Wuqi County Research Articles

Optimizing Rotation Forest-Based Decision Tree Algorithms for Groundwater Potential Mapping

Groundwater potential mapping is an important prerequisite for evaluating the exploitation, utilization, and recharge of groundwater. The study uses BFT (best-first decision tree classifier), CART (classification and regression tree), FT (functional trees), EBF (evidential belief function) benchmark models, and RF-BFTree, RF-CART, and RF-FT ensemble models to map the groundwater potential of Wuqi County, China. Firstly, select sixteen groundwater spring-related variables, such as altitude, plan curvature, profile curvature, curvature, slope angle, slope aspect, stream power index, topographic wetness index, stream sediment transport index, normalized difference vegetation index, land use, soil, lithology, distance to roads, distance to rivers, and rainfall, and make a correlation analysis of these sixteen groundwater spring-related variables. Secondly, optimize the parameters of the seven models and select the optimal parameters for groundwater modeling in Wuqi County. The predictive performance of each model was evaluated by estimating the area under the receiver operating characteristic (ROC) curve (AUC) and statistical index (accuracy, sensitivity, and specificity). The results show that the seven models have good predictive capabilities, and the ensemble model has a larger AUC value. Among them, the RF-BFT model has the highest success rate (AUC = 0.911), followed by RF-FT (0.898), RF-CART (0.894), FT (0.852), EBF (0.824), CART (0.801), and BFtree (0.784), respectively. Groundwater potential maps of these 7 models were obtained, and four different classification methods (geometric interval, natural breaks, quantile, and equal interval) were used to reclassify the obtained GPM into 5 categories: very low (VLC), low (LC), moderate (MC), high (HC), and very high (VHC). The results show that the natural breaks method has the best classification performance, and the RF-BFT model is the most reliable. The study highlights that the proposed ensemble model has more efficient and accurate performance for groundwater potential mapping.

Soil fauna community characteristics and driving factors of Pinus tabuliformis in the loess region of northern Shaanxi

This study aimed to examine the characteristics and regulatory mechanisms of the soil fauna community in Pinus tabuliformis plantations at different restoration ages. The study was conducted on the soil fauna of Pinus tabuliformis in different restoration ages (6a, 11a, 18a, and 22a) in Wuqi County. Soil fauna, soil samples, understory herb biomass were collected in the spring, summer, autumn and winter of 2021. The relationship between the soil fauna community characteristics and environmental factors were studied. The results are as follows: (1) The density increased and the number of species decreased in the soil fauna community with an increase in restoration ages, and the composition and structure of the soil fauna community were significantly different at different restoration ages. (2) The diversity of the soil fauna community was highest and the soil food web was the most stable in 6-year-old Pinus tabuliformis plantations. Followed by a 22-year-old Pinus tabuliformis plantation. The lowest soil fauna diversity and the least stable food webs were found at 11- and 18-years-old of Pinus tabuliformis plantations. (3) The understory herb community had the greatest impact on the composition and structure of soil fauna community. SOM, NCP and NHS were the main factors affecting the composition of the soil fauna community. (4) During the restoration of Pinus tabuliformis plantations, the soil fauna community is mainly controlled by the top-down food resources, and the understory herb community driven the evolution process of the soil fauna community, thereby regulating the soil food web. Our research results emphasize the importance of sub-forest herbaceous vegetation to soil animals, which is essential for the formulation of sustainable biodiversity conservation policies for planted forest ecosystems.

Carbon Sequestration Characteristics of Different Restored Vegetation Types in Loess Hilly Region

Since 1999, the "Grain for Green" Program has been extensively implemented in the Loess Plateau region. This measure has largely been of concern not only for its contribution to soil erosion reduction but also for its effects on carbon sequestration. The aim of this study was to assess the carbon sequestration characteristics of different restored vegetation types in areas with severe soil erosion on the Loess Plateau and to compare the effects of restoration age and slope direction on the vegetation carbon sequestration. To evaluate the carbon density and composition characteristics of different ecosystem types, six typical vegetation types (including farmland, grassland, Hippophae rhamnoides Linn., Caragana korshinskii Kom., Robinia pseudoacacia L., and Populus davidiana Dode.) were selected in the Loess Hilly Region, i.e., Wuqi County and Zhidan County in Northern Shaanxi province, which is a typical area for the implementation of artificial vegetation restoration. The results showed that:① vegetation restoration in the semi-arid loess region had a profound impact on carbon sequestration. The carbon density of different vegetations, as well as different vegetation components including above-ground vegetation, below-ground roots, and litter, shared the same pattern as tree>scrub>grassland>farmland. The 0-40 cm soil layer of the farmland showed the lowest soil organic carbon density (1355.5 g·m-2), compared to which those of grassland, H. rhamnoides Linn., C. korshinskii Kom., R. pseudoacacia L., and P. davidiana Dode. were higher by 91.4%, 125.2%, 144.0%, 124.5%, and 232.6%, respectively. ② It was common in grassland, H. rhamnoides Linn., C. korshinskii Kom., and P. davidiana Dode. for the carbon density of different vegetation components as well as soil organic carbon density of different soil layers (0-5, 5-20, and 20-40 cm) to generally show an increasing trend with increased restoration age. ③ Slope direction had a significant impact on the vegetation carbon density only for H. rhamnoides Linn., C. korshinskii Kom., R. pseudoacacia L., and P. davidiana Dode., while showing the contrary for farmland and grassland. Soil organic carbon densities for sunny slopes were significantly lower than those for shaded slopes by 22.9%, 34.3%, 75.8%, 49.1%, 22.4%, and 69.4%, respectively, for farmland, grassland, H. rhamnoides Linn., C. korshinskii Kom., R. pseudoacacia L., and P. davidiana Dode. ④ Ecosystem carbon density varied significantly for different ecosystem types, among which farmland showed the lowest (2022.1 g·m-2), and grassland, H. rhamnoides Linn., C. korshinskii Kom., R. pseudoacacia L., and P. davidiana Dode. showed values higher by 48.7%, 152.8%, 125.1%, 166.3%, and 530.7%, respectively. The carbon density of each ecosystem component showed a pattern as follows:soil layer>above-ground vegetation layer>root layer>litter layer. Soil organic carbon constituted the main part of the ecosystem carbon density and accounted for 67.0%, 86.3%, 59.7%, 72.7%, and 56.5%, respectively, for farmland, grassland, H. rhamnoides Linn., C. korshinskii Kom., and R. pseudoacacia L. These results can provide an essential basis for scientific management of ecosystem carbon pools and promote ecological environment management on the Loess Plateau.

An Efficient User-Friendly Integration Tool for Landslide Susceptibility Mapping Based on Support Vector Machines: SVM-LSM Toolbox

Landslide susceptibility mapping (LSM) is an important element of landslide risk assessment, but the process often needs to span multiple platforms and the operation process is complex. This paper develops an efficient user-friendly toolbox including the whole process of LSM, known as the SVM-LSM toolbox. The toolbox realizes landslide susceptibility mapping based on a support vector machine (SVM), which can be integrated into the ArcGIS or ArcGIS Pro platform. The toolbox includes three sub-toolboxes, namely: (1) influence factor production, (2) factor selection and dataset production, and (3) model training and prediction. Influence factor production provides automatic calculation of DEM-related topographic factors, converts line vector data to continuous raster factors, and performs rainfall data processing. Factor selection uses the Pearson correlation coefficient (PCC) to calculate the correlations between factors, and the information gain ratio (IGR) to calculate the contributions of different factors to landslide occurrence. Dataset sample production includes the automatic generation of non-landslide data, data sample production and dataset split. The accuracy, precision, recall, F1 value, receiver operating characteristic (ROC) and area under curve (AUC) are used to evaluate the prediction ability of the model. In addition, two methods—single processing and multiprocessing—are used to generate LSM. The prediction efficiency of multiprocessing is much higher than that of the single process. In order to verify the performance and accuracy of the toolbox, Wuqi County, Yan’an City, Shaanxi Province was selected as the test area to generate LSM. The results show that the AUC value of the model is 0.8107. At the same time, the multiprocessing prediction tool improves the efficiency of the susceptibility prediction process by about 60%. The experimental results confirm the accuracy and practicability of the proposed toolbox in LSM.

Effects of simulated grazing disturbance on soil water infiltration of biocrust slope in the hilly Loess Pla-teau, China

Water is the key factor for vegetation restoration in the Loess Plateau region. Biological soil crust (biocrust), a widely distributed soil surface cover, significantly affects soil infiltration. Disturbance would affect soil water infiltration of biocrust. The effects of different intensities of disturbance on soil water infiltration of biocrust are still unclear. By simulating the trampling disturbance of sheep, we examined the effects of disturbance intensity (10%, 20%, 30%, and 40%) estimated by the coverage of broken biocrust on the surface cover of biocrust slope in the Hegou catchment of Wuqi County, Shaanxi Province. Soil water infiltration under different intensities were measured by the linear source infiltration method. The influence mechanisms of disturbance on soil water infiltration of biocrust slope were investigated with a structural equation model and correlation analysis. Results showed that compared to that without disturbance, the coverage of cyanobacterial crust was increased by 33.6% at 10% of disturbance intensity, no difference at 20% of disturbance intensity, and decreased by 36.1% and 75.0% at 30% and 40% of disturbance intensities, respectively. Litter coverage was increased by 34.3% under 40% of disturbance intensity, while that of other treatments were not changed. Surface roughness was decreased by 22.3%, 11.1%, and 5.6% at 10%, 20%, and 30% of disturbance intensities, respectively, but increased by 8.2% at the 40% of disturbance intensity. The initial infiltration rate at 40% of disturbance intensity was 77.1% higher than that without disturbance, while other treatments had no significant difference at the initial infiltration rate. Furthermore, distur-bance did not affect the stable and average infiltration rate. Our results confirmed that disturbance mainly promoted the initial infiltration by reducing the coverage of cyanobacterial crust, increasing the coverage of litter, and changing soil roughness. This study would provide scientific basis for the management of biocrust of rehabilitated lands in the Loess Plateau region.

Representative landscape indices of biological soil crusts distribution in the hilly Loess Plateau of China

Landscape indices can quantitatively describe the distribution characteristics of biological soil crusts (biocrusts). However, there are too many landscape indices, with high redundancy. We investigated 58 plots of biocrusts with different distribution patterns in the Hegou watershed of Wuqi County, Shaanxi Province, located in the hilly Loess Plateau. First, we calculated 15 common landscape indices, and selected representative landscape indices that could describe the biocrust landscape pattern and had specific ecological significance, based on correlation analysis, factor analysis, and sensitivity analysis. The reliability and rationality of the representative landscape indices were verified with data of the different biocrusts coverage in the Yingwoshanjian watershed of Yangjing Town, Dingbian County, Shaanxi Province. The results showed that 10 of the 15 landscape indices had significant correlations. Total edge (TE) and edge density (ED) were not significantly correlated with number of patches (NP), patch density (PD), clumpiness (CLUMPY), and interspersion juxtaposition index (IJI), respectively. The percentage of landscape (PLAND), ED, patch cohesion index (COHESION), and splitting index (SPLIT) described the spatial distribution characteristics of biocrust from coverage, length, connectivity, and fragmentation, respectively. The cumulative contribution of the three common factors represented in describing the spatial distribution of biocrusts was 91.6%. The study identified the representative landscape indices that could quantify the complexity of biocrusts distribution and thus would provide a theoretical basis for studying the pattern evolution of biocrusts and their relationship with ecological processes.

Landslide Susceptibility Mapping Using Novel Hybrid Model Based on Different Mapping Units

Landslide is a most widespread geohazards around the world. Reasonable landslide susceptibility mapping can aid decision-makers in landslide prevention. Therefore, drawing regional landslide susceptibility map is of great significance to landslide prevention. This research mainly aims to explore a new method and carry out the landslide susceptibility mapping based on terrain mapping unit (TMU) and grid cells mapping unit (GCMU) in Wuqi County, Yan'an City, China. Firstly, the landslide inventory map was prepared based on 717 landslides that were extracted. Secondly, the index of entropy model (IOE) was applied to quantify landslide predisposing factors based on TMU and GCMU, respectively. Finally, the systematically developed forest of multiple trees (SysFor) was integrated with IOE to construct a novel hybrid model (IOE-SysFor) and the landslide susceptibility maps based on TMU and GCMU were obtained. Statistical indices and receiver operating characteristic curve (ROC) were applied to evaluate the results and compare the approaches. From the results, it indicated that the accuracy of landslide susceptibility maps generated by the IOE-SysFor based on TMU and GCMU was satisfactory, furthermore, the performance of IOE-SysFor model running on the TMU was better than GCMU. Therefore, the TMU was considered as a more suitable landslide mapping unit for similar regions and the approach developed by this study can provide a reference for future researches.

Comparing the long‐term effects of artificial and natural vegetation restoration strategies: A case‐study of Wuqi and its adjacent counties in northern China

AbstractThe significant increase in vegetation coverage in northern China over the past two decades has attracted worldwide attention. Revegetation has been completed via artificial and natural restoration techniques, and the relative performance of each needs to be further explored. Although some studies have focused on the comparison between artificial and natural methods in vegetation restoration from a micro‐perspective, there is a lack of evidence at the regional scale. This study considers Wuqi County and its adjacent areas of the Loess Plateau in northern China as our study area. First, natural and artificial restoration areas were identified. Then, the restoration sustainability of different restoration strategies and the adjustment effect of climate factors in the relationship between vegetation restoration strategy choice and vegetation restoration sustainability were analyzed. We found that the vegetation restoration strategies employed varied between local jurisdictions. In areas dominated by artificial restoration, vegetation coverage increased over a short period, but the growth rate diminished in the long term. In comparison, in areas mainly dominated by natural restoration, although the growth rate of revegetation was not very high in the short term, it was stable in the long term. In addition, the impact of vegetation restoration strategies on vegetation restoration sustainability exhibited spatial heterogeneity, and the temperature, humidity, and wind speed further affected strategy outcomes. This study provides a new perspective for vegetation restoration strategy evaluation and is expected to serve as a reference for the optimization of relevant ecological policies in the future.

Response of deep soil moisture to different vegetation types in the Loess Plateau of northern Shannxi, China

Deep soil moisture is a highly important source of water for vegetation in the semiarid Loess Plateau of China, vegetation restoration reduced the deep soil moisture, but how to better quantify the impact of vegetation restoration on deep soil moisture is lack of certain understanding. To explore the impact exerted by different types of vegetation on deep layers of the soil moisture, the 0–10 m soil moisture content profile was measured before and after the rainy season in Armeniaca sibirica, Robinia pseudoacacia, Populus simonii, Pinus tabuliformis, Hippophae rhamnoides and in natural grassland in Wuqi County in Shannxi Province. These results showed that the highest soil moisture in the shallow layers (0–200 cm) was exhibited in the P. simonii forest, which was followed by that in the natural grassland. Both of these results were significantly higher than that those of the A. sibirica, P. tabuliformis, H. rhamnoides and R. pseudoacacia forests. The soil moisture in the deep layer (200–1000 cm) of the natural grassland was significantly higher than that of the other vegetation types. The annual precipitation that recharges the depth of soil moisture was the highest in natural grassland and the lowest in P. simonii. The inter-annual soil moisture replenishment is primarily affected by rainfall and vegetation types. Compared with the natural grassland, the CSWSD (the comparison of the soil moisture storage deficit) of different vegetation types varies. In the shallow soil layer, P. simonii is the lowest, and R. pseudoacacia is the highest. In the deep soil layer, R. pseudoacacia and P. simonii are the highest; H. rhamnoides is the second highest, and A. sibirica and P. tabuliformis are the lowest. These results indicate that vegetation restoration can significantly reduce the amount of water in the deep layers of the soil. In the future vegetation restoration, we suggest emphasizing natural development more strongly, since it can better maintain the local vegetation stability and soil moisture balance.

Application of Bayesian Hyperparameter Optimized Random Forest and XGBoost Model for Landslide Susceptibility Mapping

Landslides are widely distributed worldwide and often result in tremendous casualties and economic losses, especially in the Loess Plateau of China. Taking Wuqi County in the hinterland of the Loess Plateau as the research area, using Bayesian hyperparameters to optimize random forest and extreme gradient boosting decision trees model for landslide susceptibility mapping, and the two optimized models are compared. In addition, 14 landslide influencing factors are selected, and 734 landslides are obtained according to field investigation and reports from literals. The landslides were randomly divided into training data (70%) and validation data (30%). The hyperparameters of the random forest and extreme gradient boosting decision tree models were optimized using a Bayesian algorithm, and then the optimal hyperparameters are selected for landslide susceptibility mapping. Both models were evaluated and compared using the receiver operating characteristic curve and confusion matrix. The results show that the AUC validation data of the Bayesian optimized random forest and extreme gradient boosting decision tree model are 0.88 and 0.86, respectively, which showed an improvement of 4 and 3%, indicating that the prediction performance of the two models has been improved. However, the random forest model has a higher predictive ability than the extreme gradient boosting decision tree model. Thus, hyperparameter optimization is of great significance in the improvement of the prediction accuracy of the model. Therefore, the optimized model can generate a high-quality landslide susceptibility map.

A time series orthophoto dataset of Wuqi County: a typical returning farmland to forest area on the Loess Plateau

A time series orthophoto dataset of Wuqi County: a typical returning farmland to forest area on the Loess Plateau

Land use structure of typical county with conversion of farmland to forests in loess areas of Northern Shaanxi

Loess Plateau is the key construction area of ecological environment restoration in China. Since implementing the project of converting farmland to forests, the land use structure and existing problems in the loess area of northern Shaanxi have received extensive attention. Land use structure is the area and proportion of all kinds of land within a certain area, which determines the play of regional functions and land use benefits. This work took Wuqi County, Loess District, Northern Shaanxi, the demonstration county of national project of converting farmland to forests. Based on the land use data of Wuqi County in Loess Ddistrict of north Shaanxi Province in 2009, this work carried out the quantitative analysis and discussion of land use quantitative structure in this area by means of quantitative geographical model and GIS spatial analysis and by using indexes such as diversification, centralization and combination coefficient of ground class. The results show that the quantity and structure of land use in Wuqi County are diversified, the concentration is low, and the complete degree of land use type is high. Additionally, the land combination type is mainly forestland-grassland, and the overall function needs to be improved. This study can provide reference for the quantitative analysis of land use structure in similar areas and counties.

Evaluating the vegetation restoration sustainability of ecological projects: A case study of Wuqi County in China

Grain for Green project has achieved substantial results in ecological reconstruction and social benefits in China. Meantime, some doubts also exist, and one of the most concerned themes is its sustainability. Although some studies address this topic, there are deficiencies in the research scale and depth. In this work, except for traditional growth trend analysis of vegetation restoration by using vegetation index from 2000 to 2016 in Wuqi County of China, Moran’s I was used to analyze the competition for water and nutrients among the vegetation due to restricted space, and the Hurst exponent was used to analyze the future development trends of the vegetation cover. The results show that although the vegetation coverage rate of the study area has improved steadily since the implementation of the ecological policy, limited further improvement in the study area is possible in the future; and vegetation restoration is generally sustainable in the southeastern part of the study area but not in the northwestern part of the study area from a spatial perspective. In terms of driving factors, natural factors are the decisive factors affecting the sustainability of vegetation restoration; ecological projects and maintenance measures may promote vegetation restoration generally but they should be controlled at a certain level, otherwise, the counterproductive result would be obtained. Therefore, vegetation restoration should be adapted to local conditions rather than uniform standards being adopted for the entire region, and this conclusion should apply equally to ecological restoration efforts in other regions of the world. Also, from a methodological point of view, this study proposes to analyze the sustainability of vegetation restoration based on the spatial and temporal perspectives by using the spatial autocorrelation and Hurst exponent methods, which is a development and supplement to previous studies and has a certain advantage for evaluating the vegetation restoration status.

Evaluating the usage of tree-based ensemble methods in groundwater spring potential mapping

The main goal of the study was to estimate the efficiency and predictive ability of a series of tree-based ensemble methods in groundwater spring potential mapping. The study introduces a novel hybrid integration approach based on J48 Decision Trees (J48), AdaBoost (AB), Bagging (Bag), RandomSubSpace (RS), Dagging (Dag) and Rotation Forest (RF) algorithms for constructing a groundwater spring potential map. The performance of the ensemble models were evaluated at the Wuqi County in Shaanxi Province, China. At first, a groundwater spring inventory map with 235 groundwater springs was constructed. The groundwater spring database was randomly divided into a training (70% of the total number of groundwater springs) and validating subset (remaining 30%). Secondly, sixteen groundwater spring related variables were selected and analyzed, such as elevation, slope, aspect, planform and profile curvature, curvature, topographic wetness index, stream transport and stream power indexes, distance from river network, lithology, soil and landuse cover, normalized difference vegetation index, mean annual rainfall and distance from road network. The contribution of each groundwater spring related variable so as to identify the most predictive was based on the correlation attribute evaluation method. The predictive performance of each model was evaluated by estimating the area under the receiver operating characteristic (ROC) curve (AUC) and several statistical indexes (accuracy, sensitivity, specificity). The outcomes revealed that all models had a good predictive performance, having AUC values greater than 0.74. Specifically, RF-J48 model appeared with the highest prediction capability (AUC = 0.797), followed by the AB-J48 model (0.793), the Bag-J48 (0.768), the RS-J48 (0.766) and the Dag-J48 (0.748), respectively. The study highlights that the proposed ensemble methodology is efficient and highly accurate appropriate for groundwater spring potential mapping.

Groundwater spring potential mapping using population-based evolutionary algorithms and data mining methods

Water scarcity in many regions of the world has become an unpleasant reality. Groundwater appears to be one of the main natural resources capable to reverse this situation. Uncovering the spatial patterns of groundwater occurrence is a crucial factor that could assist in carrying out successful water resources management projects. The main objective of the current study was to provide a novel methodology approach which utilized Genetic Algorithm (GA) in order to perform a feature selection procedure and data mining methods for generating a groundwater spring potential map. Three data mining methods, Naïve Bayes (NB), Support Vector Machine (SVM) and Random Forest (RF) were utilized to construct a groundwater spring potential map that had over 0.81 probability of occurrence for the Wuqi County, Shaanxi Province, China. Groundwater spring locations and sixteen related variables were analyzed, namely: lithology, soil cover, land use cover, normalized difference vegetation index (NDVI), elevation, slope angle, aspect, planform curvature, profile curvature, curvature, stream power index (SPI), stream transport index (STI), topographic wetness index (TWI), mean annual rainfall, distance from river network and distance from road network. The Frequency ratio method was used to weight the variables, whereas a multi-collinearity analysis was performed to identify the relation between the parameters and to decide about their usage. The optimal set of parameters, which was determined by the GA, reduced the number of parameters into twelve removing planform curvature, profile curvature, curvature and STI. The Receiver Operating Characteristic curve and the area under the curve (AUROC) were estimated so as to evaluate the predictive power of each model. The results indicated that the optimized models were superior in accuracy than the original models. The optimized RF model produced the best results (0.9572), followed by the optimized SVM (0.9529) and the optimized NB (0.8235). Overall, the current study highlights the necessity of applying feature selection techniques in groundwater spring assessments and also that data mining methods may be a highly powerful investigation approach for groundwater spring potential mapping.

Assessing the coordination of ecological and agricultural goals during ecological restoration efforts: A case study of Wuqi County, Northwest China

While the Chinese Grain for Green (GFG) policy has reduced the area of cultivated land in several regions in China, the program’s effects on Per Unit Area Productivity of Cultivated Land (PAPCL) are not clear. As the positive or negative contributions of GFG to PAPCL can vary with context, it is of great theoretical and practical significance to study the correlations between the program and crop yields in order to determine the best balance between environmental benefits and food security. In this study, Wuqi County in China’s Shaanxi Province was selected for a case study. Multi-source data were integrated in the Geographic Information System platform, and geographical weighted regression was then performed to spatially analyze the effects of the GFG on the improvement of PAPCL (GoP); with GoP as the dependent variable, we further analyzed the role of environmental variables in promoting the contribution of GFG to the improvement of PAPCL. Our findings are as follows: (1) GFG can better contribute to the PAPCL improvement in the villages with higher elevation, poor infrastructure, and denser populations, and thus, GFG could be further implemented in these areas. (2) In the area where GFG performed well, agricultural machinery and agricultural chemicals can be utilized less frequently, as they have similar effects on the improvement of PAPCL, but the increase of forest-based diseases and insect pests is possible. (3) The intensity of the GFG itself is negative compared to the GoP, which indicates that the implementation of the GFG in the study area may be excessive in improving the PAPCL.

Hydrochemical characteristics and quality evaluation of groundwater in terms of health risks in Luohe aquifer in Wuqi County of the Chinese Loess Plateau, northwest China

Groundwater is the main source of water for domestic and agricultural purposes in Wuqi County on the Loess Plateau. The present study was carried out to assess the hydrochemical characteristics and quality of groundwater in the Luohe aquifer, which is a crucial aquifer for water supply. For this study, 22 groundwater samples and 6 surface water samples were collected for analysis. Hydrochemistry and hydrochemical facies of groundwater were analyzed using statistical analysis and Tri-linear diagram. Gibbs diagram, correlation analysis and bivariate plots were used to investigate the natural evolution mechanisms of groundwater and surface water. Potential health risks of nitrate and Cr6+ through drinking water ingestion for adults and children were estimated. The results show that the major hydrochemical facies is Cl·SO4-Na, mixed Cl·SO4·HCO3-Na and SO4·Cl-Mg·Na types, and high concentration of Na+ is a remarkable feature of groundwater in the study area. Groundwater chemistry evolution is affected by rock weathering and evaporation. The high concentrations of Na+, SO42- and TDS suggest that groundwater is not suitable for irrigation purposes. According to WQI values, above 80% of the groundwater samples are fair quality water. It is also found that the groundwater of the study area is contaminated with nitrate and Cr6+. Children are at higher health risk than adults. Multiple measures such as establishing new centralized water supply sources and inter-basin water transfer projects have also been proposed in this study to guarantee the safety of sustainable groundwater supply.

Hydrogeochemical Characteristics, Groundwater Quality, and Health Risks from Hexavalent Chromium and Nitrate in Groundwater of Huanhe Formation in Wuqi County, Northwest China

This study was carried out to investigate the current status of groundwater quality in Wuqi County, northwest China. The health risk assessment was also performed to quantify the negative impacts of hexavalent chromium (Cr6+) and nitrate (NO3−) in groundwater on human health by fully considering the gender and age of local residents. For this study, thirty groundwater samples were collected from wells and boreholes distributed in the study area and analyzed for pH, total dissolved solids (TDS), total hardness (TH), major ions (Na+ + K+, Ca2+, Mg2+, HCO3−, SO42−, and Cl−), NO3−, nitrite (NO2−), and Cr6+. Statistical analysis and graphical approaches were adopted to delineate the physicochemical parameters and hydrochemistry of groundwater. Fuzzy comprehensive method was applied in this study to appraise overall groundwater quality. The model recommended by the Ministry of Environmental Protection of the People's Republic of China was selected to assess the non-carcinogenic and carcinogenic risks caused by Cr6+ and NO3− through drinking water intake. Indicated by statistical mean values, the order of cations is Na+ + K+ > Ca2+ > Mg2+, and that of anions is SO42− > Cl− > HCO3−. The averages of TH, TDS, NO3−, and NO2− are 432, 1253, 23.2, and 0.099 mg/L, respectively. Piper diagram indicates that groundwater in the study area is SO4·Cl–Na type, SO4·Cl–Ca·Mg type, and HCO3–Na type. Gibbs diagrams suggest that the major ion chemistry of groundwater in the area is governed by rock weathering and water–rock interaction, while evaporation plays a minor role. According to the results of groundwater quality assessment, over one-third (36.67%) of the groundwater samples are of poor or very poor quality. Through oral pathway, female and male adults in the study area face acceptable non-carcinogenic risks, while children face unacceptable non-carcinogenic risks caused by Cr6+ and NO3−. Both children and adults face unacceptable carcinogenic risks from Cr6+. In addition, children face higher carcinogenic risks than females and males owing to smaller body weight than adults. This study may provide local authorities with insights into making scientific decisions for sustainable groundwater exploitation and efficient groundwater environmental protection.

Does Poverty Matter in Payment for Ecosystem Services Program? Participation in the New Stage Sloping Land Conversion Program

Poverty is increasingly stressed in Payment for Ecosystem Services (PES) schemes, from targeting to outcomes. As the world’s largest PES scheme of its kind, the Sloping Land Conversion Program in China started its new stage (NSLCP), aiming to convert another 2.9 million ha sloping croplands into forest or grasslands. This paper examines whether and to what extent different dimensions of poverty impact households’ participation in the NSLCP. By using the data collected from a key demonstration area, Wuqi County in 2015, based on Sen’s capability theory, we measure the multidimensional poverty of the households, like poverty in education, physical health, food security, rights, assets and living standards. Then, we evaluate the effects of different poverty dimensions on households’ participation in the NSLCP and their efforts to comply with the policy. We find that different dimensions of poverty had very different impacts, as revealed in the participating rate and the intensity of efforts to manage the enrolled lands through different methods. The households with poverty in education, food security, or rights were less likely to be enrolled in the NSLCP. Dimensions like income, health and assets were significant contributions to fulfill the practices required by the NSLCP. Besides, the degree of multidimensional poverty further weakened households’ efforts to manage and protect the trees on enrolled lands.

Contribution of ecological policies to vegetation restoration: A case study from Wuqi County in Shaanxi Province, China

Ecological policies can regulate and modify human activities, affecting land use, and eventually, regional vegetative cover. The impact of these policies on vegetation cover is mediated by natural factors as well as social and economic statuses. The former contains meteorological and topographical indicates, and the latter includes population density, per capita cultivated land, transportation convenience, etc. The chosen study area for this study was Wuqi County, situated in the northern Shaanxi Province of China. Using remote sensing and GIS spatial analysis techniques, land use and vegetation index data of Wuqi from 1995 to 2011 were obtained along with topographical, meteorological, and socio-economic data. Further, the vector and grid data were pooled using a village as a unit, to establish a spatial database in ArcGIS 10.2. Multiple regression models, including a geographically weighted model, along with spatial analysis, were applied to calculate the contribution of ecological policies to the vegetation restoration in the study area under the constraint of resource endowment, particularly ecological policies in terms of restoration of ecological land from cultivated land, conservation of forests and pastures. The results of spatial overlay showed an interesting spatial coupling between changes in land use and improvement in vegetation index. The results of the regression models could reveal the comprehensive and quantitative contribution of ecological policies to vegetation restoration since control variables such as resource endowments were included. Moreover, analyses based on both classical regression and geographically weighted regression indicated that land use has considerable influence on vegetation restoration, while the results of the latter showed a higher significance level and could reveal the spatial differences due to policy effects.