Abstract
Three statistical models—frequency ratio (FR), weights-of-evidence (WofE) and logistic regression (LR)—produced groundwater-spring potential maps for the Birjand Township, southern Khorasan Province, Iran. In total, 304 springs were identified in a field survey and mapped in a geographic information system (GIS), out of which 212 spring locations were randomly selected to be modeled and the remaining 92 were used for the model evaluation. The effective factors—slope angle, slope aspect, elevation, topographic wetness index (TWI), stream power index (SPI), slope length (LS), plan curvature, lithology, land use, and distance to river, road, fault—were derived from the spatial database. Using these effective factors, groundwater spring potential was calculated using the three models, and the results were plotted in ArcGIS. The receiver operating characteristic (ROC) curves were drawn for spring potential maps and the area under the curve (AUC) was computed. The final results indicated that the FR model (AUC = 79.38 %) performed better than the WofE (AUC = 75.69 %) and LR (AUC = 63.71 %) models. Sensitivity and factor analyses concluded that the bivariate statistical index model (i.e. FR) can be used as a simple tool in the assessment of groundwater spring potential when a sufficient number of data are obtained.
Résumé
Trois modèles statistiques—rapport de fréquence (RF), poids d’évidence (PdE) et régression logique (RL)—ont permis de produire des cartes de potentialité des sources d’eau souterraine pour le district de Birjand, dans le Sud de la province de Khorasan en Iran. Au total 304 sources ont été identifiées lors d’une reconnaissance de terrain et cartographiées à l’aide d’un système d’information géographique (SIG), parmi lesquelles 212 locations de sources ont été sélectionnées de manière aléatoire pour être modélisées et les 92 restantes ont été utilisées pour l’évaluation du modèle. Les facteurs effectifs (angle de la pente, aspect de la pente, longueur de la pente, altitude, indice topographique d’humidité, indice de puissance d’écoulement, plan de courbure, lithologie, occupation du sol, distance au cours d’eau le plus proche, route et faille) ont été extraites de la base de données spatiales. A partir de l’utilisation de ces facteurs, la potentialité des sources d’eau souterraine a été calculée en utilisant les trois modèles, et les résultats ont été représentés graphiquement sous ArcGIS. Les courbes caractéristiques de fonctionnement de l’opérateur ont été établies pour les cartes de potentialité des sources d’eau souterraine et l’aire sous la courbe a été calculée (ASC). Les résultats finaux indiquent que le modèle RF (ASC = 79.38 %) a une meilleure performance que les modèles PdE (ASC = 75.69 %) et RL (ASC = 63.71 %). Les analyses de sensibilité et factorielles ont conclus que le modèle statistique à index à deux variables (par ex. RF) peut être utilisé comme un outil simple pour l’évaluation de la potentialité des sources d’eau souterraine lorsqu’un nombre suffisant de données est obtenu.
Resumen
Tres modelos estadísticos—relación de frecuencias (FR), pesos de evidencias (WofE) y regresión logística (LR)—produjeron mapas del potencial de manantiales de agua subterránea para el Birjand Township, en el sur de la Provincia de Khorasan, Iran. Se identificaron en total 304 manantiales en un relevamiento de campo y fueron mapeados en un sistema de información geográfica (GIS), de los cuales se seleccionaron aleatoriamente las ubicaciones de 212 manantiales para ser modelados y se usaron los 92 restantes para la evaluación del modelo. Se derivaron los factores efectivos (ángulo de la pendiente, aspecto de la pendiente, longitud de la pendiente, elevación, índice de humedad topográfica, índice de energía de la corriente, curvatura en planta, litología, uso de la tierra, y la distancia al río más cercano, carreteras y fallas) de una base de datos espaciales. Usando estos factores efectivos, el potencial de manantiales de agua subterránea fue calculado usando los tres modelos, y los resultados fueron ploteados en ArcGIS. Se elaboraron las curvas características de operación del receptor (ROC) para mapas de potencial de manantiales y se calculó el área bajo la curva (AUC). Los resultados finales indicaron que el modelo FR (AUC = 79.38 %) obtuvo un mejor desempeño que los modelos WofE (AUC = 75.69 %) y LR (AUC = 63.71 %). Los análisis de sensibilidad y factorial concluyeron que el modelo de índice estadístico bivariado (por ejemplo FR) puede ser usado como una herramienta simple en la evaluación del potencial de manantiales de agua subterránea cuando se obtienen un número suficientes de datos.
摘要
根据三个统计模型(频率比(FR)、证据加权(WofE)及逻辑回归(LR))编出了伊朗Khorasan省南部Birjand镇地下水泉潜力图。野外调查总共确定了304个泉,并用地理信息系统(GIS)绘出,其中212个泉位置随机选择进行模拟,剩下的92个泉用于模型评估。有效因子(坡角度、坡向、坡长、高程、地形湿润指数、河流功率指数、平面曲率、岩性、土地利用、到最近的河流、道路和断层的距离)来自空间数据库。利用这些有效因子,依靠三个模型计算了地下水泉潜力,计算结果用ArcGIS标绘。为泉潜力图绘制了受试者工作特征(ROC)曲线,对曲线下的区域(AUC)进行了计算。最终结果显示,FR模型(AUC = 79.38 %)运行的比WofE模型(AUC = 75.69 %)和 LR 模型(AUC = 63.71 %)要好。敏感性和因子分析认为,在获取足够数量的资料情况下,二变量的统计指数模型(也就是FR)可以用作地下水泉潜力评价的一个简单工具。
Resumo
Três modelos estatísticos—rácio de frequência (RF), evidência ponderada (EP) e regressão logística (RL)—produziram mapas de potencial em nascentes de água subterrânea para o município de Birjand, sul da Província de Khorasan, Irão. Num levantamento de campo foram identificadas um total de 304 nascentes que foram mapeadas num sistema de informação geográfica (SIG), e das quais se selecionaram aleatoriamente 212 locais de nascentes para serem modeladas, sendo as restantes 92 usadas para a avaliação do modelo. Os fatores efetivos (ângulo da vertente, orientação da vertente, extensão da vertente, altitude, índice de humidade topográfica, índice de potência de linha de água, curvatura projetada, litologia, uso do solo e distância à linha de água, à estrada e à falha mais próxima) foram obtidos a partir da base de dados espaciais. Utilizando estes fatores efetivos, foi calculado o potencial em nascentes de água subterrânea com os três modelos e os resultados foram projetados em ArcGIS. Foram desenhadas as curvas da característica de operação do recetor (COR) a partir dos mapas de potencial em nascentes e foi calculada a área subjacente à curva (ASC). Os resultados finais mostram que o modelo RF (ASC = 79.38 %) se comportou melhor que os modelos EP (ASC = 75.69 %) e RL (ASC = 63.71 %). Análises de sensibilidade e fatoriais concluíram que o modelo de índice estatístico bivariado (i.e. RF) pode ser usado como uma ferramenta simples na avaliação do potencial em nascentes de água subterrânea quando existe um número suficiente de dados.
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The authors would like to thank Dr. Vincent Post (editor of Hydrogeology Journal) and three anonymous reviewers for their helpful comments on the early version of the manuscript. As well as, the authors acknowledge of Farzaneh Hossaini, Eng. Rastegar and Eng. Etminani for supports and helps in various steps of current research.
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Pourtaghi, Z.S., Pourghasemi, H.R. GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province, Iran. Hydrogeol J 22, 643–662 (2014). https://doi.org/10.1007/s10040-013-1089-6
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DOI: https://doi.org/10.1007/s10040-013-1089-6