Showing papers in "Environmental Earth Sciences in 2010"

Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models

Abstract: This paper summarizes findings of landslide hazard analysis on Penang Island, Malaysia, using frequency ratio, logistic regression, and artificial neural network models with the aid of GIS tools and remote sensing data. Landslide locations were identified and an inventory map was constructed by trained geomorphologists using photo-interpretation from archived aerial photographs supported by field surveys. A SPOT 5 satellite pan sharpened image acquired in January 2005 was used for land-cover classification supported by a topographic map. The above digitally processed images were subsequently combined in a GIS with ancillary data, for example topographical (slope, aspect, curvature, drainage), geological (litho types and lineaments), soil types, and normalized difference vegetation index (NDVI) data, and used to construct a spatial database using GIS and image processing. Three landslide hazard maps were constructed on the basis of landslide inventories and thematic layers, using frequency ratio, logistic regression, and artificial neural network models. Further, each thematic layer’s weight was determined by the back-propagation training method and landslide hazard indices were calculated using the trained back-propagation weights. The results of the analysis were verified and compared using the landslide location data and the accuracy observed was 86.41, 89.59, and 83.55% for frequency ratio, logistic regression, and artificial neural network models, respectively. On the basis of the higher percentages of landslide bodies predicted in very highly hazardous and highly hazardous zones, the results obtained by use of the logistic regression model were slightly more accurate than those from the other models used for landslide hazard analysis. The results from the neural network model suggest the effect of topographic slope is the highest and most important factor with weightage value (1.0), which is more than twice that of the other factors, followed by the NDVI (0.52), and then precipitation (0.42). Further, the results revealed that distance from lineament has the lowest weightage, with a value of 0. This shows that in the study area, fault lines and structural features do not contribute much to landslide triggering.

Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine

Abstract: This case study presented herein compares the GIS-based landslide susceptibility mapping methods such as conditional probability (CP), logistic regression (LR), artificial neural networks (ANNs) and support vector machine (SVM) applied in Koyulhisar (Sivas, Turkey). Digital elevation model was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index, stream power index, normalized difference vegetation index, distance from settlements and roads were used in the landslide susceptibility analyses. In the last stage of the analyses, landslide susceptibility maps were produced from ANN, CP, LR, SVM models, and they were then compared by means of their validations. However, area under curve values obtained from all four methodologies showed that the map obtained from ANN model looks like more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results also showed that the CP is a simple method in landslide susceptibility mapping and highly compatible with GIS operating features. Susceptibility maps can be easily produced using CP, because input process, calculation and output processes are very simple in CP model when compared with the other methods considered in this study.

Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques

Abstract: Artificial recharge plays a pivotal role in the sustainable management of groundwater resources. This study proposes a methodology to delineate artificial recharge zones as well as to identify favorable artificial recharge sites using integrated remote sensing (RS), geographical information system (GIS) and multi-criteria decision making (MCDM) techniques for augmenting groundwater resources in the West Medinipur district of West Bengal, India, which has been facing water shortage problems for the past few years. The thematic layers considered in this study are: geomorphology, geology, drainage density, slope and aquifer transmissivity, which were prepared using IRS-1D imagery and conventional data. Different themes and their corresponding features were assigned proper weights based on their relative contribution to groundwater recharge in the area, and normalized weights were computed using the Saaty’s analytic hierarchy process (AHP). These thematic layers were then integrated in the GIS environment to delineate artificial recharge zones in the study area. The artificial recharge map thus obtained divided the study area into three zones, viz., ‘suitable,’ ‘moderately suitable’ and ‘unsuitable’ according to their suitability for artificial groundwater recharge. It was found that about 46% of the study area falls under ‘suitable’ zone, whereas 43% falls under the ‘moderately suitable’ zone. The western portion of the study area was found to be unsuitable for artificial recharge. The artificial recharge zone map of the study area was found to be in agreement with the map of mean groundwater depths over the area. Furthermore, forty possible sites for artificial recharge were also identified using RS and GIS techniques. Based on the available field information, check dams are suggested as promising artificial recharge structures. The results of this study could be used to formulate an efficient groundwater management plan for the study area so as to ensure sustainable utilization of scarce groundwater resources.

Changes in the chemistry of shallow groundwater related to the 2008 injection of CO2 at the ZERT field site, Bozeman, Montana

Abstract: Approximately 300 kg/day of food-grade CO2 was injected through a perforated pipe placed horizontally 2–2.3 m deep during July 9–August 7, 2008 at the MSU-ZERT field test to evaluate atmospheric and near-surface monitoring and detection techniques applicable to the subsurface storage and potential leakage of CO2. As part of this multidisciplinary research project, 80 samples of water were collected from 10 shallow monitoring wells (1.5 or 3.0 m deep) installed 1–6 m from the injection pipe, at the southwestern end of the slotted section (zone VI), and from two distant monitoring wells. The samples were collected before, during, and following CO2 injection. The main objective of study was to investigate changes in the concentrations of major, minor, and trace inorganic and organic compounds during and following CO2 injection. The ultimate goals were (1) to better understand the potential of groundwater quality impacts related to CO2 leakage from deep storage operations, (2) to develop geochemical tools that could provide early detection of CO2 intrusion into underground sources of drinking water (USDW), and (3) to test the predictive capabilities of geochemical codes against field data. Field determinations showed rapid and systematic changes in pH (7.0–5.6), alkalinity (400–1,330 mg/l as HCO3), and electrical conductance (600–1,800 μS/cm) following CO2 injection in samples collected from the 1.5 m-deep wells. Laboratory results show major increases in the concentrations of Ca (90–240 mg/l), Mg (25–70 mg/l), Fe (5–1,200 ppb), and Mn (5–1,400 ppb) following CO2 injection. These chemical changes could provide early detection of CO2 leakage into shallow groundwater from deep storage operations. Dissolution of observed carbonate minerals and desorption-ion exchange resulting from lowered pH values following CO2 injection are the likely geochemical processes responsible for the observed increases in the concentrations of solutes; concentrations generally decreased temporarily following four significant precipitation events. The DOC values obtained are 5 ± 2 mg/l, and the variations do not correlate with CO2 injection. CO2 injection, however, is responsible for detection of BTEX (e.g. benzene, 0–0.8 ppb), mobilization of metals, the lowered pH values, and increases in the concentrations of other solutes in groundwater. The trace metal and BTEX concentrations are all significantly below the maximum contaminant levels (MCLs). Sequential leaching of core samples is being carried out to investigate the source of metals and other solutes.

Assessing water quality using water quality index and multivariate analysis

Abstract: Groundwater is increasingly gaining significance as the main solution to the water supply problems in Ghana, especially in the rural areas. This study was conducted to determine which factors play significant roles in the hydrochemistry of groundwater from the southern Voltaian formation. Conventional graphical and multivariate statistical methods were used. The study reveals three main factors controlling the hydrochemistry. Silicate mineral weathering and reverse cation exchange are the most important processes affecting the hydrochemistry of groundwater at this part of the formation. Interpolation maps created from factor scores suggest that these processes are the most pervasive, recording high scores almost everywhere in the study area. Carbonate mineral weathering is the second most important process in the hydrochemistry. This study finds that carbonate mineral weathering in the area is probably facilitated by carbonic acid rather than sulfuric acid. Chemicals from agricultural activities constitute the third most important process influencing groundwater quality in the area. Eighty samples were used to calculate water quality indices, WQI, which were in turn used to classify groundwater from the study area. Over 98% of the samples fall within the “Excellent” and “Good” categories, suggesting that groundwater from the southern Voltaian formation is generally acceptable for drinking purposes.

Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya

Abstract: This study considers landslide susceptibility mapping by means of frequency ratio and artificial neural network approaches using geographic information system (GIS) techniques as a basic analysis tool. The selected study area was that of the Panchthar district, Nepal. GIS was used for the management and manipulation of spatial data. Landslide locations were identified from field survey and aerial photographic interpretation was used for location of lineaments. Ten factors in total are related to the occurrence of landslides. Based on the same set of factors, landslide susceptibility maps were produced from frequency ratio and neural network models, and were then compared and evaluated. The weights of each factor were determined using the back-propagation training method. Landslide susceptibility maps were produced from frequency ratio and neural network models, and they were then compared by means of their checking. The landslide location data were used for checking the results with the landslide susceptibility maps. The accuracy of the landslide susceptibility maps produced by the frequency ratio and neural networks is 82.21 and 78.25%, respectively.

Potential risks to freshwater resources as a result of leakage from CO2 geological storage: a batch-reaction experiment

Abstract: In assessing the feasibility of widespread deployment of CO2 geological storage, it is prudent to first assess potential consequences of an error or accident that could lead to CO2 leakage into groundwater resources above a sequestration interval. Information about the sensitivity of the groundwater system to introduction of CO2 is needed in order to design groundwater monitoring program. A laboratory-batch experiment was conducted to explore the range of CO2 impact on groundwater quality of a spectrum of representative aquifers, in the Gulf Coast region, USA. Results show that CO2 elevated concentrations of many cations within hours or days. Two types of cations were recognized according to their concentration trends. Type I cations—Ca, Mg, Si, K, Sr, Mn, Ba, Co, B, Zn—rapidly increased following initial CO2 flux and reached stable concentrations before the end of the experiment. Type II cations—Fe, Al, Mo, U, V, As, Cr, Cs, Rb, Ni and Cu—increased at the start of CO2 flux, but declined, in most cases, to levels lower than pre-CO2 concentrations. Dissolution of dolomite and calcite caused the largest increase in concentrations for Ca, Mg, Mn, Ba and Sr. Cation release rates decreased linearly as pH increased during mineral buffering. Experiment results suggest that carbonate minerals are the dominant contributor of changes in groundwater quality. Risk assessments of potential degradation of groundwater and monitoring strategies should focus on these fast-reacting minerals. Mobilization risk of Type II cations, however, may be self-mitigated because adsorption occurs when pH rebounds.

Landsat data to evaluate urban expansion and determine land use/land cover changes in Penang Island, Malaysia

Abstract: Land surface temperature (LST) plays an important role in local, regional and global climate studies. LST controls the distribution of the budget for radiation heat between the atmosphere and the earth’s surface. Therefore, it is important to evaluate abrupt changes in land use/land cover (LULC). Penang Island, Malaysia has been experiencing a rapid and drastic change in urban expansion over the past two decades due to growth in industrial and residential areas. The aim of this study was to investigate and evaluate the impact of LST with respect to land use changes in Penang Island, Malaysia. Three supervised classification techniques known as maximum likelihood, minimum distance-to-mean and parallelepiped were applied to the images to extract thematic information from the acquired scene by using PCI Geomatica 10.1 image processing software. These remote sensing classification techniques help to examine land-use changes in Penang Island using multi-temporal Landsat data for the period of 1999–2007. Training sites were selected within each scene and seven land cover classes were assigned to each classifier. The relative performance of each technique was evaluated. The accuracy of each classification map was assessed using a reference data set consisting of a large number of samples collected per category. Two Landsat satellite images captured in 1999 and 2007 were chosen to classify the LULC types using the maximum likelihood classification method, determined from visible and near-infrared bands. The study revealed that the maximum likelihood classifier produced superior results and achieved a high degree of accuracy. The LST and normalised difference vegetation index (NDVI) were computed based on changes in LULC. The results showed that the urban (highly built-up) area increased dramatically, and grassland area increased moderately. Inversely, barren land decreased obviously, and forest area decreased moderately. While urban (minimally built-up) area decreased slightly. These changes in LULC caused at significant difference in LST between urban and rural areas. Strong correlation values were observed between LST and NDVI for all LULC classes. The remote sensing technique used in this study was found to be efficient; it reduced the time for the analysis of the urban expansion, and it was found to be a useful tool to evaluate the impact of urbanisation with LST.

Effects of natural and calcined oyster shells on Cd and Pb immobilization in contaminated soils

Abstract: In Korea, soils adjacent to abandoned mines are commonly contaminated by heavy metals present in mine tailings. Further, the disposal of oyster shell waste by oyster farm industries has been associated with serious environmental problems. In this study, we attempted to remediate cadmium (Cd)- and lead (Pb)-contaminated soils typical of those commonly found adjacent to abandoned mines using oyster shell waste as a soil stabilizer. Natural oyster shell powder (NOSP) and calcined oyster shell powder (COSP) were applied as soil amendments to immobilize Cd and Pb. The primary components of NOSP and COSP are calcium carbonate (CaCO3) and calcium oxide (CaO), respectively. X-ray diffraction, X-ray fluorescence and scanning electron microscope analyses conducted in this study revealed that the calcination of NOSP at 770°C converted the less reactive CaCO3 to the more reactive CaO. The calcination process also decreased the sodium content in COSP, indicating that it was advantageous to use COSP as a liming material in agricultural soil. After 30 days of incubation, we found that the 0.1 N HCl-extractable Cd and Pb contents in soil decreased significantly as a result of an increase in the soil pH and the formation of metal hydroxides. COSP was more effective in immobilizing Cd and Pb in the contaminated soil than NOSP. Overall, the results of this study suggest that oyster shell waste can be recycled into an effective soil ameliorant.

The impact of CO2 on shallow groundwater chemistry: observations at a natural analog site and implications for carbon sequestration

Abstract: In a natural analog study of risks associated with carbon sequestration, impacts of CO2 on shallow groundwater quality have been measured in a sandstone aquifer in New Mexico, USA. Despite relatively high levels of dissolved CO2, originating from depth and producing geysering at one well, pH depression and consequent trace element mobility are relatively minor effects due to the buffering capacity of the aquifer. However, local contamination due to influx of brackish waters in a subset of wells is significant. Geochemical modeling of major ion concentrations suggests that high alkalinity and carbonate mineral dissolution buffers pH changes due to CO2 influx. Analysis of trends in dissolved trace elements, chloride, and CO2 reveal no evidence of in situ trace element mobilization. There is clear evidence, however, that As, U, and Pb are locally co-transported into the aquifer with CO2-rich brackish water. This study illustrates the role that local geochemical conditions will play in determining the effectiveness of monitoring strategies for CO2 leakage. For example, if buffering is significant, pH monitoring may not effectively detect CO2 leakage. This study also highlights potential complications that CO2 carrier fluids, such as brackish waters, pose in monitoring impacts of geologic sequestration.

Landslide susceptibility mapping for Ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis

Abstract: This paper presents the results of geographical information system (GIS)-based landslide susceptibility mapping in Ayvalik, western Turkey using multi-criteria decision analysis. The methodology followed in the study includes data production, standardization, and analysis stages. A landslide inventory of the study area was compiled from aerial photographs, satellite image interpretations, and detailed field surveys. In total, 45 landslides were recorded and mapped. The areal extent of the landslides is 1.75 km2. The identified landslides are mostly shallow-seated, and generally exhibit progressive character. They are mainly classified as rotational, planar, and toppling failures. In all, 51, 45, and 4% of the landslides mapped are rotational, planar, and toppling types, respectively. Morphological, geological, and land-use data were produced using existing topographical and relevant thematic maps in a GIS framework. The considered landslide-conditioning parameters were slope gradient, slope aspect, lithology, weathering state of the rocks, stream power index, topographical wetness index, distance from drainage, lineament density, and land-cover and vegetation density. These landslide parameters were standardized in a common data scale by fuzzy membership functions. Then, the degree to which each parameter contributed to landslides was determined using the analytical hierarchy process method, and the weight values of these parameters were calculated. The weight values obtained were assigned to the corresponding parameters, and then the weighted parameters were combined to produce a landslide susceptibility map. The results obtained from the susceptibility map were evaluated with the landslide location data to assess the reliability of the map. Based on the findings obtained in this study, it was found that 5.19% of the total area was prone to landsliding due to the existence of highly and completely weathered lithologic units and due to the adverse effects of topography and improper land use.

The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability and artificial neural networks

Abstract: This study presented herein compares the effect of the sampling strategies by means of landslide inventory on the landslide susceptibility mapping. The conditional probability (CP) and artificial neural networks (ANN) models were applied in Sebinkarahisar (Giresun–Turkey). Digital elevation model was first constructed using a geographical information system software and parameter maps affecting the slope stability such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index, stream power index and normalized difference vegetation index were considered. In the last stage of the analyses, landslide susceptibility maps were produced applying different sampling strategies such as; scarp, seed cell and point. The maps elaborated were then compared by means of their validations. Scarp sampling strategy gave the best results than the point, whereas the scarp and seed cell methods can be evaluated relatively similar. Comparison of the landslide susceptibility maps with known landslide locations indicated that the higher accuracy was obtained for ANN model using the scarp sampling strategy. The results obtained in this study also showed that the CP model can be used as a simple tool in assessment of the landslide susceptibility, because input process, calculations and output process are very simple and can be readily understood.

Hydrochemical characteristics and quality assessment of shallow groundwater in a coastal area of Southwest Bangladesh

Abstract: In this study, the hydrochemical characteristics of shallow groundwater in a coastal region (Khulna) of southwest Bangladesh have been evaluated based on different indices for drinking and irrigation uses. Water samples were collected from 26 boreholes and analyzed for major cations and anions. Other physico-chemical parameters like pH, electrical conductivity (EC), and total dissolved solids were also measured. Most groundwater is slightly alkaline and largely varies in chemical composition, e.g. EC ranges from 962 to 9,370 μs/cm. The abundance of the major ions is as follows: Na+ > Ca2+ > Mg2+ > K+ = Cl− > HCO3 − > SO4 2− > NO3 −. Interpretation of analytical data shows two major hydrochemical facies (Na+–K+–Cl−–SO4 2− and Na+–K+–HCO3 −) in the study area. Salinity, total hardness, and sodium percentage (Na%) indicate that most of the groundwater samples are not suitable for irrigation as well as for domestic purposes and far from drinking water standard. Results suggest that the brackish nature in most of the groundwaters is due to the seawater influence and hydrogeochemical processes.

A shallow subsurface controlled release facility in Bozeman, Montana, USA, for testing near surface CO2 detection techniques and transport models

Abstract: A controlled field pilot has been developed in Bozeman, Montana, USA, to study near surface CO2 transport and detection technologies. A slotted horizontal well divided into six zones was installed in the shallow subsurface. The scale and CO2 release rates were chosen to be relevant to developing monitoring strategies for geological carbon storage. The field site was characterized before injection, and CO2 transport and concentrations in saturated soil and the vadose zone were modeled. Controlled releases of CO2 from the horizontal well were performed in the summers of 2007 and 2008, and collaborators from six national labs, three universities, and the U.S. Geological Survey investigated movement of CO2 through the soil, water, plants, and air with a wide range of near surface detection techniques. An overview of these results will be presented.

Controlling factors of loess landslides in western China

Abstract: Based on detailed field data from recent geo-hazards surveys in the Loess Plateau region of western China, this study analyzes the key factors that control loess landslides. The evolution phase of river valleys, the geological structure of slopes and the geometry of slopes are all found to play a role in determining the occurrence, distribution and other characteristics of loess landslides. Groundwater and vegetation also contribute to their formation. A combination of human engineering activities and precipitation events are the principal triggering factors for the instability of loess slopes.

Assessment of channel dynamics, in-stream structures and post-project channel adjustments in North Carolina and its implications to effective stream restoration

Abstract: Site assessment and monitoring data were analyzed for 26 stream restoration projects in North Carolina where the channel was reconfigured. Post-project changes in channel capacity were highly variable from site to site, but more than 60% of the projects underwent, on average at a given site, at least a 20% change in channel capacity. An analysis of site and basin geomorphology revealed that large post-construction adjustments were associated with highly dynamic stream channels characterized by a combination of high sediment transport capacity, large sediment supply, and/or easily eroded bank materials. In-stream structures along dynamic, reconfigured channels also exhibited high incidences of damage. Thus, the design and construction of channels in a state of equilibrium, which do not exhibit excessive erosion or deposition along highly dynamic rivers is currently problematic. In light of these findings, a conceptual framework based on geomorphic parameters is put forth to assess the likelihood of project success early in the design process to (1) eliminate high risk sites from consideration of channel reconfiguration and (2) improve upon the implemented management strategies that are ultimately used. It is also argued that where space permits an enhanced natural channel, adjustment approach is likely to be more effective than projects based on natural channel design.

Pedo and biogeochemical studies of mafic and ultramfic rocks in the Mingora and Kabal areas, Swat, Pakistan

Abstract: This study highlights the heavy metals (HMs) distribution in soils and their uptake by wild plants grown in the soils derived from the mafic and ultramafic terrains. Plant and soil samples were analyzed for Cu, Pb, Zn, Cr, Ni and Cd using atomic absorption spectrophotometer. The data indicate that almost all the HMs in the soil samples collected from the study area exceeded the reference and normal agricultural soils. Greater variability was noticed in the uptake of HMs by various plants grown on the studied soils. High concentrations of Cu and Zn in Cannabis sativa L. (seft hemp), Pb in Ailanthus altissima (Mill.) (Ailanto), Ni and Cr in Indigofrra gerardiana Wall. ex Baker (sage), and Saccharum griffihii Munro ex Boiss. (plume grass) were noticed among the studied plants. The multifold enrichments of Cr and Ni in the Indigofrra gerardiana and Saccharum griffihii as compared to the other plants of the study area suggested that these plants have the ability to uptake and translocate high concentrations of Cr and Ni. The excessive concentrations of Cr and Ni in these plants can be used for mineral prospecting but their main concern could be of serious environmental problems and health risks in the inhabitants of the study areas.

Analysis of Baishuihe landslide influenced by the effects of reservoir water and rainfall

Abstract: Since the impoundment of the Three Gorges Reservoir in June 2003, a number of new landslides have occurred and existing landslides have been made worse. The 1,260 × 104 m3 Baishuihe landslide, located at 56 km west of the Three Gorges Dam, began to deform more noticeably after the first impoundment in early July 2003. The sliding of the two blocks comprising the landslide, one an active block and the other a relatively stable block, became apparent after approximately 5 years of monitoring. Field recordings show that the landslide displacement is affected by the combined effects of the rainfall and water level in the reservoir. These effects have been investigated in the present paper, including the deformation characteristics (movement pattern, direction, displacement and velocity) earmarking the temporal evolution of the active block. Based on a practical creep model of a large rock slide, alert velocity thresholds for pre-alert, alert and emergency phases have been computed corresponding to the imminence of failure. The alert velocity thresholds are being proposed to be included as a part of an early-warning system of an emergency plan drawn up to minimize the adverse impact in the event of landslide failure. The emergency plan is intended to be implemented as a risk management tool by the relevant authorities of the Three Gorges Reservoir in the near future.

Groundwater vulnerability and risk mapping of the Hajeb-jelma aquifer (Central Tunisia) using a GIS-based DRASTIC model

Abstract: The aim of this study is to elaborate a synthetic document for the assessment of groundwater vulnerability to pollution in the Hajeb-Jelma aquifer. The specific object is to incorporate the Geographical Information System (GIS) to generate groundwater vulnerability and risk maps with DRASTIC model. Indeed, GIS could help to make the results of a complicated model more clear through visual representation, providing an applicable tool for decision makers. The vulnerability map of Hajeb-Jelma watershed shows three classes: moderate, high and very high depending on the intrinsic properties. The risk map shows a very high risk dependant on hydrogeological characteristics, land use and human impacts in major part of the Hajeb-Jelma region. These maps could serve as a scientific basis for sustainable land use planning and groundwater management in the Hajeb-Jelma region.

Geochemistry of fluoride rich groundwater in Kolar and Tumkur Districts of Karnataka

Abstract: Groundwater is a significant water resource in India for domestic, irrigation, and industrial needs. By far the most serious natural groundwater-quality problem in India, in terms of public health, derives from high fluoride, arsenic, and iron concentrations. Hydrogeochemical investigation of fluoride contaminated groundwater samples from Kolar and Tumkur Districts in Karnataka are undertaken to understand the quality and potability of groundwater from the study area, the level of fluoride contamination, the origin and geochemical mechanisms driving the fluoride enrichment. Majority of the groundwater samples did not meet the potable water criteria as they contained excess (>1.5 mg/L) fluoride, dissolved salts (>500 mg/L) and total hardness (75-924 mg/L). Hydrogeochemical facies of the groundwater samples suggest that rock weathering and evaporation-crystallization control the groundwater composition in the study area with 50-67% of samples belonging to the Ca-HCO3 type and the remaining falling into the mixed Ca-Na-HCO3 or Ca-Mg-Cl type. The saturation index values indicated that the groundwater in the study area is oversaturated with respect to calcite and under-saturated with respect to fluorite. The deficiency of calcium ion concentration in the groundwater from calcite precipitation favors fluorite dissolution leading to excess fluoride concentration.

Assessment of effects of heavy metals combined pollution on soil enzyme activities and microbial community structure: modified ecological dose–response model and PCR-RAPD

Abstract: A laboratory study was conducted to evaluate the response of soil enzyme activities (namely dehydrogenase, phosphatase and urease) to different levels of trace element pollution in soil representative area. The improved ecological dose model and random-amplified polymorphic DNA (RAPD) were used to assess soil health. The 50% ecological dose (ED50) values modified by toxicant coefficient were calculated from the best-fit model, and determination values from the regression analysis for the three enzyme activities were studied after the incubation periods. The results showed that the elevated heavy metal concentration negatively affects the total population size of bacteria and actinomycetes and enzymatic activity; dehydrogenase (ED50 = 777) was the most sensitive soil enzyme, whereas urease activity (ED50 = 2,857) showed the lowest inhibition; combined pollution or elevated toxicant level would increase disappearing RAPD bands, and the number of denoting polymorphic bands was greater in combined polluted soils. All three mathematical modified models satisfactorily described the inhibition of soil enzyme activities caused by Cd and Pb, by giving the best fit.

Adsorption of antimony(V) on kaolinite as a function of pH, ionic strength and humic acid

Abstract: The present work investigated the adsorption and mobility (desorption) of Sb(V) on kaolinite using batch experiments. The adsorption of Sb(V) on kaolinite was studied as a function of contact time, pH, ionic strength, humic acid (HA), initial Sb(V) concentration and temperature. Kinetic studies suggest that the equilibrium is achieved within 24 h. The adsorption of Sb(V) was strongly affected by changes in I at low ionic strength and unaffected at high ionic strength. The adsorption is weakly dependent on the presence of humic acid, but is strongly dependent on pH. Within the range tested, the optimal pH for Sb(V) adsorption is 3.6, and close to 75% removal can be achieved. Desorption is dependent on the original suspension pH. The addition sequence of Sb(V)/HA do not influence the adsorption of Sb(V) on kaolinite. The adsorption data fit both the Freundlich and Langmuir isotherm. The thermodynamic parameters (ΔH 0, ΔS 0 and ΔG 0) were calculated from the temperature dependence, and the results suggest the endothermic and spontaneous nature of the process.

Evaluation of hydrogeochemical processes in arsenic-contaminated alluvial aquifers in parts of Mid-Ganga Basin, Bihar, Eastern India

Abstract: The study region covers 1,650 km2 of the Mid-Ganga Basin in Bihar, experiencing intensive groundwater draft. The area forms a part of the Gangetic alluvial plain where high incidence of arsenic groundwater contamination (>50 μg/l) has recently been detected. Seventy-seven groundwater samples have been collected and analysed for major ions, iron and arsenic. Arsenic contamination (max 620 μg/l) is confined in hand pump zones (15–35 m) within the newer alluvium deposited during Middle Holocene to Recent age. The older alluvial aquifers are arsenic-safe and recorded maximum concentration as 9 μg/l. Out of 12 hydrochemical facies identified, four have been found arsenic-affected: Ca–HCO3, Mg–HCO3, Ca–Mg–HCO3 and Mg–Ca–HCO3. The geochemical evolution of groundwater, as investigated by graphical interpretation and statistical techniques (correlation, principal component analysis) revealed that dissolution of detrital calcite, dolomite and infiltration of rainwater are the major processes shaping the groundwater chemistry in the newer alluvium. Arsenic and iron showed strong positive correlation. Rainfall infiltration, carrying organic matter from recently accumulated biomass from this flood-prone belt, plays a critical role in releasing arsenic and iron present in the sediments. Geochemical evolution of groundwater in older alluvium follows a different path, where cation-exchange has been identified as a significant process.

Contamination and potential mobility assessment of heavy metals in urban soils of Hangzhou, China: relationship with different land uses

Abstract: Concentration and distribution of heavy metals (Cd, Cu, Pb and Zn) in urban soils of Hangzhou, China, were measured based on different land uses. The contamination degree of heavy metals was assessed on the basis of pollution index (PI), integrated pollution index (IPI) and geoaccumulation index (Igeo). The 0.1 mol l−1 HCl extraction procedure and gastric juice simulation test (GJST) were used to evaluate the potential mobility and environmental risk of heavy metals in urban soils. The average concentration of Cd, Cu, Pb and Zn in urban soils was measured at 1.2 (with a range of 0.7–4.6), 52.0 (7.4–177.3), 88.2 (15.0–492.1) and 206.9 (19.3–1,249.2) mg kg−1, respectively. The degree of contamination increased in the order of industrial area (IA) > roadside (RS) > residential and commercial areas (RC) > public park and green areas (PG). The PIs for heavy metals indicated that there is a considerable Cd, Cu, Pb and Zn pollution, which originate from traffic and industrial activities. The IPI of these four metals ranged from 1.6 to 11.8 with a mean of 3.5, with the highest IPI in the industrial area. The assessment results of Igeo also supported that urban soil were moderately contaminated with Cd and to a lesser extent also with Cu, Pb and Zn. The IP and Igeo values reveal the pollution degree of heavy metal was the order of Cd > Pb > Zn ≈ Cu. It was shown that mobility and bioavailability of the heavy metals in urban soils increased in the order of Cd > Cu > Zn ≈ Pb. Owing to high mobility of Cd and Cu in the urban soils, further investigations are needed to understand their effect on the urban environment and human health. It is concluded that industrial activities and emissions from vehicles may be the major source of heavy metals in urban contamination. Results of this study present a rough guide about the distribution and potential environmental and health risk of heavy metals in the urban soils.

An ERDAS image processing method for retrieving LST and describing urban heat evolution: a case study in the Pearl River Delta Region in South China

Abstract: A spatial-temporal model with Model Maker tool is designed to retrieve Land Surface Temperature (LST) and to describe the changes of urban heat island, as well as urban development Spectral Radiance, Brightness Temperature, NDVI, and Emissivity are first calculated from TM and ETM+, which are then used to compute LST by using Qin et al’s mono-window algorithm The LST is classified based on normalized statistical method, and the normalized heat images are computed between different times Therefore, the urban heat changes can be shown in the map clearly and directly through an urban heat conversion matrix Such a model has been applied in this study to obtain the urban heat conversion matrix of South China from 1990 to 2000 The results indicate that the LST increased areas mainly locate along the major roads in the eastern bank of the Pearl River, which is a result of speedy urban expansion and need to be noticed in the future

Mobility and ecological risk assessment of heavy metals in surface sediments of Xiamen Bay and its adjacent areas, China

Abstract: Xiamen Bay (XMB) has received substantial loadings of pollutants from industrial and municipal wastewater discharged since the 1980s. To assess ecological risks and the current spatial changes of metal contaminants in bottom surface sediments, 12 samples were collected. Samples were subjected to a total digestion technique and analyzed by ICP–OES for Cu, Pb, Zn, Cr, and Cd, and by AFS for Hg and As. Among these metals, Zn had the highest values (68–268 mg kg−1), followed by Pb (27–71 mg kg−1), and lower concentrations were found for Cd (42–1,913 μg kg−1) and Hg (0–442 μg kg−1). In comparison with the average crustal abundance values, the results indicated that nearly half of the sediment samples of XMB and its adjacent areas were contaminated by Cd, Pb, Zn, and As. Furthermore, based on the modified BCR sequential extraction procedure, the chemical speciation of heavy metals (Cd, Cr, Cu, Pb, Zn, Hg, and As) in selected sediment samples were evaluated in this study. Data from BCR sequential extractions indicated that Cd posed a medium ecological risk, whereas, Cr posed low risk since its exchangeable and carbonate fractions were below 4%, and the mobility of heavy metals in XMB decreased in the order Cd > Pb > Cu > Zn > Hg > As > Cr. By applying mean effects range median quotients (mERMQ), the results showed that Yuandang Lagoon with mERMQ value >0.5 would be expected to have the greatest potential toxic risk in amphipod within XMB and its adjacent areas.

Using hyperspectral plant signatures for CO2 leak detection during the 2008 ZERT CO2 sequestration field experiment in Bozeman, Montana

Abstract: Hyperspectral plant signatures can be used as a short-term, as well as long-term (100-year timescale) monitoring technique to verify that CO2 sequestration fields have not been compromised. An influx of CO2 gas into the soil can stress vegetation, which causes changes in the visible to near-infrared reflectance spectral signature of the vegetation. For 29 days, beginning on July 9, 2008, pure carbon dioxide gas was released through a 100-m long horizontal injection well, at a flow rate of 300 kg day−1. Spectral signatures were recorded almost daily from an unmown patch of plants over the injection with a “FieldSpec Pro” spectrometer by Analytical Spectral Devices, Inc. Measurements were taken both inside and outside of the CO2 leak zone to normalize observations for other environmental factors affecting the plants. Four to five days after the injection began, stress was observed in the spectral signatures of plants within 1 m of the well. After approximately 10 days, moderate to high amounts of stress were measured out to 2.5 m from the well. This spatial distribution corresponded to areas of high CO2 flux from the injection. Airborne hyperspectral imagery, acquired by Resonon, Inc. of Bozeman, MT using their hyperspectral camera, also showed the same pattern of plant stress. Spectral signatures of the plants were also compared to the CO2 concentrations in the soil, which indicated that the lower limit of soil CO2 needed to stress vegetation is between 4 and 8% by volume.

Soil moisture dynamics under different land uses on karst hillslope in northwest Guangxi, China

Abstract: Temporal and spatial dynamics of soil moisture are little known on karst hillslope with shallow soil in subtropical region. The objectives of this paper were (1) to investigate the temporal dynamics of soil moisture at depth of 0–10 cm under different land uses; and (2) to understand the relationship between mean and coefficient of variation (CV) of moisture contents on karst hillslope in northwest Guangxi, China. Soil moisture contents had a moderate variation (CV 17.5–30.3%) over an 8-month period and they had a significant difference among different land uses at the 0.01 level with a decreasing order: native scrubland > abandoned cropland and sloping cropland > economic forestland. There were higher mean and lower CV of moisture contents in rainy season than those in drought season. Mean and CV of moisture contents had a significant negative linear relationship except in abandoned cropland with higher soil and vegetation heterogeneity. This suggested that spatial variability of soil moisture within sampling sites would decrease when soils were wet and increase when soils were arid. Compared with rainy season, more soil samples may be needed and the interval for sampling should be shortened in drought season. Such information provided some insights to better understand the dynamics and variability of soil moisture at a larger scale in karst region of southwest China.

Validation of an artificial neural network model for landslide susceptibility mapping

Abstract: The aim of this study was to validate an artificial neural network model at Youngin, Janghung, and Boeun, Korea, using the geographic information system (GIS). The factors that influence landslide occurrence, such as the slope, aspect, curvature, and geomorphology of topography, the type, material, drainage, and effective thickness of soil, the type, diameter, age, and density of forest, distance from lineament, and land cover were either calculated or extracted from the spatial database and Landsat TM satellite images. Landslide susceptibility was analyzed using the landslide occurrence factors provided by the artificial neural network model. The landslide susceptibility analysis results were validated and cross-validated using the landslide locations as study areas. For this purpose, weights for each study area were calculated by the artificial neural network model. Among the nine cases, the best accuracy (81.36%) was obtained in the case of the Boeun-based Janghung weight, whereas the Janghung-based Youngin weight showed the worst accuracy (71.72%).

Application of a fuzzy operator to susceptibility estimations of coal mine subsidence in Taebaek City, Korea

Abstract: Quantitative determination of locations vulnerable to ground subsidence at mining regions is necessary for effective prevention. In this paper, a method of constructing subsidence susceptibility maps based on fuzzy relations is proposed and tested at an abandoned underground coal mine in Korea. An advantage of fuzzy combination operators over other methods is that the operation is mathematically and logically easy to understand and its implementation to GIS software is simple and straightforward. A certainty factor analysis was used for estimating the relative weight of eight major factors influencing ground subsidence. The relative weight of each factor was then converted into a fuzzy membership value and integrated as a subsidence hazard index using fuzzy combination operators, which produced coal mine subsidence susceptibility maps. The susceptibility maps were compared with the reported ground subsidence areas, and the results showed high accuracy between our prediction and the actual subsidence. Based on the root mean square error and accuracy in terms of success rates, fuzzy γ-operator with a low γ value and fuzzy algebraic product operator, specifically, are useful for ground subsidence prediction. Comparing the results of a fuzzy γ-operator and a conventional logistic regression model, the performance of the fuzzy approach is comparative to that of a logistic regression model with improved computational. A field survey done in the area supported the method’s reliability. A combination of certainty factor analysis and fuzzy relations with a GIS is an effective method to determine locations vulnerable to coal mine subsidence.