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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]

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]