Hydrological Conditions Research Articles

A spatiotemporal correlation and attention-based model for pipeline deformation prediction in foundation pit engineering

In foundation pit engineering, the deformation prediction of adjacent pipelines is crucial for construction safety. Existing approaches depend on constitutive models, grey correlation prediction, or traditional feedforward neural networks. Due to the complex hydrological and geological conditions, as well as the nonstationary and nonlinear characteristics of monitoring data, this problem remains a challenge. By formulating the deformation of monitoring points as multivariate time series, a deep learning-based prediction model is proposed, which utilizes the convolutional neural network to extract the spatial dependencies among various monitoring points, and leverages the bi-directional long-short memory unit network to extract temporal features. Notably, an attention mechanism is introduced to adjust the trainable weights of spatial-temporal features extracted in the prediction. The evaluation of a real-world subway project demonstrates that the proposed model has advantages compared with current models, particularly in long-term prediction. It improves the Adjusted R2 index averagely by from 19.4 to 61.6%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} compared with existing models. The proposed model also exhibits a decrease in mean absolute error ranging from 51.5 to 70.3%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} compared to others. Experiments and analyses verify that the spatial-temporal dependencies in time series and the attention learning for spatial-temporal features can improve the prediction of such engineering problems.

Vegetation community recovery on restored bottomland hardwood forests in northeast Indiana, USA.

Vegetation communities in restored bottomland hardwood forests in northeast Indiana were studied 6-21 years after restoration to assess progress toward restoration objectives. The study focused on four sites that were restored to compensate for resource injuries after contaminant releases. The restored sites were compared with four reference-site conditions, including crops (prerestoration condition), old field communities representing a no-management alternative, locally sampled second-growth mature forests, and forest community types described by the US National Vegetation Classification (USNVC), which represent ideal or defining conditions of recognized vegetation communities. Fixed-area plots provided data on field-sampled environmental variables, vegetation, soil, and hydrological conditions for crops, old fields, restored areas, and mature forests. The USNVC database provided quantitative data for three historically and geographically relevant reference forest community types for comparison with the sampled communities. Results of nonmetric multidimensional scaling based on species cover revealed clear gradients relating to site age and canopy development. Along those gradients, restored areas demonstrated increasing similarity to mature forest reference communities in terms of floristic composition. Specifically, the floristic quality of restored areas was significantly greater than that of crops and old fields. Furthermore, soil health measurements of physical, chemical, and hydrological conditions indicated significant improvements in restored site soils compared with prerestoration conditions represented by cropland soils. Descriptions and data from the USNVC provided ecological context for restoration target conditions and facilitated the assessment of restoration recovery along a trajectory from starting conditions to those target conditions. Descriptions by USNVC also helped identify deviations from the intended restoration objectives (e.g., invasive species recruitment) and potential adaptive management actions to return sites to their intended trajectories. Integr Environ Assess Manag 2024;20:1917-1938. Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Unravelling Coupled Hydrological and Geochemical Controls on Long-Term Nitrogen Enrichment in a Large River Basin.

Many groundwater and surface water bodies around the world show a puzzling and often steady increase in nitrogen (N) concentrations, despite a significant decline of agricultural N inputs. This study uses a combination of long-term hydrogeochemical and hydraulic monitoring, molecular characterization of dissolved organic matter (DOM), column experiment, and reactive transport modeling to unravel the processes controlling N-reactive transport and mass budgets under the impacts of dynamic hydrologic conditions at a field site in the central Yangtze River Basin. Our analysis shows that the desorption of ammonium (NH4+) from sediments via cation exchange reactions dominates N mobilization and aqueous N concentrations, while the mineralization of organic N compounds plays only a minor role. The reactive transport modeling results illustrate the important role of cation exchange reactions that are induced by temporary NH4+ input and cation concentration changes under the impact of both seasonal and long-term hydrologic variations. Historically, cation exchangers have acted as efficient storage devices and mitigated the impacts of high levels of NH4+ input. The NH4+ residing on cation exchanger sites later acts as a long-term N source to waters with the delayed desorption of sediment-bound NH4+ induced by the change of hydrologic conditions. Our results highlight the complex linkages between highly variable hydrologic conditions and NH4+ partitioning in near-surface, river-derived sediments.

Exploring possible controlling factors of spatial distribution of microplastics in sediments of a river segment (Loire River, France).

Microplastics (MP) have been reported in many rivers across the globe but their depositional and archiving mechanisms in sediments are not fully understood yet. The aim of this study was to identify potential controlling factors of MP spatial distribution in surface sediment after a characterisation (sediment composition, hydrological conditions, sedimentary environment) of 14 sampling sites in an 8 km2 segment of the Loire river. Samples were collected from 3 sedimentary environments (sandbars, riverbanks and semi-active channels) with diverse flooding frequencies, grain size distributions and total organic carbon (TOC) contents. After treatment of sediment samples, MP concentrations and sizes were determined and polymer types identified by μFTIR (micro Fourier transform infrared) spectroscopy. After checking the influence of sample-scaled variability over river segment-scaled variability, MP concentrations were evaluated to 867-10,635 MP/kg of sediment dry weight (sed dw, size range 25-5000 μm) in the river segment. No environmental parameters were individually correlated with MP contamination in our study, possibly due to complex depositional environments in this river segment. A systemic approach however allowed insinuating that sediment composition reflecting hydro-morpho-sedimentary conditions can help to understand MP distribution in a river segment. A higher MP contamination observed in semi-active channel samples (median contamination value of 4797 MP/kg sed dw) could indicate that MP deposition is favoured in fine-grained (FGS) and TOC-rich sediment, reflecting less energetic hydrological conditions. Moreover, increasing flooding frequency seems to favor accumulation of MP only in the case of semi-active channels. On the contrary, less MP were detected in sandbars and riverbanks (median contamination of 1296 MP/kg sed dw), formed in higher hydrodynamical energy conditions. As a 10-fold variability of MP concentration exists in the study area, the importance of multiplying replicates even at the scale of a small river segment is underlined to access representativity of MP contamination.

Intensive short-term sampling with long-term consequences: characterizing pollutant transport with implications for developing monitoring.

Riverine sampling of pollutants is commonly used to understand pollutants' transport pathways, relationships with hydrology, and overall presence in a waterbody. However, temporal gaps between sample collection introduce errors to these efforts, and guidance prescribing sampling frequency remains sparse. The magnitude of error often depends on a contaminant's transport mechanisms and local hydrologic conditions, making the creation of comprehensive sampling guidance difficult. This study analyzed a unique dataset that measured 18 analytes, including pesticides, nutrients, and pathogens, in three Iowa rivers for 90 consecutive days (May 4-August 1, 2000). This dataset provided a novel opportunity to relate pollutants to local hydrology and quantify errors associated with recurring sampling. Pesticide concentrations followed the spring flush phenomenon, where values were greatest during high streamflow in May and June but often depleted by July. Fecal coliform and total phosphorus (TP) also coincided with high flow, but unlike pesticides, their concentrations never diminished. Nitrate exhibited more complex behavior; concentrations were diluted during high flows and then increased as streamflow receded. Autocorrelations were significant for nitrate and atrazine in larger rivers but negligible for fecal coliform and TP. Loads were calculated for four pollutants with minimal non-detects (atrazine, fecal coliform, nitrate, and TP). We simulated intermittent sampling by selecting evenly spaced subsets of measured values to estimate loads, which were compared to the loads calculated using every daily sample to quantify error. This method typically overestimated nitrate loads but underestimated other pollutants, and errors often decreased in larger watersheds. Nitrate generally had the lowest error, while fecal coliform had the highest. We used these results to approximate the sampling frequency needed to bind errors within a certain threshold.

Assessing the impacts of climate change on the vulnerability of coastal aquifers to the seawater intrusion

In most coastal areas, groundwater is affected by saltwater intrusion. Climate change effects, such as the sea-level rise and rainfall change are the climatic factors affecting the saltwater intrusion into groundwater. This study examines the vulnerability of the Abdan-Lamidan coastal aquifer to the intrusion of Persian Gulf saline waters under different hydrological conditions. First, the SIMCLIM model was used to calculate the regional sea-level rise of the Gulf under 24 future AOGCMs projections. The results showed that the increase in water level under the ensemble of AOGCM models and two RCP2.6 and RCP8.5 scenarios is 6.7 and 7.8 cm in 2050 compared to 2013. Then, the GALDIT vulnerability index was used to assess the vulnerability of the aquifer under the current condition and future scenarios. The results showed that parts of the aquifer that are currently at lower levels would be more vulnerable to sea-level rise in the future periods.

Drivers of Spatiotemporal Patterns of Riparian Forest NDVI Along a Hydroclimatic Gradient

ABSTRACTIn the context of rising global temperatures and their impact on weather patterns and water cycles, understanding the relationship between vegetation and hydroclimatic forcing is critical. Riparian forests are highly vulnerable to hydroclimatic variability, which can significantly affect water availability in the soil on which they primarily depend. Along large rivers, hydroclimatic forcings can vary, resulting in different vegetative responses depending on the local climatic context and site conditions. To explore this, we studied riparian forest greenness along a 512‐km river corridor with a 3° latitudinal gradient, analysing the relative contributions of climate (latitude, season, temperature, precipitation) and local hydrological conditions (groundwater). Here, we show that riparian forests along a latitudinal gradient respond differently to hydroclimatic controls, with vegetative dynamics that can be attenuated or accentuated by local site conditions. We combined Sentinel‐2 satellite Normalised Difference Vegetation Index (NDVI) data over seven years (2016–2022) with hydroclimatic data to examine riparian forest greenness responses to latitudinal, seasonal and interannual hydroclimatic variability. We found contrasting hydroclimatic controls across the latitudinal gradient, with the northernmost sites predominantly controlled by temperature, while those further south are limited by water availability. In addition, we identified temperature as the primary driver of NDVI throughout the growing season, either positively or negatively. Late season precipitation and high phreatic water availability positively influenced NDVI, emphasising the role of local conditions in governing riparian forest resilience. This study enhances understanding of climate controls on riparian tree greenness, which is critical for designing effective landscape‐scale riparian ecosystem management and restoration strategies.

The evolution of spatial and temporal distribution of rainfall erosivity in Henan Province, central China

With the advancement of urbanization, there has been a significant reduction in cultivated land, accompanied by soil erosion. Concurrently, the regularity of rainfall in recent years has been erratic, adversely impacting the grain economy and agricultural development in certain regions. Henan Province, spanning the basins of the Yangtze River, the Yellow River, the Huaihe River, and the Haihe River, possesses complex hydrological conditions and serves as a pivotal agricultural zone in China. Therefore, this paper utilizes daily rainfall data collected over 54 years (1969–2022) from 112 rain measuring stations in Henan Province to calculate the rainfall erosivity using the Zhang model and the erosivity model from the first national water survey. Meanwhile, spatial analysis was performed using the Kriging interpolation method in the ArcGIS Geostatistical Wizard, resulting in detailed spatial distribution maps of rainfall and rainfall erosivity. The study also employed Wavelet and Mann–Kendall tests to analyze the abrupt changes, trends and periodicity of rainfall and rainfall erosivity within the target region. The findings indicate that the average rainfall (1969–2022) in Henan province was 718.26 mm, while the average rainfall erosivity (R) was 3213.46 MJ mm/(hm2 h). R values are positively correlated with rainfall intensity and volume, displaying an annual upward trend. Spatially, R values increase gradually from northwest to southeast, closely aligning with topographical variations. Additionally, the analysis revealed a predominant periodic cycle of 54 years in the precipitation patterns. These results offer valuable insights for environmental and agricultural management in other regions of central China.

Strong coupling between the East Asian summer monsoon and regional hydrological conditions as evidenced by multiproxy stalagmite records for the last deglaciation

Millennial-to centennial-scale abrupt climate events during the last glacial‒interglacial transition have significant relevance to modern-day extreme climate changes, which are occurring more frequently in the context of global warming. However, the regional expression of humidity conditions during the last deglaciation and their possible forcing mechanism in northern China are controversial. Here, combined with published δ18O data, we report 35-year-resolved δ13C and 76-year-resolved Mg/Ca and Sr/Ca records from a stalagmite from 15.3 to 10.9 ka BP from Lianhua Cave, northern China. The LH4 stalagmite δ18O record clearly records a weak monsoon event during the Younger Dryas (YD) from 12.8 to 11.6 ka BP and a strong monsoon event during the Bølling-Allerød (BA) from 14.6 to 12.8 ka BP. In addition, the δ13C and trace element ratio records, which represent local hydroclimatic changes, indicate wetter conditions during the BA and drier conditions during the YD, which appear to match well with the δ18O variations on the millennial timescale. A comparison of 28 records from 17 sites along the modern margin of the China summer monsoon revealed that the BA was characterized by wet conditions; inversely, the YD was characterized by dry conditions throughout northern China, which is obviously different from the consensus of the wet YD and the dry BA in northern northeastern China. The covariance in northern China suggests that the hydrological variation may be modulated by the advance and retreat of the large-scale East Asian summer monsoon (EASM) circulation. Further comparison revealed an anticorrelated relationship between millennial-scale precipitation changes in northern China and the middle‒lower reaches of the Yangtze River Valley during the last deglaciation. This correlation is analogous to the dipole precipitation mode at present, which is likely associated with the strength and position of the westerly jet and/or the western Pacific subtropical high, both of which play important roles in the spatial distribution of precipitation over eastern China.

Assessment of Climate Change Impacts on Hydrology Using an Integrated Water Quality Index

Traditional Water Quality Indices (WQIs) often fail to capture the significant impact of flow velocity on water quality, especially under varying hydrological conditions. In this study, an Integrated Water Quality Index (IWQI) was developed by combining water quality parameters and flow rate, providing a more comprehensive assessment under various flow conditions. Compared to traditional indices, the IWQI showed slightly lower correlations in individual parameter performance, but it performed well in evaluating water quality changes associated with flow variations. Parameters such as Total Phosphorus (TP), Total Coliforms (TC), and Fecal Coliforms (FC), which are prevalent pollutants in the Cheongmi River, significantly influenced IWQI scores. River water quality was evaluated using input data simulated under a climate change scenario. When precipitation was abundant, the IWQI score remained relatively stable even with reduced flow rates. However, during periods of insufficient rainfall, water quality deteriorated sharply. While general water quality parameters exhibited approximately a 10% change as flow decreased, TC and FC showed rapid deterioration, with change rates ranging from 20% to 60%. These findings underscore the importance of managing TC and FC, particularly when insufficient rainfall is predicted, as they are major sources of pollution.

From Sangbo to urban landscape: morphological and hydrological transformations of Xuanwu Lake through integrating historical interpretation and geographic analysis

IntroductionXuanwu Lake in Nanjing has undergone a rich history, evolving from native Sangbo to a naval training ground, from an imperial garden to farmland, and finally to a vibrant urban landscape. The lake's legacy can be attributed to its unique geographical and hydrological conditions. Exploring historical transformations of the lake and surrounding landscape patterns provides insights for optimizing urban water space in contemporary China.MethodsTraditional analyses of lake changes based solely on historical records may lack precision due to deviations and artistic interpretations found in ancient maps. However, considering the reciprocal compatibility between local geomorphology, undulating terrains, and water bodies allows for accurate reduction of the lake's morphology by inferring and validating its geographical features. This research combines historical interpretation and geographical analysis to reconstruct the historical shape of Xuanwu Lake, uncover the intrinsic mechanisms driving spatial changes over time, and analyze the morphological changes and connectivity patterns of its hydrological system.ResultsThe morphology and hydrological dynamics of Xuanwu Lake are deeply intertwined with the policies prevailing in different eras. In antiquity, Xuanwu Lake, as a natural body of water, sustained the surrounding ecosystem and the livelihoods of local inhabitants. During the imperial period, it was integrated into the royal gardens, with its utilization and configuration modified by political directives, including the establishment of a naval training facility and its conversion into a royal recreational venue. Subsequently, in response to economic imperatives, Xuanwu Lake was transformed into agricultural land, which led to challenges such as flooding and drought. Ultimately, due to ecological security and recreational needs under urbanization, it was restored to lake form.DiscussionBy interpreting the bidirectional adaptation between the lake's ecosystem functions and city development activities, this research provides insights for water space management and ecological restoration in contemporary Xuanwu Lake. The findings provide guidance for the sustainable development of city-lake relationships to enhance the resilience of urban ecological spaces.

Application of SWAT to assess peatland forestry impacts on water quality

ABSTRACT Peatland drainage can affect the natural state of hydrological conditions and nutrient loading but is rarely included in catchment-scale models. To understand the gap, we aimed to use the soil and water assessment tool (SWAT) model to observe drained peatlands and their properties to predict nutrients and suspended solids (SS) in the peatland-dominated Simojoki catchment. We integrated drainage networks in SWAT to (i) identify the parameters for the drainage; (ii) determine annual loads and mean concentrations of SS, organic phosphorus (Org-P), total phosphorus (TP), organic nitrogen (Org-N), and total nitrogen (TN); (iii) understand spatial variation of nutrients and SS; and (iv) investigate the uncertainty ranges for the estimates. The calibrated SWAT model showed a 9.6% PBIAS between the simulated flow and the observations with low to medium loading variations for the water quality parameters. For Org-N and TN, the highest loading per year was at the downstream outlet, whereas for SS, Org-P, and TP, it was higher at the upstream outlet of the catchment. This approach of representing the drained peatland in SWAT indicated a maximum spatial distributed load in the peat soil in the clear-cut area and it can be beneficial in future hydrological modelling efforts in identifying the status of nutrients or SS.

A novel daily runoff forecasting model based on global features and enhanced local feature interpretation

The development of artificial intelligence has introduced new perspectives to the field of hydrological forecasting. However, there is still a lack of research on efficiently identifying the physical characteristics of runoff sequences and developing prediction models that consider global and local sequence features. This study proposes a parallel computing prediction model called IMCAEN (Integrated Multi-Feature Causal Dilated Convolutional Attention Encoder Network) to address these issues. Unlike existing models, this model can monitor fluctuations and anomalies in time series. Incorporating the CDC-AA (Causal Dilated Convolutional Network with Aggregation Attention) and encoder structure captures both local sequence variations and global abrupt anomalies, allowing for comprehensive attention to sequence features. When predicting runoff data from three different hydrological conditions, the IMCAEN model achieved NSEC (Nash-Sutcliffe Efficiency Coefficient) values of 0.98, 0.97, and 0.88, respectively, and outperformed benchmark models in other evaluation indicators as well. Given the opacity of the feature distribution process in AI models, SHAP (SHapleyAdditive exPlanations) analysis and spatial expression of feature distribution are used to assess the contribution of each feature variable to the long-term trend of runoff and to verify the distribution of features trained in each module. The proposed IMCAEN model efficiently captures local and global information in the runoff evolution process through parallel computing and shared features, enabling accurate runoff forecasting and providing critical references for timely warnings and predictions.

The ecological operation of ChiTan hydropower station based on hydrological alteration using PCA method

ABSTRACT Water infrastructure affects the quantity, quality, and environment of water. Developing reservoir construction, there was only considered the social-economic benefits and neglected the health of the downstream river. Due to the severe downstream river system, the operators and managers faced the challenge of the downstream ecosystem. Many scholars are concerned with the reservoir's optimum functioning, which considers social and economic advantages. Numerous significant opinions and research findings are being presented on ecological scheduling at the moment, both in China and overseas, which surely deepen the connotation of ecological scheduling and serve as the research basis and critical reference of this work. The influence of hydropower development on hydrological conditions, the categorization and calculation of environmental runoff, and the building and solution of ecological scheduling models are all discussed and researched in this work. The study examined how the ChiTan hydropower project influenced the Jinxi River's flow. The total hydrologic alteration calculated using RVA is 50.53%. The component analysis is also utilized to eliminate the statistical redundancy in the hydrologic indicators. The indicators’ monthly flow for July and August's mean minimum flow for 7 days are relevant indicators for the Jinxi River basin's hydrologic modification regime.

Spatial and seasonal fluctuations in fresh submarine groundwater discharge revealed by marine continuous resistivity profiling

Submarine Groundwater Discharge (SGD) is a major pathway for the discharge of fresh and saline groundwater and associated dissolved compounds into marine environments. However, assessing SGD processes in coastal aquifers is challenging due to inaccessibility, dynamic conditions, complex subsurface geology, and the need for long-term monitoring to capture temporal and spatial variations in SGD rates accurately. This study employs marine continuous resistivity profiling (MCRP) as a main method to assess the presence of freshwater or brackish SGD offshore and to examine its potential seasonal variations. The method has been applied in the coastal alluvial aquifer of Maresme (Spain) and validated with other methods to trace SGD, including salinity profiles, Ra isotopes, and piezometric levels. Several MCRP transects of 700 m long, perpendicular to the coastline, were performed in a coastal marine area to obtain electrical resistivity data of the seabed covering an area of 3 km2. The data was acquired in two field campaigns with contrasting hydrological conditions (dry and wet seasons). The MCRP results allow the identification of areas of fresh SGD in marine sediments, with a clear seasonal variability that indicates a higher discharge of fresh groundwater in the wet season.

Evaluating Hydrologic Model Performance for Characterizing Streamflow Drought in the Conterminous United States

Hydrologic models are the primary tools that are used to simulate streamflow drought and assess impacts. However, there is little consensus about how to evaluate the performance of these models, especially as hydrologic modeling moves toward larger spatial domains. This paper presents a comprehensive multi-objective approach to systematically evaluating the critical features in streamflow drought simulations performed by two widely used hydrological models. The evaluation approach captures how well a model classifies observed periods of drought and non-drought, quantifies error components during periods of drought, and assesses the models’ simulations of drought severity, duration, and intensity. We apply this approach at 4662 U.S. Geological Survey streamflow gages covering a wide range of hydrologic conditions across the conterminous U.S. from 1985 to 2016 to evaluate streamflow drought using two national-scale hydrologic models: the National Water Model (NWM) and the National Hydrologic Model (NHM); therefore, a benchmark against which to evaluate additional models is provided. Using this approach, we find that generally the NWM better simulates the timing of flows during drought, while the NHM better simulates the magnitude of flows during drought. Both models performed better in wetter eastern regions than in drier western regions. Finally, each model showed increased error when simulating the most severe drought events.

Estimation of bacterio‐, picophyto‐ and nanophytoplankton abundance in the Middle Caspian Sea by flow cytometry

Aim. For the first time, flow cytometry has been used to study the structure and functional characteristics of bacterio‐, pico‐ and nano‐ phytoplankton in the Middle Caspian during the bloom period in early September 2022.Water samples were taken at different horizons (from the surface to the bottom layer) at a series of stations along the western coast of the Caspian Sea on the border between its northern and central parts to quantitatively assess heterotrophic bacterioplankton, picophyto‐ and nanophy‐ toplankton. Sampling was undertaken in early September 2022 under summer hydrological conditions with water surface temperatures ranging from 24.7°C to 26.7°C. Sample analysis was performed using flow cytometry.Extremely high concentrations of picophytoplankton (up to 1.8×105 cells/mL), probably of Synechococcus picocyanobacteria, were detected off the northwestern coast of the Middle Caspian. Very high values of nanophytoplankton abundance (up to 1.6×105 cells/mL), dominated by small flagellates, were also found. A clear spatial uncoupling of pico‐ and nanophytoplankton was revealed. Maximum levels of nanophytoplankton were confined to the area of intensive phytoplankton blooming with high concentrations of chlorophyll a, while picophytoplankton reached peak abundance further south, outside this area. The influence of the thermocline on the vertical structure of microbial communities was detected. The concentrations of picophytoplankton and the proportion of physiologically active HNA‐bacteria decreased sharply under the thermocline.The results obtained indicate the leading role of the smallest phototrophs in the Caspian pelagial and emphasise the need for further comprehensive studies of Caspian microbial communities using modern methods.

Numerical Simulations of Impact River Morphology Evolution Mechanism Under the Influence of Floodplain Vegetation

Shallow floodplains play a crucial role in river basins by providing essential ecological, hydrological, and geomorphic functions. During floods, intricate hydrodynamic conditions arise as flow exits and re-enters the river channel, interacting with the shallow vegetation. The influence and mechanism of shoal vegetation on channel hydrodynamics, bed topography, and sediment transport remain poorly understood. This study employs numerical simulations to address this gap, focusing on the Xiaolangdi–Taochengpu river section downstream of the Yellow River. Sinusoidal-derived curves are applied to represent the meandering river channel to simulate the river’s evolutionary process at a true scale. The study simulated the conditions of bare and vegetated shallow areas using rigid water-supported vegetation with the same diameter but varying spacing. The riverbed substrate was composed of non-cohesive sand and gravel. The analysis examined alterations in in-channel sediments, bed morphology, and bed heterogeneity in relation to variations in vegetation density. Findings indicated a positive correlation between vegetation density and bed heterogeneity, implying that the ecological complexity of river habitats can be enhanced under natural hydrological conditions in shallow plain vegetation and riparian diffuse flow. Therefore, for biological river restoration, vegetation planting in shallow plain regions can provide greater effectiveness.

Algebraic expressions for convective solute transport in a homogeneous soil below a surface barrier

AbstractEngineered surface barriers are expected to be used to cover sites containing buried waste radionuclides after site closure. Understanding the transport of contaminants in the soil below a surface barrier is of importance in order to protect the underlying groundwater. The travel velocity of these contaminants is dependent on numerous factors, such as the thickness, properties, the pre‐barrier hydrologic condition of the vadose zone, and the initial depths and properties of the contaminants. Although solute transport can be modeled with numerical modeling using site‐specific data, by nature a numerical method does not reveal the relationship between inputs and outputs. This work develops algebraic expressions of the velocities of convective solute transport in the vadose zone below a surface barrier, time lag, solute safe depth, zero‐protection depth of a surface barrier, and solute travel time to the groundwater. This development shows that solute convection in the soil with a surface barrier consists of up to three stages: constant high velocity, decreasing velocity, and constant low velocity. Solute transport based on the algebraic expressions was verified against numerical simulations. The algebraic expressions may be used to assess the expected impacts of a surface barrier to the convective transport of contaminants in the vadose zone.

Investigating the Spatial Pattern of White Oak (Quercus alba L.) Mortality Using Ripley’s K Function across the Ten States of the Eastern US

White oak mortality is a significant concern in forest ecosystems due to its impact on biodiversity and ecosystem functions. Understanding the factors influencing white oak mortality is crucial for effective forest management and conservation efforts. In this study, we aimed to investigate the spatial pattern of WOM rates across the eastern US and explore the underlying processes behind the observed spatial patterns. Multicycle forest inventory and analysis data were compiled to capture all white oak plots. WOM data were selected across plot systems that utilized declining basal areas between two periods. Ripley’s K function was used to study the spatial pattern of WOM rates. Results showed clustered patterns of WOM rates at local and broad scales that may indicate stand-level competition and regional variables affecting white oaks’ dynamics across southern and northern regions. Results also indicated random patterns at broad scales, suggesting variations in topographic and hydrological conditions across the south and northern regions. However, the central region indicated both clustered and random patterns at the local scale that might be associated with inter-species competition and the possibility of environmental heterogeneity, respectively. Furthermore, uniform patterns of WOM rate at a broad scale across all regions might suggest regions with spatially homogeneous environmental factors acting on the dynamics of white oaks. This research might be helpful in identifying impacted areas of white oaks at varying scales. Future research is needed to comprehensively assess biotic and abiotic factors at various spatial scales aimed at mitigating WOM.