Hydrological Processes最新文献

Vegetation phenology is a key indicator of climate change and plays a vital role in ecosystem water use efficiency (WUE), which balances carbon sequestration and water loss. As global climate change accelerates, understanding its effects on phenology and WUE is essential for comprehending ecosystem dynamics and carbon–water cycles. Northwest China (NWC), one of the driest regions at similar latitudes, is experiencing a rapid shift from a warm-dry to a warm-wet climate, posing significant challenges to its fragile ecosystem. In this study, we used reanalysis and satellite remote sensing datasets to analyse the changes in the start of the growing season (SOS), the end of the growing season (EOS) and the length of the growing season (LOS) for various vegetation types in the NWC from 1982 to 2015. The focus was on how temperature and precipitation variations influenced phenological dynamics and their subsequent impacts on Gross Primary Productivity (GPP), evapotranspiration (ET) and WUE. Our results show that NWC has experienced a significant warming and wetting trend, with the SOS advancing by 0.04 days per year and the EOS delaying by 0.04 days per year, leading to a notable extension of the LOS by 0.08 days annually. Temperature primarily drives the SOS advance, while precipitation changes in croplands and grasslands and temperature shifts in forests and shrublands dictate the EOS delays. WUE increased at a rate of 0.005 gC m⁻² mm⁻¹ year⁻¹, with temperature and precipitation influencing GPP and ET both directly and indirectly through phenological changes. The findings underscore the cascading effects of warming and wetting on vegetation phenology and WUE in the fragile NWC ecosystem. Changes in the vegetation growing season have had significant impacts on carbon and water fluxes, with varying effects across different vegetation types. This study provides valuable insights into the response mechanisms of vegetation to rapid climate change in arid and semi-arid regions and offers critical information for the sustainable management of water resources and agriculture in the NWC.

Estimates of dynamic groundwater volumes supplying baseflow to streams are important for water availability projections during extended periods of drought. The primary goals of this study were to provide dynamic storage volume estimates, inferred from streamflow recession analysis, for baseflow regimes within seven gaged catchments within the Neversink Reservoir Watershed (NRW), a critical municipal water source for New York City. Additionally, geomorphological properties, surficial geology and hydro-meteorological processes were quantified and described in relation to time and spatially variable recession behaviour and storage estimates across the NRW. To explore these relationships, we (1) evaluated seasonal trends in streamflow recession behaviour in relation to modelled potential evapotranspiration (PET) and catchment runoff rates, (2) derived empirical streamflow models for cool-season runoff using both linear and nonlinear reservoir assumptions for baseflow and (3) calculated metrics related to the geology and geomorphology of each catchment and compared these metrics to area normalised baseflow dynamic storage estimates. Results show that baseflow recession behaves as a nonlinear reservoir, and applying linear groundwater reservoir assumptions may underestimate the total dynamic storage volumes compared to what would be predicted for a nonlinear reservoir. Increases in PET caused decreases in storage conditions that resulted in increased recession rates and nonlinearity in streamflow recession during the growing season. Additionally, we found that while no single physical catchment characteristic solely predicted catchment storage dynamics, sediment volume and stream gradients were stronger predictors of normalised storage volumes than catchment surface area or surface topography alone. Within the NRW, catchments with the highest sediment volume exhibited the lowest recession rates and higher dynamic storage volumes, while the smallest catchment, mostly devoid of sediment, had the fastest recession rate and lowest dynamic storage volume.

In June 2022, a historic flood event occurred in the headwaters of the Yellowstone River Basin. The flood resulted in millions of dollars in damages and substantial interruptions to Yellowstone National Park. The 2022 flood event was substantially higher in magnitude than other high-peak flow events over the last 30 years. The high discharge was primarily due to the combination of hydrologic mechanisms initiated by rain-on-snow, including a high-elevation snowpack that peaked later than average. However, the contributions of each hydrologic driver, rain and snow, have not been quantified and could be important for understanding future flood events in the region. The contribution of snowmelt to the total terrestrial water input (TWI) varied throughout the area, yet was concentrated in the headwaters of the Yellowstone, Stillwater, and Boulder rivers, along with the headwaters of Rock Creek in Wyoming and Montana. The primary atmospheric contributions to the TWI during the 2022 event were precipitation from moisture transported from the Pacific Ocean that converged over the Greater Yellowstone Area (GYA) and snowmelt from residual snowpack in the northeast part of Yellowstone National Park.

Hydrologic connectivity is defined as the connection among stores of water within a watershed and controls the flux of water and solutes from the subsurface to the stream. Hydrologic connectivity is difficult to quantify because it is goverened by heterogeniety in subsurface storage and permeability and responds to seasonal changes in precipitation inputs and subsurface moisture conditions. How interannual climate variability impacts hydrologic connectivity, and thus stream flow generation and chemistry, remains unclear. Using a rare, four-year synoptic stream chemistry dataset, we evaluated shifts in stream chemistry and stream flow source of Coal Creek, a montane, headwater tributary of the Upper Colorado River. We leveraged compositional principal component analysis and end-member mixing to evaluate how seasonal and interannual variation in subsurface moisture conditions impacts stream chemistry. Overall, three main findings emerged from this work. First, three geochemically distinct end members were identified that constrained stream flow chemistry: reach inflows, and quick and slow flow groundwater contributions. Reach inflows were impacted by historic base and precious metal mine inputs. Bedrock fractures facilitated much of the transport of quick flow groundwater and higher-storage subsurface features (e.g., alluvial fans) facilitated the transport of slow flow groundwater. Second, the contributions of different end members to the stream changed over the summer. In early summer, stream flow was composed of all three end members, while in late summer, it was composed predominantly of reach inflows and slow flow groundwater. Finally, we observed minimal differences in proportional composition in stream chemistry across all four years, indicating seasonal variability in subsurface moisture and spatial heterogeneity in landscape and geologic features had a greater influence than interannual climate fluctuation on hydrologic connectivity and stream water chemistry. These findings indicate that mechanisms controlling solute transport (e.g., hydrologic connectivity and flow path activation) may be resilient (i.e., able to rebound after perturbations) to predicted increases in climate variability. By establishing a framework for assessing compositional stream chemistry across variable hydrologic and subsurface moisture conditions, our study offers a method to evaluate watershed biogeochemical resilience to variations in hydrometeorological conditions.

Hydrological processes of mountainous watersheds commonly impact water resource supply in downstream areas. To better understand how re-vegetation affects the different hydrological pathways of watersheds, we investigated their change at various temporal scales for the Xiaoluan River watershed, a typical meso-scale watershed featuring a plateau–mountain transition topography in northern China. For the non-growing season from 2006 to 2020, the groundwater discharge of the watershed and the wetting of the watershed in terms of the Horton Index significantly increased, and the recession process in terms of the recession coefficient (k) was considerably prolonged. We suggest that re-vegetation and snowmelt were responsible for this change, but they affected the hydrological processes differently. That is, re-vegetation might improve the water storage capacity of the shallow soil layers of the watershed, thereby enhancing the capacity of groundwater recharge and discharge. Meanwhile, snowmelt may provide available water for recharging and discharging the watershed. Because reforestation progresses and global climate change continues, more complex hydrological processes are to be expected. Therefore, continuous monitoring and detailed investigations of subsurface hydrological processes will be necessary for adaptive watershed management.

Infiltration and hydraulic conductivity (K) play a key role in streamflow generation and groundwater recharge. The impact of agriculture on soil infiltration and K has been widely investigated. While many studies show decreases in infiltration and K, others show an increase or no change in both parameters. These variations highlight the importance of conducting local scale investigations. We investigated the impact of agricultural development and land cover changes on infiltration and K. Unsaturated hydraulic conductivity (K_unsat) was measured at the soil surface during both dry and wet seasons, and saturated hydraulic conductivity (K_sat) was measured at 25, 45, and 65 cm below the surface. Our results show that there were no significant differences in K_unsat between perennial crop cover and natural forests; however, agroforests did have significantly higher K_unsat than natural forests, which was attributed to higher soil moisture. There were no significant differences in K_sat among the perennial crops, agroforests, and natural forests at the 45 and 65 cm depths; however, at 25 cm, natural forests had significantly higher K_sat, which was attributed to the higher soil organic matter and lower bulk density in natural forest. The study showed that the impacts of agriculture and land cover change on K_sat do not extend to deeper soil layers. We used 2 years of rainfall intensity data, observed K_unsat and K_sat, and HYDRUS-1D modelling to infer any changes to runoff. We show that footpaths and perennial crop cover may generate more surface runoff than natural forests. This study adds to the literature on agricultural impacts on infiltration and K. More importantly, it shows that differences in crop type, management practices, and topographic location all play an important role on infiltration and K, showing the need for local field-based studies.