Groundwater Prospect Zoning Using Remote Sensing and Geographical Information System: A Case Study in Dala-Renukoot Area, Sonbhadra District, Uttar Pradesh

In the present study, ground water prospect zones in Dala-Renukoot area, in Sonebhadra district. Uttar Pradesh, India have been delineated, through integration of various thematic maps using ARC/INFO GIS. Thematic maps in respect of geology, geomorphology. slope, drainage, land-use/land cover, lineament and lineament intersection frequency were prepared on 1:50,000 scale using remote sensing and conventional methods. These maps were scanned and registered with reference to a basemap and are input as separate layers using ARC/INFO GIS. Each theme was assigned a weightage depending on its influence on the movement and storage of groundwater and each unit in every theme map is assigned a knowledge based ranking from 1 to 5 depending on its significance to groundwater occurrence. All the themes are overlaid, two at a time and the resultant composite coverage is classified into five groundwater prospect categories. This output map is correlated with the groundwater data collected in the field.     

Regional Groundwater Assessment of Krishna River Basin Using Integrated GIS Approach

The groundwater occurrence and movement within the flow systems are governed by many natural factors like topography, geology, geomorphology, lineament structures, soil, drainage network and land use land cover (LULC). Due to complex natural geological/hydro-geological regime a systematic planning is needed for groundwater exploitation. It is even more important to characterize the aquifer system and delineate groundwater potential zones in different geological terrain. The study employed integration of weighted index overlay analysis (WIOA) and geographical information system (GIS) techniques to assess the groundwater potential zones in Krishna river basin, India and the validation of the result with existing groundwater levels. Different thematic layers such as geology, geomorphology, soil, slope, LULC, drainage density, lineament density and annual rainfall distribution were integrated with WIOA using spatial analyst tools in Arc-GIS 10.1. These thematic layers were prepared using Geological survey of India maps, European Digital Archive of Soil Maps, Bhuvan (Indian-Geo platform of ISRO, NRSC) and 30 m global land cover data. Drainage, watershed delineation and slope were prepared from the Shuttle Radar Topography Mission digital elevation model of 30 m resolution data. WIOA is being carried out for deriving the normalized score for the suitability classification. Weight factor is assigned for every thematic layer and their individual feature classes considering their significant importance in groundwater occurrence. The final map of the study area is categorized into five classes very good, good, moderate, poor and very poor groundwater potential zones. The result describes the groundwater potential zones at regional scale which are in good agreement with observed ground water condition at field level. Thus, the results derived can be very much useful in planning and management of groundwater resources in a regional scale.     

Land cover mapping at Alkali Flat and Lake Lucero,White Sands,New Mexico,USA using multi-temporal and multi-spectral remote sensing data

The goal of this research is to map land cover patterns and to detect changes that occurred at Alkali Flat and Lake Lucero, White Sands using multispectral Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and hyperspectral Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. The other objectives of this study were: (1) to evaluate the information dimensionality limits of Landsat 7 ETM+, ASTER, ALI, Hyperion, and AVIRIS data with respect to signal-to-noise and spectral resolution, (2) to determine the spatial distribution and fractional abundances of land cover endmembers, and (3) to check ground correspondence with satellite data. A better understanding of the spatial and spectral resolution of these sensors, optimum spectral bands and their information contents, appropriate image processing methods, spectral signatures of land cover classes, and atmospheric effects are needed to our ability to detect and map minerals from space. Image spectra were validated using samples collected from various localities across Alkali Flat and Lake Lucero. These samples were measured in the laboratory using VNIR–SWIR (0.4–2.5 μm) spectra and X-ray Diffraction (XRD) method. Dry gypsum deposits, wet gypsum deposits, standing water, green vegetation, and clastic alluvial sediments dominated by mixtures of ferric iron (ferricrete) and calcite were identified in the study area using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. The results of MNF confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. ASTER and ALI data can be a reasonable alternative to AVIRIS and Hyperion data for the purpose of monitoring land cover, hydrology and sedimentation in the basin. The spectral unmixing analysis and dimensionality eigen analysis between the various datasets helped to uncover the most optimum spatial–spectral–temporal and radiometric-resolution sensor characteristics for remote sensing based on monitoring of seasonal land cover, surface water, groundwater, and alluvial sediment input changes within the basin. The results demonstrated good agreement between ground truth data and XRD analysis of samples, and the results of Matched Filtering (MF) mapping method.     

Remote Sensing and GIS Approach for Delineation of Groundwater Potential and Groundwater Quality Zones of Western Doon Valley, Uttarakhand, India

Groundwater exploration in the Western Doon valley has been carried out to delineate the groundwater potential and groundwater quality zones suitable for domestic purposes based on the integrated use of Remote Sensing and Geographical Information Systems (GIS). The Western Doon Valley, occupying broad synclinal troughs in the evolving fold-thrust system of sub-Himalaya, which is filled by post-Siwalik fluvial and debris flow deposits in the late Quaternary-Holocene. The Western Doon Valley area is bounded by the Mussoorie range in the north with 1800–2800 m elevation and in the south by young topographic relief of the frontal Siwalik range with ~800 m average elevation. Groundwater quality of Western Doon valley through pictorially representation in the GIS environment, it is inferred that calcium, magnesium, total hardness and nitrate at some locations above the desirable limit. The groundwater prospects map has been prepared by integrating the hydrogeomorphologic, land use/land cover from satellite data (IRS-ID, LISS-III data) slope, soil, drainage density, depth to water table of pre-monsoon and post-monsoon periods (unconfined aquifer), water table fluctuation, static water level (confined to semi-confined aquifers), specific capacity, discharge and drawdown maps using index overlay method in the GIS environment. The groundwater prospects are depicted in five categories Very high, high, moderate, low and very low (runoff zone) integrated with the groundwater quality zones which have been prepared from hydrochemical data. The results indicated that 16.82 % of the area is under Very high potential zone category with 16.11 % and 0.71 % of desirable and undesirable quality of groundwater and 18.65 %, 42.06 %, 6.96 % and 15.46 % classified as high, moderate, low and very low potential zones with desirable and undesirable quality of groundwater for domestic purposes. This study be useful for designing the groundwater prospects and management plan for the sustainable development of study area.     

Assessment of a data-driven evidential belief function model and GIS for groundwater potential mapping in the Koohrang Watershed,Iran

The objective of this study is to produce groundwater potential map (GPM) and its performance assessment using a data-driven evidential belief function (EBF) model. This study was carried out in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran. It’s conducted in three main stages such as data preparation, groundwater potential mapping using EBF and validation of constructed model using receiver operating characteristic (ROC) curve. At first, 864 groundwater data were collected from spring locations; out of that, 605 (70%) locations were selected for training/model building and the remaining 259 (30%) cases were used for the model validation. In the next step, 12 effective factors such as altitude, slope aspect, slope degree, slopelength (LS), topographic wetness index (TWI), plan curvature, land use, lithology, distance from rivers, drainage density, distance from faults and fault density were extracted from the spatial database. Subsequently, GPM was prepared using EBF model in ArcGIS environment. Finally, the ROC curve and area under the curves (AUC) were drawn for verification purposes. The validation of results showed that the AUC for EBF model is 81.72%. In general, this result can be helpful for planners and engineers in water resource management and land-use planning.     

Groundwater potential in the hard rock terrain of western ghats: A case study from Kottayam district,Kerala using resourcesat (IRS-P6) data and GIS techniques

The present study was aimed to identify and delineate the groundwater potential areas in parts of Western Ghats, Kottayam, covering the upper catchment of Meenachil river. The study area is composed rocks of Archaean age and Charnockite dominated over others. The information on lithology, geomorphology, lineaments, slope and land use/land cover was generated using the Resourcesat (IRS P6 LISS III) data and Survey of India (Sol) toposheets of scale 1:50,000 (surveyed in 1969) and integrated them with raster based Geographical Information System (GIS) to identify the groundwater potential of the study area. Thus, a GIS-based model which takes account of local condition/variations has been developed specifically for mapping groundwater potential. On the basis of hydrogeomorphology, three categories of groundwater potential zones namely good, moderate and poor were identified, and delineated. The high potential zones correspond to the fracture valleys, valley fills, pediments and denudational slope, which coincide with the low slope and high lineaments density areas. The low zone mainly comprise structural hills and escarpments and these act as run-off zones. The derived panchayath-wise groundwater potentiality information could be used for effective identification of suitable locations for extraction of potable water for rural populations.     

Applicability of generalized additive model in groundwater potential modelling and comparison its performance by bivariate statistical methods

Groundwater is the most valuable natural resource in arid areas. Therefore, any attempt to investigate potential zones of groundwater for further management of water supply is necessary. Hence, many researchers have worked on this subject all around the world. On the other hand, the Generalized Additive Model (GAM) has been applied to environmental and ecological modelling, but its applicability to other kinds of predictive modelling such as groundwater potential mapping has not yet been investigated. Therefore, the main purpose of this study is to evaluate the performance of GAM model and then its comparison with three popular GIS-based bivariate statistical methods, namely Frequency Ratio (FR), Statistical Index (SI) and Weight-of-Evidence (WOE) for producing groundwater spring potential map (GSPM) in Lorestan Province Iran. To achieve this, out of 6439 existed springs, 4291 spring locations were selected for training phase and the remaining 2147 springs for model evaluation. Next, the thematic layers of 12 effective spring parameters including altitude, plan curvature, slope angle, slope aspect, drainage density, distance from rivers, topographic wetness index, fault density, distance from fault, lithology, soil and land use/land cover were mapped and integrated using the ArcGIS 10.2 software to generate a groundwater prospect map using mentioned approaches. The produced GSPMs were then classified into four distinct groundwater potential zones, namely low, moderate, high and very high classes. The results of the analysis were finally validated using the receiver operating characteristic (ROC) curve technique. The results indicated that out of four models, SI is superior (prediction accuracy of 85.4%) following by FR, GAM and WOE, respectively (prediction accuracy of 83.7, 77 and 76.3%). The result of groundwater spring potential map is helpful as a guide for engineers in water resources management and land use planning in order to select suitable areas to implement development schemes and also government entities.     

Predicting salinity impacts of land-use change: Groundwater modelling with airborne electromagnetics and field data,SE Queensland,Australia

Throughout Australia, there is concern that land use change is mobilizing salt stored in the landscape, causing salinity in soil and water resources. Salt in the landscape becomes a salinity risk only if it is mobilized by groundwater movement. A combination of modelled groundwater behaviour under various land uses with three-dimensional salt-load maps developed from airborne electromagnetic survey (AEM) provides a practical tool to assess potential salt movement.AEM survey of the country around St. George, SE Queensland, revealed a potential salinity threat: significant salt stores in the uplands adjacent to flood plains which support important irrigation developments and which drain to the Darling River system. A conceptual model of the regional hydrogeology was built upon three-dimensional AEM data, an investigation-drilling program, and direct field measurement of hydraulic conductivities. This information was incorporated in a Flowtube groundwater model and groundwater responses to five different land management options were tested over a 100-year period. Surface water storage on relatively permeable soils and continuous irrigated cotton both resulted in water tables reaching the soil surface; rain-fed wheat and pasture both resulted in a raised watertable, but both established a new equilibrium without the water table reaching the ground surface.     

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.     

Semi-automatic delineation of badlands using contrast in vegetation activity: a case study in the lower Chambal valley,India

Population growth worldwide leads to an increasing pressure on the land. Recent studies reported that many areas covered by badlands are decreasing because parts of badlands are being levelled and converted into arable land. It is important to monitor these changes for environmental planning. This paper proposes a remote-sensing-based detection method which allows mapping of badland dynamics based on seasonal vegetation changes in the lower Chambal valley, India. Supervised classification was applied on three Landsat (Thematic Mapper) images, from 3 different seasons; January (winter), April (summer) and October (post-monsoon). Different band selection methods were applied to get the best classification. Validation was done by ground referencing and a GeoEye-1 satellite image. The image from January performed best with overall accuracy of 87% and 0.69 of kappa. This method opens the possibilities of using semi-automatic classification for the Chambal badlands which is so far mapped with manual interpretations only.     

Spatial analysis of groundwater potential using remote sensing and GIS in the Kanyakumari and Nambiyar basins,India

Remotely sensed data can provide useful information in understanding the distribution of groundwater, an important source of water supply throughout the world. In the present study, the modern geomatic technologies, namely remote sensing and GIS were used in the identification of groundwater potential zones in the Kanyakumari and Nambiyar basins of Tamil Nadu in India. The multivariate statistical technique was used to find out the relationship between rainfall and groundwater resource characteristics. It has been found out that groundwater not only depends upon rainfall, but various other factors also influence its occurrence. Eight such parameters were considered and multi criterion analysis has been carried out in order to find out the potential zones. Accordingly, it had been concluded that the Kanyakumari river basin has more ground water potential, whereas the Nambiyar basin has less potential. Thus surface investigation of groundwater has proved to be easier, time consistent and cheaper using the geomatic technologies.     

Identification of Groundwater Potential Zones Using Remote Sensing Techniques In and Around Guntur Town, Andhra Pradesh, India

The area in and around Guntur Town in Andhra Pradesh faces an acute water problem. It represents plain land and gentle slope responsible for infiltration and groundwater recharge. Adequate groundwater resource is reported to be available in the investigated area. It has not been properly exploited. The present investigation is, therefore, undertaken to assess groundwater favourable zones for development and exploration with the help of geomorphological units and associated features. The identified units and features by remote sensing technology with the integration of conventional information and limited ground truths are shallow weathered pediplain (PPS), moderately weathered pediplain (PPM), deeply weathered pediplain (PPD), residual hill (RH) and lineaments (L). The results show that the PPD, PPM and PPS are good, moderate to good and poor to moderate promising zones, respectively for groundwater prospecting. The RH is a poor geomorphological unit in respect to prospective zone as groundwater resource. However, adequate recharge source of groundwater can be expected surrounding the RH, as it acts as surface run-off zone. Lineaments parallel to the stream courses and intersecting-lineaments are favourable indicators for groundwater development. They can also be utilized to augment groundwater resource.     

Landsat 8热红外数据定标参数的变化及其对地表温度反演的影响

Landsat系列卫星上的TIRS热红外传感器数据已被大量应用,针对TIRS数据的地表温度反演也相继开发出一些算法,并有一些研究对TIRS数据的定标及其地表温度反演算法的精度进行了对比。本文主要就TIRS热红外传感器定标参数的变化,结合这些定标参数变化的时间点对有关地表温度反演算法的适用性和有效性进行分析,特别是对劈窗算法是否适合当前的TIRS数据进行了讨论,以使用户能够对Landsat 8 TIRS热红外数据的正确使用有进一步的认识。总的看来,由于视域外杂散光的影响,TIRS数据的定标精度仍达不到设计目标,TIRS第11波段的不确定性仍成倍大于TIRS 10波段。因此,在Landsat团队未彻底解决这一问题之前,同时用TIRS第10、第11这两个差距较大的波段构成的劈窗算法来反演地表温度,其精度存在较大的不确定性,US6-S团队仍在致力于改进第11波段的精度,改进后的波段可以用劈窗策法。目前应以TIRS第10单波段的方式来反演地表温度为宜。     

Influence of rock types and structures in the development of drainage network in hard rock area

Remote sensing techniques has proved to be an extremely useful tool in morphometric analysis and groundwater studies. Remote sensing techniques with an emphasis on lineament identifications can play a great role in groundwater prospecting in semi-arid hard rock areas of Purulia district. In the present study, morphometric analysis using remote sensing technique has been carried out in parts of Baghmundi block, Purulia district, West Bengal. The parameters worked out include Bifurcation ratio (R_b), Stream length (L_u), Form factor (R_c), Circulatory ratio (R_c), and Drainage density (D). The morphometric analysis suggests that fractured, resistant, permeable rocks cover the area, the drainage network not so affected by tectonic disturbances. Using satellite imageries of two dates of IRS, different hydrogeomorphological units have been delineated. Among different hydrogeomorphic units (i) very shallow weathered pediment and (ii) Structural hills/ residual hills/inselbergs have very poor ground water prospects, while moderately weathered pediplains and valley fills are good prospective zones for groundwater exploration.     

Use of Landsat Thematic Mapper for urban land use/land cover mapping

Visual interpretation of Landsat Thematic Mapper data coupled with ground checking has been used to extract information for urban areas. The emphasis has been given on development of land use/land cover scheme and image interpretation keys for interpretation and delineation purposes using satellite remote sensing data. Lucknow city and its surroundings have been studied to evaluate the usefulness and potentiality of satellite data particularly Landsat Thematic Mapper for urban area studies. This study has demonstrated that remote sensing can provide a valuable tool for urban data acquisition.     

InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley,Mexico

This paper illustrates how InSAR alone can be used to delineate potential ground fractures related to aquifer system compaction. An InSAR-derived ground fracturing map of the Toluca Valley, Mexico, is produced and validated through a field campaign. The results are of great interest to support sustainable urbanization and show that InSAR processing of open-access Synthetic Aperture Radar (SAR) data from the Sentinel-1 satellites can lead to reliable and cost-effective products directly usable by cities to help decision-making.The Toluca Valley Aquifer (TVA) sustains the water needs of two million inhabitants living within the valley, a growing industry, an intensively irrigated agricultural area, and 38% of the water needs of the megalopolis of Mexico City, located 40 km east of the valley. Ensuring water sustainability, infrastructure integrity, along with supporting the important economic and demographic growth of the region, is a major challenge for water managers and urban developers. This paper presents a long-term analysis of ground fracturing by interpreting 13 years of InSAR-derived ground displacement measurements. Small Baseline Subset (SBAS) and Persistent Scatterer Interferometry (PSI) techniques are applied over three SAR datasets totalling 93 acquisitions from Envisat, Radarsat-2, and Sentinel-1A satellites and covering the period from 2003 to 2016.From 2003 to 2016, groundwater level declines of up to 1.6 m/yr, land subsidence up to 77 mm/yr, and major infrastructure damages are observed. Groundwater level data show highly variable seasonal responses according to their connectivity to recharge areas. However, the trend of groundwater levels consistently range from −0.5 to −1.5 m/yr regardless of the well location and depth. By analysing the horizontal gradients of vertical land subsidence, we provide a potential ground fracture map to assist in future urban development planning in the Toluca Valley.     

A method for groundwater prospect zonation in data poor areas using remote sensing and GIS: a case study in Kalikavu Panchayath of Malappuram district,Kerala, India

Abstract

The present study was an attempt to delineate potential groundwater zones in Kalikavu Panchayat of Malappuram district, Kerala, India. The geo-spatial database on geomorphology, landuse, geology, slope and drainage network was generated in a geographic information system (GIS) environment from satellite data, Survey of India topographic sheets and field observations. To understand the movement and occurrence of groundwater, the geology, geomorphology, structural set-up and recharging conditions have to be well understood. In the present study, the potential recharge areas are delineated in terms of geology, geomorphology, land use, slope, drainage pattern, etc. Various thematic data generated were integrated using a heuristic method in the GIS domain to generate maps showing potential groundwater zones. The composite output map scores were reclassified into different zones using a decision rule. The final output map shows different zones of groundwater prospect, viz., very good (15.57% of the area), good (43.74%), moderate (28.38%) and poor (12.31%). Geomorphic units such as valley plains, valley fills and alluvial terraces were identified as good to excellent prospect zones, while the gently sloping lateritic uplands were identified as good to moderate zones. Steeply sloping hilly terrains underlain by hard rocks were identified as poor groundwater prospect zones.     

基于多级决策树分类的土地利用与覆盖信息提取

结合Landsat-8遥感数据,采用多级决策树分类方案,利用归一化植被指数、波段比值、主成分分量等光谱特征参数并融合其他非遥感知识,对黄河三角洲地区土地利用与覆盖的信息展开了全面的提取、研究与分析,获得了该地区5个一级类、12个二级类地物的分布情况,分类总体精度93.88%,优于传统监督分类。同时采用聚类、分类叠加和人机交互等分类后处理操作以获得更贴近地面实际的制图效果,开展基于海岸线的缓冲区分析以获得各地物特别是距离海岸线10 km、20 km范围内地物类型的空间分布并完成相关制图与分析,为黄河三角洲地区滨海土地的利用与开发提供了数据支持。     

Identification of Groundwater Potential Zones of a Tropical River Basin (Kerala,India) Using Remote Sensing and GIS Techniques

The present work accentuated the expediency of remote sensing and geographic information system (GIS) applications in groundwater studies, especially in the identification of groundwater potential zones in Ithikkara River Basin (IRB), Kerala, India. The information on geology, geomorphology, lineaments, slope and land use/land cover was gathered from Landsat ETM + data and Survey of India (SOI) toposheets of scale 1:50,000 in addition, GIS platform was used for the integration of various themes. The composite map generated was further classified according to the spatial variation of the groundwater potential. Four categories of groundwater potential zones namely poor, moderate, good and very good were identified and delineated. The hydrogeomorphological units like valley fills and alluvial plain and are potential zones for groundwater exploration and development and valley fills associated with lineaments is highly promising area for groundwater extraction. The spatial variation of the potential indicates that groundwater occurrence is controlled by geology, structures, slope and landforms.