Abstract Mountain System Recharge processes are significant natural recharge pathways in many arid and semi‐arid mountainous regions. However, Mountain System Recharge processes are often poorly understood and characterized in hydrologic models. Mountains are the primary water supply source to valley aquifers via lateral groundwater flow from the mountain block (Mountain Block Recharge) and focused recharge from mountain streams contributing to focused Mountain Front Recharge at the piedmont zone. Here, we present a multi‐tool isogeochemical approach to characterize mountain flow paths and Mountain System Recharge in the northern Tulare Basin, California. We used groundwater chemistry data to delineate hydrochemical facies and explain the chemical evolution of groundwater from the Sierra Nevada to the Central Valley aquifer. Stable isotopes and radiogenic groundwater tracers validated Mountain System Recharge processes by differentiating focused from diffuse recharge, and estimating apparent groundwater age, respectively. Novel application of End‐Member Mixing Analysis using conservative chemical components revealed three Mountain System Recharge end‐members: (a) evaporated Ca‐HCO3water type associated with focused Mountain Front Recharge, (b) non‐evaporated Ca‐HCO3and Na‐HCO3water types with short residence times associated with shallow Mountain Block Recharge, and (c) Na‐HCO3groundwater type with long residence time associated with deep Mountain Block Recharge. We quantified the contribution of each Mountain System Recharge process to the valley aquifer by calculating mixing ratios. Our results show that deep Mountain Block Recharge is a significant recharge component, representing 31%–53% of the valley groundwater. Greater hydraulic connectivity between the Sierra Nevada and Central Valley has significant implications for parameterizing groundwater flow models. Our framework is useful for understanding Mountain System Recharge processes in other snow‐dominated mountain watersheds. 
                        more » 
                        « less   
                    
                            
                            Combined impacts of uncertainty in precipitation and air temperature on simulated mountain system recharge from an integrated hydrologic model
                        
                    
    
            Abstract. Mountainous regions act as the water towers of the worldby producing streamflow and groundwater recharge, a function that isparticularly important in semiarid regions. Quantifying rates of mountainsystem recharge is difficult, and hydrologic models offer a method toestimate recharge over large scales. These recharge estimates are prone touncertainty from various sources including model structure and parameters.The quality of meteorological forcing datasets, particularly in mountainousregions, is a large source of uncertainty that is often neglected ingroundwater investigations. In this contribution, we quantify the impact ofuncertainty in both precipitation and air temperature forcing datasets onthe simulated groundwater recharge in the mountainous watershed of theKaweah River in California, USA. We make use of the integrated surface water–groundwater model, ParFlow.CLM, and several gridded datasets commonly usedin hydrologic studies, downscaled NLDAS-2, PRISM, Daymet, Gridmet, andTopoWx. Simulations indicate that, across all forcing datasets, mountain front recharge is an important component of the water budget in themountainous watershed, accounting for 9 %–72 % of the annual precipitation and ∼90 % of the total mountain system recharge to theadjacent Central Valley aquifer. The uncertainty in gridded air temperatureor precipitation datasets, when assessed individually, results in similarranges of uncertainty in the simulated water budget. Variations in simulatedrecharge to changes in precipitation (elasticities) and air temperature(sensitivities) are larger than 1 % change in recharge per 1 % change inprecipitation or 1 ∘C change in temperature. The total volume ofsnowmelt is the primary factor creating the high water budget sensitivity, and snowmelt volume is influenced by both precipitation and air temperatureforcings. The combined effect of uncertainty in air temperature andprecipitation on recharge is additive and results in uncertainty levels roughly equal to the sum of the individual uncertainties depending on thehydroclimatic condition of the watershed. Mountain system recharge pathwaysincluding mountain block recharge, mountain aquifer recharge, and mountainfront recharge are less sensitive to changes in air temperature than changesin precipitation. Mountain front and mountain block recharge are moresensitive to changes in precipitation than other recharge pathways. Themagnitude of uncertainty in the simulated water budget reflects theimportance of developing high-quality meteorological forcing datasets in mountainous regions. 
        more » 
        « less   
        
    
                            - Award ID(s):
- 1944161
- PAR ID:
- 10323668
- Date Published:
- Journal Name:
- Hydrology and Earth System Sciences
- Volume:
- 26
- Issue:
- 4
- ISSN:
- 1607-7938
- Page Range / eLocation ID:
- 1145 to 1164
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
- 
            
- 
            Abstract Streamflow generation in mountain watersheds is strongly influenced by snow accumulation and melt as well as groundwater connectivity. In mountainous regions with limestone and dolomite geology, bedrock formations can host karst aquifers, which play a significant role in snowmelt–discharge dynamics. However, mapping complex karst features and the resulting surface‐groundwater exchanges at large scales remains infeasible. In this study, timeseries analysis of continuous discharge and specific conductance measurements were combined with gridded snowmelt predictions to characterize seasonal streamflow response and evaluate dominant watershed controls across 12 monitoring sites in a karstified 554 km2watershed in northern Utah, USA. Immense surface water hydrologic variability across subcatchments, years and seasons was linked to geologic controls on groundwater dynamics. Unlike many mountain watersheds, the variability between subcatchments could not be well described by typical watershed properties, including elevation or surficial geology. To fill this gap, a conceptual framework was proposed to characterize subsurface controls on snowmelt–discharge dynamics in karst mountain watersheds in terms of conduit flow direction, aquifer storage capacity and connectivity. This framework requires only readily measured surface water and climatic data from nested monitoring sites and was applied to the study watershed to demonstrate its applicability for evaluating dominant controls and climate sensitivity.more » « less
- 
            The Denver Basin Aquifer System (DBAS) is an important groundwater resource for Front Range communities and is currently experiencing increasing demand as populations grow and surface water supplies remain limited. It is necessary to better constrain aquifer recharge mechanisms to enable sustainable use of this resource. In other sedimentary basin aquifer systems, mountain front recharge has been shown to be a significant contributor to local basin groundwater recharge. In the DBAS, inputs from the mountain block are poorly understood, and previous numerical models have treated large segments of the mountain-front boundary as impermeable. However, there exist potential connections between the mountain block and the DBAS, either by direct contact of permeable units, which would facilitate underflow recharge into the basin, or by surface water infiltration to the aquifer units where they outcrop near the mountain front. To observe spatial and temporal relationships between mountain block water and DBAS water, we use water stable isotopes and characterize the d2H and d18O of monthly precipitation, seasonal surface waters, and groundwaters in and around the Front Range and Denver Basin. The goal of this study is to determine if differences in the isotopic composition of waters across the Front Range permit the use of d18O and d2H as tracers of water flow between Front Range streams and groundwater and the DBAS. We analyzed the unique signature of mountain-block water to compare with DBAS water stable isotope data collected from Castle Rock Water municipal wells. Stable isotope ratios varied spatially and temporally, with the greatest temporal variance observed in precipitation. Streams showed great spatial variance, and less significant seasonal variance between the three seasonal sampling events conducted. Groundwaters showed very little temporal variance but had great spatial variance both between the aquifer units of the DBAS and between different locations within the mountain block crystalline aquifer. The lowest d2H and d18O ratios were measured in winter precipitation, winter streams, and groundwater samples collected from the high-elevation Front Range. Samples of DBAS groundwaters with the lowest d2H and d18O ratios indicate potential hydrogeologic connection to the mountain block. Interpreted mixing lines on a d-excess versus d18O plot support the potential DBAS-mountain block connection. The deepest aquifer units of the DBAS (Arapahoe and Laramie-Fox Hills) show the least relationship with meteoric or surface waters on both a d2H and d18O plot and the d-excess versus d18O plot and have higher d18O values than would be predicted based on their previously measured recharge ages and paleoclimate data from the region. Characterizing the spatial and temporal variations in water stable isotope signatures of the Front Range and DBAS region enhances understanding of the region’s hydrology and hydrogeology. Additionally, these results help to better inform models of aquifer recharge and promote sustainable use of the DBAS resource.more » « less
- 
            Abstract Mountain‐front recharge (MFR), or all inflow to a basin‐fill aquifer with its source in the mountain block, is an important component of recharge to basin‐fill aquifer systems. Distinguishing and quantifying the surface from subsurface components of MFR is necessary for water resource planning and management, particularly as climate change may impact these components in distinct ways. This study tests the hypothesis that MFR components can be distinguished in long‐screened, basin‐fill production wells by (1) groundwater age and (2) the median elevation of recharge. We developed an MFR characterization approach by combining age distributions in six wells using tritium, krypton‐85, argon‐39, and radiocarbon, and median recharge elevations from noble gas thermometry combined with numerical experiments to determine recharge temperature lapse rates using flow and energy transport modeling. We found that groundwater age distributions provided valuable information for characterizing the dominant flow system behavior captured by the basin‐fill production wells. Tracers indicated the presence of old (i.e., no detectable tritium) water in a well completed in weathered bedrock located close to the mountain front. Two production wells exhibited age distributions of binary mixing between modern and a small fraction of old water, whereas the remaining wells captured predominantly modern flow paths. Noble gas thermometry provided important complementary information to the age distributions; however, assuming constant recharge temperature lapse rates produced improbable recharge elevations. Numerical experiments suggest that surface MFR, if derived from snowmelt, can locally suppress water table temperatures in the basin‐fill aquifer, with implications for recharge elevations estimated from noble gas thermometry.more » « less
- 
            Abstract In many regions globally, snowmelt‐recharged mountainous karst aquifers serve as crucial sources for municipal and agricultural water supplies. In these watersheds, complex interplay of meteorological, topographical, and hydrogeological factors leads to intricate recharge‐discharge pathways. This study introduces a spatially distributed deep learning precipitation‐runoff model that combines Convolutional Long Short‐Term Memory (ConvLSTM) with a spatial attention mechanism. The effectiveness of the deep learning model was evaluated using data from the Logan River watershed and subwatersheds, a characteristically karst‐dominated hydrological system in northern Utah. Compared to the ConvLSTM baseline, the inclusion of a spatial attention mechanism improved performance for simulating discharge at the watershed outlet. Analysis of attention weights in the trained model unveiled distinct areas contributing the most to discharge under snowmelt and recession conditions. Furthermore, fine‐tuning the model at subwatershed scales provided insights into cross‐subwatershed subsurface connectivity. These findings align with results obtained from detailed hydrogeochemical tracer studies. Results highlight the potential of the proposed deep learning approach to unravel the complexities of karst aquifer systems, offering valuable insights for water resource management under future climate conditions. Furthermore, results suggest that the proposed explainable, spatially distributed, deep learning approach to hydrologic modeling holds promise for non‐karstic watersheds.more » « less
 An official website of the United States government
An official website of the United States government 
				
			 
					 
					
 
                                    