Hydrological Processes最新文献

In 2020, Colorado experienced the most severe wildfire season in recorded history, with wildfires burning 625 357 acres across the state. Two of the largest fires burned parts of Rocky Mountain National Park (RMNP), and a study was initiated to address concerns about potential effects on drinking water quality from mobilization of ash and sediment. The study took advantage of a wealth of pre-fire data from adjacent burned and unburned basins in western RMNP. Pre- and post-fire data collection included discrete sample collection and high-frequency water-quality measurements using in-stream sensors. Kruskal–Wallis tests on discrete data indicated that specific conductance, base cations, sulphate, chloride, nitrate, and total dissolved nitrogen concentrations increased post-fire, whereas silica and dissolved organic carbon (DOC) did not (p ≤ 0.05). In-stream sensors captured large spikes in concentrations of nutrients, turbidity, and DOC in the burned basin that were missed by discrete sampling. Sensor data indicated nitrate and turbidity increased by up to one and two orders of magnitude, respectively, from pre-event concentrations during storms, and DOC increased up to 3.5×. Empirical regression equations were developed using pre-fire data and applied to the post-fire period to estimate expected stream chemistry in the absence of fire (a ‘no-fire’ scenario). Overlays of actual post-fire chemistry showed the timing and magnitude of differences between observed and ‘estimated’ chemistry. For most solutes, observed post-fire concentrations were notably greater than expected under the ‘no-fire’ scenario, and differences were greatest during storm events. Comparison of data from the burned and unburned basins indicated DOC concentrations were affected by climate as well as fire. Results from this study demonstrate the importance of both pre-fire data and high-frequency data for characterizing dynamic hydrochemical responses in wildfire-affected areas.

Changes in the volume, rate, and timing of the snowmelt water pulse have profound implications for seasonal soil moisture, evapotranspiration (ET), groundwater recharge, and downstream water availability, especially in the context of climate change. Here, we present an empirical analysis of water available for runoff using five eddy covariance towers located in continental montane forests across a regional gradient of snow depth, precipitation seasonality, and aridity. We specifically investigated how energy-water asynchrony (i.e., snowmelt timing relative to atmospheric demand), surface water input intensity (rain and snowmelt), and observed winter ET (winter AET) impact multiple water balance metrics that determine water available for runoff (WAfR). Overall, we found that WAfR had the strongest relationship with energy-water asynchrony (adjusted r² = 0.52) and that winter AET was correlated to total water year evapotranspiration but not to other water balance metrics. Stepwise regression analysis demonstrated that none of the tested mechanisms were strongly related to the Budyko-type runoff anomaly (highest adjusted r² = 0.21). We, therefore, conclude that WAfR from continental montane forests is most sensitive to the degree of energy-water asynchrony that occurs. The results of this empirical study identify the physical mechanisms driving variability of WAfR in continental montane forests and are thus broadly relevant to the hydrologic management and modelling communities.

Soil erosion is a key concern with regard to ecosystem functionality and food, fibre and bioenergy productions worldwide. Therefore, understanding the mechanisms and controls of soil erosion, particularly the link between soil aggregate stability and soil erodibility, is of utmost importance. The use of disturbed samples and sieved soil to determine the involved erodibility and aggregate stability is standard in soil erosion studies. However, soil erodibility estimation based on disturbed-soil samples can be inaccurate as it involves changes in the architecture of the considered soil, possibly leading to overestimations. Moreover, a necessity for evaluating soil erodibility beyond intrinsic soil characteristics (e.g. texture) exists. The objective of this research was to assess the erodibility impact of soil disturbance. Undisturbed-soil cores with dimensions of 45 cm (length) × 30 cm (width) × 10 cm (depth) were extracted while preserving their architecture. An A horizon corresponding to brown clayey subtropical oxisol soil from Southern Brazil was used for performing an experiment that involved simulation of 58–mm h⁻¹ rain for 30 min. A total of seven replicate experiments were performed for each soil condition (i.e. undisturbed and disturbed soils). Results show that soil architecture deterioration had a larger impact on the involved soil loss than runoff. Further, soil structure failure did not affect the aggregate stability per se. Notably, the soil erodibility and loss were approximately 10 times larger under the disturbed-soil condition than under the undisturbed-soil condition (interrill erodibility: 4.30 × 10⁷ and 4.39 × 10⁶ kg s m⁻⁴, respectively; soil loss: 0.925 and 0.094 kg m⁻², respectively). Overall, the intrinsic soil characteristics did not change; however the soil architecture deterioration considerably increased the erodibility.

Rainfall redistribution plays a crucial role in the water cycle. However, the main factors affecting the redistribution of rainfall remain uncertain. We chose three different plantations—cork oak (Quercus variabilis Bl.), oriental arborvitae (Platycladus orientalis L.) and black locust (Robinia pseudoacacia L.)—to investigate the role of plantations in rainfall redistribution and to determine the main factors influencing rainfall redistribution. The results indicated that cork oak exhibited the highest stemflow (0.34%) and the lowest canopy interception (12.58%), whereas black locust had the lowest stemflow (0.21%), and oriental arborvitae displayed the greatest canopy interception (32.8%). Under different density conditions for cork oaks, the stemflow was highest (0.39%) in low-density forests with 750 trees ha⁻² and lowest (0.34%) in medium-density forests with 1100 trees ha⁻². Meanwhile, the highest canopy interception (17.68%) was observed in high-density forests (1300 trees ha⁻²), while the lowest interception rate (9.22%) was found in low-density forests. The main factors affecting rainfall redistribution and their contribution rates were as follows: bark roughness index (35%), wind speed (18.6%), tree species (14.2%), diameter at breast height (11.2%), stand density (9.6%) and rainfall amount (5.4%). Our findings suggested that structural characteristics of trees are the primary factors affecting rainfall redistribution. Planting cork oak in the rocky mountain regions of North China is recommended because of its substantial stemflow production, particularly under low-density growth conditions. Therefore, this study has significant guiding implications for the selection of afforestation tree species in similar rocky mountain areas globally.

Climate change and anthropogenic influences amplify drought complexity, entangle non-stationarity (NS) and further challenge drought comprehension. This study aims to understand the dynamic evolution of drought propagation patterns due to climatic and anthropogenic pressures by assessing the non-stationary linkages between hydrological variables and drought characteristics. It employs four standardized drought indicators to comprehensively examine the spatio-temporal evolution of meteorological (MD) and hydrological (HD) drought characteristics. Data from 29 semi-arid catchments from six river basins in Peninsular India, are analyzed to uncover distinct drought propagation patterns. This study utilizes a novel Non-overlapping Block-stratified Random Sampling (NBRS) approach to detect NS in drought characteristics and hydrological variables, shedding light on the underlying drivers of this dynamic behavior. The results indicate similarities in drought behavior for the Sabarmati, Mahi and Tapi (SMT) basins compared with the Godavari, Krishna and Pennar (GKP) basins, with shorter (longer) propagation times noted for SMT (GKP) basins. While HD severity decreases over time in SMT basins, it intensifies in GKP basins, which are linked to intensive anthropogenic interventions such as river regulation and reservoir operations, thus resulting in prolonged and intensified droughts. Rainfall primarily exhibits time-invariance, while significant NS is observed in potential evapotranspiration (particularly in the Krishna and Pennar basins), streamflow and baseflow across all basins. The study also identified three distinct drought propagation patterns in these basins, highlighting cases where MD did not transition to HD, instances of HD occurring without preceding MD and synchronous propagation of MD to HD. The study outcomes provide profound insights into the evolution of drought dynamics under climatic and anthropogenic pressures, which will aid policymakers and stakeholders in formulating strategies for drought preparedness and response.

The length and frequency of extreme fire weather has increased across the globe in recent decades, with potential deleterious consequences to streamflow quantity, timing and quality. Changes in the hydrologic regime following wildfire can have substantial downstream consequences, affecting communities and ecosystems through flooding, erosion, loss of habitat and degraded water quality. While there are many studies that address post-wildfire hydrology across the globe, there are few studies in the snow-dominated regions. The 2017 Elephant Hill wildfire in south-central BC burned across or adjacent to four watersheds with long-term streamflow gauges providing a rare opportunity to evaluate hydrologic change. Several approaches were used to identify patterns of change following the wildfire, all of which suggest increased post-fire flows. The before-after-control-impact design showed significant increases in annual, spring and summer water yield from the small (49 km²) Arrowstone Creek watershed (30%, 21% and 86%, respectively). Significant increases in spring water yield were observed in the larger (5318 km²) Bonaparte River watershed (48%). Annual and summer water yield increased in the Bonaparte River (31% and 58%, respectively) but these changes were not statistically significant. In both the Bonaparte River and Arrowstone Creek, the onset of spring freshet (26 days earlier in both) was significantly advanced, however, the timing of maximum snowmelt discharge was significantly advanced (27 days earlier) only in Arrowstone Creek. Smaller changes were also observed in the reference watersheds; however, these were not statistically significant. The difference in results between the small and large watershed, as well as the effects of weather and watershed attributes, highlight the need for continued research into the relationships between wildfire and hydrologic regime across diverse landscapes.

Ecological drought has emerged as a critical research topic within eco-hydrology, driven by the increased drought risk associated with global warming. This study aims to unravel the hydrological processes driving ecological drought in Northwest China by (1) constructing standardized indices for precipitation, groundwater storage anomaly, and ecological water deficit to detect variation across different hydrological components; (2) developing a framework to assess the joint and relative impacts of precipitation and groundwater variations on ecological drought; and (3) identifying the primary hydrological drivers of ecological drought across different regions. The results indicate that the joint impact of precipitation and groundwater on ecological drought variation dominates approximately 60% of the area, primarily in arid and semi-arid regions. The average contribution of this joint impact to the alleviation of ecological drought ranges between 0.26 and 0.43 across all seasons. Notably, groundwater scarcity, rather than precipitation variation, is the primary driver of ecological drought in regions such as southern Shaanxi, southeastern Gansu, and southern Qinghai, accounting for 12.7% to 21.8% of the total area. These insights into the complex hydrological processes underlying ecological drought have significant implications for water resource management and ecosystem conservation in drought-prone regions. This research provides valuable information for mitigating drought impacts and protecting vulnerable ecosystems in Northwest China and similar regions worldwide.

The formation and concentration of liquid water (LW) in the snowpack constitute key processes linking snow and runoff. Hence, the LW content of the snowpack represents a crucial target variable to investigate for snowmelt-induced runoff predictions. In this study, we capture the wet snow dynamics at higher than hectometre resolution in the alpine headwater catchment Rofental, Tyrol, Austria (98.1 km²) by means of distributed model simulations and remote sensing data for the 5 year period 10/2017–09/2022. The model simulations are conducted using the intermediate complexity open-source snow-hydrological model openAMUNDSEN. Simulation results are compared to wet snow maps (WSM) derived from Sentinel-1 data. Our investigations indicate that distributed snow models of intermediate complexity, such as openAMUNDSEN and satellite-based wet snow data are well capable of capturing the wet snow dynamics in high spatial and temporal resolutions. The areal extents of wet snow as well as the upward movement of the wet snow line to higher elevation with progressing snowmelt are captured well by both approaches. In order to evaluate the snow simulations, we use fractional snow cover (FSC) data based on Sentinel-2, which proved to provide valuable small-scale snow and snow redistribution patterns in alpine catchments. The comparison of model simulations with FSC maps with more than 50% of the non-glaciated area being cloud-free (i.e. 364 images) results in an accuracy of 0.91. This study represents a further step towards a serviceable operational snow-hydrological monitoring and modelling framework for mountain regions including wet snow dynamics in high spatial and temporal resolutions.