eastern region in the middle subtropics),Guangxi(south subtropics)and Sichuan(central region in the middle subtropics)in southern China.Linear mixed effects models were developed to predict the site index for Chinese fir,which was found to vary significantly among different climatic regions.Available P,total N,bulk density and total K were dominant predictors of site index in three climatic regions.The regional linear mixed models built using these predictors in the three climatic regions fit well(R~2=0.86–0.97).For the whole study area,the available P in the 0–20-cm soil layer and total N in the 80–100-cm soil layer were the most indicative soil factors.MAP was the most important climatic variable influencing the site index.The model evaluation results showed that the fitting performance and prediction accuracy of the global site index model using the climatic region as the dummy variable and random parameters and the most important soil factors of the three climatic regions as predictors was higher than that of global site index model using the climatic variable and the most indicative soil variables of the whole study area.Our results will help with further evaluation of site quality of Chinese fir plantations and the selection of its appropriate sites in southern China as the climatic changes.

A Modified Temperature-Vegetation Dryness Index(MTVDI)for Assessment of Surface Soil Moisture Based on MODIS Data

Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation eco-systems.The temperature-vegetation dryness index based on the triangle or trapezoid method has been used widely in previous studies.However,most existing studies simply used linear regression to construct empirical models to fit the edges of the feature space.This requires extensive data from a vast study area,and may lead to subjective results.In this study,a Modified Temperature-Vegetation Dryness Index(MTVDI)was used to monitor surface soil moisture status using MODIS(Moderate-resolution Imaging Spectroradiometer)remote sensing data,in which the dry edge conditions were determined at the pixel scale based on surface energy balance.The MTVDI was validated by field measurements at 30 sites for 10 d and compared with the Temperature-Vegetation Dryness Index(TVDI).The results showed that the R^(2) for MTVDI and soil moisture obviously improved(0.45 for TVDI,0.69 for MTVDI).As for spatial changes,MTVDI can also better reflect the actual soil moisture condition than TVDI.As a result,MTVDI can be considered an effective method to monitor the spatio-temporal changes in surface soil moisture on a regional scale.

Utilization of Wood Biomass for Organic Soil Based on the Soil Fertility Index (SOFIX)

Possibility of wood biomass for preparing organic soil was examined to construct reproducible and stable organic standard soil. Seven organic soils were constructed from base soils and additive materials based on the recommended values of the soil fertility index (SOFIX) (total carbon ≥ 25,000 mg/kg, total nitrogen ≥ 1500 mg/kg, total phosphorus ≥ 1100, and total potassium of 2500 to 10,000 mg/kg). Base soils were prepared from two types of wood biomass (big- and small-sized wood chips) at 50%, 60%, and 70% (v/v) and other organic materials such as peat moss, black soil, and mountain soil. Additive materials (soybean meal, oil cake, cow manure, and bone meal) were amended into all organic soils at the same amount. Incubation experiment showed that bacterial biomass in all organic soil was greater than 6 × 108 cells/g-soil after addition of 30% of water content for 1 week. In addition, polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE) analysis resulted in a stable bacterial diversity of the organic soil prepared from the small size wood chip at 70%. Chemical properties of all organic soils were within the recommended values of SOFIX. The plant cultivation experiment showed that fresh Brassica rapa var. peruviridis weights in the organic soils with 50%, 60%, and 70% of small-sized wood chip were 5%, 16%, and 27% higher than that of the chemical fertilizer-amended soil. The organic soil with 70% of small wood chip was the best in the seven organic soils in this study.

Combined Pollution and Pollution Index of Heavy Metals in Red Soil

A field experiment was conducted to study the effects of Pb, Cd, Cu, Zn and As coexisting in red soilon growth of rice (Oryza sativa L.), mung bean (Vigna rabiata (Linn.) Wilczek), alfalfa (Medicago sativaL.), slash pine (Pinus elliottii Engelm.) and aspen (Populus L.). Results showed that rice, mung bean andalfalfa were significantly innuenced by combined pollution of the heavy metals. The contents of Pb, cd andAs in rice grains greatly exceeded the National Standards for Food Hygiene of China. Heavy metals at ahigh concentration seriously retarded growth of mung bean and alfalfa, but not so obviously with slash pineand aspen. The composite index is suggested for evaluating the relativity of combined pollution witll heavymetals in soil.

The Effects of Land Use and Landscape Position on Labile Organic Carbon and Carbon Management Index in Red Soil Hilly Region,Southern China

Labile organic carbon(LOC) and carbon management index(CMI), which are sensitive factors to the changes of environment, can improve evaluating the effect of land management practices changes on soil quality. The objective of this study was to investigate the effects of land use types and landscape positions on soil quality as a function of LOC and CMI. A field study in a small watershed in the red soil hilly region of southern China was conducted, and soil samples were collected from four typical lands(pine forest(PF) on slope land, barren hill(BH) on slope land, citrus orchard(CO) on terrace land and Cinnarnornum Camphora(CC) on terrace land) at a sampling depth of 20 cm. Soil nutrients, soil organic carbon(SOC), LOC and CMI were measured. Results showed that the LOC and CMI correlated to not only soil carbon but also soil nutrients, and the values of LOC and CMI in different land use types followed the order CC > PF > CO > BH at the upperslope, while CO > CC > BH > PF at mid-slope and down-slope. With respect to slope positions, the values of LOC and CMI in all the lands were followed the order: upper-slope > down-slope > midslope. As whole, the mean values of LOC and CMI in different lands followed the order CC > CO > PF > BH. High CMI and LOC content were found in the terrace lands with broadleaf vegetations. These results indicated that the terracing and appropriate vegetations can increase the carbon input and lability and decrease soil erosion. However, the carbon pools and CMI in these lands were significantly lower than that in reference site. This suggested that it may require a long time for the soil to return to a highquality. Consequently, it is an efficient way to adopt the measures of terracing and appropriate vegetations planting in improving the content of LOC and CMI and controlling water and soil loss in fragile ecosystems.

Food-Security Indexes Related to Combined Pollution of Chromium and Phenol in Soil-Rice Systems

The pot-culture method combined with chemical and statistical analyses was used to get basic data for determination of the food-security indexes related to combined pollution of Cr and phenol in soil-rice systems.Regression analyses according to the experimental result indicated that the critical concentrations of Cr andphenol in brown rice were 0.37 and 0.33 mg kg-1, respectively, under the condition of Cr-phenol combined pollution.

Vegetation/Soil Synthesis Water Index Using MODIS Data

In consideration of the spectral character of MODIS (Moderate Resolution Imaging Spectroradiometer) dataand the reflective spectrum of vegetation and soil, NDVI (Normalized Difference Vegetation Index) and NDWI (Nor-malized Difference Water Index) are deduced using one visible band (0.66μm) and two near-infrared bands (0.86μm,1.24 μm). Vegetation canopy temperature is derived using two thermal infrared bands (8.6 μm and 11μm). Then thevegetation/soil synthesis water index (VSWI) is acquired through analyzing the coupling character of three indexeswhich can reflect the water condition of vegetation. Finally, the synthesis index is verified by equivalent water contentof a single leaf. The matching results show that the synthesis index is directly proportional to the modeled data,which means that the vegetation water content can be reflected using the synthesis index effectively.