Groundwater Monitoring Network Research Articles

A Multi-Objective Improved Hybrid Butterfly Artificial Gorilla Troop Optimizer for Node Localization in Wireless Sensor Groundwater Monitoring Networks

A Multi-Objective Improved Hybrid Butterfly Artificial Gorilla Troop Optimizer for Node Localization in Wireless Sensor Groundwater Monitoring Networks

Unraveling aquifer dynamics: Time series evaluation for informed groundwater management

Optimizing groundwater monitoring networks is essential for the sustainable management of this critical resource, which is vulnerable to both anthropogenic and natural changes. Focusing on the Hashtgerd aquifer in Iran, this research aims to enhance the efficiency of groundwater level monitoring systems by integrating statistical methods, artificial intelligence (AI), and hydrogeological studies. The study's core objective is to pinpoint and comprehend the factors that cause certain observation wells to become isolated from the main aquifer body, leading to parts of the aquifer being cut off from the central hydrogeological system. Employing clustering techniques on data from 29 observation wells, based on parameters like groundwater level (GWL), groundwater level change (GWLC), groundwater depth (GWD), air temperature (AT), distance (D), ground level (GL), and temperature (T) through Hierarchical Cluster Analysis (HCA), the research categorizes the groundwater information into four distinct groups. Significantly, Cluster 4 encompasses wells with similar characteristics. The analysis reveals that two wells, categorized in Clusters 1 and 2, exhibit unique behaviors, likely due to their connection to local karstic aquifers, as corroborated by geological evidence. Cluster 3's separation is determined through geophysical investigations, identifying confined conditions near specific wells, notably Wells 4 and 8. AI techniques further distinguish differences in meteorological influences and water discharges among the clusters, noting minimal weather impact on Clusters 1 and 2, considerable shallow groundwater influence on Cluster 3, and a pronounced effect of groundwater discharge on Cluster 4. This nuanced identification of aquifer segments disconnected from the main system underscores the need to refine monitoring networks for accurate assessment of groundwater resources. By leveraging a detailed analysis of aquifer complexities through state-of-the-art methodologies, the study guides towards informed, sustainable groundwater management strategies.

Hydrogeochemical processes as a conditioner of freshwater lenses associated with coastal deposits

AbstractThe aim of this work was to study the processes and factors conditioning the hydrochemistry of freshwater lenses associated with Holocene coastal deposits in an area of the Argentinean Atlantic coast. For this purpose, geomorphological units were mapped and a shallow groundwater monitoring network was established, including pre‐existing boreholes and shallow exploration wells. During the construction of the shallow exploration wells, sediment samples were extracted to determine the texture and mineralogical characteristics. Four samplings were carried out to measure in situ physicochemical parameters and to determine majority ions in the water. The chemical data were analysed considering the associated geomorphology, lithology, water balance and hydrodynamics. The geomorphological and lithological characteristics are the combined factors that favour the preferential rainwater recharge processes. Geoforms with greater topography and extension (continental and coastal dunes) tend to store freshwater lenses, while those with lower topography and little areal extension (sand sheets and beach ridges) have very thin lenses and tend to become salinized. Climate and local water balance are factor that determines that groundwater recharge occurs preferentially in winter. This causes increases in groundwater levels and a decrease in the groundwater EC. On the other hand, mineralogy is a factor that conditions the geochemical processes associated with the water–sediment interaction. Within the main geochemical processes, the dissolution and/or mineral weathering, the dissolution of CO2(g) and ion exchange determine the presence of different hydrochemical facies, where Ca‐HCO3 facies dominates in elevated geoforms, while Na‐Cl in lower ones. The results obtained in this work have provided an understanding of the factors and processes that condition groundwater chemistry in coastal deposits, being of vital importance for the management of water resources.

Groundwater governance and a snapshot of associated issues in selected coastal communities in Ghana

Groundwater is an important freshwater resource worldwide, particularly in coastal communities where it is scarce and often ignored. In Ghana, there is increasing dependence on groundwater, yet assessment of groundwater governance is rare. This study assessed the status of groundwater governance and identified existing gaps in Ghana. Groundwater-associated issues in four coastal communities (Essiama, Winneba, Korle Lagoon catchment area of Accra, and Keta) were assessed. Review of policy documents and expert-based assessment were employed to assess groundwater governance status and gaps while field observations, focus group discussions with community leaders, risk-priority matrix, and Nemerow's pollution index were employed to obtain a snapshot of local conditions that impact groundwater at the community level. Review of policy documents and expert-based assessment of groundwater governance capacity revealed that technical capacity, cross-sector policy coordination, and operational capacity were incipient, while legal and institutional capacity was acceptable. Overall, groundwater governance capacity in Ghana was shown to be incipient. Major gaps identified were (i) inadequate enforcement of groundwater policies, (ii) poor monitoring, (iii) poor technical and operational capacity, (iv) low cooperation within the water sector and across other sectors, and (v) poor public participation in water governance. The study revealed groundwater as an important resource in the studied coastal communities, where accessing potable water comes with some difficulties. Knowledge of groundwater policies was low, while there was no groundwater monitoring network in the communities. Furthermore, poor microbiological and chemical status of groundwater was observed. These findings suggest a need to build capacity in groundwater governance and to ensure robust public education on groundwater governance in Ghana.

Calling All Groundwater Professionals: Support the National Groundwater Monitoring Network.

Calling All Groundwater Professionals: Support the National Groundwater Monitoring Network.

Hydrogeochemistry of the shallow aquifer in the western Po Plain (Piedmont, Italy): spatial and temporal variability

ABSTRACT This paper describes the spatial and temporal variability of the hydrogeochemistry of shallow aquifer in the western Po Plains, located in Piedmont (northwestern Italy), using groundwater monitoring network data for the main chemical–physical parameters. Hydrochemical maps for the 2015–2020 period were created to identify the main natural and anthropogenic factors responsible for the remarkable spatial variability. Temporal variations in the 2000–2020 period were defined to show the existence of variabilities that were previously not investigated. The spatial and temporal elaborations show significant and various variabilities. The hydrochemical maps confirm the existence of several natural and anthropogenic factors, including the lithological compositions of aquifers, agricultural practices and pressure from urban centres. The temporal variations suggest different resilience capacities of the aquifers to the several impacting factors. The availability of this knowledge is crucial to create the basis for groundwater protection.

Data-driven statistical optimization of a groundwater monitoring network

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurface hydrology and to assess water resources management and protection. Here, the basic idea to optimize the efficiency of existing gauging networks is to identify correlated timeseries to guide the removal of redundant measurement sites. Three data-driven statistical methods are compared: Oscillation correlation (OC) hierarchical (HC) and timeseries clustering (TSC). These methods are applied to a hydrogeologically complex groundwater system within the Bacchiglione basin (IT). Results suggest that: (i) the OC method returns well-gathered correlation clusters while being fast and easy to apply; (ii) HC underpins more spread clusters but it is useful when considering multiple groundwater characteristics; and (iii) TSC proves the best performing method for the study area, at the cost of being the most complex to implement. The latter identified 30 out of 59 existing timeseries as redundant, i.e., where sensors might be relocated elsewhere thus gaining in information quality (or else simply saving money if dismissed). We also suggest that the microscale of a random piezometric head field is a suitable measure to extract from data the monitoring frequency of manual measures in dismissed locations.

Assessing Terrestrial Water Storage Variations in Southern Spain Using Rainfall Estimates and GRACE Data

This paper investigates the relationship between rainfall, groundwater and Gravity Recovery and Climate Experiment (GRACE) data to generate regional-scale estimates of terrestrial water storage variations in the Andalucía region of southern Spain. These estimates can provide information on groundwater depletion (caused by periods of low rainfall or droughts) and groundwater recovery. The spatial distribution of groundwater bodies in southern Spain is complex and current in situ groundwater monitoring methods are deficient, particularly in terms of obtaining representative samples and in implementing and maintaining groundwater monitoring networks. The alternative approach proposed here is to investigate the relationship between precipitation time series and changes in the terrestrial water storage estimated from GRACE observations. The results were validated against the estimated fluctuation in regional groundwater. The maximum correlation between the mean groundwater level and the GRACE observations is 0.69 and this occurs at a lag of one month because the variation in gravity is immediate, but rainfall water requires around one month to travel across the vadose zone before it reaches the groundwater table. Using graphical methods of accumulated deviations from the mean, we show that, in general, groundwater storage follows the smooth, multi-year trends of terrestrial water storage but with less short-term trends; the same is true of rainfall, for which the local trends are more pronounced. There is hysteresis-like behaviour in the variations in terrestrial water storage and in the variations of groundwater. In practical terms, this study shows that, despite the abnormal dryness of the Iberian Peninsula during the 2004–2010 drought, the depleted groundwater storage in Andalucía recovered almost to its pre-drought level by 2016. In addition, groundwater storage and terrestrial water storage show very similar trends but with a delay in the groundwater trend.

Analysis of nationwide groundwater monitoring networks using lumped-parameter models

Many countries maintain nationwide groundwater networks to monitor the status of their groundwater resources. For effective groundwater resource management, it is fundamental to understand the groundwater dynamics measured in the individual monitoring wells. Nationwide monitoring networks typically cover multiple aquifer systems with different degrees of environmental complexity. The analysis of the data of such networks thus requires flexible modeling approaches. In this study, we assessed the applicability and performance of lumped-parameter models using impulse response functions, as implemented in the Pastas software, to simulate hydraulic head data from the nationwide groundwater monitoring network in Switzerland. The selected 28 monitoring wells in the network are situated in unconsolidated, relatively shallow aquifers across Switzerland. Given the very diverse topography in the study area, snowmelt processes affect some aquifers, while groundwater–surface water interactions are important in the valleys. Different linear and nonlinear models were tested to take precipitation and potential evaporation into account, with a new model developed as part of this study to account for the effect of snow processes on recharge generation. After generally good fits in both the calibration and evaluation were achieved, the models were used to identify and quantify which stresses (e.g., precipitation, river stages) control the groundwater dynamics. The results show that precipitation and evaporation explain large parts of the measured dynamics, and about half of the monitoring wells in the network appear to be influenced by river stages. Explicitly accounting for snow processes in the recharge generating process is found to improve the simulation of the head dynamics across Switzerland, particularly for wells in high-altitude aquifers. This study demonstrates for the first time the applicability of lumped-parameter models using impulse response functions to model heads in Switzerland, and more generally, in climatic settings where snow processes are impacting the head dynamics.

Geostatistical based optimization of groundwater monitoring well network design

Monitoring groundwater quality in economically important and other aquifers is carried out regularly as part of regulatory processes for water and other resource development. Many water quality parameters are measured as part of baseline monitoring around mining and onshore gas resource development regions to develop improved understanding of the hydrogeological system as well as to inform managerial decisions to assess and manage contamination risks and health hazards. Water quality distribution in an aquifer is most often inferred from point measurements from limited number of bores drilled at arbitrary locations. Estimating the distribution of water quality parameters in the aquifer based on these point measurements is often a challenging task and results in high uncertainty in the estimates due to limited data availability. Minimizing uncertainty can be achieved by drilling more bores to collect water quality data and several approaches are available to identify optimal bore hole locations to minimize estimation uncertainty. However, optimization of borehole locations is difficult when multiple water quality parameters are of interest and have different spatial distributions in the aquifer. In this study we use geostatistical kriging to interpolate a large number of groundwater quality parameters. Then we integrate these predicted values and use the Differential Evolution algorithm to determine optimal locations for bores that would simultaneously reduce spatial prediction uncertainty of all parameters. The method is applied for designing a groundwater monitoring network in the Namoi region of Australia for monitoring groundwater quality in an economically important aquifer of the Great Artesian Basin. Optimal locations for 10 new monitoring bores are identified using this approach.

Shallow groundwater temperature patterns revealed through a regional monitoring well network

AbstractGroundwater temperature is a critical control on groundwater quality, geothermal system efficiency and ecosystem dynamics in receiving surface waters. Despite the known importance of groundwater temperature, there is a lack of dedicated aquifer thermal monitoring across spatial and temporal scales. Pressure transducers and other sensors installed in groundwater monitoring well networks often record temperature as a secondary function, but these comprehensive groundwater temperature data sets are seldom analysed. In this study, we analysed seasonal, interannual and spatial patterns of shallow groundwater temperatures from a regional groundwater monitoring network in Nova Scotia, Canada and compared these subsurface temperature data to air temperature data from nearby climate stations using linear regressions and Fourier analysis. The results showed that seasonal groundwater temperatures were damped (with seasonal amplitudes 3.6%–42% of air temperature amplitudes) and lagged (phase shifted 43–145 days) compared to air temperature, with notable year‐to‐year variations in both damping and lagging. Results also highlighted the role of snowpack thickness on the lowest mean monthly groundwater temperatures. Given potential impacts of climate change, land cover change, urbanization and geothermal energy development on groundwater temperatures, we encourage water authorities and regulators to begin or enhance aquifer thermal monitoring and provide guidance for capitalizing on existing monitoring well infrastructure to track temperature dynamics and changes.

Large‐Scale Groundwater Monitoring in Brazil Assisted With Satellite‐Based Artificial Intelligence Techniques

AbstractHere, we develop and test an artificial intelligence (AI)‐based approach to monitor major Brazilian aquifers. The approach combines Gravity Recovery and Climate Experiment (GRACE) data and ground‐based hydrogeological measurements from Brazil's Integrated Groundwater Monitoring Network at hundreds of wells distributed in 12 aquifers across the country. We tested model ensembles based on three AI approaches: Extreme Gradient Boost, Light Gradient Boosting Model and CatBoost, followed by a Linear Regression step. The approach is further boosted with wavelet and seasonal decomposition processes applied to GRACE data. To determine the AI‐based model's sensitivity to data availability, we propose four experiments combining hydrogeological measurements from different aquifers. Groundwater storage (GWS) estimates from the Global Land Data Assimilation System (GLDAS) are used as benchmark. A sensitivity analysis shows that the LR‐based model ensemble is the best suited and to reproduce GWS change in all studied Brazilian aquifers. Results show that the proposed approach outperforms GLDAS in all experiments, with an root mean square error (RMSE) value of 2.68 cm for the experiment that covers all monitored wells in Brazil. GLDAS resulted in RMSE = 6.76 cm. Using our AI model outputs, we quantified the GWS change of two major aquifers, Urucuia and Bauru‐Caiuá, over the past two decades: −31 and −6 km3, respectively. Water loss is driven by a prolonged drought across most of the country and intensification of groundwater pumping for irrigation. This study demonstrates that combining satellite data and AI can be a cost‐effective alternative to monitor poorly equipped aquifers at the continental scale, with possible global replicability.

Well-Drilling and Groundwater Monitoring Network Construction Taking Changde City as an Example

Entrusted by the Environmental Protection Bureau of Changde City we conducted drilling sampling survey and constructed a monitoring network for groundwater in several counties and districts of Changde City. This article introduces the drilling technology detection method and detection network layout plan adopted in the project and expounds the problems that occurred while executing the project in order to provide reference for similar groundwater capacity supervision and construction projects.

Effects of the 2021 La Palma volcanic eruption on groundwater resources (part I): Hydraulic impacts

The 2021 volcanic eruption in the Cumbre Vieja mountain range on La Palma Island (Canary Islands, Spain) raised concerns regarding the potential impact on groundwater resources. This study is the first part of a series of papers investigating those impacts, and focuses on the hydraulic impacts of the eruption, while subsequent papers will explore the geochemical consequences. Three boreholes equipped with sensors to measure hydraulic head, temperature, and electrical conductivity of groundwater were installed near the volcano. Monitoring started during the eruption and continued a year after it. Statistical analysis were performed to assess the relationship between the measured variables and real-time seismic-amplitude measurements (RSAM). In addition, the possibility of groundwater vaporization due to magma emergence was assessed with a groundwater flow numerical modelling of the island. Correlation coefficients were computed to assess the linear relationship between groundwater parameters and seismic signals, observing a statistically significant association, and suggesting near-instantaneous variations in parameters such as groundwater levels and EC. Different response patterns of groundwater levels were observed in recharging areas in highlands compared to discharge areas, showing an opposite correlation direction. Deduction of natural trends from the linear regression models of head and RSAM two months after the eruption revealed a more predictable impact on the groundwater system, as the hydrogeological system adjusts to the volcanic activity and its effects on the aquifer. The hydrogeological simulation of the "magma pumping effect" suggested that groundwater extraction was possible, but the absence of an appropriate groundwater monitoring network made it impossible to determine the amount of water extracted from the aquifer. The uncertainty analysis showed values up to 2000 m3·day−1. These findings have important implications for understanding the negative impacts of volcanic eruptions on groundwater resources, highlighting the need for regular monitoring and assessment by hydrogeologists and water management professionals.

Groundwater Pollution Risk Assessment in Plain Area of the Yarkant River Basin

Groundwater pollution risk assessment is an effective method to manage groundwater resources and prevent groundwater pollution. The DRSTIW model was used to evaluate the groundwater vulnerability in a plain area of the Yarkant River Basin, and factor analysis was used to identify pollution sources for pollution loading evaluation. The functional value of groundwater was estimated by considering both the mining value and the in-situ value. The entropy weight method and the analytic hierarchy process (AHP) were used to determine the comprehensive weight, and a groundwater pollution risk map was generated based on the overlay function of ArcGIS software. The results showed that the natural geological factors such as large groundwater recharge modulus, wide recharge sources, strong permeability of soil surface and unsaturated zone, and shallow groundwater depth facilitated pollutant migration and enrichment, resulting in a higher overall groundwater vulnerability. Very high vulnerability and high vulnerability areas were mainly distributed in Zepu County, Shache County, Maigaiti County, Tumushuke City, and the eastern part of Bachu County. The pollution loading of groundwater was generally low, the main pollution sources were point source pollution caused by water-rock interaction, non-point source pollution caused by pesticides and fertilizers, and point source pollution caused by industry and life. The overall functional value of groundwater was low because of human economic activities, fine water quality, and good habitat quality. Groundwater pollution risk was generally low, and very high and high pollution risk areas accounted for 20.7% of the study area, mainly distributed in Shache County, Zepu County, Maigaiti County, Tumushuke City, and the western part of Bachu County. Natural conditions such as strong aquifer permeability, weak groundwater runoff conditions, large groundwater recharge modulus, low vegetation coverage, and strong water-rock interaction, coupled with frequent human activities such as application of agricultural fertilizers and discharge of industrial and domestic sewage, made the groundwater pollution risk higher in these areas. Groundwater pollution risk assessment provided strong data support for the optimization of the groundwater monitoring network and the prevention of groundwater pollution.

Design of preliminary groundwater monitoring networks for the coastal Tra Vinh province in Mekong Delta, Vietnam

Study RegionThe study region is the coastal Tra Vinh province located in Mekong Delta, Vietnam Study FocusThe objective of the study is to design preliminary monitoring networks for groundwater level and salinity monitoring in the three heavily abstracted aquifers in the Tra Vinh province. Since data from the existing monitoring were insufficient to explore variogram analysis and subsequent Kriging interpolation for the network design, groundwater flow and saltwater transport models were constructed to create groundwater level and salinity distributions. An iterative procedure was adopted to select monitoring well locations based on the contour maps of groundwater levels and total dissolved solids (TDS) constructed from the groundwater models. The standard deviation of Kriging interpolation error was used as the criteria to assess the quality of the designed monitoring networks. Priorities for the locating groundwater level monitoring wells were targeted in areas with cones of depression and boundaries, while priorities for salinity monitoring were given to coastal zone and inland fresh/saltwater interfaces. New Hydrological Insights for the RegionGroundwater overexploitation has resulted in storage depletion and saltwater intrusion in the Tra Vinh province. Simulations from the numerical models determined the cones of the depression and predicted intrusion from inland saltwater trapped in clays from past marine transgressions and from seawater in the coastal zone. A limited number of monitoring wells is operated and is insufficient to delineate the cone of depression and fresh/salt water interfaces. This study combined the numerical model simulation results and Kriging interpolation method and designed preliminary groundwater level and salinity monitoring networks for the Tra Vinh province. Once the designed networks are implemented, observed data from the networks will provide valuable information for sustainable groundwater resources management in Tra Vinh province. Data availabilityAll data generated or analyzed during this study are available upon request from the corresponding author.

Hydrogeological characteristics and water availability in the mountainous aquifer systems of Italian Central Alps: A regional scale approach

Groundwater resources in mountain areas are strategically important to maintain adequate water supply for domestic uses, farming, industrial activities, and energy production, also considering the expected growing demand due to ongoing climate changes. Within this framework, the objective of the study is to develop a regional approach, compliant with the European requirements of the Water Framework Directive 2000/60/EC and Groundwater Directive 2006/118/EC, that could support public agencies and water companies to efficiently manage and protect the available water resources in mountainous environments.The proposed approach identifies and delineates groundwater bodies by coupling a 3D hydro-stratigraphic model with the definition of the water budget and water hydrochemical fingerprints in a geologically complex Alpine environment in Northern Italy. Sixteen groundwater bodies (GWBs) have been identified all over the 10.290 km2 area, showing an average storage capacity of more than 500 Mm³ y−1 (about 3% of the average total inflow from precipitation and snowmelt), with differences up to four times between GWBs mainly constituted of carbonate rocks and those prevalently composed of crystalline or terrigenous rocks. Groundwater quality in the study domain is generally excellent, with few exceptions due to geogenic (i.e., natural) or anthropogenic sources of contamination. The results of this study show the advantages of coupling 3D hydro-stratigraphic modelling combined with meteorological, hydrological and hydrogeological information, which consist in: i) identifying the most Strategic Storage Reservoir both in terms of quality and storage capacity; ii) evaluating the present ground- and surface water availability; iii) detecting areas of specific interest for implementing groundwater monitoring networks; iv) recognising recharge areas of the most relevant springs, to implement protection strategies of the resource.

Groundwater level monitoring of Danish chalk and limestone aquifers to survey trends in quantitative status and groundwater resources

Abstract Chalk and limestone aquifers contribute one-third of the drinking water supply in Denmark, and one-sixth of that national groundwater resource is assessed as having a ‘Poor’ status in terms of the quantitative Water Framework Directive due to intensive abstraction. This paper describes the national groundwater level monitoring network with regard to the following three applications: (1) when used for the annual surveying and reporting of groundwater resources and impacts from climate and groundwater abstraction; (2) as part of real-time monitoring and modelling for daily and seasonal forecasting; and (3) for tracking long-term climate change impacts on groundwater levels. Groundwater level monitoring provides a particularly important indicator of abstraction pressure and sustainable balance compared with recharge. Many larger chalk and limestone groundwater bodies in Denmark are only monitored by local water companies and not represented in the national groundwater level network. This raises the concern that current national groundwater level monitoring does not fully support integrated modelling and assessment purposes for chalk and limestone groundwater bodies. This also implies that, for tracking long-term climate change and anthropogenic impacts on groundwater levels, the national groundwater monitoring network especially lacks long-term records with complete 30-year time-series for many intensively exploited large chalk and limestone aquifers.

Hydrochemical signatures of springs for conceptual model development to support monitoring of transboundary aquifers

Neighboring states sharing transboundary aquifers should carry out joint assessment of the common groundwater resources to fulfill the EU Water Framework Directive's and Water Convention's aims. Therefore, the establishment of a representative cross-border groundwater monitoring network is essential. The transboundary catchments of Estonia (EE) and Latvia (LV) are sparsely populated and feature a relatively scarce monitoring network. Springs are natural groundwater outflows that may represent a significantly greater catchment area than monitoring wells, and their monitoring is more cost-effective. But a thorough evaluation is required to select the most representative springs for particular groundwater bodies/transboundary aquifer systems. In this study, 59 springs were investigated in the EE-LV transboundary area for 37 hydrochemical parameters. Additionally, we assessed 32 monitoring wells to define the aquifer system end-members. In total 409 groundwater samples were analyzed. The sampled springs were pre-classified to one of the three aquifer systems: Quaternary (Q), Upper-Devonian (D3) and Middle/Upper-Devonian (D2). Significant differences among the pre-classified groups in terms of spring elevation, Q thickness and discharge were detected. Multivariate and machine learning techniques implementing barium as a tracer, were applied to link the studied springs to their main contributing aquifer systems. This study shows that the application of diverse hydrochemical and statistical methods help to evaluate the sources of spring water in an area with relatively homogenous groundwater chemistry. The developed conceptual models provide new generalized interpretation of transboundary aquifers, needed to improve groundwater monitoring networks in data-scarce areas using springs.

Groundwater Recharge Estimation in Upper Gelana Watershed, South-Western Main Ethiopian Rift Valley

Estimating the spatial and temporal patterns of groundwater recharge through integrated water balance modeling plays an important role in sustainable groundwater resource management. Such modeling effort is particularly essential for data-scarce regions, such as the Rift Valley Lake basin in the Basement Complex of Ethiopia, which has shallow aquifers, a proliferation of wells, and poor groundwater monitoring networks. A spatially distributed water balance model (WetSpass), along with GIS and remote sensing tools, was used for groundwater recharge estimation for its suitability and efficiency in data-scarce hydrogeological regions. The WetSpass model depicted a very good performance in simulating the groundwater recharge in the Upper Gelana watershed within the Rift Valley Lake basin. The water balance analysis revealed that about 7% of the mean annual rainfall is converted to groundwater recharge, and the remaining rainfall amounts are partitioned into surface runoff (19%) and evapotranspiration (75%). The model simulation outputs are also used to investigate the relative influences of biophysical driving factors on the water balance components. While the land use types had a greater influence on the actual evapotranspiration processes, the soil texture classes were the dominant factors in the surface runoff and groundwater recharge processes in the watershed. The groundwater recharge rates were found to be higher than 400 mm/yr in the central parts (Fisehagenent, Tore, and Gedeb) and lower than 165 mm/yr in the southern parts (Hageremariam) of the watershed. The areal proportions of the low, medium, and high recharging parts of the watershed are, respectively, estimated as 15%, 68%, and 17% of the watershed area. Therefore, the spatial and temporal patterns of groundwater recharge should be taken into consideration in developing a sustainable groundwater resources management plan for the Upper Gelana watershed. Managed aquifer recharge can be adopted in high and medium groundwater recharging parts of the watershed to capture stormwater runoff during the wet season to improve the groundwater supply during dry months. Furthermore, monthly groundwater withdrawals should be regulated according to the spatial and temporal patterns of the groundwater recharge in the watershed.