Spring Discharge Research Articles

Individual return patterns of spawning flannelmouth sucker (Catostomus latipinnis) to a desert river tributary

Tributaries provide temporal and spatial habitat heterogeneity in river networks that can be critical for parts of the life history of a species. Tributary fidelity can benefit individual fish undergoing spawning migrations by reducing time and energy spent exploring new areas and leveraging previous experience, but anthropogenic activities that fragment or degrade these systems can eliminate those benefits. We used multistate models based on passive integrated transponder (PIT) detection data from 2013 to 2023 to estimate the proportion of flannelmouth suckers (Catostomus latipinnis) migrating to a tributary, McElmo Creek, from the mainstem San Juan River for spawning. Survival varied among years and among states. The top model for migration probability included sex, with males slightly more likely to migrate (0.93 vs 0.90), and the next model identified interannual variation in migration probability ranging from 0.875 to 0.999 across years, indicating high site fidelity. Individuals showed consistency in relative arrival timing across years, with the highest correlation generally during years with greater spring discharge and extended tributary residence time. Successful tributary spawning may be important for the maintenance of the mainstem San Juan River flannelmouth sucker population, but site fidelity may be maladaptive where tributaries are vulnerable to human alterations.

Testing tree-ring cellulose δ18O with water isotopes for Holocene lake δ18O interpretations in the central Rocky Mountains USA

Stable isotopes of water preserved in geologic archives, primarily as oxygen (δ18O), have proven critical for documenting Earth’s climatic and hydrologic systems past and present. However, timescale differences of water isotope inputs to proxy systems and the signal embedded in long paleorecords often confound translation to observed hydroclimatic metrics. Here, a unique 20-year dataset of meteorology, hydrology, and the isotopic composition of weekly meteoric and surface water samples (δ18O, δ2H) are combined with paleoclimate δ18O data from tree-ring cellulose and lake carbonate to better understand proxy signals of Upper Colorado river basin drought. Annual tree-ring cellulose δ18O from Picea engelmannii growing within a glacier-fed creek and a spring discharge area were used to derive annual source water δ18O using a cellulose source-water isotope model. Comparisons with the monitoring record indicates that tree-ring cellulose δ18O tracks variations in wet and dry hydroclimatic extremes. Source water isotopes are shown to reflect the hydroclimate of the current year and some number of previous years as an effective moisture-discharge proxy rather than a precipitation isotope proxy. Results contextualize Holocene lake carbonate δ18O data. The contemporary-to-paleo comparison identifies changes in seasonal precipitation extremes during recent millennia and several earlier arid and monsoon-dominated Holocene periods that exceed the arid maximum of the calibration period.

Interpretable multi-step hybrid deep learning model for karst spring discharge prediction: Integrating temporal fusion transformers with ensemble empirical mode decomposition

Karst groundwater is a critical freshwater resource for numerous regions worldwide. Monitoring and predicting karst spring discharge is essential for effective groundwater management and the preservation of karst ecosystems. However, the high heterogeneity and karstification pose significant challenges to physics-based models in providing robust predictions of karst spring discharge. In this study, an interpretable multi-step hybrid deep learning model called selective EEMD-TFT is proposed, which adaptively integrates temporal fusion transformers (TFT) with ensemble empirical mode decomposition (EEMD) for predicting karst spring discharge. The selective EEMD-TFT hybrid model leverages the strengths of both EEMD and TFT techniques to learn inherent patterns and temporal dynamics from nonlinear and nonstationary signals, eliminate redundant components, and emphasize useful characteristics of input variables, leading to the improvement of prediction performance and efficiency. It consists of two stages: in the first stage, the daily precipitation data is decomposed into multiple intrinsic mode functions using EEMD to extract valuable information from nonlinear and nonstationary signals. All decomposed components, temperature and categorical date features are then fed into the TFT model, which is an attention-based deep learning model that combines high-performance multi-horizon prediction and interpretable insights into temporal dynamics. The importance of input variables will be quantified and ranked. In the second stage, the decomposed precipitation components with high importance are selected to serve as the TFT model’s input features along with temperature and categorical date variables for the final prediction. Results indicate that the selective EEMD-TFT model outperforms other sequence-to-sequence deep learning models, such as LSTM and single TFT models, delivering reliable and robust prediction performance. Notably, it maintains more consistent prediction performance at longer forecast horizons compared to other sequence-to-sequence models, highlighting its capacity to learn complex patterns from the input data and efficiently extract valuable information for karst spring prediction. An interpretable analysis of the selective EEMD-TFT model is conducted to gain insights into relationships among various hydrological processes and analyze temporal patterns.

Enhancing water management in Northern European lowland chalk streams: A parsimonious, high-resolution hydrological model using groundwater level as a proxy for baseflow

Study regionThe River Frome, a chalk stream in West Dorset, UK. Study focusHigh-resolution hydrological models are required to integrate with the current wave of high-frequency data and advance our understanding of pollutant sources, pathways, and sinks. This presents several challenges in chalk streams, as their high-permeability and unique hydrogeological characteristics often leads to complex models that are overparameterized and computationally burdensome. In this article, we develop a novel and parsimonious modelling approach to describe the surface hydrology for a chalk stream in high resolution (15-minute frequency, ≤ 100 m cross-section spacing), using groundwater levels as a proxy for spring discharges. New hydrological insights for the regionOur results show that chalk stream dry-weather flows can be simulated accurately and parsimoniously at high-resolution (Nash-Sutcliffe efficiency = 0.97, mean relative error = 2.86 %, for a five-year period). We also show that spring discharges are the dominant form of flow accretion in all seasons and are critical to dilute sewage treatment inputs during the ecological growing season, whilst runoff and quick-flow pathways in the river valley corridor contribute a small proportion to annual flow accretion (< 5.2 %). Due to its simplicity and few parameters to calibrate, this modelling approach has broad applicability in lowland permeable catchments. Management implications include expeditious investigations of high-resolution freshwater quality responses to pollution and informing abstraction limits to sustain robust ecological conditions.

A parsimonious model for springs discharge reconstruction and forecast for drought management: Lessons from a case study in Central Italy

Study regionKarst springs located in Central Apennine ridge (Central Italy), in the Tiber River basin. Study focusThe assessment of water availability is a key issue in a water supply system because of increasing drought and water scarcity events. Analysing and predicting the dynamic behaviour of groundwater resources is challenging to conceptualize and model, especially in poorly-monitored systems. A parsimonious model based on linear regression between the monthly spring discharge time series and Standardized Precipitation Index is proposed. The model is conceived for management purposes and suitable for users with a limited background in modelling techniques, who can take advantage from an initial knowledge of the aquifers hydrological regime. New hydrological insights for the regionThe model developed for long-term monitored springs is used to reconstruct the historical groundwater hydrographs and to make predictions for poorly-monitored springs with similar properties, exploiting the “similarity principle”. Results highlight the notable performance of this approach, which represents a useful tool for overcoming the limitations in spring discharge monitoring networks. Moreover, the tool is used to test forecast performance enabling water managers to develop a monthly early-warning system fostering a sustainable water resource exploitation and limiting the critical issues of the water supply system, especially during drought periods. Results are discussed from the perspective of the water utilities entrusted to manage their resources in the study region.

Spring water resources in the Tatra Mountains

The Tatra Mountains stand out as the wettest and most water-rich region in Poland. Despite this, limited studies addressed this issue, and current knowledge largely relies on data obtained in the mid-20th century, with a substantial lack of current estimates. This study aims to fill this gap by evaluating the contemporary water resources of springs in the Tatra Mountains. The study bases on the most recent hydrological mapping of 1,018 springs. The spring resources were evaluated using parameters such as the number of springs, specific runoff, and crenological index, analysed across different physiographic regions, tectonic units, and altitudinal zones. Our studies showed that the highest number of springs occurs in the Western Tatras (66%) between 1000 and 1400 m a.s.l., especially within the Sub-Tatric unit. Springs with discharges ranging from 0.1–1.0 dm3∙s−1 constitute approximately 70% of all springs but they contribute to only 8.1% of spring water resources. Total spring discharge amounted to 2726 dm3∙s−1 and was higher in the Western Tatras (1982.5 dm3∙s−1 than in the High Tatras (743.5 dm3∙s−1 . The specific runoff amounted to 12.9 dm3∙s−1 m−2 with the highest total runoff at altitudes occupied by the most abundant karst springs (1000–1100 m a.s.l.). The crenological index amounted to 4.8 springs∙km−2 and was higher in the Western Tatras (6.5 springs∙km−2) than in the High Tatras (4.9 springs∙kmup−2) . The analysis revealed that the only five largest karst springs, constituting a mere 0.5% of all springs, account for 65% of spring water resources in the Tatras.

Monitoring the Impact of Artificial Structure on Hydrogeological Environment: A Case Study of Hydraulic Tunnel at Pirot Hydropower Plant.

Artificial objects, particularly tunnels used for water transport under pressure, impact the geological and hydrogeological environment to a greater or lesser extent, and it is vital to assess their contributions to groundwater quality. Although tunnels are typically lined with concrete, their interaction with the hydrogeological environment intensifies over time. In this study, the detailed spatiotemporal monitoring of all hydrogeological features within the potential influence zone of the hydraulic tunnel of the Pirot Hydropower Plant has been conducted in order to determine the degree of interaction between the artificial object and the natural environment in real time, and to assess the correlation between monitored parameters. Natural conditions of the environment were defined, as well as potential changes through the observing groundwater regimes. The monitoring network included observations of groundwater regimes at seven springs located in close proximity to the hydraulic tunnel, within the tunnel, at three piezometers, and along the river, while methods employed were hydrological monitoring, physicochemical monitoring, and groundwater piezometer sensing. Cross-correlation analysis has been applied for assessing the impact of precipitation dynamics on the spring discharge regime. The results indicate a direct influence of the tunnel on the hydrogeological environment, proving the consistency and high correlation between the monitored parameters.

Spring Water pH in Forest Catchments Is Modified through Fluctuating Discharge under Climate Change

Over the course of industrialization in the 20th century, vast emissions of air pollutants have occurred. The exhaust gasses contain sulfur and nitrogen oxides, which are converted to sulfuric acid and nitric acid in the atmosphere. This causes acid rain to enter aquatic and terrestrial ecosystems, the most serious consequence of which is large-scale forest dieback across Europe and North America. However, through various political measures, the exhaust gasses have been reduced and, thus, acid rain and forest dieback were stopped. Nevertheless, the lingering effects of this pollution are still present today and are reflected in hydrochemistry. More recently, fluctuating precipitation regimes are causing additional stress to ecosystems in Central Europe. Climatic extremes are becoming more pronounced with climate change. Substantial differences between drought years and years with regular precipitation are directly altering the discharge of springs. Now, two overlapping and interacting syndromes of environmental pressures can be studied in these small catchments at a landscape scale: (1) acidification and (2) climate change. In this long-term study, the waters of 102 forest springs, located in two neighboring forest landscapes in north-eastern Bavaria, Germany (Frankenwald and Fichtelgebirge), were investigated over 24 years (1996 to 2020). By linking changes in pH values with changes in precipitation and spring discharge, we found that pH increases with decreasing discharge and decreasing precipitation. This effect was strongest in the Frankenwald compared to the Fichtelgebirge. We hypothesize that this temporal pattern reflects the longer residence time and, in consequence, the increased buffering of acidic interflow in small catchments during periods of drought. However, this should not be misinterpreted as rapid recovery from acidification because this effect fades in times of enhanced precipitation. We recommend that fluctuations in weather regimes be considered when investigating biogeochemical patterns throughout forest landscapes.

Impacts of Climate Change on Groundwater in the Al-Badan Sub-Catchment, Palestine: Analyzing Historical Data and Future Scenarios

Climate change is significantly impacting water resources, especially in arid regions. This study evaluates its effects on groundwater in the Al-Badan sub-catchment, Palestine, by analyzing hydroclimatic data from 1990 to 2020 and the future predicted climate change scenarios. Using the Mann-Kendall test and Sen’s slope estimator, a significant annual decline in annual precipitation of 125 mm and a temperature increase of 1.84 °C were observed, resulting in a spring discharge reduction of 1.2 MCM. Multiple linear regression analysis showed that a 10% increase in precipitation correlates with a 5% discharge increase, while a 1 °C rise in temperature results in a 2.3% discharge decrease. Future scenarios indicate significant changes: for 2040–2060, RCP2.6 forecasts average precipitation of 334.5 mm with temperatures at 18.5 °C, resulting in spring discharge of about 4.6 MCM. In contrast, RCP4.5 and RCP8.5 predict reductions in precipitation to 307.2 mm and 311.2 mm, respectively, with temperatures rising to 18.9 °C and 19.3 °C, leading to discharge declines to 4.2 MCM and 4.0 MCM. For 2080–2100, RCP2.6 anticipates 335.8 mm of precipitation and temperatures rising to 19.5 °C, resulting in average discharge of 4.5 MCM. RCP4.5 and RCP8.5 predict further declines in precipitation and discharge, underscoring the need for effective water management strategies.

Assessing the impact of climate change on spring discharge using hydrological modelling in Musanze District, Rwanda

Assessing the impact of climate change on spring discharge using hydrological modelling in Musanze District, Rwanda

A Fully Connected Neural Network (FCNN) Model to Simulate Karst Spring Flowrates in the Umbria Region (Central Italy)

In the last decades, climate change has led to increasingly frequent drought events within the Mediterranean area, creating an urgent need of a more sustainable management of groundwater resources exploited for drinking and agricultural purposes. One of the most challenging issues is to provide reliable simulations and forecasts of karst spring discharges, whose reduced information, as well as the hydrological processes involving their feeding aquifers, is often a big issue for water service managers and researchers. In order to plan a sustainable water resource exploitation that could face future shortages, the groundwater availability should be assessed by continuously monitoring spring discharge during the hydrological year, using collected data to better understand the past behaviour and, possibly, forecast the future one in case of severe droughts. The aim of this paper is to understand the factors that govern different spring discharge patterns according to rainfall inputs and to present a model, based on artificial neural network (ANN) data training and cross-correlation analyses, to evaluate the discharge of some karst spring in the Umbria region (Central Italy). The model used is a fully connected neural network (FCNN) and has been used both for filling gaps in the spring discharge time series and for simulating the response of six springs to rainfall seasonal patterns from a 20-year continuous daily record, collected and provided by the Regional Environmental Protection Agency (ARPA) of the Umbria region.

Evolution Characteristics of Heilongtan Spring Discharge and Its Response Law to Precipitation in Lijiang City, China

The contradiction between water supply and spring preservation issues is becoming increasingly apparent as Lijiang City develops. An investigation into the dynamic variations in the discharge rate of Heilongtan Spring in Lijiang City and the response law between the water level of the spring and precipitation is crucial for safeguarding the landscape water of Heilongtan Spring. This study employed linear regression analysis, Mann–Kendall (MK) mutation test, wavelet analysis, and vector autoregression (VAR) to examine the fluctuating pattern of the Heilongtan Spring discharge and the response of the Heilongtan Spring water level to precipitation in Lijiang City. Furthermore, the study discussed the influence of human activities on the alteration of Heilongtan Spring. The results indicate that the mean discharge rate of Heilongtan Spring is 0.94 m3/s, with an annual variation of 0.05 m3/s. The time series analysis reveals that the variation pattern of Heilongtan Spring discharge aligns with the precipitation trend in Lijiang City. Nevertheless, there is a distinction between the timing of the Heilongtan Spring discharge station point and the precipitation mutation point in Lijiang City. The significant primary cycle of spring discharge change occurs every 18 months, with a cycle length of 12 months. The vector autoregression (VAR) model demonstrates a lagged relationship between the water level of Heilongtan Spring and the precipitation in Lijiang City. Specifically, the water level of Heilongtan Spring has a four-month lag response to precipitation variability in Lijiang City. The results can provide a beneficial reference for preserving spring water and managing regional water resources.

Influence of submarine groundwater discharge on the nutrient dynamics of a fringing-reef lagoon

Study regionThis study investigates nutrient distribution and flux dynamics in a coral reef lagoon in Quintana Roo, Mexico, located on a permeable limestone coast of the Mesoamerican Barrier Reef System. Study FocusEmphasis is placed on submarine groundwater discharge (SGD) as a crucial contributor to nutrient pathways, including ammonium (NH4+), nitrate and nitrite (NOx-), hydrogen silicate (HSiO3-), hydrogen phosphate (HPO42-), and urea. Inputs vary with SGD magnitudes and sources and by proximity to active spring discharges. Groundwater multi-tracer analysis and multiple linear regression identify 226Ra as explaining NH4+ variability due to long-term groundwater processes, while 223Ra predicts NOx-, HSiO3-, and urea due to short-term inputs. No significant relationship was found between HPO42- and any radium isotope, indicating complex behavior in coastal karst aquifers. New hydrological insights for the regionThe findings highlight complex nutrient dynamics in coastal karst settings, with SGD-derived fluxes primarily consisting of dissolved inorganic nitrogen (DIN) and HSiO3-. Although lower in concentration, HPO42- and urea fluxes are significant compared to other karst environments. Radium isotopes distinguish between short-term and long-term, as well as new and recycled nutrient inputs. Groundwater inputs transport fresh nutrients to healthier reefs, whereas processed, recycled inputs were detected near degraded reefs. These insights are essential for understanding global nutrient cycles and coral health, particularly in the context of global change and anthropogenic disturbances affecting coral reef ecosystems.

Springs of the Arabian Desert: Hydrogeology and Hydrochemistry of Abu Jir Springs, Central Iraq

The Arabian Desert is characterised by very low rainfall and high evaporation, yet over 210 springs are on its northeastern edge in central Iraq along the Abu Jir lineament, which represents the western depositional margin of a foreland basin infilled by the floodplain sediments of the Tigris and Euphrates Rivers; there is little evidence of faulting. The springs discharge from gently east-dipping Paleocene–Eocene limestones, either where groundwater flowpaths intersect the ground surface or where groundwater flow is forced to the surface by confining aquitards. Calculated annual recharge to the aquifer system across the Arabian Desert plateau (130–500 million m3) is significant, largely due to rapid infiltration through karst dolines, such that karst porosity is the primary enabler of groundwater recharge. The recharge is enough to maintain flow at the Abu Jir springs, but active management of groundwater extraction for agriculture is required for their long-term sustainability. The hydrochemistry of the springs is determined by evaporation, rainfall composition (high SO4 concentrations are due to the dissolution of wind-blown gypsum in rainfall), and plant uptake of Ca and K (despite the sparse vegetation). Limestone dissolution has relatively little impact; many of the springs are undersaturated with respect to calcite and lack tufa/travertine deposits. The springs at Hit-Kubaysa contain tar and high levels of H2S that probably seeped upwards along subvertical faults from underlying oil reservoirs; this is the only location along the Abu Jir lineament where deep-seated faults penetrate to the surface. The presence of hydrocarbons reduces the Hit-Kubaysa spring water and converts the dissolved SO4 to H2S.

A Simple Model of Flow Reversals in Florida’s Karst Springs

AbstractNorth Florida's karst springs are among the largest and most abundant in the world. Despite relatively stable spring discharges, flow reversals can episodically occur in some springs when river waters backflow into the aquifer during flood events. Reversals are normal features of the springs along the Suwanee River, but the changing incidence of these reversals in response to anthropogenic activities or climate change remains unclear and the mechanisms responsible for these reversals remain poorly described. Here we develop a reduced‐complexity hydrogeological model of the Suwannee River catchment to explore conditions needed to induce spring flow reversals. Our model demonstrates that reversals require two conditions: (a) a hydrogeological setting that combines an upstream catchment with rapid hydrological responses to meteorological drivers, which freely drains to a downstream catchment containing the karst aquifer (i.e., the spring‐fed river segment); and (b) meteorological conditions that create sufficient temporal variability in recharge. Given both conditions, recharge events can propagate from the upstream catchment and fill the downstream river segment faster than it can drain, causing river stage to rise above the aquifer head, resulting in temporary spring flow reversal (or bank storage). Our model accurately predicts significant post‐flood increases in spring flow as bank storage recedes, and using measured electrical conductivity at a major river‐adjacent spring we also quantify the enhancement of limestone dissolution (cave enlargement) due to reversal events. A comprehensive assessment of the incidence and duration of reversal events shows a predominant influence of climate and vegetation changes over that of groundwater pumping.

Potential Amplifiers of Hydrological Drought: A Deep Dive into the Seasonal Variations of New, Young, and Old Water Fractions in the Stream Discharge of a Pre-Alpine Catchment

This study examines runoff generation processes by focusing on new, young, and old water fractions in the stream discharge within the Swiss pre-Alpine Alp catchment and its smaller tributaries, Erlenbach and Vogelbach. Young water represents a contribution from the three most recent rainfall-runoff events. This research utilises a four-year time series of daily stable water isotope data from stream water and precipitation to investigate seasonal variations. An extended two-component hydrograph separation method is applied to analyse the catchment water and tracer mass balance across both the event and pre-event time axes. The calculated new, young and old water components in stream discharge help estimate time-varying backward travel time distributions. Factors such as air temperature, snow depth, and evapotranspiration data are considered to understand isotope fractionation because of phase changes. The results suggest that discharge generated in autumn and winter may have longer backward travel times compared with spring or summer discharge. Additionally, forest cover influences water fractions older than 40 days. The study identifies a nivo-pluvial runoff regime, with new water fractions peaking in August (Erlenbach, Vogelbach) and January (Alp). Young water fractions reach their highest levels at the start of winter and during snowmelt, while old water fractions peak towards the end of snowmelt and in mid-autumn. The Alp catchment and its tributaries exhibit higher new and young water components than old water following a month of low precipitation and high evapotranspiration in July. These findings are significant in light of the projected drier summers in Central Europe.

Geospatial AI solution to monitor and mitigate increasing adverse ecological and hydrological impacts of climate change in Uttarakhand Himalaya (India).

Though climate change and its adverse ecological and geohydrological impacts are being experienced across the world in all types of ecosystems but as far as the Himalaya mountain ecosystem is concerned, the rate of climate change and subsequent impacts have reached an alarming stage due to anthropogenic and technogenic intervention on natural process and now need most effective and less time taking management strategy. Addressing this burning environmental problem, a geospatial artificial intelligence (GeoAI) technique-based case study is presented here from one of the most densely populated and urbanized regions of Himalaya mountain, viz Uttarakhand Himalaya, which is also called central Himalaya. The results of the study suggest that due to quite a high rate of climate change, the climatic zones shifting towards higher altitudes at the average rate of 5.6 2m/year, causing several adverse ecological impacts in terms of decreasing quality dense temperate forest cover (0.05%/year), snow cover (0.02%/year), water bodies (0.01%/year), agricultural land (0.31%/year), and horticultural land (0.01%/year). Conversion of these eco-friendly land use land cover into barren land, fallow land, and built-up land causes geohydrological consequences of climate change in terms of decreasing rainy days (1%/year), drying perennial springs (0.20%/year), perennial streams (0.11%/year), decreasing spring and stream discharge during non-monsoon season, increased extreme rainfall events (6-8%/year), and subsequent surface runoff during monsoon season. Further, the study advocates that the degraded geohydrological process has resulted in an increased frequency of disaster events (floods, cloudbursts, landslides. etc.) with a 3% (12 events) annual rate, causing great loss of environment, infrastructure, lives, and economy each year. Therefore, it has been very urgent to mitigate climate change and increase geohydrological disaster events through an integrated approach. Keep in view this, the present study proposed an integrated watershed management plan which is equally useful to be implemented across the Himalaya region and other similar ecosystems across the world.

Evaluating the sustainability of groundwater abstraction in small watersheds using time series analysis

Groundwater is crucial in meeting the water needs of communities, industries, and ecosystems. The effective management of this resource is essential for maintaining the long-term stability of both the environmental and socio-economic conditions. This work focuses on assessing the sustainability of groundwater abstraction in Charlottetown, Prince Edward Island, specifically from well fields situated within the small-scale watersheds of Winter River and North River. The advanced time series analysis techniques, including Vector Error Correction Models (VECM), Impulse Response Functions (IRFs), and Forecast Error Variance Decomposition (FEVD) are employed to investigate the relationships among precipitation, temperature, groundwater abstraction, and stream flows. The analysis of IRFs reveals dynamic responses of streams to various shocks, including the variation of temperature, precipitation and well discharges, which showcase related immediate impacts, short-term responses, and long-term relationships. Temperature fluctuations exhibit complex responses, with short-term response decreases followed by sustained increases. Precipitation emerges as a dominant factor, showing sustained positive impacts on streamflow. Well operations significantly influence stream ecosystems, emphasizing the importance of optimized well operation strategies. The FEVD revealed that the first forecast horizon for all stream flows is primarily influenced by past shocks in precipitation with 16–55% in addition to other factors. The walk forward cross-validated forecast values for the next 24 months align with seasonal trends, reflecting declining discharge in summer, variable but generally decreasing discharge in fall, and increased discharge in winter and spring. The study findings provide recommendations for sustainable groundwater abstraction practices, including optimizing well operation strategies, community and stakeholder engagement, and ecosystem preservation.

An integrated approach for characterization of a fractured-rock carbonate aquifer in the Zagros Region of Iran

Karst aquifers typically exhibit a wide range of dissolution effects that include end-members of matrix, fractured-rock, and conduit-dominated types. This study employs an integrated approach involving geological studies, hydrogeological assessments, hydrochemical and isotopic analysis, and dye tracer tests to investigate the Sarvak limestone aquifer (SLA) in the Zagros Region, southwest Iran. Key characteristics of the SLA include numerous stratification boundaries, thin limestone layers with intercalated siliceous and marl impurities, extensive joint and fracture networks, predominant autogenic recharge, and absence of notable point recharge features (e.g., sinkholes, dolines), and the exchange flow with the Bakhtiari River (B-R) has made it a unique aquifer. Numerous pieces of evidence, such as low spatial and temporal changes in groundwater level, insignificant seasonal variations in the hydrochemical and isotopic composition of water samples, and the supersaturation state of groundwater with calcite and dolomite minerals, suggested a slow flow regime in many parts of the SLA. This regime is characterized by low velocity and long residence time of groundwater. The results reveal that despite the high solubility of carbonate rocks, extensive joint networks can limit significant karst development, leading to fluid flow behavior similar to that of fractured-rock aquifers. Therefore, SLA can be considered a fractured-rock and karst aquifer. The identified paths with fast flow in the dam area are unremarkable and cannot provide a large portion of the Pelle Khan Spring discharge.

Geospatial analysis of volcano-tectonic interactions: implications for spatiotemporal variations in water quality and quantity at Lake Beseka, East Africa, Ethiopia

ABSTRACT Water quality deterioration in the Main Ethiopian Rift Lakes is a problem affecting the area’s public health and socioeconomic development. The present study aimed to assess the water level rise in Lake Beseka using Landsat images from 1975 to 2023 and dilution trends at the pumping site from 2004 to 2022. In addition, the spatial water quality parameters, including pH, EC, TDS, and water surface temperature, for the years 2007, 2018, 2021, and 2023 were determined. The water level increased dramatically from 3 km2 in the 1960s to 27.5 km2 in 1980 following the construction of the Koka dam and the beginning of irrigation activity (sugarcane plantation) for the Metehara sugar estate factory. The water level reached a maximum (50 km2 in the dry season) in the mid of 1910s and become decreased and fluctuated after 2015. The observed pH, EC, and TDS were higher in the central portion of the lake, grouped under brackish water, and lower in the southwest, south, and northeast shores. The EC and TDS were higher in 2007, decreased in 2018, and fluctuated. The geothermal anomaly of the area varies from 23.1 to 47.9°C with the highest anomaly occurring at the northern side of the lake at a recent volcanic area that interlinked with geological structures. However, the observed and estimated water temperatures of the lake decreased from west to east due to hot spring discharge from the southwest shore of the lake. The series of hot springs in the southwest and west shores of the lake with high discharge rates indicate the presence of structural connectivity that leads to the emission of heat from a deep-seated source and heated groundwater of the area recharged from irrigation activity. Overall, spatiotemporal lake water quality variations were due to anthropogenic and geogenic factors, including hot springs and groundwater discharge to the lake, water level rise and bathymetric depth variation, evaporation, and irrigation activity. This study is significant in continuously estimating water level fluctuations and providing early warnings and preparedness to maintain the region's socioeconomic development.