Delineation of groundwater potential zones using remote sensing and GIS-based data-driven models

The rapid increase in human population has increased the groundwater resources demand for drinking, agricultural and industrial purposes. The main purpose of this study is to produce groundwater potential map (GPM) using weights-of-evidence (WOE) and evidential belief function (EBF) models based on geographic information system in the Azna Plain, Lorestan Province, Iran. A total number of 370 groundwater wells with discharge more than 10 m³s^?1were considered and out of them, 256 (70%) were randomly selected for training purpose, while the remaining114 (30%) were used for validating the model. In next step, the effective factors on the groundwater potential such as altitude, slope aspect, slope angle, curvature, distance from rivers, drainage density, topographic wetness index, fault distance, fault density, lithology and land use were derived from the spatial geodatabases. Subsequently, the GPM was produced using WOE and EBF models. Finally, the validation of the GPMs was carried out using areas under the ROC curve (AUC). Results showed that the GPM prepared using WOE model has the success rate of 73.62%. Similarly, the AUC plot showed 76.21% prediction accuracy for the EBF model which means both the models performed fairly good predication accuracy. The GPMs are useful sources for planners and engineers in water resource management, land use planning and hazard mitigation purpose.     

基于SRTM DEM的地形起伏度对天水市黄土滑坡的影响分析

以天水市辖区30 m分辨率的SRTM DEM数据为基础,首先利用GIS空间分析模块中邻域统计分析法,依次选取2×2、3×3、4×4、…、28×28、29×29、30×30共29个矩形邻域分析窗口,运用均值变点分析法进行最佳计算单元的计算分析。结果表明：12×12的网格大小（12.96×10⁴ m²）为曲线突变的拐点,作为曲线由陡变缓的阈值,确定12×12的网格大小（12.96×10⁴ m²）为研究区地形起伏度计算的最佳单元,生成研究区地形起伏度分级图。进而采用确定性系数法（CF）、证据权法、信息量法和条件概率法对研究区发育的黄土滑坡灾害与地形起伏度之间的相关关系进行了定量分析。研究结果表明,区内地形起伏度影响因子层中地形起伏度60~120 m的分级因子层为黄土滑坡灾害的易发因子层,而其中60~90 m区间的值最大,为黄土滑坡灾害的优势因子区间,对滑坡的响应最敏感。     

Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province,Iran

Flood is one of the most devastating natural disasters with socio-economic and environmental consequences. Thus, comprehensive flood management is essential to reduce the flood effects on human lives and livelihoods. The main goal of this study was to investigate the application of the frequency ratio (FR) and weights-of-evidence (WofE) models for flood susceptibility mapping in the Golestan Province, Iran. At first, a flood inventory map was prepared using Iranian Water Resources Department and extensive field surveys. In total, 144 flood locations were identified in the study area. Of these, 101 (70%) floods were randomly selected as training data and the remaining 43 (30%) cases were used for the validation purposes. In the next step, flood conditioning factors such as lithology, land-use, distance from rivers, soil texture, slope angle, slope aspect, plan curvature, topographic wetness index (TWI) and altitude were prepared from the spatial database. Subsequently, the receiver operating characteristic (ROC) curves were drawn for produced flood susceptibility maps and the area under the curves (AUCs) was computed. The final results indicated that the FR (AUC = 76.47%) and WofE (AUC = 74.74%) models have almost similar and reasonable results. Therefore, these flood susceptibility maps can be useful for researchers and planner in flood mitigation strategies.     

基于GIS证据权重法的陕西旬阳地区铅锌成矿远景区定量预测

针对工作区铅锌矿成因类型利用GIS空间信息系统对地质、物探、化探、遥感等各类异常综合分析与成矿要素的信息提取,并在矿产资源评价分析系统（MORPAS3．0）下建立了陕西旬阳地区铅锌矿证据权重法模型证据图层：赋矿地层、控矿构造、化探异常等18个,通过条件独立性检验确定证据权因子层15个,绘制了陕西旬阳地区铅锌矿资源远景预测区后验概率图,给出了陕西旬阳地区铅锌矿产远景定量预测区评价结论,取得了良好的预测效果。     

The Use of the Weights-of-Evidence Modeling Technique to Estimate the Vulnerability of Groundwater to Nitrate Contamination

The occurrence of elevated nitrate (NO₃⁻) concentration in the aquifer of the Province of Milan (northern Italy) is related to both natural and anthropogenic variables. Using the weights-of-evidence modeling technique a specific vulnerability assessment has been performed. This study presents an evolution of previous applications of the proposed methodology as a consequence of an updating of the available database, in terms of data type, quality, and accuracy, and of a more specific and enhanced statistical controls onto the final results. A comparison between the spatial distribution of vulnerability classes and the frequency of occurrences of nitrate in wells shows a high degree of correlation, both for low and high nitrate concentration. Similar results may be evidenced considering the correlation between posterior probability classes and mean nitrate concentrations in wells located in each of these classes: a high R ² value (0.99) and the agreement with the threshold concentration value used to define prior probability testifies a general good quality of results. Groundwater-specific vulnerability has been classified in terms of vulnerability classes and, according to the outcomes of the model, the density of population can be considered the most impacting source of nitrate. Mean annual irrigation and groundwater depth can be identified as influencing factors in the distribution of nitrate, while agricultural practice appears a negligible factor.     

Conditional Independence Test for Weights-of-Evidence Modeling

Weights-of-evidence modeling is a GIS-based technique for relating a point pattern for locations of discrete events with several map layers. In general, the map layers are binary or ternary. Weights for presence, absence or missing data are added to a prior logit. Updating with two or more map layers is allowed only if the map layers are approximately conditionally independent of the point pattern. The final product is a map of posterior probabilities of occurrence of the discrete event within a small unit cell. This paper contains formal proof that conditional independence of map layers implies that T, the sum of the posterior probabilities weighted according to unit cell area, is equal to n, being the total number of discrete events. This result is used in the overall or omnibus test for conditional independence. In practical applications, T generally exceeds n, indicating a possible lack of conditional independence. Estimation of the standard deviation of T allows performance of a one-tailed test to check whether or not T-n is significantly greater than zero. This new test is exact and simpler to use than other tests including the Kolmogorov-Smirnov test and various chi-squared tests adapted from discrete multivariate statistics.     

基于证据权法的赣南稀土矿山地质环境评价

为了解决矿山地质环境评价研究中指标权值计算和评价分级具有较大主观性的问题,本文发展了一种基于证据权法的矿山地质环境评价模式,利用GIS的空间分析功能,提取矿产开发活动、坡度、坡向、高程、构造、植被覆盖度6类地质环境评价指标,运用证据权法计算指标权值。结合条件独立性检验结果,优选评价指标并计算后验概率。采用后验概率面积频率法对赣南稀土矿山地质环境进行综合评价分级。结果表明,研究区内地质环境差区域主要分布在其东南部和西部;矿产开发活动是影响研究区内地质环境质量最主要的因素。采用效率曲线法对模型验证,正确率和预测率分别为90.1%和89.5%。证据权法能够有效避免主观因素干扰,评价结果客观,具有可重现性,适用于矿山地质环境质量评价。     

Gold resources potential assessment in eastern Kunlun Mountains of China combining weights-of-evidence model with GIS spatial analysis technique

Resources potential assessment is one of the fields in geosciences,which is able to take great advantage of GIS technology as a substitution of traditional working methods.The gold resources potential in the eastern Kunlun Mountains,Qinghai Province,China was assessed by combining weights-of-evidence model with GIS spatial analysis technique.All the data sets used in this paper were derived from an established multi-source geological spatial database,which contains geological,geophysical,geochemical and rem...     

基于GIS技术的皖南地区钨钼矿资源评价与预测

近年来,皖南地区在钨钼矿找矿方面取得了重大突破,具有较大的找矿潜力。应用GIS技术对皖南地区的地质、矿产、物化遥等综合信息建立地学空间数据库,在此基础上综合分析区内各类成矿信息和找矿信息,借助计算机处理各类数据,进行成矿信息空间综合分析,建立评价预测模型。选用证据权法对矽卡岩型、斑岩型和热液型钨钼矿资源进行空间定位评价和预测,在四级成矿远景区内圈定了23个Ⅴ级成矿区和68个重点区块,并对这些重点区块进行分级与评述,为该地区的钨钼矿勘查提供参考。     

Predicting Lahar-Inundation Zones: Case Study in West Mount Pinatubo, Philippines

This paper demonstrates techniques for pre-eruption prediction of lahar-inundation zones in areas where a volcano has not erupted within living memory and/or where baseline geological information about past lahars could be scarce or investigations to delimit past lahars might be incomplete. A lahar source (or proximal lahar-inundation) zone is predicted based on ratio of vertical descent to horizontal run-out of eruptive deposits that spawn lahars. Immediate post-eruption distal lahar-inundation zones are predicted based on “pre-eruption” distal lahar-inundation zones and on spatial factors derived from a digital elevation model. Susceptibility to distal lahar-inundation is estimated by weights-of-evidence, by logistic regression and by evidential belief functions. Predictive techniques are applied using a geographic information system and are tested in western part of Pinatubo volcano (Philippines). Predictive maps are compared with a forecast volcanic-hazard map through validation against a field-based volcanic-hazard map. The predictive model of proximal lahar-inundation zone has “true positive” prediction accuracy, “true negative” prediction accuracy, “false positive” prediction error and “false negative” prediction error that are similar to those of the forecast volcanic-hazard map. The predictive models of distal lahar inundation zones have higher “true positive” prediction accuracy and lower “false negative” prediction error than the forecast volcanic-hazard map, although the latter has higher “true negative” prediction accuracy and lower “false positive” prediction error than the former. The results illustrate utility of proposed predictive techniques in providing geo-information could be used, howbeit with caution, for planning to mitigate potential lahar hazards well ahead of an eruption that could generate substantial source materials for lahar formation.