Watershed Delineation Research Articles

Evaluating Regional Variability in Road Closure Outcomes Due to Rainfall: a Logistic Regression Approach

Abstract. This study investigated the probability of road closure due to flooding. Logistic regression model was developed using the road closure data and the daily rainfall data for Houston, TX, USA during 2017 and 2018. The road network was further divided into flood prone zones. The spatial analysis revealed that the rainfall at the road segment level could be sufficiently represented by that recorded by nearest sensors. Within a 4 d window, the rainfall in the current day and 3 d prior played a more influential role in predicting road closure. The differential outcomes due to distinct regional features were explained. Finally, a watershed delineation approach substantially improved the model's predictive power and sensitivity.

Avoid backtracking and burn your inputs: CONUS-scale watershed delineation using OpenMP

The Memory-Efficient Watershed Delineation (MESHED) parallel algorithm is introduced for Contiguous United States (CONUS)-scale hydrologic modeling. Delineating tens of thousands of watersheds for a continental-scale study can not only be computationally intensive, but also be memory-consuming. Existing algorithms require separate input and output data stores. However, as the number of watersheds to delineate and the resolution of input data grow significantly, the amount of memory required for an algorithm also quickly increases. MESHED uses one data store for both input and output by destructing input data as processed and a node-skipping depth-first search to further reduce required memory. For 1000 watersheds in Texas, MESHED performed 95% faster than the Central Processing Unit (CPU) benchmark algorithm using 33% less memory. In a scaling experiment, it delineated 100,000 watersheds across the CONUS in 13.64s. Given the same amount of memory, MESHED can solve 50% larger problems than the CPU benchmark algorithm can.

A web-based tool for watershed delineation considering lakes and reservoirs

Lakes have significant impacts on watershed hydrology. However, until now, no web-based tool has been available for watershed delineation considering lakes. In this study, we developed a tool to address this, enabling non-exports to delineate watersheds. First, a conceptual data model was proposed to represent related spatial units and their flow relationships, including rivers, lakes, river sub-basins, lake hillslopes, and flow paths. Subsequently, a web-based tool was designed and implemented, which enables users to select an area of interest and obtain watershed delineation results without the need for software installation or data preparation. This tool also supports for the customization of data and parameters. Two case studies, conducted at the Fushi Reservoir and Mahu Lake, demonstrated the system's usability. To our knowledge, this study presents the first web-based tool for watershed delineation that considers lakes, and it has great potential for applications in watershed modeling and management.

Estimation of Runoff at Shetrunji River Basin using SWAT Hydrological Modelling

The researchers and scientists have realized that this is the high time to act in accordance to the impact of change of climate. Because of climate change problem, various effects occur, one of them is hydrological extremes. This leads to the emergence of hot-spots and vulnerable areas causing difficult adaptation. The current analysis intends to estimate the influence of change in climate on the hydrological parameter on one of the most important tributaries of Saurashtra region of Gujarat, Western India. Out of number of methods available to perform this task, simulation (hydrological modelling) which is the most widely used techniques available at this time, has been adopted. Here in this research the SWAT (Soil and Water Assessment Tool) model which happens to be a semi-distributed model and integrates the GIS information with the attribute database of the River has been utilized. The watershed delineation has been done using AWD (Automatic Watershed Delineation) which is available as a plugin in ArcSWAT. It has classified the catchment into 28 subbasins. From Esri Sentinel-2 landuse map has been used and the soil map is extracted from FAO Raster world soil map. Moreover, we can classify the sub basins into 173 HRUs (Hydrological Response Unit) by the model. The weather files from 1982 to 2019 has been used from the global weather source as a seed to the model. The successful run of the model gives elucidate fluctuating runoff volumes over time, spanning from a lowest of 2.56 mm to a extreme of 503.78mm. Notably, the annual average runoff stands at 190.82 mm, representing approximately 28.34% of the cumulative rainfall experienced within the river basin. The estimation of runoff is helpful in allocating water for agriculture, household demands, and industrial requirements.

Watershed Modelling, Using the Geographical Information System (GIS) Approach (Federal University of Technology Owerri, Imo State Nigeria as Case study)

In a typical watershed area such as the Federal University of Technology, Owerri, Nigeria, watershed modelling is essential for the sustainable management of water resources, protection of ecosystems and more. In this study, we will be creating a watershed model for FUTO, this study will also cover other aspects such as estimating the depression-less flow direction, delineating the flow accumulation, extracting realistic drainage network using the Strahler’s stream order method and we will also delineate the watershed’s boundary and identify possible outlets / pour points, using the digital elevation model (DEM) gotten from Alaska satellite facility used as a main data source in combination with the PC version of ArcGIS software (ArcMap 10.7) and then we extract the hydrologic information from the DEM in ArcGIS using Hydrology tools. The estimation of depression-less flow direction is done by filling the digital elevation model (DEM). This includes performing fill on sinks to ensure proper delineation of basins and streams. If the sinks are not filled, a derived drainage network may be discontinuous. After the DEM has been filled, then we can now move on to delineating the flow accumulation in the study area. The results shows that by using watershed function in ArcGIS for watershed flow direction and accumulation in FUTO can be determined. The results also shows the drainage network that was extracted by Strahler’s method, showing different orders of streams and it also shows the watershed boundary and pour point / outlets along the Otamiri River which the watershed drains into. This work simply shows the applicability of GIS as a tool of watershed delineation and drainage extraction.

Panzara River Watershed Prioritization Based on Geomorphometric and LULC Change Analysis using Geo-Spatial Techniques

Human activities can significantly influence the quality of water flowing from a watershed, either positively or negatively. As water moves through the system, these impacts accumulate, with all land-based activities having the potential to affect the water quality and quantity experienced by downstream stakeholders. Similarly, the actions of upstream landowners impact the water that flows across others' properties. Geospatial techniques like remote sensing and geographic information systems (GIS) are invaluable tools for analysing drainage patterns within a watershed and the associated changes in land use and cover. This study focuses on the Panzara river basin, a principal tributary of the larger Tapi river basin, situated in central India between the westward-flowing Godavari and Narmada river systems, which both ultimately discharge into the Arabian Sea. The study area spans latitudes from 20°42'0" N to 21°18'0" N and longitudes from 74°06'0" E to 75°00'0" E, covering a geographical area of 2,986.05 square kilometers with a perimeter of 570.51 kilometers. The watershed delineation was carried out using Shuttle Radar Terrain Mapper (SRTM) data with a 30-meter resolution. For land use and land cover (LULC) analysis, Landsat 5 TM C2L1 and Landsat 8 OLI/TIRS C2L1 datasets, both with 30-meter resolution, were utilized. The present study conducts a morphometric analysis and assesses LULC changes within the Panzara river basin between 2000 and 2021. Morphometric parameters such as linear parameters [Drainage density (Dd), Stream frequency (Fs), Mean bifurcation ratio (Rbm), Drainage texture ratio (Dt), Length of overland flow (Lo)] and areal parameters [Elongation ratio (Re), Circulatory ratio (Cr), Form factor (Rf), Compactness coefficient (Cc)] were used to prioritize sub-watersheds. Furthermore, the study classifies the observed LULC changes between satellite imagery datasets from 2000 and 2021, quantifying the percentage changes in the respective LULC classes across the sub-watersheds over the two decades. The overall accuracy of the LULC classification was 81.82% for 2000 and 88.88% for 2021, with Kappa coefficients of 0.772 and 0.85, respectively. In terms of prioritizing sub-watersheds, common sub- watersheds such as SW-1, SW-10, and SW-15 were classified under moderate priority, while SW-5, SW-8, and SW-14 were classified under the lowest priority. The results of this study, particularly the prioritization of sub-watersheds, can be instrumental for hydraulic engineers in planning and managing water resources in the Panzara river basin.

Improving the identification of pollution source areas with catchment-resolution sensitivity analysis

The significant impacts of total nitrogen (TN) and total phosphorus (TP) on riverine ecosystems underscores the critical need to identify the primary nutrient source areas in watersheds. This study aims to unravel the influences of terrain and land use types on mean monthly TN (TNM) and mean monthly TP (TPM) export across varying catchment resolutions in the Qiantang River Watershed of China. The findings of this study illuminated the critical role of topography in understanding nutrient dynamics, wielding a profound influence over water flow patterns and nutrient dispersion. Both land slope and Stream Power Index (SPI) displayed substantial negative correlations (r < −0.6) with TNM and TPM concentrations, whereas the Topographic Wetness Index (TWI) showed positive correlations with the nutrient indexes. In addition to terrain characteristics, impervious land surfaces had a positive correlation with nutrient concentrations, while grassland and forest areas exhibited negative correlations. Results further underscored the substantial influence of catchment resolution on correlations between watershed properties and riverine nutrient concentrations. It was imperative to choose an effective catchment resolution in watershed delineation – not too coarse, nor too fine – to accurately capture the topographic and land use impacts on nutrient dynamics. With the most appropriate catchment size (Catchment 700 km2), the critical pollution source areas for TN and TP pollution were identified, and thus could be used to guide future pollution reduction efforts. The study not only highlights the importance of identifying an appropriate catchment size for water pollution, but also emphasizes the necessity of effectively extracting critical pollution source areas to mitigate water nutrient pollution and increase the ecological integrity of the Qiantang River Watershed.

PAVLIB4SWAT: a Python analysis and visualization tool and library based on Kepler.gl for SWAT models

Abstract The Soil and Water Assessment Tool (SWAT) has been widely applied to simulate the hydrological cycle, investigate cause-and-effect relationships, and aid decision-making for better watershed management. However, the software tools for model dataset analysis and visualization to support informed decision-making in a web environment are not considered fully fledged and are technically intensive to implement. This study focuses on addressing these issues by establishing a tool and library (named PAVLIB4SWAT) that can largely reduce technical expertise requirements for developers to adopt and customize this work to their own demands. Specifically, we created PAVLIB4SWAT based on a Kepler.gl widget to visualize SWAT model data, including shapefiles from the watershed delineation process, model inputs, and simulated results via dynamic and interactive maps. We evaluated PAVLIB4SWAT through a Jinjiang watershed SWAT model use case to demonstrate its utility and ease of adoption. The case study shows that PAVLIB4SWAT can provide various geospatial analysis and mapping functionalities for SWAT models and can flexibly distribute visualized results as standalone offline web pages and web servers. In addition, PAVLIB4SWAT was designed as an open-source project and implemented purely in the Python programming language; thus, developers can easily adapt and customize it to suit their demands.

Estimation of Runoff by SWAT Model in Noyyal River Basin

Accurate assessment of water balance components holds paramount importance for the sustainable management of water resources in river basins. This study specifically concentrates on the application of the Soil and Water Assessment Tool (SWAT) model to evaluate water balance elements within the Noyyal River basin, a tributary of the Kaveri River originating from the Vellingiri hills in Western Tamil Nadu grapples with escalating water stress brought about by both anthropogenic activities and climatic fluctuations.&#x0D; The methodology adopted encompasses the harmonious integration of diverse spatial and temporal datasets. These datasets are seamlessly incorporated within the confines of a Geographic Information System (GIS) framework. Through the process of watershed delineation 21 sub-basin was partitioned and which is further subdivided into 217 unique Hydrological Response Units (HRUs) are derived, each corresponding to a distinct hydrological reaction. The simulation employs 33 years of daily precipitation, coupled with minimum and maximum temperature records, enabling the continuous execution of the SWAT model for runoff prediction. The findings elucidate fluctuating runoff volumes over time, spanning from a minimum of 11.17 mm to a maximum of 610.32 mm. Notably, the annual average runoff stands at 206.7 mm, representing approximately 25.6% of the cumulative rainfall experienced within the Noyyal river basin.

Automatic Extraction of Watershed Model by using Python Programming

In earlier days, watershed delineation was mainly conducted by the method of hand delineation. Now a days GIS tools are being widely used for delineation of watershed boundary and identifying stream network. The advancements and new techniques in information technologies are making it possible to acquire large-scale spatial data through satellite data, elevation models with help of user-friendly programming. Watershed delineation is a process for creating a boundary that represents the contributing area for a specific control point or water outlet, with the intent of characterization and analysis of portions of a study area. Although many GIS tools and software are available for watershed analysis, there is a need for optimized libraries for client-side and for better illustration of data in interactive environment for hydrological data analysis. In this connection, presently we are developing a model for the automatic delineation of watershed area from Shuttle Radar Topographical Mission (SRTM) digital elevation model by using Python program. The data required by the model are digital elevation and the spatial coordinate of spill way, outlets etc. In this project, we can be developed and demonstrated several watershed delineation techniques on large scale by using Python programming.

Ascertainment of Hydropower Potential Sites Using Location Search Algorithm in Hunza River Basin, Pakistan

The recent energy shortfall in Pakistan has prompted the need for the development of hydropower projects to cope with the energy and monetary crisis. Hydropower in the northern areas is available yet has not been explored too much. Focusing on the sustainable development goal (SDG) “Ensure access to affordable, reliable, sustainable and modern energy”, thirteen proposed sites were selected from upstream to downstream of the Hunza River for analysis. The head on all the proposed sites was determined by taking the elevation difference between the proposed turbine and the intake at all sites. The discharge on all proposed ungauged sites was determined using ArcGIS for watershed delineation and the area ratio method along with Soil Conservation Service–Curve Number (SCS-CN) by using gauged data of Hunza River provided by Water and Power Development Authority (WAPDA) Pakistan at Daniyor bridge Gilgit, Shimshal and the Passo tributaries of Hunza River. The Location Search Algorithm (LSA) approach used a multi-criteria decision-making tool (MDM) to make a decision matrix considering the location and constraint criteria and then normalizing the decision matrix using benefit and cost criteria, the relative weights were assigned to all criteria using a rank sum weighted method and the sites were ranked on the basis of the final score. The results revealed that Hunza River has a significant hydropower potential and based on the final score in the LSA approach, proposed site 13, site 4 and site 9 were concluded as the most promising sites among proposed alternatives. The proposed methodology could be an encouraging step for decision makers for future hydropower development in Pakistan.

BasinMaker 3.0: A GIS toolbox for distributed watershed delineation of complex lake-river routing networks

BasinMaker 3.0: A GIS toolbox for distributed watershed delineation of complex lake-river routing networks

The Delineation of Watersheds in the Dhenkanal District, Odisha, India; Using Arc-GIS

The watersheds of the Dhenkanal district of Odisha, India with the centrally flowing, river Brahmani identified and explored. The watersheds added with anthropogenic stresses are unattended that affect the land, hydrology, ecology, vegetation, and fertility of the soil. Population growth, migration to cities, challenges, continuous disasters, and anthropogenic stresses block the growth.&#x0D; The Arc GIS software and its Hydrology toolset were utilized. The Digital Elevation Model is used to scale various maps like flow direction, stream order, flow accumulation, Stream features, Pour points, and watershed maps of the district. The Rengali Dam, and Samal barrage of the Brahmani system and its left and right canal system have a positive impact on watersheds on both sides of the river Brahmani but the surface and groundwater are polluted by industrial effluents. &#x0D; The watersheds in transition ridges of the Mahanadi and the Baitarani basin of the Brahmani basin have been poorly attended in Dhenkanal. Construction of farm ponds, groundwater recharge units, soil conservation activities, renovation, and new construction of waterbodies can cater to and care for the land, water, and vegetation of the district. It is high time to prepare large-scale maps by modern survey techniques (UAV, drones, GIS, and GPS) and the observed data used to identify, delineate, prioritize, and plan for sustainable environment management considering availability v/s demand of water through Integrated Watershed Management in the district.

Development and evaluation of a method to identify potential release areas of snow avalanches based on watershed delineation

Abstract. Snow avalanches are a prevalent threat in mountain territories. Large-scale mapping of avalanche-prone terrain is a prerequisite for land-use planning where historical information about past events is insufficient. To this aim, the most common approach is the identification of potential release areas (PRAs) followed by numerical avalanche simulations. Existing methods for identifying PRAs rely on terrain analysis. Despite their efficiency, they suffer from (i) a lack of systematic evaluation on the basis of adapted metrics and past observations over large areas and (ii) a limited ability to distinguish PRAs corresponding to individual avalanche paths. The latter may preclude performing numerical simulations corresponding to individual avalanche events, questioning the realism of resulting hazard assessments. In this paper, a method that accurately identifies individual snow avalanche PRAs based on terrain parameters and watershed delineation is developed, and confusion matrices and different scores are proposed to evaluate it. Comparison to an extensive cadastre of past avalanche limits from different massifs of the French Alps used as ground truth leads to true positive rates (recall) between 80 % and 87 % in PRA numbers and between 92.4 % and 94 % in PRA areas, which shows the applicability of the method to the French Alps context. A parametric study is performed, highlighting the overall robustness of the approach and the most important steps/choices to maximize PRA detection, among which the important role of watershed delineation to identify the right number of individual PRAs is highlighted. These results may contribute to better understanding avalanche hazard in the French Alps. Wider outcomes include an in-depth investigation of the issue of evaluating automated PRA detection methods and a large data set that could be used for additional developments, and to benchmark existing and/or new PRA detection methods.

Spatial analysis of malaria hotspots in Dilla sub-watershed: Western Ethiopia.

This study aimed to examine the spatial variations in malaria hotspots along Dilla sub-watershed in western Ethiopia based on environmental factors for the prevalence; and compare the risk level along with districts and their respective kebele. The purpose was to identify the extent of the community's exposure to the risk of malaria due to their geographical and biophysical situations, and the results contribute to proactive interventions to halt the impacts. The descriptive survey design was used in this study. Ethiopia Central Statistical Agency based meteorological data, digital elevation model, and soil and hydrological data were integrated with other primary data such as the observations of the study area for ground truthing. The spatial analysis tools and software were used for watershed delineation, generating malaria risk map for all variables, reclassification of factors, weighted overlay analysis, and generation of risk maps. The findings of the study reveal that the significant spatial variations in magnitudes of malaria risk have persisted in the watershed due to discrepancy in their geographical and biophysical situations. Accordingly, significant areas in most of the districts in the watershed are characterized by high and moderate in malaria risks. In general, out of the total area of the watershed which accounts 2773 km2, about 54.8% (1522km2) identified as high and moderate malaria risk area. These areas are explicitly identified and mapped along with the districts and kebele in the watershed to make the result suitable for planning proactive interventions and other decision making. The research output may help the government and humanitarian organizations to prioritize the interventions based on identified spatial situations in severity of malaria risks. The study was aimed only for hotspot analysis which may not provide inclusive account for community's vulnerability to malaria. Thus, the findings in this study needs to be integrated with the socio-economic and other relevant data for better malaria management in the area. Therefore, future research should comprehend the analysis of vulnerability to the impacts of malaria through integrating the level of exposure to the risk, for instance identified in this study, with factors of sensitivity and adaptation capacity of the local community.

Determination of Parameters for Watershed delineation using various satellite derived Digital Elevation Models and its accuracy

&lt;p&gt;Digital Elevation Model (DEM) is an inevitable tool for many applications, such as natural resource management. In the present scenario, it is available with various resolutions from meter to sub-meter accuracy. These data are used extensively to explore the river basin's physical features by detecting and extracting watershed boundaries, elevation points, drainage networks, flow directions, and morphological parameters. Although many researchers have used DEMs to delineate the watershed boundaries of the river basin, accuracy makes the significant distinction and usage of various DEMs. In this study, the accuracy of watershed delineation derived from various open-source DEMs such as Shuttle Radar Topographic Mission (SRTM), Advanced Spaceborne Thermal Emission, and Reflection Radiometer (ASTER), Cartosat-1, and ALOS Palsar, in the vaigai river basin have been observed. The Arc SWAT hydrological modeling tool was used to delineate the watershed boundary using the DEMs mentioned above. Eventually, the outcome is validated with the help of base data received from TN-PWD (Tamilnadu Public Work Department). The results attained from the extraction of the watershed boundary from various DEMs reveal that the watershed boundary delineated from ALOS – Palsar is closely matching with the actual boundary of vaigai river basin. The regression analysis of the watershed on area and perimeter obtained from the ALOS Palsar DEM yielded R2 as 0.97 and 0.99. This R2 exhibits the close fitness of the predicted value with data obtained from TN-PWD data. The ALOS Palsar DEM provided low vertical errors and high vertical accuracy compared to other DEMs. Overall the ALOS Palsar DEM generated outcome exhibited comparatively better results than the rest of the DEMs.&lt;/p&gt;&#x0D;

High-performance watershed delineation algorithm for GPU using CUDA and OpenMP

Watershed delineation is one of the fundamental tasks in hydrological studies. Tools for extracting watersheds from digital elevation models and flow direction rasters are commonly implemented in GIS software packages. However, the performance of available techniques and algorithms often turns out to be far from sufficient, especially when working with large datasets. While modern hardware offers high computing performance through massive parallelism, there is still a need for algorithms that can effectively use these capabilities. This paper proposes an algorithm for rapid watershed delineation directly from flow direction rasters, using the possibilities offered by modern GPU devices. Performance measurements show a significant reduction in execution time compared to other parallel solutions proposed for this task in the literature. Moreover, this implementation makes it possible to delineate multiple watersheds from the same dataset simultaneously, each having one or more outlet cells, with virtually no additional computational cost.

Assessment of Land Cover and Land Use Change Dynamics in Kibwezi Watershed, Kenya.

Land use and land cover (LULC) parameters influence the hydrological and ecological processes taking place in a watershed. Understanding the changes in LULC is essential in the planning and development of management strategies for water resources. The purpose of the study was to detect changes in LULC in the Kibwezi watershed in Kenya, using geospatial approaches. Supervised and unsupervised classification techniques using remote sensing (RS) and geographical information system (GIS) were used to process Landsat imagery for 1999, 2009, and 2019 while ERDAS IMAGINE™ 14 and MS Excel software were used to derive change detection, and the Soil and Water Assessment Tool (SWAT) model was used to delineate the watershed using an in-built watershed delineation tool. The watershed was classified into ten major LULC classes, namely cropland (rainfed), cropland (irrigated), cropland (perennial), crop and shrubs/trees, closed shrublands, open shrubland, shrub grasslands, wooded shrublands, riverine woodlands, and built-up land. The results showed that LULC under shrub grassland, urban areas, and crops and shrubs increased drastically by 552.5%, 366.2%, and 357.1% respectively between 1999 and 2019 with an annual increase of 35.55%, 35.38%, and 33.86% per annum. The area under open shrubland and closed shrubland declined by73.7%, and 30.4% annually. These LULC transformations pose a negative impact on the watershed resources. There is therefore a need for proper management of the watershed for sustainable socio-economic development of the Kibwezi area.

Effects of digital elevation model data source on HSPF-based watershed-scale flow and water quality simulations.

Digital elevation models (DEMs) from different sources have been widely utilized in watershed modeling and environment management. Yet, little is known about how DEMs from different data sources affect modeling results and management decisions. This paper presents new insights into how the DEMs from three different sources affect model-simulated flow, nitrate (NO3), phosphorus (P), and sediment by using the BASINS/HSPF watershed modeling system. It was found that DEM source-induced uncertainties in simulation results are higher than the DEM resolution-induced uncertainties regardless of watershed slope or delineation method. Moreover, DEM source introduces higher uncertainties in simulation results for automatically delineated low-gradient watersheds than high gradient watersheds. Sediment and NO3 concentrations were the most and the least sensitive water quality parameters, respectively, to DEM sources. The uncertainties in simulation results may be reduced by using the manual method for watershed delineation but they cannot be completely eliminated. It is recommended that high precision (such as NED) DEMs be employed especially for flat watersheds. The findings provide guidelines for selection of DEM source based on available resources.

Mapping Groundwater Potential Zones Using Remote Sensing and GIS Techniques in Sainj River Sub-Watershed, Kullu, Himachal Pradesh

Ensuring availability of drinking and irrigation water for population living in mountainous environment has been an important challenge for researchers, spatial planners and policy makers. The identification and mapping of groundwater potential zones in such type of regions may prove a better input to meet this challenge. The present study is an attempt to find out the groundwater potential zones using state-of-the-art technologies of Remote Sensing (RS) and Geographic Information System (GIS) selecting a case study area of Sainj river sub-watershed (area 81 km 2 ) in Kullu of Himachal Pradesh, India. Landsat-8 (OLI) satellite data (October 2016, spatial resolution (30 m resolution) Survey of India (SOI) Toposheet (Scale 1:50,000) and GIS software ArcGIS version 10.5 were used to prepare various thematic layers such as Geology, Soil, Geomorphology, Land Use Land Cover (LULC), Slope, Lineament, and Drainage Density. The watershed delineation and contour lines (100 m interval) generation were performed using Digital Elevation Model (DEM). The LULC map was prepared through supervised classification using Support Vector Machine (SVM) method in ENVI 5.0 software. Spatial analyst tool of ArcGIS 10.5 was used to identify groundwater potential zones using weighted overlay method. The study indicates that the spatial variations in groundwater occurrence are largely controlled by geological structures, landforms and slope in the study area. The study also reveals the importance and usefulness of RS and GIS techniques for proper groundwater resource appraisal and mapping groundwater potential zones. The five groundwater potential zones were identified and mapped in the study area viz. very poor (1.1 km2, 1.36%), poor (7.3 km 2 ,9.03%), moderate to good (67.2 km 2 ,83.17%), good (4 km2,4.95%) and very good (1.2 km2,1.49%). The weathered / fractured quartzite, limestone, slate, schist, and phyllite, among other minerals, characterize the zone with very good groundwater potential. While, the granite, car-biotite, met basalt, and granite gneiss are commonly found in the zone, which has a moderate to good (medium) groundwater potential. Low groundwater zone locations are generally underlain by granitoid, gneisses, and migmatite.