Journal of Hydrology最新文献

The changes of hydrodynamic conditions and the related eutrophication have been observed among reservoir-impacted regions. However, the evolution and impacts of the hydrodynamic characteristics of tributaries under the interference of the reservoir still need further explanation. The three-dimensional Environmental Fluid Dynamics Code (EFDC) model coupling with the watershed hydrological model was built to explore the special flow field of the tributaries in the Three Gorges Reservoir Region. The results showed that there was significant laminar flow pattern driven by water temperature, except during low level and storage periods. During the rising level period, the difference in response to temperature changes between the main stream and tributaries caused the invading flow to converge in bottom layer. The convergence of cold and warm peaks resulted in water masses flowing out in opposite directions from surface layer. During this process, there existed transition from horizontal circulation to vertical circulation, breaking up vertical differences of 0.40 mg/L of nitrogen, aggravating eutrophication in surface layer during the low level period. Instead, the low velocities in stagnant areas did not lead to significant accumulation of nutrients. However, the variation of nutrients in the annular section exhibited a short-term lag compared to the longitudinal profile. Finally, the stepped tides by interrupting the continuous raise processes of water level was more efficient for controlling eutrophication than general regulating rules during the impoundment period. The results could be used for managing eutrophication in similar regions.

Water use efficiency (WUE), which is strongly related to carbon and water cycles, is crucial for maintaining fragile and sensitive alpine ecosystems. An accurate assessment of the spatial and temporal variations in WUE among alpine shrubs under different aridity levels is essential for quantifying the carbon and water balance in alpine environments. We calibrated the Biome-BGC model using the parameter estimation (PEST) approach with one year of data from an eddy covariance tower and validated the model against three years of carbon–water flux and carbon storage data from 80 biomass sampling sites in Qinghai Province, China. We then simulated the carbon and water cycles of alpine shrubs in Qinghai Province from 1980 to 2019. Using meteorological data from the study area, we analyzed the spatiotemporal variations and factors influencing WUE in regions with different aridity levels. The results showed that after optimization using the PEST approach, the mean absolute error (MAE) and root mean square error (RMSE) of gross primary productivity (GPP) decreased by 0.58 and 1.05 g C m⁻² d⁻¹, respectively, and those of evapotranspiration (ET) decreased by 0.41 and 0.77 mm d⁻¹, respectively. Spatial distribution analysis revealed that the annual mean GPP and ET generally decreased from southeast to northwest in the order of humid, subhumid, semi-arid, arid, and hyper-arid climate regions. In other regions, WUE exhibited a biphasic trend with the aridity index, decreasing under severe dryness but increasing as aridity increased. The primary controlling factor in humid and sub-humid regions is the mean annual temperature, whereas in arid and semi-arid regions it is the mean annual precipitation. These findings are critical for improving the prediction of carbon sequestration and water-holding capacity of alpine shrublands under drought conditions.

The integrated warm-wet trends over the Tibetan Plateau (TP) have posed a vital influence on human society and natural ecosystem in recent decades. However, there is currently a lack of in-depth research on the trends over the TP. In this study, CN05.1 high-resolution grid data and ERA5 reanalysis data were analyzed to explore temporal and spatial changes of the integrated warm-wet trends over the TP during 1961-2020 based on temperature, precipitation and the new defined Warm-Wet index (WWI). The results are shown as follow: (1) Temporally, annual surface mean temperature (0.34°C per decade), precipitation (0.73% per decade), latent heat flux (0.08W·m^-2 per decade), and sensible heat flux (0.19W·m^-2 per decade) have overall increased over the TP. Further, defined by the above climate variables, WWI has increased in the most regions from 1960s to 1980s, then the variations have become relatively mild in the following two decades. (2) Spatially, WWI has finally formed a pattern of significant increase in the semi-humid region and eastern semi-arid region and significant decrease in the humid region, which is similar to precipitation. Noticeably, arid region, semi-arid region, and semi-humid region have all experienced significant increase of WWI but humid regions have experienced decrease. That is, the relatively dry regions over the TP have become warmer-wetter but the relatively wet regions have become warmer-drier. (3) In addition, seasonal asymmetric has been revealed, and winter has experienced the most significant warming-wetting in spite of the smallest values of temperature and precipitation in climatology. (4) Finally, among all independent variables, precipitation contributes the most to the variations of WWI over the entire TP, while temperature is crucial in the arid region and surface heat flux plays an important role in the humid region. Our findings may provide additional insights regarding the risk evaluation over the TP, and the proposed framework to evaluate the trends over different climate zones could also offer a meaningful guide to other regions.

Wildfires can dramatically alter vegetation cover and soil properties across large scales, resulting in substantial shifts in runoff generation, streamflow, and water quality. In September 2020, extensive and high-severity wildfires burned more than 490,000 ha of forest land on the westside of the Cascade Mountain Range in the Pacific Northwest. Much of the area impacted by these fires is critical for the provision of water for downstream aquatic ecosystems, agriculture, hydropower, recreation, and municipal drinking water. We undertook a study to evaluate the effects of four of the large high severity wildfires from 2020 (Riverside, Beachie Creek, Lionshead, and Holiday Farm) on streamflow in nine burned catchments in western Oregon. We also included four unburned, reference catchments in our analysis to enable us to assess post-fire streamflow changes in the burned catchments. To quantify the effects of wildfire on the catchment water balance we used publicly available streamflow data and estimated precipitation, potential evapotranspiration (PET), and actual evapotranspiration (ET), using satellite-based meteorological data. We quantified catchment area burned and burn severity with the average differenced normalized burn ratio (dNBR). We compared hydrologic conditions for the pre-fire (2001–2020) and post-fire (2021–2022) periods by analyzing catchment runoff ratios, ET ratios (evaporative index: quotient of ET divided by precipitation, referred to as EI hereafter), and Budyko curves. We also used random forest models to explore factors influencing the variability in EI. During the post-fire period, we observed decreases in EI and increases in runoff ratio in the burned catchments. Post-fire declines in EI were positively related to burn severity (R² = 0.70 in 2021; 0.76 in 2022) and area burned (R² = 0.91 in 2021; 0.95 in 2022), and were primarily driven by decreases in ET. Declines in ET were highly variable, ranging from 10.7–40.2 % in the first year after the fires and 6.1–32.0 % in the second year after the fires, and were generally related to catchment burn severity and area burned. The greatest increases in runoff (16.1 % in 2021 and 19.8 % in 2022) occurred in the same catchment. These results were reinforced by the random forest analysis, which illustrated the importance of burn severity as a predictor of EI. Interestingly, the variability in changes in EI during the post-fire period was also associated with other geomorphic factors such as catchment slope, elevation, geology, aspect, and pre-fire vegetation type. Since the duration and seasonality of post-fire impacts on hydrology remain uncertain, our findings bring new insights and guide future studies into the post-fire responses on hydrology that are crucial for water and forest management.

Hydrograph separation assessment is crucial to understand stormflow generation at catchments worldwide. Tracer-based methods provide robust estimations of event (or new) and pre-event (or old) water fractions as they account for external and internal catchment hydrological behavior. While models of different mathematical and computational complexity are often used in tracer-based hydrograph separation studies, direct comparisons between those models are limited. Here, we compare hydrograph separation results yielded by the simplest Two-Component Mixing Model (TCMM) and a Tracer-based Streamflow Partitioning ANalysis model (TraSPAN) assumed to provide robust results as it combines conceptual rainfall-runoff modelling with tracers’ mass balance. We carried out the analysis using high temporal frequency (sub-daily to sub-hourly) data of two tracers, Oxygen-18 and Electrical Conductivity (EC), monitored during 37 rainfall-runoff events with different hydrometeorological conditions in a high-Andean páramo catchment located at the Zhurucay Ecohydrological Observatory in southern Ecuador. Both approaches yield similar estimations of event and pre-event water fractions regardless of the tracer used as long as appropriate concentrations of event (C_e) and pre-event (C_p) water for the TCMM are determined. Although the estimate of C_e has little influence with one rainfall sample collected during the event being sufficient to obtain reliable results, results hinge heavily on the estimate of C_p. We found that the TCMM yields similar results than TraSPAN when C_p is represented by the stream water concentration corresponding to a sample collected prior to the beginning of each of the events. We conclude that the combination of a simple framework (TCMM) with sub-hourly EC measurements provides reliable hydrograph separation results when representative C_p samples are used. These findings will allow to lower the logistical and economical resources needed to adequately assess hydrograph separation and to carry out quasi-continuous assessments of flow partitioning with high accuracy in high-Andean páramo catchments.

Irrigated arid oasis areas experience shortages in water resources and imbalances between supply and demand. A rational water resources allocation strategy must be devised to solve such problems; however, this remains a challenging issue to overcome. In this study, a multi-objective water resources optimization model based on a metaheuristic algorithm was established for the Manas River irrigation area in Xinjiang. First, considering future population growth and the development of the ecological environment in arid oasis irrigation areas, a multi-objective water resource optimization allocation model was established. This model was developed to derive the maximum economic benefits from water supply allocation to users, improve the degree to which ecological water demand is met for ecological environmental restoration, and reduce water shortages. The model adheres to the constraints of the total water resources in this area and can be used to effectively solve future water resources supply and demand imbalances in the Manas River irrigation area. Second, a multi-objective beluga whale optimization algorithm was selected to solve multi-objective problems. In contrast to traditional optimization algorithms, the multi-objective beluga whale optimization algorithm does not rely on the knowledge of a specific problem domain, representing a more generalized approach. Instead, this algorithm provides a general framework for searching for solutions, finding an approximate optimal solution, and generating a multi-objective solution set, taking into account the model computation time and domain. Finally, the target solution set obtained after 100 iterations is used as the basis for identifying the optimal solution. The key findings of this study are as follows: (1) The solution sets obtained by applying the multi-objective beluga whale optimization algorithm to solve the multi-objective optimal allocation model for irrigation water resources in each subirrigation district (Shihezi, Mosouwan, and Xiayedi irrigation districts), for four distinct user categories (agriculture, industry, household, and ecological water), consistently adhered to the comprehensive water resources index of the irrigation district. (2) After employing the 2030 projections for the Shihezi irrigation district as an example, the binary comparison methodology helped ascertain the objective weights (0.43, 0.35, and 0.22). The multi-objective fuzzy preference model was then used to shift through the solution set, highlighting the solution with the highest degree of superiority ($u_i$ = 0.979) as the optimal solution. (3) Under this scenario, the economic objective of the optimal solution for the Shihezi irrigation district for 2030 is 14,912.91 million yuan, with social and ecological objectives of 1186.77 and 1.22 million m³, respectively. The results of this scenario can serve as a reference for decisi