scholarly journals Improving real-time operational streamflow simulations using discharge data to update state variables of a distributed hydrological model

2021 ◽  
Author(s):  
Francesco Silvestro ◽  
Giulia Ercolani ◽  
Simone Gabellani ◽  
Pietro Giordano ◽  
Marco Falzacappa
Keyword(s):  
Water Level ◽  
Real Time ◽  
Large Scale ◽  
Root Zone ◽  
Time Window ◽  
Distributed Model ◽  
Level Gauge ◽  
State Variables ◽  
Model Errors ◽  
Discharge Data

Abstract Reducing errors in streamflow simulations is one of the main issues for a reliable forecast system aimed to manage floods and water resources. Data assimilation is a powerful tool to reduce model errors. Unfortunately, its use in operational chains with distributed and physically based models is a challenging issue since many methodologies require computational times that are hardly compatible with operational needs. The implemented methodology corrects modelled water level in channels and root-zone soil moisture using real-time water level gauge stations. Model's variables are corrected locally, then the updates are propagated upstream with a simple approach that accounts for sub-basins’ contributions. The overfitting issue, which arises when updating a spatially distributed model with sparse streamflow data, is hence here addressed in the context of a large-scale operational implementation working in real time thanks to the simplicity of the strategy. To test the method, a hindcast of daily simulations covering 18 months was performed on the Italian Tevere basin, and the modelling results with and without assimilation were compared. The setup was that currently in place in the operational framework in both cases. The analysis evidences a clear overall benefit of applying the proposed method even out of the assimilation time window.

scholarly journals Early warning flood detector adopting camera by Sobel Canny edge detection algorithm method

2021 ◽  
Vol 22 (3) ◽  
pp. 1796
Author(s):  
Satryo B. Utomo ◽  
Januar Fery Irawan ◽  
Rizqi Renafasih Alinra
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Detection System ◽  
Water Levels ◽  
Level Gauge ◽  
Canny Edge Detection ◽  
Canny Edge

Early warning of floods is an essential part of disaster management. Various automatic detectors have been developed in flood mitigation, including cameras. But reliability and accuracy have not been improved. Besides, the use of monitoring devices has been employed to monitor water levels in various water building facilities. The early warning flood detector was carried out with a sensor camera using an orange ball that floats near the water level gauge in a bounding box. This approach uses the integration of computer vision and image processing, namely digital image processing techniques, with Sobel Canny edge detection (SCED) algorithms to detect quickly and accurately water levels in real-time. After the water level is measured, a flood detection process is carried out based on the specified water level. According to the results of experiments in the laboratory, it has been shown that the proposed approach can detect objects accurately and fast in real-time. Besides, from the water level detection experiment, good results were obtained. Therefore, the object detection system and water level can be used as an efficient and accurate early detection system for flood disasters.

Measuring Flood Discharge

2017 ◽  
Author(s):  
Marian Muste ◽  
Ton Hoitink
Keyword(s):  
Real Time ◽  
Water Resource Management ◽  
Large Scale ◽  
Water Cycle ◽  
Ground Truth ◽  
Flood Frequency ◽  
Main Concern ◽  
Essential Difference ◽  
Discharge Data ◽  
Ground Truth Data

With a continuous global increase in flood frequency and intensity, there is an immediate need for new science-based solutions for flood mitigation, resilience, and adaptation that can be quickly deployed in any flood-prone area. An integral part of these solutions is the availability of river discharge measurements delivered in real time with high spatiotemporal density and over large-scale areas. Stream stages and the associated discharges are the most perceivable variables of the water cycle and the ones that eventually determine the levels of hazard during floods. Consequently, the availability of discharge records (a.k.a. streamflows) is paramount for flood-risk management because they provide actionable information for organizing the activities before, during, and after floods, and they supply the data for planning and designing floodplain infrastructure. Moreover, the discharge records represent the ground-truth data for developing and continuously improving the accuracy of the hydrologic models used for forecasting streamflows. Acquiring discharge data for streams is critically important not only for flood forecasting and monitoring but also for many other practical uses, such as monitoring water abstractions for supporting decisions in various socioeconomic activities (from agriculture to industry, transportation, and recreation) and for ensuring healthy ecological flows. All these activities require knowledge of past, current, and future flows in rivers and streams. Given its importance, an ability to measure the flow in channels has preoccupied water users for millennia. Starting with the simplest volumetric methods to estimate flows, the measurement of discharge has evolved through continued innovation to sophisticated methods so that today we can continuously acquire and communicate the data in real time. There is no essential difference between the instruments and methods used to acquire streamflow data during normal conditions versus during floods. The measurements during floods are, however, complex, hazardous, and of limited accuracy compared with those acquired during normal flows. The essential differences in the configuration and operation of the instruments and methods for discharge estimation stem from the type of measurements they acquire—that is, discrete and autonomous measurements (i.e., measurements that can be taken any time any place) and those acquired continuously (i.e., estimates based on indirect methods developed for fixed locations). Regardless of the measurement situation and approach, the main concern of the data providers for flooding (as well as for other areas of water resource management) is the timely delivery of accurate discharge data at flood-prone locations across river basins.

Synthetic Satellite Imagery for Real-Time High-Resolution Model Evaluation

2012 ◽  
Vol 27 (3) ◽  
pp. 784-795 ◽  
Author(s):  
Dan Bikos ◽  
Daniel T. Lindsey ◽  
Jason Otkin ◽  
Justin Sieglaff ◽  
Louie Grasso ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Satellite Imagery ◽  
Large Scale ◽  
Subsequent Development ◽  
Model Errors ◽  
Convective Storms ◽  
Storm Evolution ◽  
Resolution Model ◽  
Convective Weather

Abstract Output from a real-time high-resolution numerical model is used to generate synthetic infrared satellite imagery. It is shown that this imagery helps to characterize model-simulated large-scale precursors to the formation of deep-convective storms as well as the subsequent development of storm systems. A strategy for using this imagery in the forecasting of severe convective weather is presented. This strategy involves comparing model-simulated precursors to their observed counterparts to help anticipate model errors in the timing and location of storm formation, while using the simulated storm evolution as guidance.

scholarly journals Adaptive Use of a Conceptual Model for Real Time Flood Forecasting

1997 ◽  
Vol 28 (3) ◽  
pp. 169-188 ◽  
Author(s):  
D. Da Ros ◽  
M. Borga
Keyword(s):  
Real Time ◽  
Initial Conditions ◽  
Flood Forecasting ◽  
Distributed Model ◽  
State Variables ◽  
Rainfall Runoff ◽  
Adaptive Use ◽  
On Line ◽  
Rainfall Runoff Model ◽  
Runoff Model

This paper investigates the adaptive use of a simple conceptual lumped rainfall-runoff model based on a Probability Distributed Model complemented with a Geomorphological Unit Hydrograph. Three different approaches for updating the model and for its use for real time flood forecasting are compared: the first two are based on a parameter updating approach; in the third procedure the model is cast into a state-space form and an Extended Kalman Filter is applied for the on-line estimation of the state variables. The comparison shows that the procedure based on the filtering techniques provides more reliable results; acceptable results are also obtained by using a parameter updating approach based on the on-line adjustment of the initial conditions.

scholarly journals Stochastic generation of spatially coherent river discharge peaks for large-scale, event-based flood risk assessment

2018 ◽  
Author(s):  
Dirk Diederen ◽  
Ye Liu ◽  
Ben Gouldby ◽  
Ferdinand Diermanse ◽  
Sergiy Vorogushyn
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
River Discharge ◽  
Large Scale ◽  
Time Window ◽  
Insurance Industry ◽  
Flood Risk Assessment ◽  
Data Set ◽  
Discharge Data ◽  
Short Time Window

Abstract. Flood risk assessments are required for long-term planning, e.g. for investments in infrastructure and other urban capital. Vorogushyn et al. (2018) call for new methods in large-scale Flood Risk Assessment (FRA) to enable the capturing of system interactions and feedbacks. With the increase of computational power, large-scale, continental FRAs have recently become feasible (Ward et al., 2013; Alfieri et al., 2014; Dottori et al., 2016; Vousdoukas, 2016; Winsemius et al., 2016; Paprotny et al., 2017). Flood events cause large damages worldwide (Desai et al., 2015). Moreover, widespread flooding can potentially cause large damage in a short time window. Therefore, large-scale (e.g. pan-European) events and for instance maximum probable damages are of interest, in particular for the (re)insurance industry, because they want to know the chance of their widespread portfolio of assets getting affected by large-scale events (Jongman et al., 2014). Using a pan-European data set of modelled, gridded river discharge data, we tracked discharge waves in all major European river basins. We synthetically generated a large catalogue of synthetic, pan-European events, consisting of spatially coherent discharge peak sets.

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.

Methods for the Quantification of Salivary Cortisol and of a-amylase in Biosensors and Portable Devices

2018 ◽  
Vol 68 (12) ◽  
pp. 2857-2859
Author(s):  
Cristina Mihaela Ghiciuc ◽  
Andreea Silvana Szalontay ◽  
Luminita Radulescu ◽  
Sebastian Cozma ◽  
Catalina Elena Lupusoru ◽  
...  
Keyword(s):  
Real Time ◽  
Medical Practice ◽  
Salivary Cortisol ◽  
Clinical Studies ◽  
Large Scale ◽  
Psychological Research ◽  
Portable Devices ◽  
Salivary Amylase ◽  
Specificity And Sensitivity

There is an increasing interest in the analysis of salivary biomarkers for medical practice. The objective of this article was to identify the specificity and sensitivity of quantification methods used in biosensors or portable devices for the determination of salivary cortisol and salivary a-amylase. There are no biosensors and portable devices for salivary amylase and cortisol that are used on a large scale in clinical studies. These devices would be useful in assessing more real-time psychological research in the future.

Use of artificial wetland for the treatment of surface and wastewater

1996 ◽  
Vol 33 (4-5) ◽  
pp. 309-313
Author(s):  
Jan Šálek ◽  
František Marcián ◽  
Iman Elazizy
Keyword(s):  
Water Level ◽  
Root Zone ◽  
Artificial Wetland ◽  
Root Zones ◽  
Different Types ◽  
Water Media ◽  
Inlet Zone

Vegetative root zone methods are based on self-purifying processes that take place in the soil, wetland and vegetation containing water media. Our studies are concentrated on the course of puryfying in relation with the length of the filtration bed and on the progress of eliminating the ammoniacal pollution. The research proved that the essential part of the puryfying process takes place within the inlet zone (Figs 1 and 2). The decomposition of ammonia proceeds very slowly. The process of nitrification is affected by the lack of oxygen in the filtration media. To improve the effectiveness of vegetative root zone methods we suggest specific steps: an adjustment of the inlet zone, a system of cascades, a water level pulsation system and combinations of different types and arrangements of vegetative root zones.

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