Browsing by Author "Lindenschmidt, Karl-Erich"
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Item Assessing and Mitigating Ice-Jam Flood Hazards and Risks: A European Perspective(MDPI, 2022) Lindenschmidt, Karl-Erich; Alfredsen, Knut Tore; Carstensen, Dirk; Choryński, Adam; Gustafsson, David; Halicki, Michał; Hentschel, Bernd; Karjalainen, Niina; Kögel, Michael; Kolerski, Tomasz; Korna´s-Dynia, Marika; Kubicki, Michał; Kundzewicz, Zbigniew; Lauschke, Cornelia; Marszelewski, Włodzimierz; Möldner, Fabian; Näslund-Landenmark, Barbro; Niedzielski, Tomasz; Parjanne, Antti; Pawłowski, Bogusław; Pińskwar, Iwona; Remisz, Joanna; Renner, Maik; Roers, Michael; Rybacki, Maksymilian; Szałkiewicz, Ewelina; Szydłowski, Michał; Walusiak, Grzegorz; Witek, Matylda Katarzyna; Zagata, Mateusz; Zdralewicz, MaciejThe assessment and mapping of riverine flood hazards and risks is recognized by many countries as an important tool for characterizing floods and developing flood management plans. Often, however, these management plans give attention primarily to open-water floods, with ice-jam floods being mostly an afterthought once these plans have been drafted. In some Nordic regions, ice-jam floods can be more severe than open-water floods, with floodwater levels of ice-jam floods often exceeding levels of open-water floods for the same return periods. Hence, it is imperative that flooding due to river ice processes be considered in flood management plans. This also pertains to European member states who are required to submit renewed flood management plans every six years to the European governance authorities. On 19 and 20 October 2022, a workshop entitled “Assessing and mitigating ice-jam flood hazard and risk” was hosted in Pozna´ n, Poland to explore the necessity of incorporating ice-jam flood hazard and risk assessments in the European Union’s Flood Directive. The presentations given at the workshop provided a good overview of flood risk assessments in Europe and how they may change due to the climate in the future. Perspectives from Norway, Sweden, Finland, Germany, and Poland were presented. Mitigation measures, particularly the artificial breakage of river ice covers and ice-jam flood forecasting, were shared. Advances in ice processes were also presented at the workshop, including state-of-the-art developments in tracking ice-floe velocities using particle tracking velocimetry, characterizing hanging dam ice, designing new ice-control structures, detecting, and monitoring river ice covers using composite imagery from both radar and optical satellite sensors, and calculating ice-jam flood hazards using a stochastic modelling approach.Item Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed(MDPI, 2023) Lee, Ju Hyoung; Lindenschmidt, Karl-ErichSatellites are designed to monitor geospatial data over large areas at a catchment scale. However, most of satellite validation works are conducted at local point scales with a lack of spatial representativeness. Although upscaling them with a spatial average of several point data collected in the field, it is almost impossible to reorganize backscattering responses at pixel scales. Considering the influence of soil storage on watershed streamflow, we thus suggested watershed-scale hydrological validation. In addition, to overcome the limitations of backscattering models that are widely used for C-band Synthetic Aperture Radar (SAR) soil moisture but applied to bare soils only, in this study, RADARSAT-2 soil moisture was stochastically retrieved to correct vegetation effects arising from agricultural lands. Roughness-corrected soil moisture retrievals were assessed at various spatial scales over the Brightwater Creek basin (land cover: crop lands, gross drainage area: 1540 km2) in Saskatchewan, Canada. At the point scale, local station data showed that the Root Mean Square Errors (RMSEs), Unbiased RMSEs (ubRMSEs) and biases of Radarsat-2 were 0.06~0.09 m3/m3, 0.04~0.08 m3/m3 and 0.01~0.05 m3/m3, respectively, while 1 km Soil Moisture Active Passive (SMAP) showed underestimation at RMSEs of 0.1~0.22 m3/m3 and biases of 0.036~0.2080 m3/m3. Although SMAP soil moisture better distinguished the contributing area at the catchment scale, Radarsat-2 soil moisture showed a better discharge hysteresis. A reliable estimation of the soil storage dynamics is more important for discharge forecasting than a static classification of contributing and noncontributing areas.Item Development of an ice-jam flood forecasting modelling framework for freeze-up/winter breakup(IWA Publishing, 2023) Das, Apurba; Budhathoki, Sujata; Lindenschmidt, Karl-ErichRiver ice-jams can create severe flooding along many rivers in cold regions. While ice-jams often form during the spring breakup, the midwinter 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.Item Extension and refinement of a stochastic modelling approach to assess ice-jam flood hazard(IWA Publishing, 2023) Lindenschmidt, Karl-ErichIn the spring of 2020, the town of Fort McMurray, which lies on the banks of the Athabasca River, experienced an ice-jam flood event that was the most severe in approximately 60 years. In order to capture the severity of the event, a stochastic modelling approach, previously developed by the author for ice-jam flood forecasting, has been refined for ice-jam flood hazard and risk assessments and ice-jam mitigation feasibility studies, which is the subject of this paper. Scenarios of artificial breakage demonstrate the applicability of the revised modelling framework.Item Frazil ice events: Assessing what to expect in the future(IWA Publishing, 2023) Barrette, Paul; Lindenschmidt, Karl-ErichThis article addresses the question: What is expected from frazil ice activity in rivers, taking into account the changing climate? It begins with an overview of what frazil ice is and what is required for the occurrence of frazil ice events, namely a supercooled water column. Methodologies to anticipate frazil ice events in the short term are based on air temperature and water discharge, underlining the significance of these two parameters for any predictive methods. Longer-term approaches, calibrated against past events (hindcasting), are used to anticipate frazil ice activity into the future, with indicators such as frazil ice risk, water temperature and frazil volume. Any of these approaches could conceivably be applied to frazil-prone river stretches. To assess climate impact, each location should be treated separately. River ice dynamics can lead to the formation of a hanging dam, a frequent outcome of frazil ice generation in the early winter, causing flow restriction. Flood modeling and forecasting capabilities have been developed and implemented for operational use. More frequent mid-winter breakups are expected to extend the occurrence of frazil ice events into the winter months – the prediction of these will require climate model output to adequately capture month-to-month variability.Item Modelling transverse mixing of sediment and vanadium in a river impacted by oil sands mining operations(Elsevier B.V., 2022) Lindenschmidt, Karl-Erich; Sabokruhie, Pouya; Rosner, TammyStudy region: The lower Athabasca River was used as a test case using total suspended sediment, chloride and vanadium as the model variables. Upstream model boundary conditions included water from the tributary Clearwater River (right stream tube) and the upper Athabasca River extending upstream of the tributary mouth (left stream tube). This model will be extended to include the Peace-Athabasca Delta (PAD), to determine the implications of mining outfall discharges on a large region of the Athabasca – PAD region. Study focus: A novel, quasi-two-dimensional surface water-quality modelling approach is presented in which the model domain can be discretised in two dimensions, but a one-dimension solver can still be applied to capture water flow between the discretisation units (segments). The approach requires a river reach to be divided into two stream tubes, along the left and right river sides, with flows exchanging through the segments longitudinally and also laterally between adjacent segments along the two streams. New hydrological insights for the region: The new method allows the transverse mixing of tributary and outfall water of different constituent concentrations to be simulated along the course of the river. Additional diffuse loading of dissolved vanadium could be determined from the model’s substance balance. A scenario was then simulated in which the transport and fate of vanadium in a floodplain lake and a secondary channel was determined.Item Stochastic bias correction for RADARSAT-2 soil moisture retrieved over vegetated areas(Geocarto International, 2021) Lee, Ju Hyoung; Budhathoki, Sujata; Lindenschmidt, Karl-ErichSAR data provide the high-resolution images useful for monitoring environment, and natural resources. Nevertheless, it has been a great challenge to retrieve soil moisture over vegetated sites from SAR backscatter coefficients, as it is almost impossible to parameterize spatially heterogeneous and time-varying roughness, the effect of rainfall or canopy volume scattering with implicit equations. We suggest a Monte Carlo Method (MCM) as a strategy to mitigate non-linear errors in retrievals arising from rainfall, and vegetation growth. The Advanced Integral Equation Model (AIEM) is repeatedly run in a forward mode for establishing the Gaussian-distributed soil roughness and backscatter coefficients. The mean value of soil moisture ensembles inverted from those was taken as an optimal estimate. Local validations show that Root Mean Square Errors (RMSEs) were 0.05~0.07 m3/m3 at the stations in Saskatchewan, Canada. Biases were 0.01m3/m3. Spatial distribution illustrates that the retrieval biases were mitigated, resolving AIEM inversion errors.Item Surface Water Quality Modelling(MDPI, 2023) Lindenschmidt, Karl-ErichSurface water quality modelling has become an important means of better understanding aquatic and riparian ecosystem processes at all scales, from the micro-scale (e.g., bottom sediment dynamics), to the meso-scale (e.g., algal bloom growth) and the macro-scale (e.g., the role of cascading reservoirs in sediment transport). Increasingly, surface water quality models are being coupled to other models (e.g., hydrological models) to determine catchment area impacts on water quality. These impacts include future climate change and land-use developments. Coupling with water resource dynamics models also provides insight into changes in water supply and demand and flow regulation as they relate to surface water quality. Modelling the quality of surface waters under ice-covered conditions has also gained special attention due to the increased realization that a holistic all-year perspective is required to deepen our understanding of aquatic ecosystem functioning (e.g., the impact of lake ice phenology on spring succession of phytoplankton) (excerpts and adaptations from my Global Water Futures https://gwf.usask.ca/ (accessed on 16 February 2023) reporting and https://www.mdpi.com/journal/water/special_issues/surface_water (accessed on 16 February 2023) announcement).Item Water Quality and Flow Management Scenarios in the Qu’Appelle River–Reservoir System Using Loosely Coupled WASP and CE-QUAL-W2 Models(MDPI, 2023) Terry, Julie; Lindenschmidt, Karl-ErichThe water bodies of the Saskatchewan Prairies suffer multiple stressors, and demand for water is expected to increase. Water quality models can help evaluate water management strategies and risks such as climate change. This study assesses the impact of interbasin water transfers on the water quality of a strategic, eutrophic prairie reservoir that receives poor-quality watershed run-off. A one-dimensional WASP model was used to estimate nutrient transformations in the transfers along a 97 km river channel. The WASP model was then loosely coupled to a two-dimensional CE-QUAL-W2 model of the downstream receiving reservoir. Output from the WASP model was manually transformed into boundary conditions for the CE-QUAL-W2 reservoir model. This method improves on an earlier attempt to estimate nutrient transformations in the transfers using linear regression. Results from the loosely coupled models suggest Buffalo Pound Lake would respond well to the interbasin transfers. The number of threshold exceedances decreased for all modeled water quality variables. Nutrient concentrations were most influenced in the open water season following spring freshet. Any additional reduction of threshold exceedances during winter was minimal in comparison. These results are interesting from a management perspective as increased transfers under winter operations risk ice damage to the river channel.