Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Assessing implications of land use and land cover changes in forest ecosystems of NE Turkey

Monitoring land use and land cover change (LUCC) and understanding forest cover dynamics is extremely important in sustainable development and management of forest ecosystems. This study analyzed the spatial and temporal pattern of LUCC in the Yaln?zçam and U?urlu forest planning units which are located in the northeast corner of Turkey. The investigation also evaluates the temporal changes of the spatial structure of forest conditions through the spatial analysis of forest-cover type maps from 1972 and 2005 using geographical information systems and FRAGSTATS^TM. As an overall change between 1972 and 2005, there was a net increase of 1,823 ha in forested areas, and cumulative forest improvement accounted for 2.06 %. In terms of spatial configuration, the landscape structure in the study area changed substantially over the 33-year study period, resulting in fragmentation of the landscape as indicated by large patch numbers and smaller mean patch sizes, owing to heavy grazing, illegal cutting, and uncontrolled stand treatments.     

Estimation of spatial distrubition of groundwater level and risky areas of seawater intrusion on the coastal region in Çarşamba Plain,Turkey, using different interpolation methods

Groundwater level plays a significant role in coastal plains. Heavy pumping and excessive use of near-coast groundwater can increase the intrusion of seawater into the aquifers. In the present study, groundwater levels were measured at 59 groundwater wells at different times during pre- and post-irrigation seasons (April and September of the year 2012) in Çar?amba Plain, Turkey. To select the best method, two deterministic interpolation methods (inverse distance weighing (IDW) with the weights of 1, 2, and 3 and radial basis function (RBF) with spline with tension (SPT) and completely regularized spline (CRS)) and two stochastic methods (ordinary kriging (OK) with spherical, exponential, and Gaussian variograms) and cokriging (COK)) were compared and then the best interpolation method was used to evaluate the spatial distribution of groundwater levels in different seasons and seasonal changes. A total of nine different techniques were tested. Also, risky areas of seawater intrusion in coastal area were determined using the best methods for two periods. The performance of these interpolation methods is evaluated by using a validation test method. Statistical indices of correlation (R ²), mean absolute error (MAE), and root-mean-square error (RMSE) were used to select and validate the best methods. Comparisons between predicted and observed values indicated RBF as the optimal method for groundwater level estimation in April and September. When the best method RBF and the worst method IDW were compared, significant differences were observed in the spatial distribution of groundwater. Results of the study also revealed that excessive groundwater withdrawals during the post-irrigation season dropped the groundwater levels up to 2.0 m in some sections. With regard to seawater intrusion, 9,103 ha of land area was determined to be highly risky and risky.     

Advantages of Geographically Weighted Regression for Modeling Benthic Substrate in Two Greater Yellowstone Ecosystem Streams

Stream habitat assessments are commonplace in fish management, and often involve nonspatial analysis methods for quantifying or predicting habitat, such as ordinary least squares regression (OLS). Spatial relationships, however, often exist among stream habitat variables. For example, water depth, water velocity, and benthic substrate sizes within streams are often spatially correlated and may exhibit spatial nonstationarity or inconsistency in geographic space. Thus, analysis methods should address spatial relationships within habitat datasets. In this study, OLS and a recently developed method, geographically weighted regression (GWR), were used to model benthic substrate from water depth and water velocity data at two stream sites within the Greater Yellowstone Ecosystem. For data collection, each site was represented by a grid of 0.1 m² cells, where actual values of water depth, water velocity, and benthic substrate class were measured for each cell. Accuracies of regressed substrate class data by OLS and GWR methods were calculated by comparing maps, parameter estimates, and determination coefficient r ². For analysis of data from both sites, Akaike’s Information Criterion corrected for sample size indicated the best approximating model for the data resulted from GWR and not from OLS. Adjusted r ² values also supported GWR as a better approach than OLS for prediction of substrate. This study supports GWR (a spatial analysis approach) over nonspatial OLS methods for prediction of habitat for stream habitat assessments.     

Effect of land use land cover change on soil erosion potential in an agricultural watershed

Universal soil loss equation (USLE) was used in conjunction with a geographic information system to determine the influence of land use and land cover change (LUCC) on soil erosion potential of a reservoir catchment during the period 1989 to 2004. Results showed that the mean soil erosion potential of the watershed was increased slightly from 12.11 t ha^???1 year^???1 in the year 1989 to 13.21 t ha^???1 year^???1 in the year 2004. Spatial analysis revealed that the disappearance of forest patches from relatively flat areas, increased in wasteland in steep slope, and intensification of cultivation practice in relatively more erosion-prone soil were the main factors contributing toward the increased soil erosion potential of the watershed during the study period. Results indicated that transition of other land use land cover (LUC) categories to cropland was the most detrimental to watershed in terms of soil loss while forest acted as the most effective barrier to soil loss. A p value of 0.5503 obtained for two-tailed paired t test between the mean erosion potential of microwatersheds in 1989 and 2004 also indicated towards a moderate change in soil erosion potential of the watershed over the studied period. This study revealed that the spatial location of LUC parcels with respect to terrain and associated soil properties should be an important consideration in soil erosion assessment process.     

Dynamics of Typical Agricultural Landscape and its Relationship With Water Resource in Inland Shiyang River Watershed, Gansu Province, Northwest China

Shiyang River basin is located in Hexi Corridor, central-west Gansu province, northwest China. It is an area of typical arid to semiarid features. Based on the TM image of Liangzhou oasis and Minqin oasis in 1986 and 2000, this paper calculated and analyzed the changes of percentage and area of land use/cover types, and also have got the transformation matrix of the landscape mosaics. Dynamics of runoff and exploitation of groundwater, the most important factors influencing land use changes were also analyzed. The ratio of utilized water quantity in upper and middle reaches to that in lower reaches has increased largely from less than 2 before 1970 reached up to more than 8 since 1995; groundwater exploitation has developed progressively. As a result of overuse of groundwater, the groundwater table lowering obviously, the lowering rates reached up to 0.6–0.8 m/year in some place. In addition, the cropping patterns in study area were also distributed irrefficiently that if the planting percentage of water-wasting grain crops dropped to 50% in both oases, it could save irrigating water by 1.2×10⁸ m³ in Liangzhou oasis and 0.2×10⁸ m³ in Minqin oasis one year.     

Monitoring and assessment of seasonal land cover changes using remote sensing: a 30-year (1987–2016) case study of Hamoun Wetland,Iran

The availability of Landsat data allows improving the monitoring and assessment of large-scale areas with land cover changes in rapid developing regions. Thus, we pretend to show a combined methodology to assess land cover changes (LCCs) in the Hamoun Wetland region (Iran) over a period of 30-year (1987–2016) and to quantify seasonal and decadal landscape and land use variabilities. Using the pixel-based change detection (PBCD) and the post-classification comparison (PCC), four land cover classes were compared among spring, summer, and fall seasons. Our findings showed for the water class a higher correlation between spring and summer (R²?=?0.94) than fall and spring (R²?=?0.58) seasons. Before 2000, ~?50% of the total area was covered by bare soil and 40% by water. However, after 2000, more than 70% of wetland was transformed into bare soils. The results of the long-term monitoring period showed that fall season was the most representative time to show the inter-annual variability of LCCs monitoring and the least affected by seasonal-scale climatic variations. In the Hamoun Wetland region, land cover was highly controlled by changes in surface water, which in turn responded to both climatic and anthropogenic impacts. We were able to divide the water budget monitoring into three different ecological regimes: (1) a period of high water level, which sustained healthy extensive plant life, and approximately 40% of the total surface water was retained until the end of the hydrological year; (2) a period of drought during high evaporation rates was observed, and a mean wetland surface of about 85% was characterized by bare land; and (3) a recovery period in which water levels were overall rising, but they are not maintained from year to year. After a spring flood, in 2006 and 2013, grassland reached the highest extensions, covering till more than 20% of the region, and the dynamics of the ecosystem were affected by the differences in moisture. The Hamoun wetland region served as an important example and demonstration of the feedbacks between land cover and land uses, particularly as pertaining to water resources available to a rapidly expanding population.     

Estimating impacts of land use on groundwater quality using trilinear analysis

Groundwater is connected to the landscape above and is thus affected by the overlaying land uses. This study evaluated the impacts of land uses upon groundwater quality using trilinear analysis. Trilinear analysis is a display of experimental data in a triangular graph. Groundwater quality data collected from agricultural, septic tank, forest, and wastewater land uses for a 6-year period were used for the analysis. Results showed that among the three nitrogen species (i.e., nitrate and nitrite (NO_x), dissolved organic nitrogen (DON), and total organic nitrogen (TON)), NO_x had a high percentage and was a dominant species in the groundwater beneath the septic tank lands, whereas TON was a major species in groundwater beneath the forest lands. Among the three phosphorus species, namely the particulate phosphorus (PP), dissolved ortho phosphorus (PO ₄ ^3?? ) and dissolved organic phosphorus (DOP), there was a high percentage of PP in the groundwater beneath the septic tank, forest, and agricultural lands. In general, Ca was a dominant cation in the groundwater beneath the septic tank lands, whereas Na was a dominant cation in the groundwater beneath the forest lands. For the three major anions (i.e., F^?, Cl^?, and SO ₄ ^2?? ), F^? accounted for <1 % of the total anions in the groundwater beneath the forest, wastewater, and agricultural lands. Impacts of land uses on groundwater Cd and Cr distributions were not profound. This study suggests that trilinear analysis is a useful technique to characterize the relationship between land use and groundwater quality.     

Semiquantitative color profiling of soils over a land degradation gradient in Sakaerat, Thailand

In this study, we attempted multivariate color profiling of soils over a land degradation gradient represented by dry evergreen forest (original vegetation), dry deciduous forest (moderately disturbed by fire), and bare ground (severely degraded) in Sakaerat, Thailand. The soils were sampled in a dry-to-wet seasonal transition. Values of the red–green–blue (RGB), cyan–magenta–yellow–key black (CMYK), L*a*b*, and hue–intensity–saturation (HIS) color models were determined using the digital software Adobe Photoshop^TM. Land degradation produced significant variations (p?R, C, Y, L*, a*, b*, S, and I values (p?p?R, G, B, C, M, K, L*, b*, and I values. In discriminating the soils, the color models did not differ in discriminatory power, while discriminatory power was affected by seasonal changes. Most color variation patterns had nonlinear relationships with the intensity of the land degradation gradient, due to effects of fire that darkened the deciduous forest soil, masking the nature of the soil as the intermediate between the evergreen forest and the bare ground soils. Taking these findings into account, the utilization of color profiling of soils in land conservation and rehabilitation is discussed.     

Spatial Modeling of Mean Annual Temperature in Iran: Comparing Cokriging and Geographically Weighted Regression

Mapping spatial distribution of climatological parameters with a good degree of accuracy is crucial in environmental modeling and planning. Nowadays, there are various models to estimate and predict spatial variables in an area but some such as cokriging and geographically weighted regression (GWR) have got more attention from experts in this field. The objectives of this study are to evaluate and compare GWR with ordinary cokriging (OCK) techniques for estimating the mean annual air temperature (MAT) of Iran using European Centre for Medium-Range Weather Forecasts (ECMWF) data and auxiliary variables (e.g., longitude, latitude and altitude). The MAT-gridded data for Iran was collected in pixels during the time interval of 1987–2015 from the ERA-Interim re-analysis version of ECMWF. Validation results indicate that cokriging model with latitude and altitude for estimating MAT has the lowest MAE (0.0155), MBE (0.00085), RMSE (0.0251), and the highest NS (0.9999) in relation to other cokriging methods. On the other hand, GWR with altitude has better results than those of GWR with other auxiliary variables because of its MAE (0.1271), MBE (0.0124), RMSE (0.1760), and NS (0.9969). By comparing two mentioned methods, cokriging with latitude and altitude has provided the best performance in relation to GWR for prediction of MAT in Iran. To obtain accurate estimation of the spatial distribution of MAT, local residuals were analyzed. Results concluded that residuals of the OCK model have high spatial adaptations between the observed and predicted MAT data compared to the GWR model. Hence, OCK was a relatively optimum method for the estimation of MAT compared with GWR.

     

Compositing climate change vulnerability of a Mediterranean region using spatiotemporally dynamic proxies for ecological and socioeconomic impacts and stabilities

The study presents a new methodology to quantify spatiotemporal dynamics of climate change vulnerability at a regional scale adopting a new conceptual model of vulnerability as a function of climate change impacts, ecological stability, and socioeconomic stability. Spatiotemporal trends of equally weighted proxy variables for the three vulnerability components were generated to develop a composite climate change vulnerability index (CCVI) for a Mediterranean region of Turkey combining Landsat time series data, digital elevation model (DEM)-derived data, ordinary kriging, and geographical information system. Climate change impact was based on spatiotemporal trends of August land surface temperature (LST) between 1987 and 2016. Ecological stability was based on DEM, slope, aspect, and spatiotemporal trends of normalized difference vegetation index (NDVI), while socioeconomic stability was quantified as a function of spatiotemporal trends of land cover, population density, per capita gross domestic product, and illiteracy. The zones ranked on the five classes of no-to-extreme vulnerability were identified where highly and moderately vulnerable lands covered 0.02% (12 km²) and 11.8% (6374 km²) of the study region, respectively, mostly occurring in the interior central part. The adoption of this composite CCVI approach is expected to lead to spatiotemporally dynamic policy recommendations towards sustainability and tailor preventive and mitigative measures to locally specific characteristics of coupled ecological–socioeconomic systems.     

Soil salinity evolution and its relationship with dynamics of groundwater in the oasis of inland river basins: case study from the Fubei region of Xinjiang Province, China

Soil salinization is an important worldwide environmental problem, especially in arid and semi-arid regions. Knowledge of its temporal and spatial variability is crucial for the management of oasis agriculture. The study area has experienced dramatic change in the shallow groundwater table and soil salinization during the 20th century, especially in the past two decades. Classical statistics, geostatistics and geographic information system (GIS) were applied to estimate the spatial variability of the soil salt content in relation to the shallow groundwater table and land use from 1983 to 2005. Consumption of reservoir water for agricultural irrigation was the main cause of a rise in the shallow groundwater table under intense evapotranspiration conditions, and this led indirectly to soil salinization. The area of soil salt accumulation was greater in irrigated than in non-irrigated landscape types with an increasing of 40.04% from 1983 to 2005 in cropland at ∼0.43 t ha⁻¹ year⁻¹, and an increase at ∼0.68 t ha⁻¹ year⁻¹ in saline alkaline land. Maps of the shallow groundwater table in 1985 and 2000 were used to deduce maps for 1983 and 1999, respectively, and the registration accuracy was 99%.     

Use of fuzzy logic models for prediction of taste and odor compounds in algal bloom-affected inland water bodies

Mechanistic modeling of how algal species produce metabolites (e.g., taste and odor compounds geosmin and 2-methyl isoborneol (2-MIB)) as a biological response is currently not well understood. However, water managers and water utilities using these reservoirs often need methods for predicting metabolite production, so that appropriate water treatment procedures can be implemented. In this research, a heuristic approach using Adaptive Network-based Fuzzy Inference System (ANFIS) was developed to determine the underlying nonlinear and uncertain quantitative relationship between observed cyanobacterial metabolites (2-MIB and geosmin), various algal species, and physical and chemical variables. The model is proposed to be used in conjunction with numerical water quality models that can predict spatial–temporal distribution of flows, velocities, water quality parameters, and algal functional groups. The coupling of the proposed metabolite model with the numerical water quality models would assist various utilities which use mechanistic water quality models to also be able to predict distribution of taste and odor metabolites, especially when monitoring of metabolites is limited. The proposed metabolite model was developed and tested for the Eagle Creek Reservoir in Indiana (USA) using observations over a 3-year period (2008–2010). Results show that the developed models performed well for geosmin (R ²?=?0.83 for all training data and R ²?=?0.78 for validation of all 10 data points in the validation dataset) and reasonably well for the 2-MIB (R ²?=?0.82 for all training data and R ²?=?0.70 for 7 out of 10 data points in the validation dataset).     

The Impact of Urbanization and Protection of Water Resources in Owerri and Environs SE, Nigeria

Untreated sewage and agriculture are the most important sources of contamination. The study was carried out by conducting a short-term surface water and groundwater pollution survey of the Owerri Urban area and its environs, in order to establish the current levels of pollution. An attempt has been made to show the relationships between pollution levels, population density, industrial and agricultural activities. The spatial distribution of pollutants due to a poor land use system and to human activities was investigated. This emphasises integrated planned development as a preventive measure for arresting pollution levels in fast growing urban centres. The total groundwater stored in the area amounts to 7.87 × 10⁹ m³. Twenty five percent of this is released as base flow into the adjacent rivers (Otamiri and Nworie). The annual groundwater recharge is 3.4 × 10⁹ m³. The enormous volume of groundwater stored and the comparatively low cost of development makes groundwater an excellent alternative supply source for the area (Uma et al., 1984).     

Land use pattern, socio-economic development, and assessment of their impacts on ecosystem service value: study on natural wetlands distribution area (NWDA) in Fuzhou city, southeastern China

This paper quantifies the allocation of ecosystem services value (ESV) associated with land use pattern and qualitatively examined impacts of land use changes and socio-economic factors on spatiotemporal variation of ESV in the Natural Wetland Distribution Area (NWDA), Fuzhou city, China. The results showed that total ESV of the study area decreased from 4,332.16?×?10⁶ RMB Yuan in 1989 to 3,697.42?×?10⁶ RMB Yuan in 2009, mainly due to the remarkable decreases in cropland (decreased by 55.3 %) and wetland (decreased by 74.2 %). Forest, water, and wetland played major roles in providing ecosystem services, accounting for over 90 % of the total ESV. Based on time series Landsat TM/ETM+ imagery, geographic information system, and historical data, analysis of the spatiotemporal variation of ESV from 1989 to 2009 was performed. It indicated that rapid expansion of urban areas along the Minjiang River resulted in significant changes in land use types, leading to a dramatic decline in ecosystem services. Meanwhile, because of land scarcity and unique ecosystem functions, the emergency of wetland and cropland protection in built-up area has become an urgent task of local authorities to the local government. Furthermore, there was still a significant negative correlation between ESV of cropland and wetland and the GDP. The results suggest that future planning of land use pattern should control encroachment of urban areas into cropland and wetland in addition to scientific and rational policies towards minimizing the adverse effects of urbanization.     

Spatial and temporal dynamics of land use pattern in Eastern Turkey: a case study in Gümüşhane

Recognition and understanding of landscape dynamics as a historical legacy of disturbances are necessary for sustainable management of forest ecosystems. This study analyzed spatial and temporal changes in land use and land cover patterns in a typical mountain watershed in the Gumushane district along the Northeastern part of Turkey. The area is investigated by comparing LANDSAT images from 1987 to 2000 and evaluated the temporal changes of spatial structure of forest conditions through spatial analysis of forest cover type maps from 1971 and 1987 using GIS and FRAGSTATS™. The results show a general decreasing trend in area of natural land cover types including broadleaf and conifer forests as well as coppice between 1971 and 1987 (0.54%, respectively). In contrast, between 1987 and 2000 this natural land cover types show increasing trend (1.6%). In parallel with forest dynamics, the area of managed land including lowland and upland agricultural areas, rangelands and grasslands increased during the first period and decreased during second period. In terms of spatial configuration, Gümüşhane forests aren’t generally fragmented by intensive forest utilization in the latter periods. This is partially due to out-migration of rural population in Gümüşhane. Nevertheless, land use pattern significantly changed over time depending on a few factors such as unregulated management actions, social pressure and demographic movements. The study revealed that demographic movements have a major effect on landscape dynamics.     

Assessment of phenol infiltration resilience in soil media by HYDRUS-1D transport model for a waste discharge site

The movement of contaminants through soil imparts a variety of geo-environmental problem inclusive of lithospheric pollution. Near-surface aquifers are often vulnerable to contamination from surface source if overlying soil possesses poor resilience or contaminant attenuation capacity. The prediction of contaminant transport through soil is urged to protect groundwater from sources of pollutants. Using field simulation through column experiments and mathematical modeling like HYDRUS-1D, assessment of soil resilience and movement of contaminants through the subsurface to reach aquifers can be predicted. An outfall site of effluents of a coke oven plant comprising of alarming concentration of phenol (4–12.2 mg/L) have been considered for studying groundwater condition and quality, in situ soil characterization, and effluent characterization. Hydrogeological feature suggests the presence of near-surface aquifers at the effluent discharge site. Analysis of groundwater of nearby locality reveals the phenol concentration (0.11–0.75 mg/L) exceeded the prescribed limit of WHO specification (0.002 mg/L). The in situ soil, used in column experiment, possess higher saturated hydraulic conductivity (K _S ?=?5.25?×?10^?4 cm/s). The soil containing 47 % silt, 11 % clay, and 1.54 % organic carbon content was found to be a poor absorber of phenol (24 mg/kg). The linear phenol adsorption isotherm model showed the best fit (R ²?=?0.977, RMSE?=?1.057) to the test results. Column experiments revealed that the phenol removal percent and the length of the mass transfer zone increased with increasing bed heights. The overall phenol adsorption efficiency was found to be 42–49 %. Breakthrough curves (BTCs) predicted by HYDRUS-1D model appears to be close fitting with the BTCs derived from the column experiments. The phenol BTC predicted by the HYDRUS-1D model for 1.2 m depth subsurface soil, i.e., up to the depth of groundwater in the study area, showed that the exhaustion point was reached within 12 days of elapsed time. This clearly demonstrated poor attenuation capacity of the soil to retard migration of phenol to the groundwater from the surface outfall site. Suitable liner, based on these data, may be designed to inhibit subsurface transport of phenol and thereby to protect precious groundwater from contamination.     

Spatial variability of depth and salinity of groundwater under irrigated ustifluvents in the Middle Black Sea Region of Turkey

Information on the potential risk for soil salinity buildup can be very helpful for soil salinity management in irrigated areas. We evaluated the spatial and temporal variability of groundwater salinity (GWS) and groundwater depth (GWD), which are two of the most important indicators of soil salinity, by indicator kriging technique in a large irrigated area in northern Turkey. GWS and GWD were measured on a monthly basis from irrigation season (August 2003) to rainy season (April 2004) at 60 observation wells in the 8,187-ha irrigated area. Five indicator thresholds were used for GWS and GWD. The semivariogram for each of the thresholds for both variables was analyzed then used together with experimental data to interpolate and map the corresponding conditional cumulative distribution functions (CCDF). Risk for soil salinity buildup was greater in the irrigation season compared to that in the rainy season. The greatest risk for soil salinity buildup occurred in the eastern part of the study area, suffering from poor drainage problem due to malfunctioning drainage infrastructure, as indicated by the CCDF of GWS and GWD obtained in both seasons. It was concluded that a combination of mechanical and cultural measures should be taken in high-risk locations to avoid further salinity problems.     

Characteristics of atmospheric non-methane hydrocarbons during haze episode in Beijing, China

This study firstly focused on non-methane hydrocarbons (NMHCs) during three successive days with haze episode (16–18 August 2006) in Beijing. Concentrations of alkanes, alkenes, aromatic hydrocarbons, and ethyne all peaked at traffic rush hour, implying vehicular emission; and alkanes also peaked at non-traffic rush hour in the daytime, implying additional source. Especially, alkanes and aromatics clearly showed higher levels in the nighttime than that in the daytime, implying their active photochemical reactions in the daytime. Correlation coefficients (R ²) showed that propane, n-butane, i-butane, ethene, propene, and benzene correlated with ethyne (R ²?=?0.61–0.66), suggesting that their main source is vehicular emission; 2-methylpentane and n-hexane correlated with i-pentane (R ²?=?0.61–0.64), suggesting that gasoline evaporation is their main source; and ethylbezene, m-/p-xylene, and o-xylene correlated with toluene (R ²?=?0.60–0.79), suggesting that their main source is similar to that of toluene (e.g., solvent usage). The R ² of ethyne, i-pentane, and toluene with total NMHCs were 0.58, 0.76, and 0.60, respectively, indicating that ambient hydrocarbons are associated with vehicular emission, gasoline evaporation, and solvent usage. The sources of other hydrocarbons (e.g., ethane) might be natural gas leakage, biogenic emission, or long-range transport of air pollutants. Measured higher mean B/T ratio (0.78?±?0.27) was caused by the more intensive photochemical activity of toluene than benzene, still indicating the dominant emission from vehicles.     

Impacts of ecological water conveyance on groundwater dynamics and vegetation recovery in the lower reaches of the Tarim River in northwest China

The ecological water conveyance project (EWCP) in the lower reaches of the Tarim River provided a valuable opportunity to study hydro-ecological processes of desert riparian vegetation. Ecological effects of the EWCP were assessed at large spatial and temporal scales based on 13 years of monitoring data. This study analyzed the trends in hydrological processes and the ecological effects of the EWCP. The EWCP resulted in increased groundwater storage—expressed as a general rise in the groundwater table—and improved soil moisture conditions. The change of water conditions also directly affected vegetative cover and the phenology of herbs, trees, and shrubs. Vegetative cover of herbs was most closely correlated to groundwater depth at the last year-end (R?=?0.81), and trees and shrubs were most closely correlated to annual average groundwater depth (R?=?0.79 and 0.66, respectively). The Normalized Difference Vegetation Index (NDVI) responded to groundwater depth on a 1-year time lag. Although the EWCP improved the NDVI, the study area is still sparsely vegetated. The main limitation of the EWCP is that it can only preserve the survival of existing vegetation, but it does not effectively promote the reproduction and regeneration of natural vegetation.