scholarly journals Flood inundation forecasts using validation data generated with the assistance of computer vision

2018 ◽  
Vol 21 (2) ◽  
pp. 240-256 ◽  
Author(s):  
Punit Kumar Bhola ◽  
Bhavana B. Nair ◽  
Jorge Leandro ◽  
Sethuraman N. Rao ◽  
Markus Disse
Keyword(s):  
Computer Vision ◽  
Urban Areas ◽  
Water Surface ◽  
Goodness Of Fit ◽  
Water Levels ◽  
Data Sources ◽  
Flood Inundation ◽  
Validation Data ◽  
Detection Techniques ◽  
Recent Developments

Abstract Forecasting flood inundation in urban areas is challenging due to the lack of validation data. Recent developments have led to new genres of data sources, such as images and videos from smartphones and CCTV cameras. If the reference dimensions of objects, such as bridges or buildings, in images are known, the images can be used to estimate water levels using computer vision algorithms. Such algorithms employ deep learning and edge detection techniques to identify the water surface in an image, which can be used as additional validation data for forecasting inundation. In this study, a methodology is presented for flood inundation forecasting that integrates validation data generated with the assistance of computer vision. Six equifinal models are run simultaneously, one of which is selected for forecasting based on a goodness-of-fit (least error), estimated using the validation data. Collection and processing of images is done offline on a regular basis or following a flood event. The results show that the accuracy of inundation forecasting can be improved significantly using additional validation data.

Using computer vision to monitor varying water levels: an exploratory laboratory experience

2021 ◽  
Author(s):  
Jorge Isidoro ◽  
Ricardo Martins ◽  
João de Lima
Keyword(s):  
Computer Vision ◽  
Free Surface ◽  
Water Surface ◽  
Free Water ◽  
Water Levels ◽  
High Temporal Resolution ◽  
Piping System ◽  
Measuring Device ◽  
Spatial And Temporal Scales ◽  
Free Water Surface

<p>Monitoring water levels is fundamental in a variety of fields within geosciences, hydraulics, and hydrology. Examples of this can be found in the field in rivers, reservoirs, or surface runoff while, at a much lower scale, in the laboratory, e.g., open channel flow. This is an area of ​​great complexity, due to the large diversity of spatial and temporal scales of hydraulic systems and phenomena such as the non-linearity of fluid mechanics, sediment or pollutant transport, turbulence, the interactions between water and solid surfaces (natural or artificial), or atmospheric boundary conditions. The last decade has brought important advances in techniques associated with the acquisition and analysis of images, techniques encompassed in what is currently called “computer vision”.</p><p>In this work, a methodology based on image treatment and segmentation techniques was developed, which allows the detection of the free flow water surface over time in laboratory conditions using simple video equipment.</p><p>The objective of this work was to develop and validate an algorithm for detecting the free water surface with high temporal resolution. Other specific objectives were: (i) to validate the algorithm against measurements in a steady-state flow; (ii) to test the algorithm for accentuated oscillations of the free surface resulting from different bed geometries, slope, and discharge; and (iii) to assert the feasibility of the systematic use of non-specialized and inexpensive video equipment as a level measuring device, without compromising its accuracy.</p><p>All laboratory work took place at the Laboratory of Hydraulics, Water Resources and Environment of the Department of Civil Engineering of the Faculty of Sciences and Technology of the University of Coimbra. The channel has dimensions of 4.00m × 0.15m (L×W) and the slope is adjustable. Water is supplied to the channel, in a closed circuit, from a reservoir by means of a pump and piping system, and the flow controlled by a ball valve. The algorithm developed for detecting the free surface is based on the acquisition, treatment, analysis, and segmentation of images. MATLAB® was used to code functions to recognize the edges present in an image by the image intensity gradient as well as the best-defined segment present in the image, which, in this case, corresponds to the free water surface.</p>

scholarly journals Flood Inundation Assessment in the Low-Lying River Basin Considering Extreme Rainfall Impacts and Topographic Vulnerability

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 896
Author(s):  
Thanh Thu Nguyen ◽  
Makoto Nakatsugawa ◽  
Tomohito J. Yamada ◽  
Tsuyoshi Hoshino
Keyword(s):  
River Basin ◽  
Extreme Rainfall ◽  
Flood Damage ◽  
Water Levels ◽  
Flood Inundation ◽  
Inundation Area ◽  
Inundation Depth ◽  
Study Results ◽  
Inundation Duration ◽  
Short Time

This study aims to evaluate the change in flood inundation in the Chitose River basin (CRB), a tributary of the Ishikari River, considering the extreme rainfall impacts and topographic vulnerability. The changing impacts were assessed using a large-ensemble rainfall dataset with a high resolution of 5 km (d4PDF) as input data for the rainfall–runoff–inundation (RRI) model. Additionally, the prediction of time differences between the peak discharge in the Chitose River and peak water levels at the confluence point intersecting the Ishikari River were improved compared to the previous study. Results indicate that due to climatic changes, extreme river floods are expected to increase by 21–24% in the Ishikari River basin (IRB), while flood inundation is expected to be severe and higher in the CRB, with increases of 24.5, 46.5, and 13.8% for the inundation area, inundation volume, and peak inundation depth, respectively. Flood inundation is likely to occur in the CRB downstream area with a frequency of 90–100%. Additionally, the inundation duration is expected to increase by 5–10 h here. Moreover, the short time difference (0–10 h) is predicted to increase significantly in the CRB. This study provides useful information for policymakers to mitigate flood damage in vulnerable areas.

scholarly journals A Cumulative Rainfall Function for Subhourly Design Storm in Mediterranean Urban Areas

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Marco Carbone ◽  
Michele Turco ◽  
Giuseppe Brunetti ◽  
Patrizia Piro
Keyword(s):  
Urban Areas ◽  
Goodness Of Fit ◽  
Nonlinear Least Squares ◽  
Least Square ◽  
Rainfall Time Series ◽  
Storm Events ◽  
Design Storm ◽  
Double Exponential ◽  
Two Parameters ◽  
Precipitation Records

Design storms are very useful in many hydrological and hydraulic practices and are obtained from statistical analysis of precipitation records. However considering design storms, which are often quite unlike the natural rainstorms, may result in designing oversized or undersized drainage facilities. For these reasons, in this study, a two-parameter double exponential function is proposed to parameterize historical storm events. The proposed function has been assessed against the storms selected from 5-year rainfall time series with a 1-minute resolution, measured by three meteorological stations located in Calabria, Italy. In particular, a nonlinear least square optimization has been used to identify parameters. In previous studies, several evaluation methods to measure the goodness of fit have been used with excellent performances. One parameter is related to the centroid of the rain distribution; the second one is related to high values of the standard deviation of the kurtosis for the selected events. Finally, considering the similarity between the proposed function and the Gumbel function, the two parameters have been computed with the method of moments; in this case, the correlation values were lower than those computed with nonlinear least squares optimization but sufficiently accurate for designing purposes.

Denoising of river surface photogrammetric DEMs using deep learning

2021 ◽  
Author(s):  
Radosław Szostak ◽  
Przemysław Wachniew ◽  
Mirosław Zimnoch ◽  
Paweł Ćwiąkała ◽  
Edyta Puniach ◽  
...  
Keyword(s):  
Higher Education ◽  
Deep Learning ◽  
Water Level ◽  
Water Surface ◽  
Research University ◽  
Static Characteristic ◽  
Water Levels ◽  
Training Dataset ◽  
Observation Data ◽  
Characteristic Points

<p>Unmanned Aerial Vehicles (UAVs) can be an excellent tool for environmental measurements due to their ability to reach inaccessible places and fast data acquisition over large areas. In particular drones may have a potential application in hydrology, as they can be used to create photogrammetric digital elevation models (DEM) of the terrain allowing to obtain high resolution spatial distribution of water level in the river to be fed into hydrological models. Nevertheless, photogrammetric algorithms generate distortions on the DEM at the water bodies. This is due to light penetration below the water surface and the lack of static characteristic points on water surface that can be distinguished by the photogrammetric algorithm. The correction of these disturbances could be achieved by applying deep learning methods. For this purpose, it is necessary to build a training dataset containing DEMs before and after water surfaces denoising. A method has been developed to prepare such a dataset. It is divided into several stages. In the first step a photogrammetric surveys and geodetic water level measurements are performed. The second one includes generation of DEMs and orthomosaics using photogrammetric software. Finally in the last one the interpolation of the measured water levels is done to obtain a plane of the water surface and apply it to the DEMs to correct the distortion. The resulting dataset was used to train deep learning model based on convolutional neural networks. The proposed method has been validated on observation data representing part of Kocinka river catchment located in the central Poland.</p><p>This research has been partly supported by the Ministry of Science and Higher Education Project “Initiative for Excellence – Research University” and Ministry of Science and Higher Education subsidy, project no. 16.16.220.842-B02 / 16.16.150.545.</p>

scholarly journals The geometric parameters of plants on the spur dykes in a selected section of the Odra River

2018 ◽  
Vol 45 ◽  
pp. 00110
Author(s):  
Magda Hudak
Keyword(s):  
Water Surface ◽  
Flow Resistance ◽  
Water Levels ◽  
Flow Conditions ◽  
Plant Structure ◽  
Central Section ◽  
Quantitative Characteristics ◽  
Odra River ◽  
The Impact ◽  
Resistance Coefficients

Spur dykes are structures for regulating rivers. They are designed for medium water levels, when spur dyke tops are above the water surface. In the central section of the Odra River the water level is changeable, and the spur dykes work in different hydrological conditions: as non-submerged and submerged. Correct recognition of the plant structure growing on the spur dykes is of great importance in the context of the subsequent allocation of its measure related to the hydraulic action, among others coefficients of resistance of plant zones and refers mainly to grasses. In hydraulic calculations, it is required to determine the value of flow resistance coefficients. In such a departure, the flow is omitted in the area occupied by vegetation. Therefore, it is necessary to know the quantitative characteristics of overgrowth. Vegetation should be presented in the form of a model reflecting the impact of plants growing on the spur dykes and their impact on the water flow conditions in the river. Literature data are not very numerous and are still awake unsatisfied. The paper presents the results of research on the density of vegetation on the Odra River in the Nowa Sól region.

scholarly journals Observing river stages using unmanned aerial vehicles

2016 ◽  
Author(s):  
Tomasz Niedzielski ◽  
Matylda Witek ◽  
Waldemar Spallek
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Water Surface ◽  
Water Levels ◽  
Hydrodynamic Models ◽  
Surface Areas ◽  
Aerial Vehicles ◽  
Potential Applications ◽  
Sw Poland ◽  
High Flows ◽  
Student’S T

Abstract. We elaborated a new method for observing water surface areas and river stages using unmanned aerial vehicles (UAVs). It is based on processing multitemporal m orthophotomaps produced from the UAV-taken visual-light photographs of n sites of the river, acquired with a sufficient overlap in each part. Water surface areas are calculated in the first place, and subsequently expressed as fractions of total areas of water-covered terrain at a given site of the river recorded on m dates. The logarithms of the fractions are later calculated, producing m samples of size n. In order to detect statistically significant increments of water surface areas between two orthophotomaps we apply the asymptotic and bootstrapped versions of the Student's t-test, preceded by other tests that aim to check model assumptions. The procedure is applied to five orthophotomaps covering nine sites of the Ścinawka river (SW Poland). The data have been acquired during the experimental campaign, at which flight settings were kept unchanged over nearly 3 years (2012–2014). We have found that it is possible to detect transitions between water surface areas produced by all characteristic water levels (low, mean, intermediate and high stages). In addition, we infer that the identified transitions hold for characteristic river stages as well. In the experiment we detected all increments of water level: (1) from low stages to: mean, intermediate and high stages; (2) from mean stages to: intermediate and high stages; (3) from intermediate stages to high stages. Potential applications of the elaborated method include verification of hydrodynamic models and the associated predictions of high flows using on-demand UAV flights performed in near real-time as well as monitoring water levels of rivers in ungauged basins.

Highway Freight Flow Assignment in Massachusetts Using Geographic Information Systems

1998 ◽  
Vol 1625 (1) ◽  
pp. 156-164 ◽  
Author(s):  
Venkatesh Krishnan ◽  
Kathleen L. Hancock
Keyword(s):  
Urban Areas ◽  
Economic Indicator ◽  
Data Sources ◽  
Flow Data ◽  
Indicator Variable ◽  
Commodity Flow ◽  
Goods Movement ◽  
Flow Assignment ◽  
Freight Flow ◽  
Quantitative Procedure

Goods movement is an important aspect of the transportation system. Freight flow, complemented with the much-researched passenger movement, provides a way for understanding the complete vehicle flow scenario on the highways. Commodity movement prediction has not received much attention because of the lack of sufficient and easily accessible data sources. Most data sources give aggregated commodity movements and, because of the heterogeneity of freight, accurate predictions of truck flows have not been possible. A methodology for calculating the truck flows on the various highways in Massachusetts from interstate commodity flow data is presented. Freight tons originating and ending in Massachusetts have been converted to truck numbers by using a quantitative procedure and distributed to different areas in the state by using employment as an economic indicator variable. The truck flow is assigned to the important highways and validated against existing survey counts. On comparison, a large percentage of the roads show the estimated truck counts are within a tolerable error margin. The research also shows that statewide analyses need to be refined near urban areas because of a variety of complexities involved.

scholarly journals Measuring Education and Skill

2014 ◽  
Vol 657 (1) ◽  
pp. 136-148 ◽  
Author(s):  
Chandra Muller
Keyword(s):  
Social Mobility ◽  
Data Sources ◽  
Half Century ◽  
Administrative Records ◽  
The Past ◽  
Past Half Century ◽  
Recent Developments ◽  
Testing Practices ◽  
Assessment And Testing ◽  
Past Half

This article reviews recent developments in measuring education and skill that need to be taken into account in any new initiative to monitor social mobility. Over the past half-century, patterns of educational participation and attainment have become more heterogeneous, a trend that has been accompanied by increases in assessment and testing practices, and the availability of electronic data sources and other administrative records, including official school transcripts that are generally held indefinitely. This article describes the most promising approaches to measuring education and discusses some of the possible challenges for using the information to study social mobility. Measures of educational concepts fall along at least one of several dimensions: credentials earned, qualities of the schools attended, the amount and nature of curricular exposure, and the development and acquisition of skills. Selected data sources, with an emphasis on school transcripts and administrative records, and their possible uses are described.

Assimilation of inundation extent observations into a flood forecasting system:  a tempered particle filter for combatting degeneracy and sample impoverishment.

2021 ◽  
Author(s):  
Concetta Di Mauro ◽  
Renaud Hostache ◽  
Patrick Matgen ◽  
Peter Jan van Leeuwen ◽  
Nancy Nichols ◽  
...  
Keyword(s):  
Particle Filter ◽  
Main Idea ◽  
Water Levels ◽  
Smooth Transition ◽  
Observation Data ◽  
Flood Inundation ◽  
State Variables ◽  
Time Step ◽  
Radar Images ◽  
Forecasting System

<p>Data assimilation uses observation for updating model variables and improving model output accuracy. In this study, flood extent information derived from Earth Observation data (namely Synthetic Aperture Radar images) are assimilated into a loosely coupled flood inundation forecasting system via a Particle Filter (PF). A previous study based on a synthetic experiment has shown the validity and efficiency of a recently developed PF-based assimilation framework allowing to effectively integrate remote sensing-derived probabilistic flood inundation maps into a coupled hydrologic-hydraulic model. One of the main limitations of this recent framework based on sequential importance sampling is the sample degeneracy and impoverishment, as particles loose diversity and only few of them keep a substantial importance weight in the posterior distribution. In order to circumvent this limitation, a new methodology is adopted and evaluated: a tempered particle filter. The main idea is to update a set of state variables, namely through a smooth transition (iterative and adaptative process). To do so, the likelihood is factorized using small tempering factors. Each iteration includes subsequent resampling and mutation steps using a Monte Carlo Metropolis Hasting algorithm. The mutation step is required to regain diversity between the particles after the resampling. The new methodology is tested using synthetic twin experiments and the results are compared to the one obtained with the previous approach. The new proposed method enables to substantially improve the predictions of streamflow and water levels within the hydraulic domain at the assimilation time step. Moreover, the preliminary results show that these improvements are longer lasting. The proposed tempered particle filter also helps in keeping more diversity within the ensemble.</p>

Sign in / Sign up

Export Citation Format

Share Document