Rivers In Cold Regions Research Articles

Refined Simulation Study of Hydrodynamic Properties and Flow Field Characteristics around Tandem Bridge Piers under Ice-Cover Conditions

Ice cover is a common phenomenon in rivers in cold regions during the winter freeze-up period, leading to the formation of unsteady bypass structures around underwater piers. To reveal the variation law of the flow field around a pier under ice, a numerical calculation method is proposed to obtain the spatial and temporal characteristics of the fluid flow environment around the pier. The verification of flow conditions and convergence showed that the numerical model constructed in this study is reliable and can meet research requirements. The simulation results showed that the ice-cover condition considerably impacted the extent of a scour hole, and in the horizontal plane Z of −0.02 m, the lateral influence of the scour hole was approximately 2.6 times the diameter of the pier, which was approximately 42% wider than that of a scour hole under open-flow conditions; in the area on the side of the pier, there was a peak in longitudinal section y/D of −0.6, and the relative turbulence intensity was 0.4 and 0.51 under open-flow and ice-cover conditions, respectively, indicating that ice cover made the peak more significant in the area.

Cold Region River Flood Mapping and Scour Potential Prediction: Insights from Hydraulic Model Using Advanced Autonomous Surface Vehicles

This study aimed to map the 2022 flood with a 16.5-year return period near a bridge on the Red River, close to Grafton City, North Dakota, and evaluate the scour potential around the bridge. The Red River Basin (RRB) near Grand Forks, ND, and Emerson, ND, is a cold region river vulnerable to floods. Local scouring around bridge piers during floods can lead to hydraulic structure failure. An Autonomous Surface Vehicle (ASV) equipped with LiDAR DEM data from the ND DWR’s LiDAR dataset was used to collect comprehensive bathymetry and discharge data, including the 2022 flood. The HEC-RAS model was used to create flood maps, and the Colorado State University (CSU) methodology was employed to assess local scour around the bridge pier. The study area recorded maximum velocities of 1.71 m/s, 1.87 m/s, and 1.56 m/s for discharge values of 368 m3/s, 784 m3/s, and 1335 m3/s, respectively, with higher velocities recorded upstream of the bridge. The maximum water depth reached 13.14 m during the peak discharge of 1335 m3/s. Higher discharge resulted in increased Froude number and contraction scour depth, with the latter continuing to increase even when the Froude number decreased as water reached the bridge deck. The study highlights the effectiveness of integrating ASVs, bathymetry, and LiDAR data to comprehensively understand flood dynamics and bridge scour in cold region rivers, offering the way for the development of effective flood control measures and strategies to safeguard critical infrastructure.

Elements and Processes Required for the Development of a Spring-Breakup Ice-Jam Flood Forecasting System (Churchill River, Atlantic Canada)

Spring-breakup ice-jam floods are a major hazard for many rivers in cold regions. They can cause severe damage to infrastructure, property, and ecosystems along riverbanks. To reduce the risk and impact of these events, it is essential to develop reliable and timely forecasting systems that can provide early warning and guidance for mitigation actions. In this paper, we highlight the elements and processes required for the successful development of a spring-breakup ice-jam flood forecasting system, using the lower Churchill River in Labrador, Canada as a case study. We review the existing forecasting methodologies and systems for spring-breakup ice-jam floods and discuss their strengths and limitations. We then describe the case study of the lower Churchill River, where a large ice-jam flood occurred in May 2017, triggering an independent review and a series of recommendations for improving the flood preparedness and response. We present the main components and features of the forecasting system that was developed for the lower Churchill River, based on the recommendations from the independent review. We also discuss the improvements that were made to the forecasting system, such as parallelization, adaptation, and determination of ice-jam prone areas. Finally, we provide some conclusions and recommendations for future research and development of spring-breakup ice-jam flood forecasting systems, focusing on the requirements for a technical framework that incorporates community engagement and special considerations for regulated rivers.

Investigating the differences in driving mechanisms for phytoplankton community composition under various human disturbances in cold regions

In river ecosystems, phytoplankton are essential components, and this study delves into their response to critical environmental indicators. We analyzed the spatiotemporal variations of phytoplankton diversity in cold regions, employing techniques such as Principal Component Analysis (PCA), Spearman correlation coefficient, and Generalized Additive Model (GAM) to unveil the critical environmental factors influencing phytoplankton diversity and habitat suitability under varying degrees of human interference. With 37 monitoring stations across two cold region rivers, phytoplankton and water bodies were monitored in spring, summer, and autumn, resulting in the collection and analysis of 111 phytoplankton samples and 13 environmental indicators at each station. By identifying critical water quality indicators and exploring nonlinear relationships, the study revealed intricate interactions between phytoplankton diversity and environmental factors. Our findings suggest that overall phytoplankton species diversity is lower in rivers with high human interference, with turbidity, NH4+-N, chlorophyll-a, and total phosphorus (TP) deemed critical factors. Conversely, chlorophyll-a, NH4+-N, and electrical conductivity (EC) were identified as important factors in rivers with lower human interference, indicating differences in phytoplankton driving mechanisms between the two rivers. These insights provide valuable references for the sustainable development and effective assessment of cold region river ecosystems in the Anthropocene.

Estimation of the suspended sediment concentration in ice-covered channels based on the gravitational theory

Rivers in cold high latitude northern regions usually freeze during winter, thereby forming an ice cover on the water surface. The additional ice cover significantly changes the flow characteristics of the rivers and hence affects the process of water and sediment transport. Understanding the vertical profile of suspended sediment concentration (SSC) in ice-covered channel flows is helpful for investigating the sediment deposition and the bed morphology of rivers located in cold regions. To predict the SSC distribution in ice-covered channels, this study is based on the gravitational theory and puts forward a new SSC model by dividing the flow underneath the ice cover into the upper ice layer and the lower bed layer with the maximum streamwise velocity and the zero Reynolds shear stress as the interface. The calculated results of the new SSC model agree well with the collected experimental data, and the accuracy of the prediction results is evaluated by error analysis. Besides, the differences in the governing equations and the prediction accuracy between the gravitational theory and the diffusion theory are discussed, and thus the pros and cons of the proposed SSC model are illustrated. Although the gravitational theory has the controversial point, the validation results and discussions demonstrate that adopting the gravitational theory to estimate the SSC distribution in ice-covered channels is effective. The theoretical approach used herein can provide some guidance for studying the sediment-laden flow of freezing rivers in high-latitude northern regions.

Characteristics and multi-factor mechanisms of dam construction on food web structure in cold-region rivers

Most previous studies have focused on the detrimental effects of dam construction on river ecosystems. However, because of the unique traits of cold-regions, the impact characteristics and multi-factor mechanisms of dam construction on ecological systems remain unclear. In this study, food web structure models were constructed for different river sections based on field data to calculate topological indicators, trophic levels, and diet compositions to characterize the impact of dam construction on the food web structure in cold-region rivers and identify spatial differences. The findings suggest that dam construction can improve the ecological systems of rivers in cold-regions to a certain extent. Specifically, the pre-reservoir sections exhibit a more diverse and complex food web structure than a natural river section, while the food web structure downstream of the reservoir shows a trend of “simplification”, accompanied by a continuous decrease in trophic levels and a shift towards herbivorous feeding. Moreover, redundancy analysis and partial least squares structural equation modeling were used to investigate the mechanisms of the synergistic effects of multiple factors, including flow assurance, water quality, and aquatic organisms, on food web structure. The key influential factor was identified as the “flow assurance degree” (path coefficient 0.716), which needs to be appropriately increased the flow during the ice-covered period (0.849) while meeting the environmental flow targets (0.897) in order to enhance the diversity and complexity of the food web structure. This study provides technical support for the protection and restoration of the ecosystem of rivers in the cold-region.

A hydrologic and river ice modelling framework for assessing ungauged sub-basin streamflow impact in a large cold-region river basin

ABSTRACT Modelling snow- and ice-affected streamflow in cold regions is challenging. Neglecting the streamflow from ungauged regions/sub-basins of a river basin in the inflow boundaries of a river ice model adds further uncertainties. This study combined a river ice model (River1D) with a hydrological model (Soil and Water Assessment Tool, SWAT) to investigate the impacts of ungauged sub-basin streamflow on peak flow simulation under both open water and river ice breakup conditions in the Peace River Basin (PRB). Results showed that ungauged sub-basins of the PRB can greatly affect peak flow simulation of the River1D for both open water and river ice breakup events, especially for flood events. Although they represent only about 26.54% of the whole modelled area in the PRB, the SWAT model simulated results show that the ungauged sub-basins can contribute nearly 50% of peak flow for the open water and river ice breakup flood events.

Refined Simulation Study on the Effect of Scour Environments on Local Scour of Tandem Bridge Piers

Ice cover is a natural phenomenon unique to rivers in cold regions, and its existence is one of the reasons for the collapse of structural foundations of bridge piers across rivers. In order to understand the influence of different scouring environments on the hydrodynamics and sand bed morphology in the local scour holes around bridge pier foundations, this paper simulates the dynamic evolution process of the local scouring of tandem combination piers under open-flow and ice-cover environments, based on a turbulence model using the Reynolds-averaged Navier Stokes (RANS) method and a sediment transport model considering the slope collapse effect, respectively. This study also takes the vortex flow and shear stress distribution at different characteristic moments of the pier perimeter section as the penetration point to analyze the effect of the influence law of the scouring environment on the morphology and relative time scale of the scour hole, and makes a detailed comparison with the results of the indoor flume test. The results of this study show that: for local scouring in open-flow conditions, sediment initiation is doubly inhibited and the hydrodynamic forces in the scouring hole are weakened; the local scouring caused by ice cover contributes to the total scouring of the submerged pier within its coverage area, which significantly increases the depth and range of the local scouring hole; and, although the interaction of turbulent eddies and shear stress on the pier side is the main dynamic mechanism of the scouring generated around the pier, the two have a strong correlation. The results of this study, obtained by accurately quantifying the amount of eddies and shear stress around the pier, are the basis for the reasonable estimation of the maximum local scouring depth, which can provide a reference for the study of the evolution of the riverbed around submerged structures in cold areas and is essential to avoid structural damage to the piers and reduce the economic loss of traffic..

Development of an ice-jam flood forecasting modelling framework for freeze-up/winter breakup

AbstractRiver ice-jams can create severe flooding along many rivers in cold regions. While ice-jams often form during the spring breakup, the mid-winter breakup can cause ice-jamming and flooding. Although many studies have already been focused on forecasting spring ice-jam flooding, studies related to forecasting mid-winter breakup jamming and flooding severity are sparse. The main purpose of this research is to develop a stochastic framework to forecast the severity of mid-winter ice-jam flooding along the transborder (New Brunswick/Maine) Saint John River of North America. A combination of hydrological (MESH) and hydraulic model (RIVICE) simulations was applied to develop the stochastic framework. A mid-winter breakup along the river that occurred in 2018 has been hindcasted as a case study. The result shows that the modelling framework can capture the real-time ice-jam severity. The results of this research will help to improve the capacity of ice-jam flood management in cold regions.

Accumulation and evolution of ice jams influenced by different ice discharge: An experimental analysis

Ice jam, a unique hydrological phenomenon of rivers in cold regions, is a major cause of ice flooding. There are many different kinds of damage that can result from ice jams: e.g., blockage of the water flow, rising water levels that can flood farmland and dwellings, damage to hydraulic structures, and interruptions to shipping. The formation of an ice jam is influenced by various factors associated with different fields of study. The accumulation of an ice jam is thus a complex process worth investigating. However, previous studies seldom take account of ice discharge factors. This study carries out 29 tests on the accumulation of an ice jam, and discovers four kinds of phenomena: inlet ice that fails to submerge (case 1); thickening ice from upstream to downstream (case 2); thickening ice from downstream to upstream (case 3); and failure to form an ice jam (case 4). Two typical examples are used to detail cases 2 and 3. The authors suggest differentiating between the two cases using the longitudinal boundary line running through the point of the Froude number (Fr) = 0.119. Furthermore, the authors analyze the phenomena that make it difficult for an ice jam to form and suggest using the critical discriminant line to distinguish between cases 3 and 4. Combined with the longitudinal boundary line, a partition result diagram of the different accumulation features of ice jams is presented to differentiate between the four modes of accumulation of ice jams.

Waved-Shape Accumulation of Ice Jam—Analysis and Experimental Study

Ice jam is a unique hydrological phenomenon in rivers in cold regions. The appearance of an ice jam in a river results in an increase in the wetted perimeter of the flow cross-section, and thus an increase in flow resistance as well as water level. It may cause ice flooding sometimes. Similar to the “sand wave” phenomenon in riverbed, it has been observed in laboratory experiments that the waved-shape accumulation of ice particles (termed as “ice wave”) under an ice jam occurred. In this study, an Equation for describing the relationship between the approaching flow Froude number (Fr) and the ratio of ice jam thickness to flow depth (t/H) has been proposed. Taking the inflection point value of the equation under different flow depths, a characteristic curve has been developed to judge whether ice waves under an ice jam occurs. When the flow Froude number in front of an ice jam is below the value at the inflection point of the curve, the ice jam can maintain a mechanical stability within the ice jam thickness in a range from the lower limiting value to the upper limiting value, which were close to the ice wave trough thickness and the ice wave crest thickness, respectively. An Equation for calculating the ice wavelength has been derived and verified by using results of laboratory experiments. The relationship between the migration speed of ice wave and the ratio of ice discharge to water flow rate (Qi/Q) has been also analyzed. At last, case studies have been conducted with respect to ice accumulation in the St. Lawrence River, the Beauharnois Canal and the La Grande River. Results of case studies show that the shoving and ice dam have been dominated by mechanical factors, which would be accompanied by the ice wave phenomenon during the ice jam accumulation process. Results of case studies about ice accumulation in natural rivers also show that the relative thickness of an ice jam (t/H) of 0.4 is the criterion for assessing whether an ice jam in a river belongs to an ice dam.

Impacts of wastewater effluents and seasonal trends on levels of antipsychotic pharmaceuticals in water and sediments from two cold-region rivers

Most pharmaceuticals are found at trace concentrations in aquatic systems, but their continuous release and potential accumulation can lead to adverse health effects in exposed organisms. Concentrations can vary temporally, driven by variations in discharges of receiving waters, sorption to sediments, and other biotic and abiotic exchange processes. The principal aim of this research was to better understand the occurrence, trends, and dynamics of pharmaceuticals in a cold-climate, riverine environment. To this end, a suite of seven representative antipsychotic pharmaceuticals was measured upstream and downstream of two wastewater treatment plants (WWTPs) in Saskatchewan, Canada, located in the South Saskatchewan River and Wascana Creek, respectively, across three seasons. Concentrations of analytes were in the ng/L range and generally greater downstream of both WWTPs compared to upstream. Some compounds, including the tricyclic antidepressant amitriptyline, which was the most abundant analyte in water and sediment from both sites and across seasons, reached low μg/L concentrations. Data collected from this research effort indicate contamination with antipsychotic pharmaceuticals, with the potential to adversely impact exposed organisms.

River Extraction from Remote Sensing Images in Cold and Arid Regions Based on Attention Mechanism

The extraction of rivers in cold and arid regions is of great significance for applications such as ecological environment monitoring, agricultural planning, and disaster warning. However, there are few related studies on river extraction in cold and arid regions, and it is still in its infancy. The accuracy of river extraction is low, and the details are blurred. The rapid development of deep learning has provided us with new ideas, but with lack of corresponding professional datasets, the accuracy of the current semantic segmentation network is not high. This study mainly presents the following. (1) According to the characteristics of cold and arid regions, a professional dataset was made to support the extraction of rivers from remote sensing images in these regions. (2) Combine transfer learning and deep learning, migrate the ResNet-101 network to the LinkNet network, and introduce the attention mechanism to obtain the AR-LinkNet network, which is used to improve the recognition accuracy of the network. (3) A channel attention module and a spatial attention module with residual structure are proposed to strengthen the effective features and improve the segmentation accuracy. (4) Combining dense atrous spatial pyramid pooling (DenseASPP) with AR-LinkNet network expands the network receptive field, which can extract more detailed information and increase the coherence of extracted rivers. (5) For the first time, the binary cross-entropy loss function combined with the Dice loss function is applied to river extraction as a new loss function, which accelerates the network convergence and improves the image quality. Validation on the dataset shows that, compared with typical semantic segmentation networks, the method performs better on evaluation metrics such as recall, intersection ratio, precision, and F 1 score, and the extracted rivers are clearer and more coherent.

Effects of ecological restoration on water quality and benthic macroinvertebrates in rural rivers of cold regions: A case study of the Huaide River, Northeast China

Various human activities can damage the structure of rural rivers ecosystems and reduce their self-purification capacity. In Northeast China, the cold climate also poses serious challenges to river restoration. What types of restoration technology should be adopted and what impacts the restoration project will bring, in terms of river ecological function improvements, should be further discussed. To investigate the effects of ecological restoration projects and different restoration measures on water quality and benthic macroinvertebrates of rural rivers in cold regions in Northeast China, benthic macroinvertebrates and 10 indicators of water quality including ammonium (NH4+-N), nitrate (NO3–-N), total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), dissolved oxygen (DO), water temperature (Tem), pH (pH), electrical conductivity (EC) and chlorophyll-a (Chla) were monitored. We analyzed the temporal and spatial changes of benthic macroinvertebrates and 6 typical water quality indicators including NH4+-N, NO3–-N, TN, TP, COD and DO, which were collected in 4 seasons at 7 typical river sections. The Water Quality Index (WQI) was used to evaluate the seasonal and spatial variation of water quality during monitoring period, and a new WQImin model consisting of six crucial parameters, i.e., pH, DO, NH4+-N, TN, TP and COD, was established by principal component analysis. The results showed that the ecological restoration project enhanced the self-purification capacity of the river, and increased diversity of benthic macroinvertebrates. The maximum removal rates of the main pollution indicators NH4+-N, NO3–-N, TN, TP and COD were 96.49 %, 43.92 %, 49.69 %, 8.3 % and 25.95 %, respectively. The maximum increase rates of DO and benthic macroinvertebrates diversity were 77.96 % and 310.9 %, respectively. The operation effect of the restoration project had an obvious seasonal effect, with the best effect during the spring and summer. The project still has good repair effect in winter. In terms of water purification, the effect of the overflow weir combined with aquatic organisms was better than that of the single overflow weir in the river channel. There was the best effect of the engineering measures in summer. The ecological restoration project can improve the river water quality and the benthic macroinvertebrates conditions. Compared to before the restoration, WQImin values increased 168.81 % and 44.21 % in winter and summer, respectively, and Shannon index increased 6.57 % and 41.67 % in summer and autumn, respectively.

Assessing and predicting the severity of mid-winter breakups based on Canada-wide river ice data

Mid-winter breakups (MWBs), consisting of the early breakup of the winter river ice cover before the typical spring breakup season, are becoming increasingly common events in cold region rivers. These events can lead to potentially severe flooding, while also altering the expected spring flow regime, yet data on these events is limited. In this study, a newly released Canadian River Ice Database (CRID), containing river ice data from 196 rivers across Canada obtained from time series analysis, was used to analyse these MWBs on a previously impossible national scale. The CRID data was combined with the Natural Resources Canada (NRCan) gridded daily climate dataset to identify a list of potential hydrologic and climatic drivers for MWB events. Techniques such as correlation analysis, Least Absolute Selection Shrinkage Operator (LASSO) regression, and input omission were combined to select 20 key drivers of the severity of MWB events. A random forest model that was trained with these drivers using data-driven modelling techniques successfully classified the MWBs as either low, medium, or high severity, achieving an overall accuracy of 80%. A new threshold for the prediction of MWB initiation based on climatic conditions was subsequently proposed through the use of optimization via an exhaustive grid search and its accuracy in identifying MWBs exceeded those proposed by previous studies. The new threshold used in conjunction with the random forest model provide valuable tools for both the prediction of MWBs and the assessment of their potential severity.

Forecast of winter low flows in a cold-region river under the impact of climate warming

Changes in winter low flow (WLF) in cold-region rivers affect engineering design, water quality, and river ecosystem health. This paper aims to quantify to what extent WLF will change under climate warming and to propose a practical forecasting model for WLF predictions. The new concept of cumulative watershed temperature (CWT) is used as a convenient lumped surrogate for complicated hydrological processes that influence WLF. Statistical analyses of century-long flow data from the Fraser River in British Columbia, Canada show a strong dependence of WLF on CWT. In winter season, time series of CWT and WLF are shown to each divide into a falling and a rising limb at the data point of their lowest values, being −358 °C and 827 m3/s (historical averages), respectively. The falling and rising limbs describe the cumulative freezing and thawing effects of air temperatures fluctuating around the freezing point on WLF changes. The correlation between CWT and WLF (time series) data points on the rising limbs forms the forecasting model, expressing WLF as a function of CWT in terms of their z-scores. The model takes input of Global Circulation Model (GCM) projections of temperature increases by the end of 21st century under different Representative Concentration Pathways (RCPs), and predicts changes of Fraser River WLF from the historical average. RCP4.5 causes a 22.6% increase (ensemble average from six GCMs). RCP8.5 increases WLF by 20% (for some future years) to 44% (for others). The methods reported in this paper can be adapted to other cold regions.

IceMaskNet: River ice detection and characterization using deep learning algorithms applied to aerial photography

Dynamic ice processes can significantly affect various river characteristics such as hydraulics, sediment transport, water quality and morphology. River ice can also impede ship navigation and can induce flood hazard. Study of ice processes is thus crucial for understanding rivers in cold regions. These processes vary according to the four different phases of river ice development: formation, progression, recession and breakup. Monitoring and observation of river ice by remote sensing and close-range photogrammetry have recently attracted significant attention from river ice researchers, and the emergence of remotely piloted aircraft systems with onboard cameras has facilitated safe surveying of river ice. Despite all the developments in this field, fast and accurate data acquisition is still very demanding. One of the challenging tasks in data acquisition from aerial imagery is ice detection and classification. This study presents a novel algorithm called IceMaskNet for automatic river ice detection and characterization from aerial imagery. IceMaskNet utilizes an improved version of the Mask R-CNN, a novel Region-based Convolutional Neural Network with an additional mask. The presented deep learning algorithm is able to detect river ice from aerial imagery and characterize it as belonging to one of six different classes: broken ice, frazil slush, ice cover, open water, border ice, or frazil pan. The developed algorithm is tested using data collected on the Dauphin River, in Manitoba, Canada. Aerial photography from several sections of the river with various slopes and bend scales were used to train IceMaskNet to detect, classify and characterize river ice. The presented algorithm detected and classified river ice with average accuracies of 95% and 91%, respectively.

Predicting River Flow Using an AI-Based Sequential Adaptive Neuro-Fuzzy Inference System

Artificial intelligence (AI) techniques have been successfully adopted in predictive modeling to capture the nonlinearity of natural systems. The high seasonal variability of rivers in cold weather regions poses a challenge to river flow forecasting, which tends to be complex and data demanding. This study proposes a novel technique to forecast flows that use a single-input sequential adaptive neuro-fuzzy inference system (ANFIS) along the Athabasca River in Alberta, Canada. After estimating the optimal lead time between four hydrometric stations, gauging data measured near the source were used to predict river flow near the mouth, over approximately 1000 km. The performance of this technique was compared to nonsequential and multi-input ANFISs, which use gauging data measured at each of the four hydrometric stations. The results show that a sequential ANFIS can accurately predict river flow (r2 = 0.99, Nash–Sutcliffe = 0.98) with a longer lead time (6 days) by using a single input, compared to nonsequential and multi-input ANFIS (2 days). This method provides accurate predictions over large distances, allowing for flow forecasts over longer periods of time. Therefore, governmental agencies and community planners could utilize this technique to improve flood prevention and planning, operations, maintenance, and the administration of water resource systems.

River-ice and water velocities using the Planet optical cubesat constellation

Abstract. The PlanetScope constellation consists of ∼150 optical cubesats that are evenly distributed like strings of pearls on two orbital planes, scanning the Earth's land surface once per day with an approximate spatial image resolution of 3 m. Subsequent cubesats on each of the orbital planes image the Earth surface with a nominal time lag of approximately 90 s between them, which produces near-simultaneous image pairs over the across-track overlaps of the cubesat swaths. We exploit this short time lag between subsequent Planet cubesat images to track river ice floes on northern rivers as indicators of water surface velocities. The method is demonstrated for a 60 km long reach of the Amur River in Siberia, and a 200 km long reach of the Yukon River in Alaska. The accuracy of the estimated horizontal surface velocities is of the order of ±0.01 m s−1. The application of our approach is complicated by cloud cover and low sun angles at high latitudes during the periods where rivers typically carry ice floes, and by the fact that the near-simultaneous swath overlaps, by design, do not cover the complete Earth surface. Still, the approach enables direct remote sensing of river surface velocities for numerous cold-region rivers at a number of locations and occasionally several times per year – which is much more frequent and over much larger areas than currently feasible. We find that freeze-up conditions seem to offer ice floes that are generally more suitable for tracking, and over longer time periods, compared with typical ice break-up conditions. The coverage of river velocities obtained could be particularly useful in combination with satellite measurements of river area, and river surface height and slope.

A comprehensive ecological management approach for northern mountain rivers in China

Mountain rivers not only play an important role in flood control, but also perform other functions such as conserving water sources, regulating microclimate, and maintaining water ecology and biodiversity. Because the conventional approach to managing mountain rivers overlooks the intrinsic requirements of river water, alters the natural landscape of river channels, and destroys habitats, it leads to water quality deterioration and ecological imbalance. The Yang River is characteristic of northern mountain rivers, and so the ecological management project for this river – at the site of the forthcoming Beijing 2022 Olympic Winter Games – was selected as an example of comprehensive ecological management. This comprises an ecological, permeable dam–pond–wetland system. Results showed that: (Zhu et al., 2006): river water quality improved substantially; improvements in the water quality indices exhibited the trend suspended solids (SS) > ammonium-nitrogen (NH3-N) > chemical oxygen demand (COD) (Mikus et al., 2019). The Shannon–Wiener diversity index, Margalef species richness index, and Pielou evenness index all indicated increased phytoplankton by an average of 52.1%, 2.4%, and 98.9%, respectively. These three diversity indices showed increased zooplankton, by an average of 1.2%, 0.5%, and 3.3%, respectively. Water quality in the Yang River was found to have changed from moderate to light pollution (Kuemmerlen et al., 2019). Each subsystem increased removal of pollutants from the Yang River. Removal efficiencies of COD, total phosphorous (TP), total nitrogen (TN), NH3-N, and SS by the dam system were 28.57%, 28.3%, 20.5%, 24.0%, and 95%, respectively. Corresponding pollutant removal efficiencies by the pond system were 16.7%, 29.58%, 21.63%, 20.0%, and 99.8%, respectively. The wetland system achieved pollutant removal efficiencies of 44.0%, 17.1%, 6.7%, 13.9%, and 80.0%, respectively. This approach can mitigate flood control pressure, restore river ecology, and improve water quality in northern mountain rivers, and allow such rivers to achieve “retention–storage–restoration” effects. The ecological treatment approach provides an important theoretical foundation and technical reference for global mountain river management, and is especially applicable to mountain rivers in cold and arid regions in the northern hemisphere.