River Stage Research Articles

Proglacial river stage derived from georectified time-lapse camera images, Inglefield Land, Northwest Greenland

The Greenland Ice Sheet is a leading source of global sea level rise, due to surface meltwater runoff and glacier calving. However, given a scarcity of proglacial river gauge measurements, ice sheet runoff remains poorly quantified. This lack of in situ observations is particularly acute in Northwest Greenland, a remote area releasing significant runoff and where traditional river gauging is exceptionally challenging. Here, we demonstrate that georectified time-lapse camera images accurately retrieve stage fluctuations of the proglacial Minturn River, Inglefield Land, over a 3 year study period. Camera images discern the river’s wetted shoreline position, and a terrestrial LiDAR scanner (TLS) scan of riverbank microtopography enables georectification of these positions to vertical estimates of river stage. This non-contact approach captures seasonal, diurnal, and episodic runoff draining a large (∼2,800 km2) lobe of grounded ice at Inglefield Land with good accuracy relative to traditional in situ bubble-gauge measurements (r2 = 0.81, Root Mean Square Error (RMSE) ±0.185 m for image collection at 3-h frequency; r2 = 0.92, RMSE ±0.109 m for resampled average daily frequency). Furthermore, camera images effectively supplement other instrument data gaps during icy and/or low flow conditions, which challenge bubble-gauges and other contact-based instruments. This benefit alone extends the effective seasonal hydrological monitoring period by ∼2–4 weeks each year for the Minturn River. We conclude that low-cost, non-contact time-lapse camera methods offer good promise for monitoring proglacial meltwater runoff from the Greenland Ice Sheet and other harsh polar environments.

Assessment of riverbank filtration performance for climatic change and a growing population

Riverbank filtration (RBF) consists of green drinking water production in many regions and is used as a pre-treatment phase. This study investigates the performance of the RBF in the Nile delta, Egypt, for climate change and population growth scenarios of 2030, 2040, and 2050. This study presents a new method for predicting the sharing of riverbanks considering three cases: i) the river stage controlling the water levels in the river, ii) increasing RBF pumping, and iii) changing the groundwater levels. This last scenario is achieved by changing the general head in the MODFLOW model. The results showed that RBF sharing (RBFS) is a proportion of the river leakage inflow, in which the decrease of the river stage due to the influence of climate change reduced the river leakage inflow and RBFS. In addition, increasing RBF pumping, decreasing RBF pumping, and lowering the groundwater levels due to the increase in the future drinking water pumping for the population growth increased the river leakage inflow and RBFS. Finally, combining the three cases decreased RBFS in the coming years of 2030, 2040, and 2050, respectively, due to more groundwater sharing than the river inflow. The results show that the water budget is a good tool to investigate RBFS compared with MT3D results. This technique can reduce the cost of water quality collection and analysis; moreover, it will help with the estimation of RBF and save time compared with solute transport modeling.

A copula model of extracting DEM-based cross-sections for estimating ecological flow regimes in data-limited deltaic-branched river systems

For operational flood control and estimating ecological flow regimes in deltaic branched-river systems with limited surveyed cross-sections, accurate river stage and discharge estimation using public domain Digital Elevation Model (DEM)-extracted cross-sections are challenging. To estimate the spatiotemporal variability of streamflow and river stage in a deltaic river system using a hydrodynamic model, this study demonstrates a novel copula-based framework to obtain reliable river cross-sections from SRTM (Shuttle Radar Topographic Mission) and ASTER (Advanced Spaceborne Thermal Emission and Reflection) DEMs. Firstly, the accuracy of the CSRTM and CASTER models was assessed against the surveyed river cross-sections. Thereafter, the sensitivity of the copula-based river cross-sections was evaluated by simulating river stage and discharge using MIKE11-HD in a complex deltaic branched-river system (7000 km2) of Eastern India having a network of 19 distributaries. For this, three MIKE11-HD models were developed based on surveyed cross-sections and synthetic cross-sections (CSRTM and CASTER models). The results indicated that the developed Copula-SRTM (CSRTM) and Copula-ASTER (CASTER) models significantly reduce biases (NSE>0.8; IOA>0.9) in the DEM-derived cross-sections and hence, are capable of satisfactorily reproducing observed streamflow regimes and water levels using MIKE11-HD. The performance evaluation metrics and uncertainty analysis indicated that the MIKE11-HD model based on the surveyed cross-sections simulates with higher accuracies (streamflow regimes: NSE>0.81; water levels: NSE>0.70). The MIKE11-HD model based on the CSRTM and CASTER cross-sections, reasonably simulates streamflow regimes (CSRTM: NSE>0.74; CASTER: NSE>0.61) and water levels (CSRTM: NSE>0.54; CASTER: NSE>0.51). Conclusively, the proposed framework is a useful tool for the hydrologic community to derive synthetic river cross-sections from public domain DEMs, and simulate streamflow regimes and water levels under data-scarce conditions. This modelling framework can be easily replicated in other river systems of the world under varying topographic and hydro-climatic conditions.

A New Graph-Based Deep Learning Model to Predict Flooding with Validation on a Case Study on the Humber River

Floods are one of the most lethal natural disasters. It is crucial to forecast the timing and evolution of these events and create an advanced warning system to allow for the proper implementation of preventive measures. This work introduced a new graph-based forecasting model, namely, graph neural network sample and aggregate (GNN-SAGE), to estimate river flooding. It then validated the proposed model in the Humber River watershed in Ontario, Canada. Using past precipitation and stage data from reference and neighboring stations, the proposed GNN-SAGE model could estimate the river stage for flooding events up to 24 h ahead, improving its forecasting performance by an average of 18% compared with the persistence model and 9% compared with the graph-based model residual gated graph convolutional network (GNN-ResGated), which were used as baselines. Furthermore, GNN-SAGE generated smaller errors than those reported in the current literature. The Shapley additive explanations (SHAP) revealed that prior data from the reference station was the most significant factor for all prediction intervals, with seasonality and precipitation being more influential for longer-range forecasts. The findings positioned the proposed GNN-SAGE model as a cutting-edge solution for flood forecasting and a valuable resource for devising early flood-warning systems.

Contrasting two urban wetland parks created for improving habitat and downstream water quality

This paper describes the ecology and management of two flow-through created wetlands that, in turn, defined 30 years of research by Bill Mitsch, 20 years in Columbus, Ohio (1992–2012) and 10 years in Naples, Florida (2012−2022). The Olentangy River Wetland Research Park was built in several stages from 1993 through 2010. The first stage was the creation of dual 1-ha kidney-shaped wetlands primarily fed by pumped Olentangy River water. A pattern of inflow that depended on river stage was maintained for 17 years. The two experimental wetlands were established by planting one of the wetlands with a variety of wetland macrophytes and leaving the second wetland unplanted to ultimately determine whether human introduction of wetland plants matter in the long run. In addition to maintaining data collection for hydrology, water quality, and other functions, these wetlands and several others constructed on the 20-ha floodplain site were heavily used as was the mesocosm compound, mostly for short-term (2 to 3 year) experiments by graduate students.Another 20-ha created wetland complex, called Freedom Park Wetlands, was constructed in 2007–2008 in Naples, Florida, at an abandoned citrus grove, to seasonally treat urban stormwater runoff. During that wet season, the design calls for an average water detention time of 18 days. The wetland system included a 1.9-ha deepwater pond for temporary storage of the urban stormwater pulses from what is mostly an urban watershed, followed by 2.7 ha of shallower vegetated wetland ponds designed to sequentially improve water quality. Within each wetland, there are three deep-water cells and two shallow-water cells. The water eventually exits the treatment wetlands via a rectangular and travels diffusely through a restored bottomland forest to the Gordon River and ultimately toward Naples Bay and the Gulf of Mexico. During our tenure at Florida Gulf Coast University's (FGCU) Everglades Wetland Research Park, Freedom Park was a venue with active mesocosm experiments in a constructed mesocosm compound. Several of these mesocosm experiments were the subjects of master's theses from FGCU and doctoral dissertations from our partner, University of South Florida. Our students also contributed to the local environmental communities by giving tours of the Freedom Park wetlands and our mesocosm research.

Use of Censored Multiple Regression to Interpret Temporal Environmental Data and Assess Remedy Progress.

Many methods to evaluate temporal trends in monitoring data focus on univariate techniques that account for changes in the response variable (e.g., concentration) by means of a single variable, namely time. When predictable site-specific factors, such as groundwater-surface water interactions, are associated with or may cause concentration changes, univariate methods may be insufficient for characterizing, estimating, and forecasting temporal trends. Multiple regression methods can incorporate additional explanatory variables, thereby minimizing the amount of unexplained variability that is relegated to the "error" term. However, the presence of sample results that are below laboratory reporting limits (i.e., censored) prohibits the direct application of the standard least-squares method for multiple regression. Maximum Likelihood Estimation (MLE) for multiple regression analysis can enhance temporal trend analysis in the presence of censored response data and improve characterizing, estimating and forecasting of temporal trends. Multiple regression using MLE (or censored multiple regression) was demonstrated at the U.S. Department of Energy Hanford Site where analyte concentrations in groundwater samples are negatively correlated with the stage of the nearby Columbia River. Incorporating a time-lagged stage variable in the regression analysis of these data provides more reliable estimates of future concentrations, reducing the uncertainty in evaluating the progress of remediation toward remedial action objectives. Censored multiple regression can identify significant changes over time; project when maxima and minima of interest are likely to occur; estimate average values and their confidence limits over time periods relevant to regulatory compliance; and thereby improve the management of remedial action monitoring programs. This article is protected by copyright. All rights reserved.

Characterizing hydraulic heterogeneity of Bayin River Basin using river stage tomography

The drastic spatial and temporal variations of water resources are one of the causes of the fragile ecological environment in the Bayin River Basin. While the temporal variation is less predictable, a detailed spatial distribution of hydrological parameters of the basin is invaluable for developing guidance for allocating and utilizing water resources in the Bayin River Basin. This study estimates the two-dimensional spatial distribution of hydraulic diffusivity (D) of the Bayin River Basin through the relationship between river flow and groundwater using limited available river stages data along the river. It first conducted a wavelet analysis to illustrate strong correlations between river flow and groundwater during the flood season in the basin. Subsequently, it used a simple linear model to estimate temporal and spatial variations of the river stage along the river due to flood. Then, the study applied a recently developed river stage tomography (RST) to the alluvial fan to estimate the spatial distribution of the D values. The RST treats the flood river stage as a signal pressure transmitter, and the groundwater fluctuation recorded in the observation wells as the images of the aquifer heterogeneity between the river and observation wells. The RST then synthesizes these images to characterize the heterogeneous distribution of D in the alluvial fan in the Bayin River Basin. The results show that the northeast area of the alluvial fan has a relatively high D, while the D is relatively low in the tail and the southwest area of the fan. These findings are consistent with the general concept of alluvial fan evolution.Moreover, the predicted groundwater levels during the flood event in 2019 based on the RST-estimated D is more accurate than the preliminary stratigraphic survey, confirming that capturing groundwater responses at various parts of a basin caused by some disturbances could reveal hydraulic connectivity, which the prior geologic information cannot. This result is essential to advancing aquifer characterization technologies and affirming the contribution of RST and the view toward the future subsurface sciences advocated by Yeh et al. (2008).

Benthic macroinvertebrate assemblages in large river secondary channels: Contemporaneous and legacy effects of flow connectivity

AbstractIn large rivers, secondary channels occur where the main channel is divided by an instream island, forming one or multiple smaller channels outside the main channel. Secondary channels are highly variable in morphometry, flow characteristics, and degree of connectivity to the main channel. Engineered closing structures at the upstream end of most secondary channels restrict inflow from the main channel, resulting in gradients of flow connectivity among secondary channels that vary with river stage. We investigated the relationship of flow connectivity to benthic macroinvertebrate assemblage richness and structure among a series of secondary channels of the Lower Mississippi River. Samples were collected over 2 years at times of high and low river stages. We discovered (1) macroinvertebrate assemblage structure and taxonomic richness varied along the flow connectivity gradient, and (2) there was a legacy effect of prior connection on assemblage structure that lasted up to a year. We contend that for management and restoration planning aimed at conservation of large river biological diversity, an important consideration are the life history requirements of animals utilizing secondary channel habitats.

Error-correction-based data-driven models for multiple-hour-ahead river stage predictions: A case study of the upstream region of the Cho-Shui River, Taiwan

Study RegionThe Cho-Shui River Basin is located in central Taiwan and has a catchment area of approximately 3157 km2 and an annual average rainfall of 2200 mm. It is the longest river in Taiwan, and its mainstream has an average slope of 0.018. However, the prediction of flash floods upstream of the Cho-Shui River has yet to be investigated. Because of the river’s steep slope, typhoons or storms can result in significant flood disasters. Therefore, accurate and reliable river stage prediction is required for flood disaster mitigation. Study FocusA predictor-corrector multiple-hour-ahead methodology was developed and used for constructing seven data-driven models for river stage predictions. The proposed methodology employs both river-stage and residual-error prediction models. The optimal residual-error prediction model was determined using seven data-driven models. An extensive comparison of the seven data-driven models was conducted regarding prediction performance with 1–24-h lead times. New Hydrological Insights for the RegionThe proposed error-correction-based data-driven models exhibited high prediction accuracy, making them suitable for improvements of river stage predictions with the decrease in lead-time-averaged root mean square error (RMSE), up to − 73.7 %. The error-correction-based categorical gradient boosting regression (CGBR) and encoder-decoder long short-term memory (LSTM) models outperformed the other models, yielding the average peak water-level error (PWE) of 0.3 m for the 24-hour-ahead prediction. Thus, these two models could be helpful for early-warning river flood forecasting during typhoons or storms.

Movement ecology of diploid and triploid grass carp in a large reservoir and upstream tributaries.

Grass carp Ctenopharyngodon idella, is an herbivorous fish originally brought to North America from Asia in 1963 to control nuisance aquatic vegetation. Since their arrival, detrimental alterations to aquatic ecosystems have sometimes occurred in waterways where they were initially stocked and into which they have escaped. The movements of grass carp from lentic systems into tributaries required for spawning is poorly understood, and understanding environmental conditions associated with upstream migrations may aid in management of the species. We stocked 43 fertile diploid and 43 sterile triploid grass carp implanted with acoustic transmitters into Truman Reservoir, Missouri, USA between January 2017 and October 2018 to characterize movements during spring and summer when spawning conditions occur. Twenty fish (11 diploid/9 triploid) exhibited upstream migration behavior in the Osage River, a major tributary, in 2018 and 2019. Migration primarily occurred in April and May, during high discharge events associated with increasing river stage when water temperatures were between 15 and 28°C. Observed migrations ranged from 3.0-108 river km in length, and six individuals were observed making multiple upstream migrations in one season. Eleven fish initiated upstream migrations while in the lentic main body of the reservoir. These findings provide some evidence for upstream migrations by diploid and triploid grass carp as well both lake and river residents. Evidence of similar upstream migration behavior by both diploid and triploid grass carp suggests that triploids may be suitable surrogates for diploids for study of movement ecology. Removal efforts in tributaries targeting periods of increasing river stage during spring may provide the best opportunity of encountering large concentrations of grass carp.

A new method for effective parameterization of catchment-scale aquifer through event-scale recession analysis

Accurate estimation of aquifer properties is of critical importance in representing the interactions between hydraulically connected surface-subsurface systems. The variability in recession characteristics (i.e., decline rates and slope nonlinearity) shows that each recession event (RE) occurs under different hydraulic diffusivity conditions between the stream-hillslope. Therefore, the streamflow recession characteristics should be considered in the effective parameterization of the catchment-scale aquifer. This study presents a new method for estimating catchment-scale aquifer properties while accounting for distinct recession characteristics through event-scale recession analysis. In this work, we used the recently developed BE3S (Hong et al., 2020) for (1) explicit incorporation of river stage observations as forcing data to account for the distinct recession characteristics and (2) numerical prediction of outflow from a Boussinesq aquifer to comparatively evaluate analytically derived effective groundwater parameters. We also addressed the relevance of the net subsurface discharge (NSD) observations in event-scale recession analysis for the catchment-scale aquifer parameterization. Specifically, we found that the catchment-scale NSD data plays a role in determining the initial saturated aquifer thickness (Dini) and the size of contributing aquifer (Ac), which varies in individual REs. The applicability of the proposed parameterization scheme was successfully validated for individual REs with distinct recession slopes, demonstrating that hydraulic diffusivity parameters can be estimated by explicitly incorporating recession characteristics. As a catchment-scale application of hydraulic groundwater theory, we expect that the proposed scheme for effective groundwater parameterization will contribute to the accurate representation of the catchment-scale stream-hillslope hydrologic continuum.

Vertical Hydrologic Exchange Flows Control Methane Emissions from Riverbed Sediments.

CH4 emissions from inland waters are highly uncertain in the current global CH4 budget, especially for streams, rivers, and other lotic systems. Previous studies have attributed the strong spatiotemporal heterogeneity of riverine CH4 to environmental factors such as sediment type, water level, temperature, or particulate organic carbon abundance through correlation analysis. However, a mechanistic understanding of the basis for such heterogeneity is lacking. Here, we combine sediment CH4 data from the Hanford reach of the Columbia River with a biogeochemical-transport model to show that vertical hydrologic exchange flows (VHEFs), driven by the difference between river stage and groundwater level, determine CH4 flux at the sediment-water interface. CH4 fluxes show a nonlinear relationship with the magnitude of VHEFs, where high VHEFs introduce O2 into riverbed sediments, which inhibit CH4 production and induce CH4 oxidation, and low VHEFs cause transient reduction in CH4 flux (relative to production) due to reduced advective CH4 transport. In addition, VHEFs lead to the hysteresis of temperature rise and CH4 emissions because high river discharge caused by snowmelt in spring leads to strong downwelling flow that offsets increasing CH4 production with temperature rise. Our findings reveal how the interplay between in-stream hydrologic flux besides fluvial-wetland connectivity and microbial metabolic pathways that compete with methanogenic pathways can produce complex patterns in CH4 production and emission in riverbed alluvial sediments.

Acesulfame allows the tracing of multiple sources of wastewater and riverbank filtration

Aquifers providing drinking water are increasingly threatened by emerging contaminants due to wastewater inputs from multiple sources. These inputs have to be identified, differentiated, and characterized to allow an accurate risk assessment and thus ensure the safety of drinking water through appropriate management. We hypothesize, that in climates with seasonal temperature variations, the sweetener acesulfame potassium (ACE) provides new pathways to study wastewater inputs to aquifers. Specifically, this study investigates the temperature-driven seasonal oscillation of ACE to assess multiple sources of wastewater inputs at a riverbank filtration site. ACE concentrations in the river water varied from 0.2 to 1 μg L−1 in the cold season (T < 10 °C) to 0–0.1 μg L−1 in the warm season (T > 10 °C), due to temperature-dependent biodegradation during wastewater treatment. This oscillating signal could be traced throughout the aquifer over distances up to 3250 m from two different infiltration sources. A transient numerical model of groundwater flow and ACE transport was calibrated over hydraulic heads and ACE concentrations, allowing the accurate calculation of mixing ratios, travel times, and flow-path directions for each of the two infiltration sources. The calculated travel time from the distant infiltration source was of 67 days, while that from the near source was of 20 days. The difference in travel times leads to different potential degradation of contaminants flowing into the aquifer from the river, thus demonstrating the importance of individually assessing the locations of riverbank infiltration. The calibrated ACE transport model allowed calculating transient mixing ratios, which confirmed the impact of river stage and groundwater levels on the mixing ratio of the original groundwater and the bank filtrate. Therefore, continuous monitoring of ACE concentrations can help to optimize the management of the water works with the aim to avoid collection of water with very short travel times, which has important regulative aspects. Our findings demonstrate the suitability of ACE as a transient tracer for identifying multiple sources of wastewater, including riverbank filtration sites affected by wastewater treatment plant effluents. ACE seasonal oscillation tracking thus provides a new tool to be used in climates with pronounced seasonal temperature variations to assess the origins of contamination in aquifers, with time and cost advantages over multi-tracer approaches.

Intercomparison of global reanalysis precipitation for flood risk modelling

Abstract. Reanalysis datasets are increasingly used to drive flood models, especially for continental and global analysis and in areas of data scarcity. However, the consequence of this for risk estimation has not been fully explored. We investigate the implications of four reanalysis products (ERA-5, CFSR, MERRA-2 and JRA-55) on simulations of historic flood events in five basins in England. These results are compared to a benchmark national gauge-based product (CEH-GEAR1hr). The benchmark demonstrated better accuracy than reanalysis products when compared with observations of water depth and flood extent. All reanalysis products predicted fewer buildings would be inundated by the events than the national dataset. JRA-55 was the worst by a significant margin, underestimating by 40 % compared with 14 %–18 % for the other reanalysis products. CFSR estimated building inundation the most accurately, while ERA-5 demonstrated the lowest error in terms of river stage (29.4 %) and floodplain depth (28.6 %). Accuracy varied geographically, and no product performed best across all basins. Global reanalysis products provide a useful resource for flood modelling where no other data are available, but they should be used with caution due to the underestimation of impacts shown here. Until a more systematic international strategy for the collection of rainfall and flood impact data ensures more complete global coverage for validation, multiple reanalysis products should be used concurrently to capture the range of uncertainties.

Analysis of transient seepage through a river embankment by means of centrifuge modelling

Earthen river embankments are typically in unsaturated conditions during their lifetime and the degree of saturation within their bodies may vary significantly throughout the year, due to seasonalfluctuations of the river stage, as well as infiltrations of meteoric precipitation and evapotranspiration phenomena. Given the significant effects of partial saturation on the hydro-mechanical behaviour of soils, realistic assumptions on the actual water content distribution inside the embankments are essential forproperly modelling their response to hydraulic loadings. In this framework, centrifuge modelling is a useful tool to get insights into the evolution of saturation conditions of a water retaining structure during flood events. It allows for the direct observation of the groundwater flow process, which is hardly detectable at the prototype scale, enabling, at the same time, the validation and calibration of predictive numerical tools.In this paper, the results of a centrifuge test carried out on small-scale physical model of a compacted silty clayey sand embankment subjected to a simulated high-water event, at the enhanced gravity of 50-g, are presented and discussed. The physical model was carefully instrumented with potentiometers, miniaturized pore pressure transducers and tensiometers. Pore pressures and suctions measured during the experiment showed that the stationary flow conditions were reached only after an unrealistic hydrometric peak persistence. It therefore emerges that, for the design and/or the assessment of the safety conditions of a river embankment similar to the one tested, the simplified hypothesis of a steady-state seepage, in equilibrium with the maximum river stage expected could result, in many cases, an excessively conservative assumption.

Sediment-Loading Processes in a Forested Catchment: Modeling and Observations

In order to investigate sediment-loading processes in a catchment, the daily time series of river discharge and sediment load were applied to a semi-distributed model, the Soil and Water Assessment Tool (SWAT). The time series of discharge and sediment load were obtained by monitoring the river stage and water turbidity of the Oikamanai River, Hokkaido, Japan, in the rainfall season (April-November) of 2011-2014. The catchment is forested (ca 90% area) but underlain by the Neogene sedimentary rocks with currently active faults and forest soils with tephra layers, which tend to frequently produce slope failure such as landslide and bank collapse by rainfall or snowmelt. The water turbidity, T, in ppm was converted into suspended sediment concentration, SSC, in g/L by applying the linear relationship between T and SSC. The acquisition of the time series of discharge, Q (m3/s) and sediment load, L (=Q·SSC in g/s) of the river allowed us to distinguish the fluvial sediment transport, accompanied by slope failure in the upstream, from that under no slope failure. The SWAT was used to simulate soil erosion and identify the region prone to the soil erosion in the Oikamanai River basin. The model’s results showed a satisfactory agreement between daily observed and simulated sediment load as indicated by the high Nash-Sutcliffe efficiency. This evidences that the upper mountainous region of the catchment provides a main sediment source, accompanied by slope failure.

Nitrate sink function of riparian zones induced by river stage fluctuations

River stage fluctuation (RSF) induced by tides, dam releases, or storms may lead to enhanced nitrogen cycling (N cycling) in riparian zones (RZ). We conducted a laboratory water table manipulation experiment and applied a multiphase flow and transport model (TOUGHREACT) to investigate the role of RSF in N cycling in the RZ. Coupled nitrification and denitrification occur in the water table fluctuation zone under alternating aerobic and anaerobic conditions. Nitrate removal was enhanced in the saturated and unsaturated zones of the RZ. The net nitrate reduction rate in groundwater increased with the increasing number of RSF, as a result, the cumulative water influx. The RZ nitrate sink function became stronger with increasing RSF amplitude and soil organic matter (SOM) content, and weaker with increasing [NH4+]/[NO3−] ratio and mineralization rate. RSF generally creates a hot moment for net nitrate removal in the RZ. However, a hot moment for the nitrate source function might occur if the [NH4+]/[NO3−] ratio of groundwater is much greater than 1 and/or if a large pool of nitrate accumulates in the topsoil over a prolonged dry period. The absence of oxygen diffusion in the model would overestimate the nitrate removal capacity of the RZ.

Dynamic Response Characteristics of Shallow Groundwater Level to Hydro-Meteorological Factors and Well Irrigation Water Withdrawals under Different Conditions of Groundwater Buried Depth

Many irrigation districts along the Yellow River have been suffering shallow groundwater depression and agriculture-use water shortage. For comprehending response relationships of shallow groundwater level and various factors under different conditions of groundwater buried depth, the hydro-meteorological time series and the agricultural production data in Puyang area of Henan Province, China during 2006–2018 were collected for performing wavelet analysis of the relationship between the groundwater level and the four different factors, such as precipitation, air temperature, water stage of the Yellow River, and well irrigation water amount. It is shown that when the burial depth of groundwater varied from 0–10 m to over 10 m, the groundwater level was related with both the precipitation and air temperature from moderately to weakly and the delayed response times of the groundwater level to them extended from 2–4 months to more than 5 months. The groundwater level maintained a medium correlation with the well irrigation water amount as the burial depth increased, but the lag response time of groundwater level to well irrigation dramatically decreased when the burial depth exceeded 10 m. The dynamic response relationship between the groundwater and the water stage of the Yellow River was mainly affected by the distance away from the Yellow River rather than the burial depth and the influence of the river stage on the groundwater level was limited within the distance approximate to 20 km away from the Yellow River. The findings are expected to provide the reference for groundwater level prediction and groundwater resources protection.

Factors Affecting the Rates and Modes of Landslide Colluvium Removal in River Channels of Podhale (Western Carpathians)

This paper presented some hydrological factors affecting the course and rate of fluvial erosion of landslide colluvium at its contact with river flow. Volumes of colluvium eroded by rivers in the period 2013–2019 were measured at Podhale (a part of Polish West Carpathians) on four landslides representing various geological settings. At each landslide, changes in shape and position of the contact zone between colluvium and river water were registered after episodes of high river stage. The obtained data on changes in relief of the landslide fronts and adjacent river channels were used to calculate volumes of colluvium removed during each episode. The course of erosion and volumes of colluvium eroded were compared with the water stage records for the studied period of time. Intensity of colluvium erosion was found to be strongly dependent on the water levels and cohesion of colluvium. Volumes of removed colluvium were the greatest during short-lived (1–2 days) and prolonged (7–10 days) periods of high river stages. The rate of erosional removal was the highest for colluvium consisting of poorly consolidated Quaternary matrix-supported massive gravel and overlying fine deposits stored within river terraces. Colluvium composed of Neogene mudstones and sandstones was removed at a lower rate and the rate of removal was lowest for large blocks and slices composed of solid layers of alternating sandstone and shales belonging to the Podhale Flysch series. Erosion of the landslide toes was more intense at those sites where the river flow approached the landslide front at a wider angle.

Study on the time-varying law of mechanics of the crossing suspended pipeline under flood action

In order to study the mechanical behavior of the river crossing pipeline before and after the flood, the suspended coefficient was defined, the correspondence between the suspended length of the pipeline and the flood flow velocity was characterized, and the flood hydrograph design encountered in the past 50 years was predicted according to the hydrological conditions of a pipeline crossing the river. Then, the dynamic change process of the X80 gas pipeline under the action of a flood is simulated by finite element software. Finally, the change law of pipeline mechanical behavior with time at each stage of river crossing pipeline under the condition that the suspended coefficient is known and a flood hydrograph is obtained. The results indicate that in the process of pipeline suspension from 5 m to pipeline failure, the failure time of pipelines with suspension coefficients of 0.005 and 0.01 is 3780s and 2200s, respectively. In the pipeline suspended 30–40 m stage, the impact of suspension length on pipeline stress exceeds the flood flow velocity, and the pipeline stress in this section increases greatly, and its stress growth rate is about 1.7 times the average growth rate of the pipeline suspension from 5 m to pipeline failure. Therefore, protective measures should be taken in emergency rescue before the X80 pipeline suspension of 30 m.