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About 80 % of the precipitation at the Colorado River's headwaters is snow, and the resulting snowmelt-driven hydrograph is a crucial water source for about 40 million people. Snowmelt from alpine and subalpine snowpack contributes substantially to groundwater recharge and river flow. However, the dynamics of snowmelt progression are not well understood because observations of the high-elevation snowpack are difficult due to challenging access in complex mountainous terrain as well as the cost and labor intensity of currently available methods. We present a novel approach to infer the processes and dynamics of high-elevation snowmelt contributions predicated upon stable hydrogen and oxygen isotope ratios observed in streamflow. We show that deuterium-excess (d-excess) values of stream water could serve as a comparatively cost-effective proxy for a catchment-integrated signal of high-elevation snowmelt contributions to catchment runoff. We sampled stable hydrogen and oxygen isotope ratios of the precipitation, snowpack, and stream water in the East River, a headwater catchment of the Colorado River, and the stream water of larger catchments at sites on the Gunnison River and Colorado River. The d-excess of snowpack increased with elevation; the upper subalpine and alpine snowpack (> 3200 m) had substantially higher d-excess compared to lower elevations (< 3200 m) in the study area. The d-excess values of stream water reflected this because d-excess values increased as the higher-elevation snowpack contributed more to stream water generation later in the snowmelt/runoff season. End-member mixing analyses based on the d-excess data showed that the share of high-elevation snowmelt contributions within the snowmelt hydrograph was on average 44 % and generally increased during melt period progression, up to 70 %. The observed pattern was consistent during 6 years for the East River, and a similar relation was found for the larger catchments on the Gunnison and Colorado rivers. High-elevation snowpack contributions were found to be higher for years with lower snowpack and warmer spring temperatures. Thus, we conclude that the d-excess of stream water is a viable proxy to observe changes in high-elevation snowmelt contributions in catchments at various scales. Inter-catchment comparisons and temporal trends of the d-excess of stream water could therefore serve as a catchment-integrated measure to monitor if mountain systems rely on high-elevation water inputs more during snow drought compared to years of average snowpack depths. [ABSTRACT FROM AUTHOR]

The western U.S. is experiencing increasing rain to snow ratios due to climate change, and scientists are uncertain how changing recharge patterns will affect future groundwater‐surface water connection. We examined how watershed topography and streambed hydraulic conductivity impact groundwater age and stream discharge at eight sites along a headwater stream within the Manitou Experimental Forest, CO USA. To do so, we measured: (a) continuous stream and groundwater discharge/level and specific conductivity from April to November 2021; (b) biweekly stream and groundwater chemistry; (c) groundwater chlorofluorocarbons and tritium in spring and fall; (d) streambed hydraulic conductivity; and (e) local slope. We used the chemistry data to calculate fluorite saturation states that were used to inform end‐member mixing analysis of streamflow source. We then combined chlorofluorocarbon and tritium data to estimate the age composition of riparian groundwater. Our data suggest that future stream drying is more probable where local slope is steep and streambed hydraulic conductivity is high. In these areas, groundwater source shifted seasonally, as indicated by age increases, and we observed a high fraction of groundwater in streamflow, primarily interflow from adjacent hillslopes. In contrast, where local slope is flat and streambed hydraulic conductivity is low, streamflow is more likely to persist as groundwater age was seasonally constant and buffered by storage in alluvial sediments. Groundwater age and streamflow paired with characterization of watershed topography and subsurface characteristics enabled identification of likely controls on future stream drying patterns. Plain Language Summary: In the western U.S., climate change is causing more precipitation to fall as rain rather than snow and it is currently unclear how, where, and when this shift is going to impact groundwater contributions to streams, which is important for predicting streamflow and many ecosystem services, including stream contaminant processing or thermal refugia for fish habitat. In this study, we instrumented a small, high‐elevation stream in Colorado, USA to determine (a) how much groundwater is contributing to streamflow and (b) how long groundwater spends traveling through the subsurface before doing so. We found that groundwater age ranged from 10 to 55 years, with older groundwater located in areas with flat topography and where water could not move through streambed sediment quickly. We found the areas with steeper topography had more groundwater contributing to streamflow, but this groundwater was younger. We predict that under future climate scenarios, streams in areas with steep topography and young groundwater are more likely to dry. Key Points: Mean groundwater age is youngest in areas with high slope and streambed hydraulic conductivityMean groundwater age shifts older during low flow periodsFuture stream drying is more probable where local slope and streambed hydraulic conductivity are high [ABSTRACT FROM AUTHOR]

Streambed fluxes are highly variable through time and space, having a range implications for stream‐aquifer processes. This study investigated streambed fluxes over a 3‐year study period to characterize short‐ and long‐term variations and related implications for seepage recharge and hyporheic exchange. Time series of streambed fluxes were estimated through Darcy‐based methods using water level and temperature inputs from shallow (<1.5 m) nested streambed piezometers installed in two mountain‐front streams in Colorado, USA. Three predominant temporal scales of variability were characterized: sub‐daily (<1 day), daily (>1 day; <1 year), and interannual (>1 year). Temporal variability was quantified using the median absolute deviation (MAD), a statistical measure that is resistant to extreme values associated with short‐duration events. Sub‐daily variability (MADS‐D) was related to ET, temperature‐induced changes in hydraulic conductivity, and variable stream stage, and was quantified using the MAD of detrended fluxes (daily mean subtracted). Daily variability (MADD), calculated as the MAD of daily median fluxes for a given year, exceeded sub‐daily variability, and was influenced by strong seasonality at some sites. For individual sites and water years, the ratio of MADS‐D to MADD ranged from 0.03 to 0.70, with an average of 0.25. Annual median fluxes at each site varied across years, but typically remained consistent in order of magnitude and direction. Results reveal a strong linear correlation between the daily variability and the median annual flux at individual sites. Within a year, summer months characterized by stronger losing conditions showed greater overall variability. 1D numerical heat and flow modelling was performed to calibrate hydraulic parameters and to investigate temperature‐related controls for sub‐daily variations. We discuss implications of documented temporal variability for analyses of hyporheic exchange and groundwater recharge. Results provide a basis for quantifying temporal variations in streambed fluxes and highlight the extent to which fluxes vary over multiple timescales. [ABSTRACT FROM AUTHOR]

Artificial recharge ponds have been used increasingly in recent years to store water in underlying aquifers and modify baseline groundwater gradients or alter natural hydrologic fluxes and state variables in an aquifer system. The number of constructed ponds, their geographic spacing, and the volume of water diverted to each pond can have a significant impact on baseline system hydrologic fluxes and state variables such as groundwater head, with the latter sometimes rising to cause waterlogging in cultivated areas. This study seeks to quantify the impact of recharge ponds on groundwater state variables (head, saturated thickness) and associated fluxes within an irrigated stream-aquifer system. We use a numerical modeling approach to assess the impact of a set of 40 recharge ponds in a 246 km2 region of the South Platte River Basin, Colorado on localized groundwater head, regional groundwater flow patterns, and groundwater interactions with the South Platte River. We then use this information to determine the overall influence of recharge ponds on the hydrologic system. A linked agroecosystem–groundwater (DayCent-MODFLOW) modeling system is used to simulate irrigation, crop evapotranspiration, deep percolation to the water table, groundwater pumping, seepage from irrigation canals, seepage from recharge ponds, groundwater flow, and groundwater–surface water interactions. The DayCent model simulates the plant–soil-water dynamics in the root zone and soil profile, while MODFLOW simulates the water balance in the aquifer system. After calibration and testing, the model is used in scenario analysis to quantify the hydrologic impact of recharge ponds. Results indicate that recharge ponds can raise groundwater levels by approximately 2.5 m in localized areas, but only 15 cm when averaged over the entire study region. Ponds also increase the rate of total groundwater discharge to the South Platte River by approximately 3%, due to an increase in groundwater hydraulic gradient, which generally offsets stream depletion caused by groundwater pumping. These results can assist with groundwater resource management in the study region, and generally provide valuable information for the interplay between pumping wells and recharge ponds, and their composite effect on groundwater–surface water interactions. In addition, the developed linked DayCent-MODFLOW modeling system presented herein can be used in any region for which recharge rates should be calculated on a per-field basis. [ABSTRACT FROM AUTHOR]

Waterlogging on croplands has been a known problem for a long time, leading to adverse social, physical, economic and environmental issues. To better solve the problem, the complicated plant-soil-water dynamics system needs to be better understood. The challenge is to simulate the interactions between the components in the systems. There are models that simulate plant-soil-water system but either run the processes independently leading to inaccuracy or has high invasiveness of using integrated models. This paper presents a tightly coupled model, DayCent-MODFLOW, that links a 3D ground-water flow (MODFLOW) model and a 1D agroecosystem model (DayCent). DayCent is responsible for plant-soil-water dynamic in the root zone, whereas MODFLOW simulates head and groundwater flow in the saturated zone of the aquifer. DayCent passes deep percolation from the soil profile to the water table and, under conditions of waterlogging in which the water table is within the soil profile, DayCent soil hydrologic processes are constrained by the presence of the water table simulated by MODFLOW. The coupling is achieved by adopting a parallel inter-process communication technique MPI (Message Passing Interface). The model is applied to a waterlogged agricultural area (22 km2) in northern Colorado, USA and tested against groundwater head and rates of evapotranspiration (ET). The model runs in parallel with multiple processes on the largest AWS Linux server. Groundwater heads match measured heads to a reasonable degree, and ET rates match reference ET and are highly correlated with crop type. Results show the strong hydrologic interaction between the two models. Greenhouse gas emissions from soil (N 2 O and CH 4) were also estimated by the model under the waterlogged conditions. Although the model can be used to simulate any plant-soil-aquifer system, no matter the depth of the water table, results from this study show that the model can be used to assess crop productivity, recharge, ET, and greenhouse gas emissions in areas of shallow groundwater. • A new hydro-agronomic model is introduced by integrating the MODFLOW groundwater flow model and the DayCent 1D agronomic model. • The crop-soil-water dynamics are better simulated in the waterlogged areas using the coupled model. • MPI is utilized as communication tool for the coupling models to decrease overall run time and minimize code invasiveness. • The model can assess recharge, and gas emissions under deep and shallow water table conditions in agricultural areas. [ABSTRACT FROM AUTHOR]

APEX (A gricultural P olicy/ E nvironmental e X tender) is an oft-used agroecosystem model but has limited use in groundwater-driven watersheds due to a simplistic representation of groundwater processes. This paper presents the linkage of APEX and the groundwater flow model MODFLOW into a single modeling code. The mapping of recharge, groundwater head, and groundwater-surface water interactions are handled internally via subroutines. The APEX-MODFLOW model is applied to three watersheds in the United States for testing code accuracy and hydrologic state variables and fluxes: the Animas River Watershed, Colorado and New Mexico (3543 km2); the Price River Watershed, Utah (4886 km2); and the Middle Bosque River Watershed, Texas (470 km2). Whereas the hydrology of the Animas River and Price River watersheds is driven by snowmelt and spring runoff, the hydrology of the Middle Bosque River Watershed is driven by summer thunderstorms. The model can be used for scenario analysis in groundwater-driven watersheds. • New integrated hydrologic model links APEX model to MODFLOW model. • Model passes recharge, water table elevation, and gw-sw flux rates internally. • APEX-MODFLOW applied to three watersheds in Utah, Colorado, and Texas, USA. • Model results show importance of including physically based groundwater flow. [ABSTRACT FROM AUTHOR]

Sustained pumping of groundwater can lead to declining water levels in wellfields and concerns regarding the sustainability of groundwater resources. Aquifer Storage and Recovery (ASR) is a promising approach for maintaining water levels in wells and increasing the sustainability of groundwater resources. Herein, an analytical model relying on superposition of the Theis equation is used to resolve water levels at 40 wells in three vertically stacked ASR wellfields operating in the Denver Basin Aquifers, Colorado (USA). Fifteen years of dynamic recovery/recharge data are used to estimate aquifer and well properties, which are then used to predict water levels at individual wells. Close agreement between modeled and observed water levels supports the validity of the analytical model for ASR wellfield applications. During the study period, 45 million m3 of groundwater is produced and 11 million m3 is recharged, leading to a net withdrawal of 34 million m3 of groundwater. To quantify the benefits of recharge, the analytical model is applied to predict water levels at wells absent the historical recharge. Results indicate that during recovery and no-flow periods, recharge has increased water levels at wells up to 60 m compared to the no-recharge scenario. On average, the recharge increased water levels during the study period by 3, 4, and 11 m for wells in the Denver, Arapahoe, and Laramie Fox-Hills Aquifers, respectively. This study demonstrates the utility of analytical modeling to quantify the effects of long-term ASR at wells. [ABSTRACT FROM AUTHOR]

• A new method quantifies the influence of groundwater stresses on water table elevation. • Global sensitivity analysis used to rank and quantify influence of each stress. • Sensitivity analysis results shown spatially and temporally for each stress. • Method applied to a managed irrigated stream-aquifer system in Colorado, USA. High groundwater levels in urban and irrigated areas around the world can lead to infrastructure damage, land degradation, and crop yield reduction. Causes can include groundwater flooding due to fluvial processes, excess rainfall and irrigation, inadequate subsurface drainage, and additional sources such as injection and seepage from earthen canals and recharge ponds. The principal causes of shallow water tables, however, are difficult to quantify due to the inter-connectedness of all possible causes. This paper presents a method to analyze and quantify the cause of high groundwater levels in highly managed, irrigated stream-aquifer systems, using a combination of numerical groundwater flow modeling and global sensitivity analysis (GSA) tools. A tested MODFLOW groundwater model and Sobol GSA methods are used to simulate and then quantify the influence of all major groundwater stresses on water table elevation for a region in northern Colorado, USA experiencing high groundwater levels, with results showing that recharge from surface water irrigation, canal seepage, and groundwater pumping have the strongest influence on water table elevation, whereas precipitation recharge and recharge from groundwater irrigation have small influences. Time series sensitivity plots quantify the seasonality of these influences over a decadal period, and spatial sensitivity plots indicate regions that are strongly influenced by individual stresses. Results from best management practice (BMP) implementation indicate that limiting canal seepage and transitioning >50 % of cultivated fields from surface water irrigation to groundwater irrigation can decrease water table elevation by 1.5 m–3 m over a 5-year period, leading to beneficial conditions for crop growth in the root zone and dewatering of subsurface infrastructure. These methods can be applied to any waterlogged region worldwide. However, proposed management practices to lower water table may be constrained by local, state, or national water law. [ABSTRACT FROM AUTHOR]