Integration of remote sensing data and the geographical information system (GIS) for the exploration of groundwater resources has become a breakthrough in the field of groundwater research, which assists in assessing, monitoring, and conserving groundwater resources. In the present paper, various groundwater potential zones for the assessment of groundwater availability in Theni district have been delineated using remote sensing and GIS techniques. Survey of India toposheets and IRS-1C satellite imageries are used to prepare various thematic layers viz. lithology, slope, land-use, lineament, drainage, soil, and rainfall were transformed to raster data using feature to raster converter tool in ArcGIS. The raster maps of these factors are allocated a fixed score and weight computed from multi influencing factor (MIF) technique. Moreover, each weighted thematic layer is statistically computed to get the groundwater potential zones. The groundwater potential zones thus obtained were divided into four categories, viz., very poor, poor, good, and very good zones. The result depicts the groundwater potential zones in the study area and found to be helpful in better planning and management of groundwater resources.

Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques

Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learning models: boosted regression tree (BRT), classification and regression tree (CART), and random forest (RF). Thirteen hydrological-geological-physiographical (HGP) factors that influence locations of springs were considered in this research. These factors include slope degree, slope aspect, altitude, topographic wetness index (TWI), slope length (LS), plan curvature, profile curvature, distance to rivers, distance to faults, lithology, land use, drainage density, and fault density. Subsequently, groundwater spring potential was modeled and mapped using CART, RF, and BRT algorithms. The predicted results from the three models were validated using the receiver operating characteristics curve (ROC). From 864 springs identified, 605 (≈70 %) locations were used for the spring potential mapping, while the remaining 259 (≈30 %) springs were used for the model validation. The area under the curve (AUC) for the BRT model was calculated as 0.8103 and for CART and RF the AUC were 0.7870 and 0.7119, respectively. Therefore, it was concluded that the BRT model produced the best prediction results while predicting locations of springs followed by CART and RF models, respectively. Geospatially integrated BRT, CART, and RF methods proved to be useful in generating the spring potential map (SPM) with reasonable accuracy.

GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran

Remote sensing (RS) and geographic information system (GIS) are promising tools for efficient planning and management of vital groundwater resources, especially in data-scarce developing nations. In this study, a standard methodology is proposed to delineate groundwater potential zones using integrated RS, GIS and multi-criteria decision making (MCDM) techniques. The developed methodology is demonstrated by a case study in Udaipur district of Rajasthan, western India. Initially, ten thematic layers, viz., topographic elevation, land slope, geomorphology, geology, soil, pre- and post-monsoon groundwater depths, annual net recharge, annual rainfall, and proximity to surface water bodies were considered in this study. These thematic layers were scrutinized by principal component analysis technique to select influential layers for groundwater prospecting. Selected seven thematic layers and their features were assigned suitable weights on the Saaty’s scale according to their relative importance in groundwater occurrence. The assigned weights of the thematic layers and their features were then normalized by using AHP (analytic hierarchy process) MCDM technique and eigenvector method. Finally, the selected thematic maps were integrated by weighted linear combination method in a GIS environment to generate a groundwater potential map. Thus, four groundwater potential zones were identified and demarcated in the study area, viz., ‘good’, ‘moderate’, ‘poor’ and ‘very poor’ based on groundwater potential index values. The area falling in the ‘good’ zone is about 2,113 km2 (17% of the total study area), which encompasses major portions of Sarada, Salumber, Girwa, Dhariawad, and Mavli blocks of the study area. The northeast and southwest portions along with some scattered patches fall in the ‘moderate’ zone, which encompasses an area of 3,710 km2 (about 29%). The ‘poor’ zone is dominant in the study area which covers an area of 4,599 km2 (36% of the total area). The western portion and parts of eastern and southeast portions of the study area are characterized as having ‘very poor’ groundwater potential, and this zone covers an area of 2,273 km2 (18%). Moreover, in the ‘good’ zone, the mean annually exploitable groundwater reserve is estimated at 0.026 million cubic metres per km2 (MCM/km2), whereas it is 0.024 MCM/km2 in the ‘moderate’ zone, 0.018 MCM/km2 in the ‘poor’ zone, and 0.013 MCM/km2 in the ‘very poor’ zone. The groundwater potential map was finally verified using the well yield data of 39 pumping wells, and the result was found satisfactory.

Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing, GIS and MCDM Techniques

Multi-criteria decision analysis (MCDA) as an advantageous tool has been applied by various researchers to improve their management ability. Management of groundwater resource, especially under data-scarce and arid areas, encountered a lot of problems and issues which drives the planers to use of MCDA. In this research, a standard methodology has been applied to delineate groundwater resource potential zonation based on integrated analytical hierarchy process (AHP), geographic information system (GIS), and remote sensing (RS) techniques in Kurdistan plain, Iran. At first, the effective thematic layers on the groundwater potential such as rainfall, lithology, drainage density, lineament density, and slope percent were derived from the spatial geodatabase. Then, the assigned weights of thematic layers based on expert knowledge were normalized by eigenvector technique of AHP. To prepare the groundwater potential index, the weighted linear combination (WLC) method was applied in GIS. Finally, the receiver operating characteristic (ROC) curve was drawn for groundwater potential map, and the area under curve (AUC) was computed. Results indicated that the rainfall and slope percent factors have taken the highest and lowest weights, respectively. Validation of results showed that the AHP method (AUC = 73.66 %) performed fairly good predication accuracy. Such findings revealed that in the regions suffering from data scarcity through the MCDM methodology, the planners would be able to having accurate knowledge on groundwater resources based on geospatial data analysis. Therefore, the developing scenario for future planning of groundwater exploration can be achieved in an efficient manner.

Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS

Application of GIS based data driven evidential belief function model to predict groundwater potential zonation

Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS

River basin assessment is crucial for water management and to address the watershed issues. So, an integrated river basin management and assessment model using morphometric assessment, remo...

Assessment and planning for integrated river basin management using remote sensing, SWAT model and morphometric analysis (case study: Kaddam river basin, India)

River basins are prone to degradation due to soil erosion induced by anthropogenic activities and natural calamities. In this study, an integrated approach using morphometric analysis, geo-informatics, and fuzzy analytical hierarchy process was employed to prioritize the watersheds. Hydrological parameter “erosion” is a major deciding factor to assess and prioritize the watersheds using the fuzzy analytical hierarchy process (FAHP) method in the Peddavagu watershed of the Krishna river basin. The major characteristics of watershed parameters such as basin length (Lb), drainage density (Dd), form factor, stream frequency (Fs), elongation ratio (Re), circularity ratio (Rc), drainage texture (T), bifurcation ratio (Rb), and compactness constant (Cc) are arranged in matrix form for FAHP analysis. The FAHP analysis was carried out using Triangular Fuzzy Network; for further analysis, the values were classified as follows: 1.25 as moderate susceptibility, 1.5 as high susceptibility, and 1.75 as very high susceptibility. The results of FAHP analysis showed that five watersheds have a very high susceptibility to erosion (30.32%), 16 watersheds as high susceptibility (53.28%), and the remaining 10 watersheds were categorized as moderate susceptibility (16.4%). It implies that soil and water conservation measures have to be implemented on priority in “very high susceptibility category watersheds,” followed by the “high susceptibility” and “moderate susceptibility” categories. Furthermore, the universal soil loss equation (USLE) equation was used to compare the outcomes of the FAHP method. The results have been complacent with FAHP analysis, and the very high susceptibility, high susceptibility, and moderate susceptibility categories were having sediment yields of 54.96 t/ha/year (4D2D1-26), 30.00 t/ha/year (4D2D3-31), and 15.07 t/ha/year (4D2D2-17). The Spearman rank correlation coefficient has been used to validate the USLE and Fuzzy simulations. The results have shown a strong positive correlation for the study area. As the integrated morphometric analysis using FAHP for prioritizing watersheds has shown reliable outcomes, this method has the potential for adoption in other case studies elsewhere.

Morphometric analysis using fuzzy analytical hierarchy process (FAHP) and geographic information systems (GIS) for the prioritization of watersheds

This paper presents spatio-temporal meteorological drought analysis of Pedda Vagu and Ookacheti Vagu watersheds of Mahabubnagar and Ranga Reddy Districts of Telangana state, South Central India. Rainfall anomaly index (RAI) and run analysis have been leveraged to assess drought characteristics at different stations in the basin. The study also presents the interpolation of RAI values using spline technique in a geographic information system (GIS) environment to map the spatial extent and variation of drought severity in different time steps. The study reveals that the occurrence, magnitude, and recurrence of drought varied among the stations in the basin during an observed time frame, i.e., 1986 to 2013. Significant variations in the occurrences of number of drought events are observed among the stations in the basin. The spline interpolated rainfall anomaly index maps illustrated that some regions experienced more severe drought while other regions were well-off. This uncertainty in rainfall essentially indicates that a finer scale of drought vulnerability assessment is highly necessary for better drought management practices. Furthermore, empirical relationships were developed between drought duration and magnitude to support decision-making during various agricultural practices and water management.

Spatio-temporal analysis of droughts in the semi-arid Pedda Vagu and Ookacheti Vagu watersheds, Mahabubnagar District, India

The Pedda vagu and Ookachetti vagu watersheds located in the semi-arid regions of Mahabubnagar district are highly dependent on groundwater for irrigation owing to unreliable rainfall and over extraction of groundwater. The present study has been conducted to identify spatio-temporal groundwater droughts and drought-prone zones. Temporal groundwater droughts have been determined using a standardized water-level index along with spatial groundwater droughts using spline interpolation in Geographic Information Systems. The study shows that the groundwater droughts varied among the stations during the observation period, i.e. 1998–2011. However, the spatial assessment shows that the region as such experienced more mild groundwater droughts except during severe meteorological drought years (1998, 2002, 2004 and 2008); this indicates that the region has good scope for groundwater exploitation during dry spells and initial stages of droughts. Therefore, it is critical to have plans for the development of ground...

Sreedhar Ganapuram

Papers

Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS

Assessment and planning for integrated river basin management using remote sensing, SWAT model and morphometric analysis (case study: Kaddam river basin, India)

Morphometric analysis using fuzzy analytical hierarchy process (FAHP) and geographic information systems (GIS) for the prioritization of watersheds

Spatio-temporal analysis of droughts in the semi-arid Pedda Vagu and Ookacheti Vagu watersheds, Mahabubnagar District, India

Identification of groundwater drought prone zones in Pedda vagu and Ookachetti vagu watersheds, tributaries of the Krishna River, India