Hydrological Processes最新文献

The measurement of the stream water temperature signal is subject to various issues and environmental phenomena. Accurate interpretations of the data composing water temperature time series (WTS) often require a high-level human expertise during data preprocessing steps to sort out meaningful temperature signals. This study proposes a method to highlight two main types of particular behaviours encountered in WTS, apart from outliers: intensified data and buffered data. The method uses a metric based on the WTS itself to identify periods with particular data. It enables the identification and the visualisation of regular and irregular particular behaviours in a given WTS. The method was applied to a large national dataset collected in mainland France. The dataset contains 993 WTS with a wide range of data quality and environmental measurement conditions. Data identified as particular behaviour accounts for up to 7% of the dataset. Depending on the measurement conditions, up to 25% of a given WTS data can be considered as ‘occasional particular behaviour’ and potentially not exploitable. Buffered data mostly occur during winter months with no apparent spatial pattern. Intensified data occur mainly in summer months and a spatial pattern shows WTS containing the highest percentage of intensified data in the south-east part of the study area. The identification method was also applied to several known situations where a high-level human expertise was available. It provided robust identification performances at regional scale confronted with human expertise as well as at national scale, on a large dataset. Such methods can facilitate the selection of exploitable data in large datasets which are more widely available today. Potentially problematic data becomes straightforward and subsequent data qualification or correction is facilitated.

Dynamic water storage reflects the movement of water within a watershed, including infiltration from the surface to the subsurface. In this study, we addressed two questions: (a) What are the spatiotemporal patterns of dynamic water storage during 13 extreme drought events? and (b) How do these patterns correlate with specific hydroclimatic and physiographic characteristics? To answer these questions, we analysed the variability of dynamic water storage dS(t), estimated via a water-balance approach as the increase or decrease in storage over time from the beginning to the end of the rainy season across 43 watersheds in south-central Chile (1980–2020), focusing on how meteorological droughts influence watershed storage dynamics. Our results show that dynamic water storage responds rapidly to precipitation, with maximum values ranging from 17 to 632 mm, and declines to negative values during dry periods. On average, storage peaks were observed 126 days after the onset of precipitation. The initial storage reduction during the droughts averaged 51 mm. Lower storage maxima are associated with drier climatic conditions (negative values of the standardised precipitation index [SPI] and the Palmer drought severity index [PDSI]), increased numbers of consecutive dry days in both summer and winter, and catchment characteristics such as higher elevation, steeper slopes and higher flow velocities. Seasonal shifts in storage, with accumulation at the beginning of the wet season and a rapid decline to negative values at the end of the dry season, reflect periods of water connectivity and disconnection, offering critical insights into hydrological modelling and drought mitigation strategies. We interpret the disconnection period as one in which surface water levels decrease owing to the absence of precipitation and increased evapotranspiration rates, highlighting the vulnerability of watersheds to extreme climatic events.

Lake Balkhash, the third-largest water body in arid Central Asia, is facing increasing concern as a result of recent declines in its water level. The Global Ecosystem Dynamics Investigation (GEDI) lidar, operational since April 2019 aboard the International Space Station, offers valuable data for measuring and monitoring inland water levels. However, GEDI-derived elevation estimates are generally less accurate than those from radar or lidar altimeters dedicated to water-level monitoring, exhibiting standard deviations ranging from 0.14 to 0.66 m compared to ICESat-2's from 0.03 to 0.05 m. To leverage the temporal resolution of GEDI data while mitigating its limitations, this study integrates GEDI and ICESat-2 satellite altimetry to investigate the water level dynamics of Lake Balkhash. A custom data processing protocol, including both global and local refinements, was applied prior to data integration. A gradient boosting machine (GBM) effectively reduced biases between the datasets, revealing a long-term water level decline of 0.22 m/y over the period 2019–2023. In comparison to the Hydroweb and DAHITI datasets, the integrated product demonstrated improved consistency, temporal resolution and reduced noise. The integrated dataset showed good agreement with Hydroweb (RMSD of 0.32 m and R² of 0.89) and DAHITI (RMSD of 0.21 m and R² of 0.84), and exhibited superior stability, with intra-annual standard deviations of 0.07–0.16 m. The distributed lag multivariate regression model showed that current-month precipitation positively influenced water levels, while current-month evaporation had a significant negative effect, with spring precipitation boosting levels and summer evaporation dominating water loss. These results indicate that this integrated satellite altimetry approach provides a robust tool for water resource monitoring and climate studies, particularly in data-scarce regions.

A comprehensive understanding of groundwater hydrochemical characteristics and its evolution mechanisms that control the salinization process is essential for sustainable groundwater management, particularly in coastal plains with intensive anthropogenic activities. In this study, a combination of hydrochemical analysis, stable isotope tracing, PCA, and HFE-D methods was used to identify the spatial characteristics of groundwater hydrochemistry and assess the processes controlling its evolution associated with groundwater salinization in the Wenhuang Plain, Southeast China. The results indicate that rock weathering dominated the hydrochemical evolution of groundwater in conjunction with cation exchange, and silicate weathering was the dominant weathering type controlling the chemical composition of surface water and groundwater. The weathering of evaporites was a major contributor to salinity in deep groundwater (DGW) II, related to lateral runoff recharge with the long-term water–rock interaction. Seawater intrusion, induced by groundwater over-exploitation, caused an imbalance in mineral saturation. This provided favorable conditions for reverse cation exchange, consequently leading to an excess of Ca²⁺ and Mg²⁺ in the DGW, particularly for the samples adjacent to the estuary and coastal zones. The salinization of surface water and shallow groundwater was primarily controlled by evaporation and anthropogenic inputs. Freshwater–saltwater mixing was the dominant process controlling groundwater salinization in DGW I, accounting for 25.8% of the samples identified as being in the intrusion phase. Principal component analysis (PCA) confirmed that water–rock interactions, anthropogenic activities, and seawater intrusion are the key factors governing groundwater geochemistry, explaining 82.62% of the total variance. These findings can help improve groundwater utilization and management for sustainable development in coastal areas and reveal the negative impacts of seawater intrusion on groundwater quality.

This study presents a mathematical model based on the temporally relaxed theory (TRT) of Fick's law to describe one-dimensional (1D) non-Fickian solute transport in a layered heterogeneous porous medium. The model incorporates dual relaxation times accounting for flux lag ($��{\tau }_J�$) and storage lag ($��{\tau }_C�$), to capture non-equilibrium dynamics, yielding novel advection-dispersion equations (ADEs) for each layer. The system, which includes a time-dependent input source, is solved semi-analytically using Laplace Transform Techniques, followed by numerical inversion. Graphical representations are generated using MATLAB software. The TRT model is rigorously validated against classical analytical solutions, including the linear equilibrium (LE) and mobile-immobile (MIM) models, showing excellent agreement. Furthermore, excellent agreement with a high-resolution finite volume numerical solution confirms its robustness under complex conditions. The results demonstrate that the relaxation times significantly influence spatial concentration profiles, remediation time and hydrological processes, with their impact being transport-parameter-dependent. The time lags effectively capture non-linear phenomena like multi-scale behaviour and anomalous transport, such as super-diffusion, sub-diffusion. This innovative approach provides valuable insights into solute transport in layered media and its implications for groundwater contamination, serving as a preliminary tool for studying decaying solute migration, such as radionuclides, and their impact on water quality.

Water use efficiency (WUE) is an important indicator for assessing the trade-off between carbon uptake and water loss in terrestrial ecosystems. The WUE is generally calculated as the ratio of gross primary productivity (GPP) or net primary production (NPP) to evapotranspiration (ET) or transpiration (T) in previous studies. However, these traditional WUE formulas only reflect the final water consumption and vegetation productivity, and the intermediate steps of vegetation water utilisation were ignored. Here, based on the eddy covariance (EC) technique, the WUE chain was developed by dividing WUE into four steps: GPP/T, T/ET, ET/SW (SW is the soil water) and SW/TWI (TWI is the total water input) in four typical ecosystems in northwest China. Then, the characteristics of change in the growing season WUE chain for four ecosystems were analysed. Finally, the random forests model and structural equation model were employed to investigate the controlling factors affecting the WUE chain by examining the relationship between the intermediate steps of the WUE chain and major impact factors. The forest ecosystem had the highest growing season WUE (0.89 gC·m⁻²·mm⁻¹), followed by cropland (0.30 gC·m⁻²·mm⁻¹) and grassland (0.24 gC·m⁻²·mm⁻¹), while the smallest was in the desert (0.20 gC·m⁻²·mm⁻¹). The controlling factors impacting WUE differed greatly among the four ecosystems by regulating the intermediate steps of the WUE chain. Air temperature mainly controlled WUE change in croplands and deserts by simultaneously regulating GPP/T, T/ET and ET/SW. Leaf area index primarily controlled WUE in grasslands by affecting T/ET and ET/SW. Atmospheric pressure primarily influenced the forest WUE by regulating T/ET. Applying the WUE chain enhances our understanding of the water use process of vegetation and further promotes sustainable water resources management in arid and semi-arid areas.

The aim of this study is to assess the key drivers of runoff generation in permeable volcanic catchments, and notably the role of geology. Therefore, the hydrological response of 28 catchments located on the tropical volcanic Island of la Réunion, characterised by strong climatic forcing and geological contrasts, was studied. High-frequency measurements (15-min time step) of radar rainfall and discharge records over the 2014–2022 period were analyzed to develop a hydroclimatic database including 4591 storm-flood events. At the annual scale, results show regional patterns in the rainfall-runoff relationship, associated with the geological age and the local climate. Our results provide evidence of windward/leeward and geological effects on hydrological response at both the annual and flood event scales, with a significant correlation between the event-scale runoff coefficient and annual rainfall. Combined with a statistical analysis of the data, including the application of a random forest algorithm, results suggest the importance of antecedent saturation conditions, preferentially occurring on the older and more weathered geology, while younger geology displayed a more episodic pattern. This study contributes to increasing our understanding of the hydrological behaviour of tropical volcanic catchments, by analysing the relative importance of climate and geology in controlling the catchments' hydrological response, which may help improve water management and flood prediction.