Soil hydrological processes play an important role in land-atmosphere system. In most climate models, these processes are described by soil moisture variations in the first 2 m of soil resulting from precipitation, evaporation, and transpiration. Groundwater effects on soil moisture variations and surface evaporation are either neglected or not explicitly treated. Although groundwater may have a small effect on soil moisture in areas with a deep groundwater table, groundwater can act as a soil water source and have substantial effects in areas where the water table is near or within a model's soil column. How groundwater affects soil moisture, its vertical distribution, as well as the surface water flux are the issues addressed in this study.A soil hydrological model was developed to include groundwater effects by allowing water exchange between the unsaturated zone and groundwater. The model uses a vertically varying saturation hydraulic conductivity, and is evaluated using observations at one station in the Nebraska Sand Hills. Model results show its ability to describe the roles of groundwater in maintaining the observed soil moisture, especially in deep layers. In addition, comparisons show that the soil moisture content in the first meter of the soil column from the model with groundwater is 21% greater than that from a model without groundwater. High soil moisture content in the root zone results in increased evapotranspiration (ET). The average ET in three periods from 1998 to 2000 is 7 -21% higher when groundwater is considered in the model. Because of the groundwater effects, spatial variations in the groundwater table can create an additional spatial variability of soil moisture and surface water flux. This additional variability could be important in development of storms in regions whose domain has a large portion with high groundwater table. q

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Snow and glacier melting and accumulation are important processes of the hydrological cycle in the cryosphere, e.g., high‐mountain areas. Glaciers and snow cover respond to climate change notably over the Tibetan Plateau (TP) as the Earth's Third Pole where complex topography and lack of ground‐based observations result in knowledge gaps in hydrological processes and large uncertainties in model output. This study develops a snow and glacier melt model for a distributed hydrological model (Coupled Routing and Excess Storage model, CREST) using the Upper Brahmaputra River (UBR) basin in the TP as a case study. Satellite and ground‐based precipitation and land surface temperature are jointly used as model forcing. A progressive two‐stage calibration strategy is developed to derive model parameters, i.e., (1) snow melting processes (stage I) and (2) glacier melting and runoff generation and routing using multisource data (stage II). Stage‐I calibration is performed using the MODIS snow cover area (SCA) product and a blending snow water equivalent (SWE) product combined with partial in situ measurements. Stage‐II calibration is based on Gravity Recovery and Climate Experiment (GRACE) satellite‐derived total water storage (TWS) changes and streamflow observed at a gauging station of the lower reach of the UBR. Results indicate that the developed two‐stage calibration method provides more reliable streamflow, snow (both SCA and SWE), and TWS change simulations against corresponding observations than commonly used methods based on streamflow and/or SCA performance. The simulated TWS time series shows high consistency with GRACE counterparts for the study period 2003–2014, and overestimated melting rates and contributions of glacier meltwater to runoff in previous studies are improved to some degree by the developed model and calibration strategy. Snow and glacier runoff contributed 10.6% and 9.9% to the total runoff, and the depletion rate of glacier mass was ∼ −10 mm/a (∼ −2.4 Gt/a, Gt/a is gigaton (km3 of water) per year) over the UBR basin during the study period. This study is valuable in examining the impacts of climate change on hydrological processes of cryospheric regions and providing an improved approach for simulating more reliable hydrological variables over the UBR basin and potentially similar regions globally.

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Abstract. We developed a new tracer-aided hydrological model that disaggregates cockpit karst terrain into the two dominant landscape units of hillslopes and depressions (with fast and slow flow systems). The new model was calibrated by using high temporal resolution hydrometric and isotope data in the outflow of Chenqi catchment in Guizhou Province of south-western China. The model could track hourly water and isotope fluxes through each landscape unit and estimate the associated storage and water age dynamics. From the model results we inferred that the fast flow reservoir in the depression had the smallest water storage and the slow flow reservoir the largest, with the hillslope intermediate. The estimated mean ages of water draining the hillslope unit, and the fast and slow flow reservoirs during the study period, were 137, 326 and 493 days, respectively. Distinct seasonal variability in hydroclimatic conditions and associated water storage dynamics (captured by the model) were the main drivers of non-stationary hydrological connectivity between the hillslope and depression. During the dry season, slow flow in the depression contributes the largest proportion (78.4 %) of flow to the underground stream draining the catchment, resulting in weak hydrological connectivity between the hillslope and depression. During the wet period, with the resulting rapid increase in storage, the hillslope unit contributes the largest proportion (57.5 %) of flow to the underground stream due to the strong hydrological connectivity between the hillslope and depression. Meanwhile, the tracer-aided model can be used to identify the sources of uncertainty in the model results. Our analysis showed that the model uncertainty of the hydrological variables in the different units relies on their connectivity with the outlet when the calibration target uses only the outlet information. The model uncertainty was much lower for the “newer” water from the fast flow system in the depression and flow from the hillslope unit during the wet season and higher for “older” water from the slow flow system in the depression. This suggests that to constrain model parameters further, increased high-resolution hydrometric and tracer data on the internal dynamics of systems (e.g. groundwater responses during low flow periods) could be used in calibration.

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