Hydrological Processes最新文献

Drought is a natural event that slowly deteriorates water reserves. This study aims to develop a machine learning–based computational framework for monitoring drought status in water-scarce regions. The proposed framework integrates the precipitation index (PI) with support vector machine models to forecast drought occurrences based on an autoregressive modelling scheme. Due to the suitability of the PI for drought analysis in arid climates, the developed hybrid model is appropriate in regions with limited rainfall. This study used a historical precipitation dataset from 1958 to 2020 at the Kuwait International Airport, Kuwait City. The study area is characterised by scarce rainfall and is vulnerable to severe water shortages owing to limited water resources. Initially, historical PI time-series datasets were examined for stationarity to validate the utility of the autoregressive model. The autocorrelation function test was significantly associated with the PI time series at the 12- and 24-month drought-monitoring scales. Predictive drought forecasting models were constructed to predict drought occurrences up to 3 months in advance. Statistical evaluation metrics were used to assess model performance for the 12- and 24-month drought-monitoring scales. The results showed a strong association between the observed and predicted drought events, with coefficients of determination (R²) ranging between 0.865 and 0.925 for the 12- and 24-month drought-monitoring scales. The proposed computational framework aims to provide water managers in arid and water-scarce regions with efficient and reliable drought-monitoring tools to assist in preparing appropriate water management plans. This study provides guidance for improving water resource resilience under water shortage scenarios in the study area and other climatic regions by applying suitable drought indices in conjunction with robust data-driven models. The results provide a baseline for water resource policymakers worldwide to establish sustainable water conservation strategies and provide crucial insights for drought disaster preparation.

Seawater intrusion is an ongoing issue exacerbated internationally by the growing need for freshwater along coastlines, which is affected by shifting sea levels and changing climates, challenging sustainable management. This research primarily focuses on determining intrusion behaviour within a sloping boundary in a heterogeneous aquifer and assessing the efficiency of subsurface barriers. The glass-box method was incorporated with an inclined permeable barrier. High-resolution images were taken at defined intervals and enhanced for clear intrusion visuals. Comparing the results of the heterogeneous base case and barrier installed condition, a huge quantity of about 38.93% of groundwater was conserved from being contaminated. Homogeneous media shows a faster rate of intrusion with a progressive rate of contamination, while heterogeneous media, without barrier, shows slower rates of intrusion due to reduced permeability. Longitudinal dispersivity as 0.5 cm and transverse dispersivity as 0.05 cm were considered. The Péclet number was calculated as 3, which comes under the range defined in the literature. Sensitivity analysis for the height of the barrier shows that a higher height is required for remediation by heterogeneous media of higher permeability. Analysis of the toe length using sensitivity analysis in the heterogeneous case shows a range of 24.82 to 75 cm before barrier installation and a range of 13.05–65.24 cm after installation of a barrier (15, 20, and 25 cm height). This implies that a higher toe length had formed with a smaller barrier height, and lower efforts were required for backwashing.

Analysis of PRISM and SNOTEL station data paired with USGS streamflow gage data in the western United States shows that, in snow-dominated mountainous watersheds, streamflow regimes differ between watersheds with karst geology and their non-karst neighbours. These carbonate aquifers exhibit a spectrum of flow paths encompassing karst conduits, including large fractures or voids that transmit water readily to springs and other surface waters, and matrix flow paths through soils, highly fractured bedrock, or porous media bedrock grains. A well-connected karst aquifer will discharge a large portion of its accumulated precipitation to surface water via springs and other groundwater flow paths on an annual scale, exhibiting a lagged response to precipitation presenting as a “memory effect” in hydrograph time series. These patterns were observed in the hydrologic records of gaged watersheds with exposed or near-surface carbonate layers accounting for > 30% of their drainage area. In western snow-dominated watersheds, where paired streamflow and SNOTEL data are available, analysis of the precipitation and flow time series shows low-flow volume is strongly related to karst aquifer conditions and winter precipitation when compared to low-flow volumes present in non-karst watersheds, which have a complex relationship to multiple driving metrics. Analysis of normalised streamflow and cumulative precipitation in karst watersheds show that low-flow conditions are highly dependent on the preceding winter precipitation and streamflow in both wet and dry periods. In non-karst watersheds, increased precipitation primarily impacts high-flow, spring runoff volumes with no clear relationship to low-flow periods. When comparing cumulative streamflow and precipitation volumes within each water year and over longer timescales, karst watersheds show the potential filling and draining of large amounts of karst storage, whereas non-karst watersheds demonstrate a more stable storage regime. Communities in many western US watersheds are dependent on snow-dominated karst watersheds for their water supply. This analysis, using widely available hydrologic data, can provide insight into the recharge and storage processes within these watersheds, improve our ability to assess current flow regimes, anticipate the impacts of climate change on water availability, and help manage water supplies.

Lateral terrestrial water flow in the Weather Research and Forecasting (WRF) Model and its hydrologically enhanced version, WRF-Hydro, is calculated on a routing grid based on infiltration excess in Land Surface Model (LSM) grid disaggregates to the routing grids. However, this design neglects the lateral terrestrial water flow within LSM grids and does not resolve water lateral transport in LSM. In this study, we develop a lateral terrestrial water flow scheme in the Noah with multiparameterization (Noah-MP) of WRF-Hydro grids to address this knowledge gap and evaluate its influence on land surface hydrological processes. Our results indicate that lateral terrestrial water flow leads to 62.3% of grid surface water outflow, resulting in a decrease in accumulated water depth by 123.88 mm. In urban areas, the accumulated water depth further reduces by 21.11 mm when considering the pipe discharge scheme. Compared to the default WRF-Hydro simulation, the lateral terrestrial water flow combined with pipe discharge can effectively advance the calibrated WRF-Hydro modelling capability and reproduce the water depth reasonably compared to the observation in urban areas. Further, our analysis indicates that the decreasing lateral terrestrial water flow in LSM primarily reduces overland flow and increases streamflow in routing grids, mainly through redistributing water from the steep slopes towards the lower elevations and ultimately converting it to streamflow in the channel network.

Aquatic vegetation is an important component of natural river ecosystem, usually growing in riverine, marsh, and coastal areas, interacting with water flow to form complex flow structure, which has an important impact on bank slope stability and flood discharge capacity of river channels. Four sets of indoor flume vegetation-flow experiments were conducted using a typical beach trough structure in the lower section of the Yangtze River. The compound channel was divided into the main channel, side slope and side beach zones, and simulated vegetation such as reeds, sedges and dwarf grass were used. The emphasis was on the hydrodynamic properties under semi-covered emergent rigid vegetation and semi-covered non-submerged rigid vegetation. In this study, the Shiono and Knight equation (SKM model) was used to elucidate the distribution characteristics of ‘the depth-averaged velocity U_d’ and ‘equivalent diameter D’ of vegetation in water gradient, and the Taylor method was used to demonstrate that the proposed ‘equivalent diameter D’ of vegetation has a certain level of accuracy within a reasonable threshold range. In addition, a new secondary flow model was proposed using a genetic algorithm that considers many hydraulic and vegetation parameters. Further, a new secondary flow model was proposed using a genetic algorithm that considers many hydraulic and vegetation parameters. Finally, ‘the depth-averaged velocity U_d’ of the compound channel was accurately predicted by combining the experimental data with the new SKM model. In this study, we investigated the water-blocking ability of gradient vegetation in river water. A method in which the secondary flow law and formula are difficult to determine was solved, which could provide technical support for the design of complex vegetated rivers and the evaluation of the flood discharge capacity of rivers.

Anthropogenic climate change leads to increased precipitation intensity and exacerbated droughts in California, challenging the reliability and drought resiliency of water supply. Storing floodwater underground via managed aquifer recharge can mitigate these effects through direct infiltration or streambed infiltration. Seasonally dry streams (arroyos) already play an important part in managing groundwater recharge to the Livermore basin (CA). Understanding how, when and where stormwater and arroyo water infiltrate is critical to effectively utilise this strategy. To track water from recent storms (water year 2022–2023, WY23) into the Livermore Valley Groundwater Basin, we analysed stable water isotopes (δ¹⁸O and δ²H) in combination with naturally occurring radioactive isotopic tracers, sulphur-35 (³⁵S, t½ = 87 days) and tritium (³H, t½ = 12.3 years). By comparing measurements of δ¹⁸O, ³⁵S and ³H in arroyos to precipitation and groundwater, we classified the relative age and identified source of recharge to 16 wells near two arroyos. Two wells contained water with recent recharge (from WY23) from local precipitation. One well had recent recharge from variable (precipitation and imported water) sources. One well contained imported water recharge. Three wells contained water from mixed recent and older (pre-WY23) waters, from local precipitation sources. Two wells contained recent recharge from local mine settling ponds. Seven wells had older recharge from local precipitation sources. This combination of isotopes allows us to delineate where local and imported water recharges in this highly managed basin and identify locations where managed aquifer recharge is contributing to rapid groundwater infiltration. Our combined interpretation of isotopic water ages and sources in the context of land use shows that local infiltration of precipitation in open spaces is an important recharge mechanism, in addition to the managed arroyo recharge. A broader familiarity with ³⁵S will enable more extensive research on the infiltration of urban floodwaters.