scholarly journals Integrating a 2D Hydraulic Model and GIS Algorithms into a Data Assimilation Framework for Real Time Flood Forecasting and Mapping

10.29007/29nd ◽  
2018 ◽  
Author(s):  
Antonio Annis ◽  
Noemi Gonzalez-Ramirez ◽  
Fernando Nardi ◽  
Fabio Castelli
Keyword(s):  
Data Assimilation ◽  
Water Level ◽  
Real Time ◽  
Satellite Images ◽  
Early Warning Systems ◽  
Hydraulic Model ◽  
Water Levels ◽  
Data Types ◽  
Flow Measurements ◽  
The Impact

The intensification of flood-related damages and fatalities is challenging Early Warning Systems (EWS) to always better perform in predicting flood levels allowing decision makers to take the most effective decisions for mitigating the impact of extreme events. EWS require hydrologic and hydraulic modelling that are usually affected by uncertainties that can be extremely significant in data scarce regions. This work presents the implementation and application of a Data Assimilation (DA) framework, based on the Ensemble Kalman Filter, integrating the hydraulic model FLO-2D and geospatial algorithms for data post-processing and mapping. The hydraulic model is forced by both flow gages and simulated flow data produced by a simplified GIS-based hydrologic modelling for flood wave analysis tailored for small ungauged basins. The hydraulic code is adapted to assimilate different observation data types: flow measurements taken along the channel, water level observations captured within the floodplain, such as water signs on vegetation and buildings pictures by human sensors, and inundation extents obtained by processing satellite images. This DA framework required the development of significant novelties for incorporating the 2D hydraulic model and for integrating the different types of measurements considering the heterogeneous specifications and uncertainty of the various assimilated data types. Advanced GIS algorithms are implemented for improving the real time flood mapping taking advantage of the distributed output provided by the 2D inundation model. Results show improved model performances in terms of water level simulations and reduced uncertainties. The integrated hydraulic and geospatial modelling allows to empower the water levels correction on the flood extension prediction. Additionally, the capability of using the different available observations, from satellite images to crowdsourced data, is promising for the development of a flexible and scalable flood EWS model overcoming the limitations of standard DA working generally with 1D hydraulic models and traditional sensors.

scholarly journals Simultaneous assimilation of water levels from river gauges and satellite flood maps for near-real time flood mapping

2021 ◽  
Author(s):  
Antonio Annis ◽  
Fernando Nardi ◽  
Fabio Castelli
Keyword(s):  
Data Assimilation ◽  
Real Time ◽  
River Flow ◽  
Central Italy ◽  
Early Warning Systems ◽  
Water Levels ◽  
State Variables ◽  
Ungauged Catchments ◽  
Flood Prediction ◽  
Modelling Approach

Abstract. Hydro-meteo hazard Early Warning Systems (EWSs) are operating in many regions of the world to mitigate nuisance effects of floods. EWSs performances are majorly impacted by the computational burden and complexity affecting flood prediction tools, especially for ungauged catchments that lack adequate river flow gauging stations. Earth Observation (EO) systems may surrogate to the lack of fluvial monitoring systems supporting the setting up of affordable EWSs. But, EO data, constrained by spatial and temporal resolution limitations, are not sufficient alone, especially at medium-small scales. Multiple sources of distributed flood observations need to be used for managing uncertainties of flood models, but this is not a trivial task for EWSs. In this work, a near real-time flood modelling approach is developed and tested for the simultaneous assimilation of both water level observations and EO-derived flood extents. An integrated physically-based flood wave generation and propagation modelling approach, that implements a Ensemble Kalman Filter, a parsimonious geomorphic rainfall-runoff algorithm (WFIUH) and a Quasi-2D hydraulic algorithm, is proposed. A data assimilation scheme is tested that retrieves distributed observed water depths from satellite images to update 2D hydraulic modelling state variables. Performances of the proposed approach are tested on a flood event for the Tiber river basin in central Italy. The selected case study shows varying performances depending if local and distributed observations are separately or simultaneously assimilated. Results suggest that the injection of multiple data sources into a flexible data assimilation framework, constitute an effective and viable advancement for flood mitigation tackling EWSs data scarcity, uncertainty and numerical stability issues.

scholarly journals Flood Routing Model with Particle Filter-Based Data Assimilation for Flash Flood Forecasting in the Micro-Model of Lower Yellow River, China

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1612 ◽  
Author(s):  
Minghong Chen ◽  
Juanjuan Pang ◽  
Pengxiang Wu
Keyword(s):  
Data Assimilation ◽  
Water Level ◽  
Real Time ◽  
Hydrodynamic Model ◽  
Yellow River ◽  
Flood Forecasting ◽  
Water Levels ◽  
Flood Routing ◽  
Micro Model ◽  
Assimilation Model

Reliable real-time flood forecasting is a challenging prerequisite for successful flood protection. This study developed a flood routing model combined with a particle filter-based assimilation model and a one-dimensional hydrodynamic model. This model was applied to an indoor micro-model, using the Lower Yellow River (LYR) as prototype. Real-time observations of the water level from the micro-model were used for data assimilation. The results show that, compared to the traditional hydrodynamic model, the assimilation model could effectively update water level, flow discharge, and roughness coefficient in real time, thus yielding improved results. The mean water levels of the particle posterior distribution are closer to the observed values than before assimilation, even when water levels change greatly. In addition, the calculation results for different lead times indicate that the root mean square error of the forecasting water level gradually increases with increasing lead time. This is because the roughness value changes greatly in response to unsteady water flow, and the incurring error accumulates with the predicted period. The results show that the assimilation model can simulate water level changes in the micro-model and provide both research method and technical support for real flood forecasting in the LYR.

AUTOMATIC WATER LEVEL MONITORING WITH IOT AND LPWAN

2019 ◽  
pp. 95-103
Author(s):  
Krum Videnov ◽  
Vanya Stoykova
Keyword(s):  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Water Sources ◽  
Water Levels ◽  
Water Level Fluctuations ◽  
Level Monitoring ◽  
Water Level Monitoring

Monitoring water levels of lakes, streams, rivers and other water basins is of essential importance and is a popular measurement for a number of different industries and organisations. Remote water level monitoring helps to provide an early warning feature by sending advance alerts when the water level is increased (reaches a certain threshold). The purpose of this report is to present an affordable solution for measuring water levels in water sources using IoT and LPWAN. The assembled system enables recording of water level fluctuations in real time and storing the collected data on a remote database through LoRaWAN for further processing and analysis.

Quantifying recent lake level changes in Patagonia (Argentina and Chile): Back to the future?

2021 ◽  
Author(s):  
Daniel Ariztegui ◽  
Clément Pollier ◽  
Andrés Bilmes
Keyword(s):  
Water Level ◽  
Lake Level ◽  
Satellite Images ◽  
Meteorological Data ◽  
Tierra Del Fuego ◽  
Water Level Fluctuations ◽  
Lake Levels ◽  
The Past ◽  
Rainfall Variations ◽  
The Impact

<p>Lake levels in hydrologically closed-basins are very sensitive to climatically and/or anthropogenically triggered environmental changes. Their record through time can provide valuable information to forecast changes that can have substantial economical and societal impact.</p><p>Increasing precipitation in eastern Patagonia (Argentina) have been documented following years with strong El Niño (cold) events using historical and meteorological data. Quantifying changes in modern lake levels allow determining the impact of rainfall variations while contributing to anticipate the evolution of lacustrine systems over the next decades with expected fluctuations in ENSO frequencies. Laguna Carrilaufquen Grande is located in the intermontane Maquinchao Basin, Argentina. Its dimension fluctuates greatly, from 20 to 55 km<sup>2</sup> water surface area and an average water depth of 3 m. Several well-preserved gravelly beach ridges witness rainfall variations that can be compared to meteorological data and satellite images covering the last ~50 years. Our results show that in 2016 lake level was the lowest of the past 44 years whereas the maximum lake level was recorded in 1985 (+11.8 m above the current lake level) in a position 1.6 km to the east of the present shoreline. A five-years moving average rainfall record of the area was calculated smoothing the extreme annual events and correlated to the determined lake level fluctuations. The annual variation of lake levels was up to 1.2 m (e.g. 2014) whereas decadal variations related to humid-arid periods for the interval 2002 to 2016 were up to 9.4 m. These data are consistent with those from other monitored lakes and, thus, our approach opens up new perspectives to understand the historical water level fluctuations of lakes with non-available monitoring data.</p><p> </p><p>Laguna de los Cisnes in the Chilean section of the island of Tierra del Fuego, is a closed-lake presently divided into two sections of 2.2 and 11.9 km<sup>2</sup>, respectively. These two water bodies were united in the past forming a single larger lake. The lake level was  ca. 4 m higher than today as shown by clear shorelines and the outcropping of large Ca-rich microbialites. Historical data, aerial photographs and satellite images indicate that the most recent changes in lake level are the result of a massive decrease of water input during the last half of the 20<sup>th</sup> century triggered by an indiscriminate use of the incoming water for agricultural purposes. The spectacular outcropping of living and fossil microbialites is not only interesting from a scientific point of view but has also initiated the development of the site as a local touristic attraction. However, if the use of the incoming water for agriculture in the catchment remains unregulated the lake water level might drop dangerously and eventually the lake might fully desiccate.</p><p>These two examples illustrate how recent changes in lake level can be used to anticipate the near future of lakes. They show that ongoing climate changes along with the growing demand of natural resources have already started to impact lacustrine systems and this is likely to increase in the decades to come.</p>

scholarly journals Determining Extreme Still Water Levels for Design and Planning Purposes Incorporating Sea Level Rise: Sydney, Australia

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Phil J. Watson
Keyword(s):  
Sea Level Rise ◽  
Water Level ◽  
Sea Level ◽  
Tide Gauge ◽  
Water Levels ◽  
Extreme Value Analysis ◽  
Tide Gauge Record ◽  
Value Analysis ◽  
Mean Sea Level ◽  
The Impact

This paper provides an Extreme Value Analysis (EVA) of the hourly water level record at Fort Denison dating back to 1915 to understand the statistical likelihood of the combination of high predicted tides and the more dynamic influences that can drive ocean water levels higher at the coast. The analysis is based on the Peaks-Over-Threshold (POT) method using a fitted Generalised Pareto Distribution (GPD) function to estimate extreme hourly heights above mean sea level. The analysis highlights the impact of the 1974 East Coast Low event and rarity of the associated measured water level above mean sea level at Sydney, with an estimated return period exceeding 1000 years. Extreme hourly predictions are integrated with future projections of sea level rise to provide estimates of relevant still water levels at 2050, 2070 and 2100 for a range of return periods (1 to 1000 years) for use in coastal zone management, design, and sea level rise adaptation planning along the NSW coastline. The analytical procedures described provide a step-by-step guide for practitioners on how to develop similar baseline information from any long tide gauge record and the associated limitations and key sensitivities that must be understood and appreciated in applying EVA.

scholarly journals The Role of Mean Sea Level Annual Cycle on Extreme Water Levels Along European Coastline

2020 ◽  
Vol 12 (20) ◽  
pp. 3419
Author(s):  
Tomás Fernández-Montblanc ◽  
Jesús Gómez-Enri ◽  
Paolo Ciavola
Keyword(s):  
Water Level ◽  
Sea Level ◽  
North Sea ◽  
Extreme Events ◽  
Annual Cycle ◽  
Coastal Flooding ◽  
Water Levels ◽  
Total Water ◽  
Mean Sea Level ◽  
The Impact

The knowledge of extreme total water levels (ETWLs) and the derived impact, coastal flooding and erosion, is crucial to face the present and future challenges exacerbated in European densely populated coastal areas. Based on 24 years (1993–2016) of multimission radar altimetry, this paper investigates the contribution of each water level component: tide, surge and annual cycle of monthly mean sea level (MMSL) to the ETWLs. It focuses on the contribution of the annual variation of MMSL in the coastal flooding extreme events registered in a European database. In microtidal areas (Black, Baltic and Mediterranean Sea), the MMSL contribution is mostly larger than tide, and it can be at the same order of magnitude of the surge. In meso and macrotidal areas, the MMSL contribution is <20% of the total water level, but larger (>30%) in the North Sea. No correlation was observed between the average annual cycle of monthly mean sea level (AMMSL) and coastal flooding extreme events (CFEEs) along the European coastal line. Positive correlations of the component variance of MMSL with the relative frequency of CFEEs extend to the Central Mediterranean (r = 0.59), North Sea (r = 0.60) and Baltic Sea (r = 0.75). In the case of positive MMSL anomalies, the correlation expands to the Bay of Biscay and northern North Atlantic (at >90% of statistical significance). The understanding of the spatial and temporal patterns of a combination of all the components of the ETWLs shall improve the preparedness and coastal adaptation measures to reduce the impact of coastal flooding.

Explicit Finite Element Study of Liquid Sloshing Behavior in Fluid-Structure Interaction Condition

2017 ◽  
Author(s):  
Shuo Yang ◽  
Raymond K. Yee
Keyword(s):  
Finite Element ◽  
Water Level ◽  
Similarity Theory ◽  
Fluid Structure Interaction ◽  
Water Levels ◽  
Tank Wall ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Sloshing Phenomenon ◽  
The Impact

As a common phenomenon in liquid motions, sloshing usually happens in a partially filled liquid tank of moving vehicle or structure. The objectives of this paper are to study sloshing behavior in rigid tank and deformable tank, and to develop a better performance baffle design in the tank under seismic excitations. The tank is surged with a sinusoidal oscillation about horizontal x-direction. The hydro-elasticity effect of sloshing pressure on the tank wall was taken into consideration due to the fluid-structure interaction between impact pressures and tank structures. ABAQUS finite element program using Coupled Eulerian-Lagrangian (CEL) technique was employed to simulate fluid sloshing. The sloshing phenomenon was studied in rigid tank and deformable tank models with three different water levels, and the effect of wall thickness of the deformable tank on sloshing behavior was discussed. One way to minimize the effect of sloshing in a tank, baffles are used and installed in the middle of the tank, and then various heights and material types of baffle were evaluated. The simulation results show that higher water level case creates greater pressure impact on the tank wall than lower water level case, and the elasticity of the tank structure would reduce the impact pressure of the wall. For the simulation tank model with size of 1m (H) × 1m (W) × 0.2m (D), better performance baffle was found to be the one with the height of 0.35m and was made of acrylic material. Moreover, the conclusion of this study can be extrapolated to other dimensions of the model based on similarity theory. This paper also can serve as an aid in further studying sloshing phenomenon. The findings of this study can be applied to restrain or minimize sloshing motions inside a tank.

scholarly journals Advancing from Convection-Allowing NWP to Warn-on-Forecast: Evidence of Progress

2018 ◽  
Vol 33 (2) ◽  
pp. 599-607 ◽  
Author(s):  
John R. Lawson ◽  
John S. Kain ◽  
Nusrat Yussouf ◽  
David C. Dowell ◽  
Dustan M. Wheatley ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Real Time ◽  
Initial Conditions ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Radar Data ◽  
Model Systems ◽  
Deterministic Systems ◽  
Forecast Lead Time ◽  
The Impact

Abstract The Warn-on-Forecast (WoF) program, driven by advanced data assimilation and ensemble design of numerical weather prediction (NWP) systems, seeks to advance 0–3-h NWP to aid National Weather Service warnings for thunderstorm-induced hazards. An early prototype of the WoF prediction system is the National Severe Storms Laboratory (NSSL) Experimental WoF System for ensembles (NEWSe), which comprises 36 ensemble members with varied initial conditions and parameterization suites. In the present study, real-time 3-h quantitative precipitation forecasts (QPFs) during spring 2016 from NEWSe members are compared against those from two real-time deterministic systems: the operational High Resolution Rapid Refresh (HRRR, version 1) and an upgraded, experimental configuration of the HRRR. All three model systems were run at 3-km horizontal grid spacing and differ in initialization, particularly in the radar data assimilation methods. It is the impact of this difference that is evaluated herein using both traditional and scale-aware verification schemes. NEWSe, evaluated deterministically for each member, shows marked improvement over the two HRRR versions for 0–3-h QPFs, especially at higher thresholds and smaller spatial scales. This improvement diminishes with forecast lead time. The experimental HRRR model, which became operational as HRRR version 2 in August 2016, also provides added skill over HRRR version 1.

scholarly journals Monitoring Temporal Change of River Islands in the Yangtze River by Remotely Sensed Data

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1484 ◽  
Author(s):  
Jinyan Sun ◽  
Lei Ding ◽  
Jiaze Li ◽  
Haiming Qian ◽  
Mengting Huang ◽  
...  
Keyword(s):  
Water Level ◽  
Yangtze River ◽  
Temporal Change ◽  
Flood Disaster ◽  
Water Levels ◽  
Sediment Supply ◽  
The Yangtze River ◽  
Flood Warning ◽  
River Islands ◽  
The Impact

The spatial extent and area of river islands are always changing due to the impact of hydrodynamic conditions, sediment supply and human activities. A catastrophic flood disaster was driven by sustained and heavy rainfall around the middle and lower Yangtze River in 18 June to 21 July 2016. The flood resulted in the most serious social-economic loss since 1954 and caused a larger-scale inundation for a short time. It is essential to continuously monitor the dynamics changes of river islands because this can avoid frequent field measurements in river islands before and after flood disasters, which are helpful for flood warning. This paper focuses on the temporal change of three river islands called Fenghuangzhou, Changshazhou, and one uninhabited island in the Yangtze River in 2016. In this study, GF-1 (GaoFen-1) WFV (wide field view) data was used for our study owing to its fine spatial and temporal resolution. A simple NDWI (Normalized Difference Water Index) method was used for the river island mapping. Human checking was then performed to ensure mapping accuracy. We estimated the relationship between the area of river islands and measured water levels using four models. Furthermore, we mapped the spatial pattern of inundation risk of river islands. The results indicate a good ability of the GF-1 WFV data with a 16-m spatial resolution to characterize the variation of river islands and to study the association between flood disaster and river islands. A significantly negative but nonlinear relationship between the water level and the area of the river island was observed. We also found that the cubic function fits best among three models (R2 > 0.8, P < 0.001). The maximum of the inundated area at the river island appeared in the rainy season on 8 July 2016 and the minimum occurred in the dry season on 28 December 2016, which is consistent with the water level measured by the hydrological station. Our results derived from GF-1 data can provide a useful reference for decision-making of flood warning, disaster assessment, and post-disaster reconstruction.

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