Hydrological Processes最新文献

The hydrologic flows across the river–aquifer interface play an important role in groundwater dynamics and biogeochemical reactions within the subsurface; however, little is known about the effects of river–aquifer interactions on land surface processes. In this study, we developed a fully coupled three-dimensional (3D) land surface and subsurface model at a high resolution (~1 km) that accounts for high-frequency hydrologic exchange flow conditions to investigate how river–aquifer interactions modulate surface water budgets in the Upper Columbia-Priest Rapids watershed, a typical semiarid watershed located in the northwestern United States where river stage fluctuates in response to reservoir releases changing. Our results show that the spatiotemporal dynamics of river–aquifer interactions are highly heterogeneous, driven mainly by river-stage fluctuations. Adding 6.64 × 10⁶ m³ year⁻¹ of water over the watershed from the river to groundwater owing to the lateral flow, river–aquifer interactions led to an increase in soil evaporation and transpiration supplied by higher soil moisture content, particularly in deeper subsurface. In a hypothetic future scenarios where a 5-m rise in river stage was assumed, the hydrologic flow exchange rates were intensified, resulting in higher surface water over the entire watershed. Overall, lateral flow induced by river–aquifer exchanges leads to an increase in evapotranspiration of ~75% in the historical period and of ~83% in the hypothetical future scenario. Our study demonstrates the potential of coupled model as an effective tool for understanding river–aquifer–land surface interactions, and indicates that river–aquifer interactions fundamentally alter the water balance of the riparian zone for the semiarid watershed and will likely become more frequent and intense in the future under the effects of climate change.

Digital Elevation Models (DEMs) are a crucial tool for watershed analysis, offering valuable insights into landscape-scale hydrology. Traditional watershed delineations are derived by filling a DEM to force flow paths through topographic depressions, thus creating a continuous drainage network throughout the domain. However, this approach is challenged in landscapes with abundant real-world depression storage, intermittently flowing stream channels, and internally drained lake basin (endorheic basin) such as the Canadian Shield (CS). The CS landscape is characterized by “fill-and-spill” surface water hydrology, with runoff flow paths controlled by bedrock sills and rocky cascades that overtop when water levels are high but cease flowing when water levels are low. To better represent these intermittent drainage networks, we apply a non-traditional, less-aggressive DEM filling model (Fill-Spill-Merge or FSM) to a continental-scale DEM (MERIT) all of Canada. To ensure adequate filling of DEM noise while also preserving real-world topographic depressions, we propose a climatic method to initialize a key FSM parameter (“runoff depth”) that calibrates observed discharges from 1690 Environment and Climate Change Canada (ECCC) river gauges with climate model P-ET (precipitation minus evapotranspiration) data. Our application of FSM to all 1690 gauged watersheds identifies 916 significant topographical control points controlling >20% and/or 1000 km² of their respective areas. The Geikie, Snare, Kazan, Tazin, and Seal rivers may be particularly affected, with impacted watershed areas ranging from 12% to 64%. Extending this approach to ungauged parts of the CS reveals an additional 635 significant topographical control points. Ensemble climate model projections suggest that around 10% of these control points are currently dry but will become active by 2100. This research explicitly determines how CS watersheds are affected by fill-and-spill hydrology, and demonstrates the importance of accurate terrain modelling for delineating surface water flow paths in depressional landscapes.

Exploring the contributions of new and old water to runoff during precipitation events in agricultural catchments is essential for understanding runoff generation, solute transport, and soil erosion. The aim of this study was to investigate the variability in the isotopic composition of precipitation and runoff in the 66 ha agricultural catchment in Austria, in the Hydrological Open Air Laboratory (HOAL), in order to compare two isotope hydrograph separation methods. The classical two-component (IHS) and the ensemble hydrograph separation (EHS) were applied to multiple large events in May–October of 2013–2018 using δ¹⁸O and δ²H. The peak flow new water contributions obtained by IHS were compared with the average new water fraction from EHS. The average new water fraction calculated with EHS based on regular weekly sampling was close to zero, which can be explained by the large diffuse groundwater discharge into the stream between the events. When only investigating events with high temporal resolution sampling, the results suggest that EHS provided average new water fractions during peak flows (0.46 ± 0.04 for δ¹⁸O, 0.47 ± 0.03 for δ²H) that were close to the averages obtained by IHS (0.47 for δ¹⁸O, 0.50 for δ²H). New water fractions tended to be higher for larger rainfall intensities. High peak flow new water fractions could be explained by the agricultural land use and soils with low permeability promoting overland flow generation and by some of the tile drainage systems contributing to the delivery of water. In conclusion, a weekly sampling frequency was not sufficient in the HOAL but instead high-resolution sampling during events was necessary to estimate the average new water contributions during events. While EHS may be a more robust approach compared to IHS, as it relaxes some of the assumptions of IHS, IHS can provide information on the variability of new water contributions of individual events.

Changes in rainfall patterns due to climate change may accelerate the runoff of sulfate (SO₄²⁻), which is anthropogenically emitted and deposited as an air pollutant, cycled in forest ecosystems, and partly accumulated in forest soils. A forested catchment on the Sea of Japan side in central Japan is significantly affected by transboundary air pollution from the Asian continent due to northwesterly seasonal winds in winter. In this study, intensive 24-h observations were conducted every hour eight times from 2019 to 2020 to clarify changes in stream water quality and runoff processes during rainfall events. The pH, electrical conductivity, and SO₄²⁻ concentration in stream water decreased with increasing hourly average discharge rate (L sec⁻¹). The SO₄²⁻ concentration was negatively correlated with discharge rate. Hydrograph separations using the water isotopic parameter (deuterium excess, d-excess = δ²H – 8 × δ¹⁸O) showed that most of the stream flow during the rain events was derived from pre-storm water. A significant negative correlation between the d-excess and stream water discharge was found for all six events where the water isotope analysis was applied. However, the S isotope ratio (δ³⁴S) in stream water was not correlated with discharge rate during rainfall events and was obviously different (>1.5‰) from rainwater δ³⁴S in the same month. This suggests that rainwater SO₄²⁻ during rainfall events did not directly flow to the stream but was retained in the forest ecosystem. The isotopically well homogenized internal SO₄²⁻ appeared to be mainly released into the stream during rainfall events. Future climate change may further accelerate SO₄²⁻ runoff from forest catchments and disrupt material cycles in the ecosystem if warming causes more intense rainfall.

Sediment sources and sinks are an effective reflection of the comprehensive management of soil and water conservation in a watershed. However, human interference has made the sediment transport process in watersheds more complex. Research that distinguishes hillslopes and channels to reveal changes in sediment sources and sinks within a watershed and the relationships with key driving factors requires strengthening. In this study, the characteristics of sediment sources and sinks on hillslopes in the Mahuyu watershed, located on the Loess Plateau, were simulated using the Revised Universal Soil Loss Equation model and hillslope sediment delivery ratio model. Furthermore, variations in channel scour and siltation at the event scale were analysed based on the simulated hillslope sediment yield and measured sediment yield at the outlet station. Additionally, the principal hydrological driving factors affecting the sediment yield at the outlet were explored. The results show that 66 sediment yield events occurred in the Mahuyu watershed during the period 2006–2018, and channel sediment yield has emerged as the leading contributor to the watershed sediment yield, accounting for a minimum of 69.8%. There is also a marked decoupling between hillslope sediment yield and watershed sediment yield in the Mahuyu watershed. Furthermore, the maximum daily average streamflow is identified as the critical driving factor responsible for determining the watershed sediment yield, indicated by a coefficient of determination of 0.850. Therefore, we recommend that the future focus of soil and water conservation measures should be shifted from hillslopes to channels.

The essay describes how a combination of scaling theory from percolation, that relates pore scale flow and transport through catchment scales to global scales (bottom-up), as well as water fluxes to soil formation and vegetation growth, can be used to support an accurate ecological optimization that (top-down): solves the central problem of hydrology, that is., “the water balance,” and generates critically important derived quantities, namely streamflow response to climate change, net primary productivity, and plant species richness. Moreover, the essay describes how this particular theoretical approach came to be designed and how it, in retrospect, fits in with the vision of the Committee on Opportunities in the Hydrologic Sciences which met 34 years ago to formulate a research, teaching, and infrastructure guide for the community, and “rebrand our science as a geoscience.” Finally, it demonstrates how the research satisfies the present desires of the community to unite Darwinian and Newtonian scientific methods in the solution of this central problem and how it relates to present research directions in the fields of hydrologic sciences and ecology.

In the western United States, water supplies largely originate as snowmelt from forested land. Forests impact the water balance of these headwater streams, yet most predictive runoff models do not explicitly account for changing snow-vegetation dynamics. Here, we present a case study showing how warmer temperatures and changing forests in the Henrys Fork of the Snake River, a seasonally snow-covered headwater basin in the Greater Yellowstone Ecosystem, have altered the relationship between April 1st snow water equivalent (SWE) and summer streamflow. Since the onset and recovery of severe drought in the early 2000s, predictive models based on pre-drought relationships over-predict summer runoff in all three headwater tributaries of the Henrys Fork, despite minimal changes in precipitation or snow accumulation. Compared with the pre-drought period, late springs and summers (May–September) are warmer and vegetation is greener with denser forests due to recovery from multiple historical disturbances. Shifts in the alignment of snowmelt and energy availability due to warmer temperatures may reduce runoff efficiency by changing the amount of precipitation that goes to evapotranspiration versus runoff and recharge. To quantify the alignment between snowmelt and energy on a timeframe needed for predictive models, we propose a new metric, the Vegetation-Water Alignment Index (VWA), to characterize the synchrony of vegetation greenness and snowmelt and rain inputs. New predictive models show that in addition to April 1st SWE, the previous year's VWA and summer reference evapotranspiration are the most significant predictors of runoff in each watershed and provide more predictive power than traditionally used metrics. These results suggest that the timing of snowmelt relative to the start of the growing season affects not only annual partitioning of streamflow, but can also determine the groundwater storage state that dictates runoff efficiency the following spring.

Floodplains are one of the most threatened ecosystems. Even though the vegetation composition in floodplain forests is expected to reflect the variation in groundwater levels and flood duration and frequency, there is little field data on the inundation dynamics (e.g., the variability in flood duration and flood frequency), especially for the understudied seasonally dry tropics. This limits our understanding of these ecosystems and the mechanisms that cause the flooding. We, therefore, investigated six floodplain forests in the state of Minas Gerais in Brazil for 1.5 years (two wet seasons): Capivari, Jacaré, and Aiuruoca in the Rio Grande basin, and Jequitaí, Verde Grande, and Carinhanha in the São Francisco basin. These locations span a range of climates (humid subtropical to seasonal tropical) and biomes (Atlantic forest to Caatinga). At each location, we continuously measured water levels in five geomorphologically distinct eco-units: marginal levee, lower terrace, higher terrace, lower plain, and higher plain, providing a unique hydrological dataset for these understudied regions. The levees and terraces were flooded for longer periods than the plains. Inundation of the terraces lasted around 40 days per year. The levees in the Rio Grande basin were flooded for shorter durations. In the São Francisco basin, the flooding of the levees lasted longer and the water level regime of the levees was more similar to that of the terraces. In the Rio Grande basin, flooding was most likely caused by rising groundwater levels (i.e., “flow pulse”) and flood pulses that caused overbank flooding. In the São Francisco basin, inundation was most likely caused by overbank flooding (i.e., “flood pulse”). These findings highlight the large variation in inundation dynamics across floodplain forests and are relevant to predict the impacts of changes in the flood regime due to climate change and other anthropogenic changes on floodplain forest functioning.

Water is essential for humans as well as for all living organisms to sustain their lives. Therefore, any climate-driven change in available resources has significant impacts on the environment and life. Global climate models (GCMs) are one of the most practical methods to evaluate climate change. Based on this, this research evaluated the capability of GCMs from the Coupled Model Intercomparison Project 6 (CMIP6) to reproduce the historical flow of climate prediction centre data for the Konya Closed basin and to project the climate of the basin using the selected GCMs. Global climate models based on the CMIP6 under the scenario of common socioeconomic pathways (SSP245 and SSP 585) were used to analyse the climate change effect on streamflow of the study area by Bias Correction of GCM Models using Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), AdaBoost, Gradient Boosting, Regression Tree, and Random Forest methods. The coefficient of determination (R²), mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE) were used to assess the performance of the methods. Findings show that the Random Forest Model consistently outperformed other models in both the testing and training phases. A significant downward in the volume of water flowing through the region's rivers and streams in the next decades. It is critical to enhance climate-resilient water infrastructure financing, establish an early warning system for drought, introduce best management practices, implement integrated water resource management, public awareness, and support water research to alleviate the negative consequences of drought and increase resilience against the effects of climate change on Turkey's water resources.

While green roofs have gained widespread popularity as a measure to detain and retain runoff in urban areas, their performance during extreme events is not well studied. In this study 15 years of runoff and precipitation observations from a small extensive green roof in Norway are analysed. GEV-distributions were fitted to the annual max values for precipitation and runoff in order to develop intensity-duration-frequency (IDF) and runoff-duration-frequency (RDF) data. Using the IDF and RDF data a total of 31 extreme events were identified (containing precipitation or runoff values with return period greater than 2 years for one or more durations). While nearly all extreme runoff events were caused by extreme precipitation, only 69% of the extreme precipitation events resulted in extreme runoff. The assumption of 1:1 equivalency of return periods did not hold true, and deviations were mainly explained by variations in substrate water content prior to the extreme event. Moreover, in 50% of the events, the runoff duration with the greatest return period was shorter than the precipitation duration with the greatest return period. Hence, the results indicate that the use of design storms to predict runoff from green roofs may be inappropriate. The potential of having IDF and RDF data available was demonstrated by the development of simple empirical equations, which ensure conservations of both return period and duration. To generate reliable green roof RDF data, future research should prioritize evaluating various continuous models with the aim of accurately describing extreme events.