Spatial Prediction of Ground Subsidence Susceptibility Using an Artificial Neural Network

Ground subsidence in abandoned underground coal mine areas can result in loss of life and property. We analyzed ground subsidence susceptibility (GSS) around abandoned coal mines in Jeong-am, Gangwon-do, South Korea, using artificial neural network (ANN) and geographic information system approaches. Spatial data of subsidence area, topography, and geology, as well as various ground-engineering data, were collected and used to create a raster database of relevant factors for a GSS map. Eight major factors causing ground subsidence were extracted from the existing ground subsidence area: slope, depth of coal mine, distance from pit, groundwater depth, rock-mass rating, distance from fault, geology, and land use. Areas of ground subsidence were randomly divided into a training set to analyze GSS using the ANN and a test set to validate the predicted GSS map. Weights of each factor’s relative importance were determined by the back-propagation training algorithms and applied to the input factor. The GSS was then calculated using the weights, and GSS maps were created. The process was repeated ten times to check the stability of analysis model using a different training data set. The map was validated using area-under-the-curve analysis with the ground subsidence areas that had not been used to train the model. The validation showed prediction accuracies between 94.84 and 95.98%, representing overall satisfactory agreement. Among the input factors, “distance from fault” had the highest average weight (i.e., 1.5477), indicating that this factor was most important. The generated maps can be used to estimate hazards to people, property, and existing infrastructure, such as the transportation network, and as part of land-use and infrastructure planning.     

Groundwater Vulnerability Assessment for Organic Compounds: Fuzzy Multicriteria Approach for Mexico City

This study was based on a groundwater vulnerability assessment approach implemented for the Mexico City Metropolitan Area (MCMA). The approach is based on a fuzzy multicriteria procedure integrated in a geographic information system. The approach combined the potential contaminant sources with the permeability of geological materials. Initially, contaminant sources were ranked by experts through the Analytic Hierarchy Process. An aggregated contaminant sources map layer was obtained through the simple additive weighting method, using a scalar multiplication of criteria weights and binary maps showing the location of each source. A permeability map layer was obtained through the reclassification of a geology map using the respective hydraulic conductivity values, followed by a linear normalization of these values against a compatible scale. A fuzzy logic procedure was then applied to transform and combine the two map layers, resulting in a groundwater vulnerability map layer of five classes: very low, low, moderate, high, and very high. Results provided a more coherent assessment of the policy-making priorities considered when discussing the vulnerability of groundwater to organic compounds. The very high and high vulnerability areas covered a relatively small area (71 km² or 1.5% of the total study area), allowing the identification of the more critical locations. The advantage of a fuzzy logic procedure is that it enables the best possible use to be made of the information available regarding groundwater vulnerability in the MCMA.     

Artificial Groundwater Recharge Zones Mapping Using Remote Sensing and GIS: A Case Study in Indian Punjab

Artificial groundwater recharge plays a vital role in sustainable management of groundwater resources. The present study was carried out to identify the artificial groundwater recharge zones in Bist Doab basin of Indian Punjab using remote sensing and geographical information system (GIS) for augmenting groundwater resources. The study area has been facing severe water scarcity due to intensive agriculture for the past few years. The thematic layers considered in the present study are: geomorphology (2004), geology (2004), land use/land cover (2008), drainage density, slope, soil texture (2000), aquifer transmissivity, and specific yield. Different themes and related features were assigned proper weights based on their relative contribution to groundwater recharge. Normalized weights were computed using the Saaty’s analytic hierarchy process. Thematic layers were integrated in ArcGIS for delineation of artificial groundwater recharge zones. The recharge map thus obtained was divided into four zones (poor, moderate, good, and very good) based on their influence to groundwater recharge. Results indicate that 15, 18, 37, and 30 % of the study area falls under “poor,” “moderate,” “good,” and “very good” groundwater recharge zones, respectively. The highest recharge potential area is located towards western and parts of middle region because of high infiltration rates caused due to the distribution of flood plains, alluvial plain, and agricultural land. The least effective recharge potential is in the eastern and middle parts of the study area due to low infiltration rate. The results of the study can be used to formulate an efficient groundwater management plan for sustainable utilization of limited groundwater resources.     

Groundwater vulnerability assessment for the Banyas Catchment of the Syrian coastal area using GIS and the RISKE method

Vulnerability assessment to delineate areas that are more susceptible to contamination from anthropogenic sources has become an important element for sensible resource management and landuse planning. This contribution aims at estimating aquifer vulnerability by applying the RISKE model in Banyas Catchment Area (BCA), Tartous Prefecture, west Syria. An additional objective is to demonstrate the combined use of the RISKE model and a geographical information system (GIS) as an effective method for groundwater pollution risk assessment. The RISKE model uses five environmental parameters (Rock of aquifer media, Infiltration, Soil media, Karst, and Epikarst) to characterize the hydro-geological setting and evaluate aquifer vulnerability. The elevated eastern and low western part of the study area was dominated by high vulnerability classes, while the middle part was characterized by moderate vulnerability classes. Based on the vulnerability analysis, it was found that 2% and 39% of BCA is under low and high vulnerability to groundwater contamination, respectively, while more than 52% and 5% of the area of BCA can be designated as an area of moderate and very high vulnerability to groundwater contamination, respectively. The GIS technique has provided an efficient environment for analyses and high capabilities of handling a large amount of spatial data.     

A GEOGRAPHIC INFORMATION SYSTEM PROCEDURE TO QUANTIFY DRAINAGE-BASIN CHARACTERISTICS1

ABSTRACT: The Basin Characteristics System (BCS) has been developed to quantify characteristics of a drainage basin. The first of four main BCS processing steps creates four geographic information system (GIS) digital maps representing the drainage divide, the drainage network, elevation contours, and the basin length. The drainage divide and basin length are manually digitized from 1:250,000-scale topographic maps. The drainage network is extracted using GIS software from 1:100,000-scale digital line graph data. The elevation contours are generated using GIS software from 1:250,000-scale digital elevation model data. The second and third steps use software developed to assign attributes to specific features in three of the four digital maps and analyze the four maps to quantify 24 morphometric basin characteristics. The fourth step quantifies two climatic characteristics from digitized State maps of precipitation data. Compared to manual methods of measurement, the BCS provides a reduction in the time required to quantify the 26 basin characteristics. Comparison tests indicate the BCS measurements are not significantly different from manual topographic-map measurements for 11 of 12 primary drainage-basin characteristics. Tests indicate the BCS significantly underestimates basin slope. Comparison-measurement differences for basin slope, main channel slope, and basin relief appear to be due to limitations in the digital elevation model data.     

Topographic Effects on Soil Organic Carbon in Louisiana Watersheds

Terrestrial carbon storage is influenced by a number of environmental factors, among which topographic and geomorphological features are of special significance. This study was designed to examine the relationships of soil organic carbon (SOC) density to various terrain parameters and watershed characteristics across Louisiana, USA. A polygon data set of 484 watersheds and 12 river drainage basins for Louisiana was used to form the landscape units. SOC densities were calculated for each soil map unit using the State Soil Geographic (STATSGO) database. Average drainage densities and average slopes at watershed and basin scales were quantified with the 1:24 K Digital Elevation Models (DEM) data, and the Louisiana hydrographic water features. Correlation and regression analyses were performed to determine relationships among drainage density, slope, elevation, and SOC. The study found an average watershed drainage density of 1.6 km/km² and an average watershed slope of 2.9 degrees in Louisiana. The results revealed that SOC density at both watershed and basin scales was closely related to drainage density, slope, and elevation. SOC density was positively correlated with watershed drainage density, but negatively correlated with watershed slope gradient and elevation. Regression models were developed for predicting SOC density at watershed and basin scales, obtaining regression coefficients (r ²) ranging from 0.43 to 0.83. The study showed that estimation of SOC at watershed and drainage basin scales combining DEM data can be a feasible approach to improve the understanding of the relationships among SOC, topographic, and geomorphological features.     

NETWORK AND SUBWATERSHED PARAMETERS EXTRACTED FROM DIGITAL ELEVATION MODELS: THE BILLS CREEK EXPERIENCE1

ABSTRACT: An automated extraction of channel network and sub-watershed characteristics from digital elevation models (DEM) is performed by model DEDNM. This model can process DEM data of limited vertical resolution representing low relief terrain. Such representations often include ill-defined drainage boundaries and indeterminate flow paths. The application watershed is an 84 km² low relief watershed in southwestern Oklahoma. The standard for validation is the network and subwatershed parameters defined by the blue line method on USGS 7.5–minute topographic maps. Evaluation of the generated and validation networks by visual comparisons shows a high degree of correlation. Comparison of selected network parameters (channel length, slope, drainage density, etc.) and of drainage network composition (bifurcation, length, slope, and area ratios) shows that, on the average, the generated parameters are within 5 percent of those derived from the validation network. The largest discrepancies were found for the channel slope values. The results of this application demonstrate that DEDNM effectively addresses network definition problems often encountered in low relief terrain and that it can generate accurate network and subwatershed parameters under those conditions.     

Spatial Variability of Groundwater Depth and Quality Parameters in the National Capital Territory of Delhi

The groundwater quantity and quality scenario is of much concern in the National Capital Territory of Delhi, India, which necessitates an investigation to envisage the extent of spatial variability of groundwater depth and pollutant concentration levels in this region. Therefore, in this study, an effort was made to generate the spatial variability map of groundwater depth and quality parameters (viz. chloride, electrical conductivity, fluoride, magnesium, and nitrate). Ordinary kriging was used to analyze the spatial variability of groundwater depth and quality parameters, whereas indicator kriging was used to analyze groundwater quality parameters equal to or greater than the pollution threshold values. It was observed that the semivariogram parameters fitted well in the exponential model for water depth and in the spherical model for water quality parameters. The generated spatial variability maps indicated that in 43% of the study area, groundwater depth was within 20 m. The salinity level was higher than 2.5 dS m⁻¹ in 69% of the study area and the nitrate concentration exceeded 45 mg l⁻¹ in 36% of the area. The probability maps showed that about 24% of the area had the highest probability (0.8–1.0) of exceedence of the threshold electrical conductivity value and an area of 2% exhibited the highest probability of exceedence of the threshold value of nitrate concentration in the groundwater. The generated spatial variability and probability maps will assist water resource managers and policymakers in development of guidelines in judicious management of groundwater resources for agricultural and drinking purposes in the study area.     

SURFACE AREA CORRECTIONS APPLIED TO A RESOURCE MAP1

ABSTRACT: Generally a difference exists between the horizontal planar area of a watershed as measured on a map and the actual surface area. A technique is presented, utilizing a topographic map, for computing the difference in the two areas as well as yielding a prediction of the actual surface area. Spatial variations in the magnitude of the difference in the two areas for small local sites over the watershed are displayed on computer generated maps. The technique is also used to adjust various inventory variables on maps, such as vegetation density, to reflect actual surface coverage. This allows estimates to be made of the difference in using corrected versus uncorrected area related parameters in mathematical functions describing processes occurring in the atmosphere-surface boundary layer.     

STATISTICAL LOW FLOW ESTIMATION USING GIS ANALYSIS IN HUMID MONTANE REGIONS IN PUERTO RICO1

ABSTRACT: Statistical analysis of watershed parameters derived using a Geographical Information system (GIS) was done to develop equations for estimating the 7d–10yr, 30d–10yr, and 7d–2yr low flow for watersheds in humid montane regions of Puerto Rico. Digital elevation models and land use, geology, soils, and stream network coverages were used to evaluate 21 geomorphic, 10 stream channel, 9 relief, 7 geology, 4 climate, and 2 soil parameters for each watershed. To assess which parameters should be used for further investigation, a correlation analysis was used to determine the independence and collinearity among these parameters and their relationship with low flows. Multiple regression analyses using the selected parameters were then performed to develop the statistical models of low flows. The final models were selected in the basis of the Mallow Cp statistic, the adjusted R², the Press statistic, the degree of collinearity, and an analysis of the residuals. In the final models, drainage density, the ratio of length of tributaries to the length of the main channel, the percent of drainage area with northeast aspect, and the average weighted slope of the drainage were the most significant parameters. The final models had adjusted standard errors of 58.7 percent, 59.2 percent, and 48.6 percent for the 7d–10yr, 30d–10yr, and 7d–2yr low flows respectively. For comparison, the best model based on watershed parameters that can be easily measured without a GIS had an adjusted standard error of 82.8 percent.     

STREAM-CHANNEL INCISION FOLLOWING DRAINAGE-BASIN URBANIZATION1

ABSTRACT: Urbanization of a drainage basin results in pervasive hydrologic changes that in turn initiate long-term changes in stream channels. Increases in peak discharges and in durations of high flows result in either quasi-equilibrium channel expansion, where cross-section area increases in near-proportion to the discharge increase, or catastrophic channel incision, where changes occur far out of proportion to the discharge increases that initiated them. Field data and hydrologic modeling of rapidly urbanizing basins in King County, Washington, define conditions of flow, topography, geology, and channel roughness that identify streams susceptible to incision. Channel slope and geologic material are particularly critical; thus simple map overlays, nearly irrespective of contributing drainage area, provide a valuable planning tool for identification of susceptible terrain. Where such conditions exist, basal shear stress provides a quantifiable parameter for predicting likely problems, although knickpoints are typical in such settings and confound simple calculation of sediment-transport rates. Where urbanization proceeds in such areas, effective mitigation of the incision hazards requires a degree of stormwater control far in excess of standards typically applied to present development activity.     

川北高台原区废弃煤矿枯水期矿井涌水水化学特征及成因分析

对废弃煤矿矿井涌水的水化学特征及成因进行分析,可为保护矿区地下水环境提供理论支撑。基于地质背景,通过对比枯水季节川北高台原区废弃煤矿矿井涌水与背景泉点水化学指标,并采用聚类分析方法对矿井涌水中离子指标进行统计,进而对其特征及成因进行了研究。结果表明:地层中黄铁矿中硫元素氧化是矿井涌水水化学特征变化的开端,受研究区矿井涌水补给范围小,地下水短途径流等条件的控制,最终形成了铁质硫酸型水。低pH值的矿井涌水与围岩发生水岩反应,进一步改变其水化学特征,使其富集砷、镉、铜、锰、铅、硒、锌等微量元素。     

Tools for Groundwater Protection Planning: An Example from McHenry County, Illinois, USA

/ This paper presents an approach for producing aquifer sensitivity maps from three-dimensional geologic maps, called stack-unit maps. Stack-unit maps depict the succession of geologic materials to a given depth, and aquifer sensitivity maps interpret the successions according totheir ability to transmit potential contaminants. Using McHenry County, Illinois, as a case study, stack-unit maps and an aquifer sensitivity assessment were made to help land-use planners, public health officials, consultants, developers, and the public make informed decisions regarding land use. A map of aquifer sensitivity is important for planning because the county is one of the fastest growing counties in the nation, and highly vulnerable sand and gravel aquifers occur within 6 m of ground surface over 75% of its area. The aquifer sensitivity map can provide guidance to regulators seeking optimal protection of groundwater resources where these resources are particularly vulnerable. In addition, the map can be used to help officials direct waste-disposal and industrial facilities and other sensitive land-use practices to areas where the least damage is likely to occur, thereby reducing potential future liabilities. KEY WORDS: Geologic mapping; Groundwater; Aquifers; Aquifer sensitivity; Land-use planning     

A Gis-Based Assessment of Groundwater Suitability for Irrigation Purposes in Flat Areas of the Wet Pampa Plain, Argentina

The Pampa in Argentina is a large plain with a quite obvious dependence on agriculture, water availability and its quality. It is a sensitive environment due to weather changes and slope variations. Supplementary irrigation is a useful practice for compensating the production in the zone. However, potential negative impacts of this type of irrigation in salinization and sodification of soils are evident. Most conventional methodologies for assessing water irrigation quality have difficulties in their application in the region because they do not adjust to the defined assumptions for them. Consequently, a new GIS-based methodology integrating multiparametric data was proposed for evaluating and delineating groundwater suitability zones for irrigation purposes in flat areas. Hydrogeological surveys including water level measurements, groundwater samples for chemical analysis and electrical conductivity (EC) measurements were performed. The combination of EC, sodium adsorption ratio, residual sodium carbonate, slopes and hydraulic gradient parameters generated an irrigation water index (IWI). With the integration of the IWI 1 to 3 classes (categories of suitable waters for irrigation) and the aquifer thickness the restricted irrigation water index (RIWI) was obtained. The IWI's index application showed that 61.3?% of the area has "Very high" to "Moderate" potential for irrigation, while the 31.4?% of it has unsuitable waters. Approximately, 46?% of the tested area has high suitability for irrigation and moderate groundwater availability. This proposed methodology has advantages over traditional methods because it allows for better discrimination in homogeneous areas.     

Classification and spatial mapping of riparian habitat with applications toward management of streams impacted by nonpoint source pollution

Management of riparian habitats has been recognized for its importance in reducing instream effects of agricultural nonpoint source pollution. By serving as a buffer, well structured riparian habitats can reduce nonpoint source impacts by filtering surface runoff from field to stream. A system has been developed where key characteristics of riparian habitat, vegetation type, height, width, riparian and shoreline bank slope, and land use are classified as discrete categorical units. This classification system recognizes seven riparian vegetation types, which are determined by dominant plant type. Riparian and shoreline bank slope, in addition to riparian width and height, each consist of five categories. Classification by discrete units allows for ready digitizing of information for production of spatial maps using a geographic information system (GIS). The classification system was tested for field efficiency on Tom Beall Creek watershed, an agriculturally impacted third-order stream in the Clearwater River drainage, Nez Perce County, Idaho, USA. The classification system was simple to use during field applications and provided a good inventory of riparian habitat. After successful field tests, spatial maps were produced for each component using the Professional Map Analysis Package (pMAP), a GIS program. With pMAP, a map describing general riparian habitat condition was produced by combining the maps of components of riparian habitat, and the condition map was integrated with a map of soil erosion potential in order to determine areas along the stream that are susceptible to nonpoint source pollution inputs. Integration of spatial maps of riparian classification and watershed characteristics has great potential as a tool for aiding in making management decisions for mitigating off-site impacts of agricultural nonpoint source pollution.     

Life cycle assessment analysis of active and passive acid mine drainage treatment technologies

Acid mine drainage (AMD), resulting from open-cast coal mining, is currently one of the largest environmental challenges facing the mining industry. In this study, a life cycle assessment (LCA) was conducted to evaluate the environmental impacts associated with the construction, operation and maintenance of different AMD treatment options typically employed. LCA is a well-reported tool but is not documented for AMD treatment systems despite their ubiquitous implementation worldwide. This study conducted detailed LCA analysis for various passive and active AMD treatment approaches implemented or considered at a major coal mine in New Zealand using a comparative functional unit of kg acidity removed per day for each treatment option. Eight treatment scenarios were assessed including active limestone and hydrated lime treatments, and compared to passive treatments using limestone and waste materials such as mussel shells. Both midpoint and endpoint LCA impact categories were assessed. Generally, the active treatment scenarios demonstrated greater LCA impacts compared to an equivalent level of treatment for the passive treatment approaches. Lime slaking had the greatest LCA impacts, while passive treatment approaches incurred consistently less impacts except for one passive treatment with a purchased energy scenario. A 50% reduction in transportation distances resulted in the lowest LCA impacts for all scenarios. This study highlights the importance of evaluating the environmental and social impacts of AMD treatment for the mining industry.     

AUTOMATED EXTRACTION OF DRAINAGE NETWORK AND WATERSHED DATA FROM DIGITAL ELEVATION MODELS1

ABSTRACT: This paper discusses a computer program which extracts a number of watershed and drainage network properties directly from digital elevation models (DEM) to assist in the rapid parameterization of hydrologic runoff models. The program integrates new and established algorithms to address problems inherent in the analysis low-relief terrain from raster DEMs similar to those distributed by the U.S. Geological Survey for 7.5-minute quadrangles. The program delineates the drainage network from a DEM, and determines the Strahler order, total and direct drainage area, length, slope, and upstream and downstream coordinates of each channel link. It also identifies the subwatershed of each channel source and of the left and right bank of each channel link, and assigns a unique number to each network node. The node numbers are used to associate each subwatershed with the channel link to which it drains, and can be used to control flow routing in cascade hydrologic models. Program output includes tabular data and raster maps of the drainage network and subwatersheds. The raster maps are intended for import to a Geographical Information System where they can be registered to other data layers and used as templates to extract additional network and subwatershed information.     

Application of Likelihood Ratio and Logistic Regression Models to Landslide Susceptibility Mapping Using GIS

For landslide susceptibility mapping, this study applied and verified a Bayesian probability model, a likelihood ratio and statistical model, and logistic regression to Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite imagery and field surveys; and a spatial database was constructed from topographic maps, soil type, forest cover, geology and land cover. The factors that influence landslide occurrence, such as slope gradient, slope aspect, and curvature of topography, were calculated from the topographic database. Soil texture, material, drainage, and effective depth were extracted from the soil database, while forest type, diameter, and density were extracted from the forest database. Land cover was classified from Landsat TM satellite imagery using unsupervised classification. The likelihood ratio and logistic regression coefficient were overlaid to determine each factors rating for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared with known landslide locations. The logistic regression model had higher prediction accuracy than the likelihood ratio model. The method can be used to reduce hazards associated with landslides and to land cover planning. Note: This version was published online in June 2005 with the cover date of August 2004.     

EXTRACTION AND UTILIZATION OF SPACE ACQUIRED PHYSIOGRAPHIC DATA FOR WATER RESOURCES DEVELOPMENT1

ABSTRACT: ERTS-1 satellite imagery has been evaluated as a means of providing useful watershed physiography information. From these data physiographic parameters such as drainage basin area and shape, drainage density, stream length and sinuosity, and the percentage of a watershed occupied by major land use types were obtained in three study areas. The study areas were: (1) Southwestern Wisconsin; (2) Eastern Colorado; and (3) portions of the Middle Atlantic States Using ERTS-1 imagery at 1:250,000 and 1:100,000 scales it was found that drainage basin area and shape and stream sinuosity were comparable (within 10%) in all study areas to physiographic measurements derived from conventional topographic maps at the same scales Land use information can be usefully extracted for watersheds as small as 30 mi²(78 km²) in area. Improved drainage network and density information is obtained from ERTS-1 imagery in dissected areas such as Southwestern Wisconsin, but in heavily vegetated areas (Middle Atlantic States) or areas with little physical relief (Eastern Colorado) low order streams are difficult to detect and the derived drainage densities are significantly smaller than those obtained from standard maps. It is concluded that ERTS-1 imagery can be employed to advantage in mean annual runoff prediction techniques and in providing or maintaining land use information used in the calibration and operation of watershed models.     

An Approach for Recreation Suitability Analysis to Recreation Planning in Gölcük Nature Park

Gölcük Nature Park (GNP) is an area protected by law in Turkey. It is an important nature park with rich flora, fauna, geomorphologic forms, landscape features, and recreational potential in the region. However, GNP does not have a recreation management plan. The purpose of this study was to determine the actual natural, cultural, and visual resources of GNP, determine the most suitable recreational sites with multiple factors, evaluate the demands and tendencies of visitors, and suggest recreational activities and facilities for the most suitable sites of GNP. However, it was also conceived as leading to a recreational plan and design of GNP in the future and identifying the entire appropriate and current data of GNP with the creation of various maps. This study used multifactor analysis to determine the most suitable recreation sites of GNP. Used recreation factors were established including degree of slope, proximity to water resources, accessibility, elevation, vegetation, soil, climate, aspect, current cultural facilities, visual values, and some limiting factors in accordance with the characteristics of GNP. Weighting and suitability values of factors were determined by 30 local expert surveys. All obtained data were evaluated and integrated in the Geographical Information Systems base. Obtained maps were overlapped. Thus, recreational suitability zones map were created manually. However, the demands and behaviours from visitor surveys in GNP were focused on the most suitable recreation sites of the park. Finally, 10% of GNP was identified as the most suitable sites for recreational use. Various recreational facilities and activities (including picnicking, sports facilities and playgrounds, camping sites, walking paths, food and local outlets, etc.) were recommended for nine of the most suitable areas on the proposed recreational map.