Estimate Water Discharge Research Articles

Using remote sensing technology in estimating flood discharge

Floods are the most natural disasters occurring on earth. Recently, Egypt has been subjected to more frequent floods due to climate change. The main objective of this paper is creating hydrological analysis and estimating water discharge due to a flood hitting a hazardous zone near Safaga city. The research is divided into four main stages; 1) Morphological study, 2) Meteorological study, 3) Losses estimation, and 4) Flood discharge estimation. First, morphological study in which watershed boundaries, main streams and morphological data are delineated using geographic information system (GIS) with the aid of Landsat-8 satellite images and 30-m resolution digital elevation model (DEM). Second, meteorological study in which conventional rainfall frequency analysis is generated to estimate rainfall depth at different return periods using 15-years rainfall historical data from weather stations. Third, losses estimation is determined by using soil conservation service-curve number method (SCS-CN). Fourth, water discharge volume is carried out through hydrological modelling using a hydrologic engineering centre model. The estimated water volume is an appropriate information for decision makers to propose the adequate protection works to mitigate flood impacts.

Discharge estimation using brink depth over a trapezoidal-shaped weir

A weir is an accurate hydraulic structure for estimating water discharge in open channels and rivers. It can be constructed with a standard shape with vertical upstream and downstream faces or it can be modified by inclining one or both weir faces to enhance its hydraulic characteristics. In this study, the feasibility of using the brink depth over a trapezoidal-shaped weir (yb) for discharge estimation was experimentally investigated for free flow conditions. The experimental work involved the use of three lengths of the weir crest, L (10, 20, and 30) cm, and four different slopes (37°, 54°, 75°, and 90°) for both upstream and downstream faces, each with different water discharge. In addition, the effect of channel bed slopes on the water head over the weir (h) and the brink depth (yb) was investigated. The results indicated that the (yb) can be used for discharge estimation with good accuracy for a trapezoidal-shaped weir instead of water head over the weir (h), which is usually used in estimating water over the weir, as (yb) does not affect by the channel bed slope and insignificantly affected by changing the upstream and/or downstream face angle, contrary to the (h). Hence, an empirical equation for estimating water discharge based on (yb) with different upstream and downstream slopes was developed and examined using some available previous studies data. The mean absolute percentage error (MAPE) between (yc/L) with (yb/L) and between the measured and estimated discharge is 4.73% and 7.02%, respectively.

Filling data gaps using citizen science for flood modeling in urbanized catchment of Akaki

Identifying and understanding the value of citizen science to improve flood modeling is of importance to flood risk management. However, there are few studies that explore the value of citizen science data, with most studies focusing on evaluating the accuracy of the data. This research articulates the added value of citizen science data in flood modeling studies. During flood events, citizen scientists measured river water levels at selected sites along a main reach of the Big Akaki River in Addis Ababa, Ethiopia. They also provided information to estimate water discharge of the ungauged tributaries. The data acquired was used to force a one-dimensional (1D) HECRAS flood model, and to evaluate the model's sensitivity to inputs and parameters. Varying the downstream boundary condition caused a significant difference in the simulated water level (up to 3.5 ​km upstream of the downstream boundary site). Correcting the Digital Elevation Model and consideration of river tributary flows in the model simulation resulted in an underestimation of the observed stage by 0.08 ​m. The sensitivity analysis also showed that results were more sensitive to the Manning roughness values of the channel than that of the floodplain. Finally, this study identifies future flood modeling data collection priorities (e.g. flow data for the tributary). The flood modeling of the study area would not have been realized without the citizen science data.

Remote Sensing of Sediment Discharge in Rivers Using Sentinel-2 Images and Machine-Learning Algorithms

The spatio-temporal dynamism of sediment discharge (Qs) in rivers is influenced by various natural and anthropogenic factors. Unfortunately, most rivers are only monitored at a limited number of stations or not gauged at all. Therefore, this study aims to provide a remote-sensing-based alternative for Qs monitoring. The at-a-station hydraulic geometry (AHG) power–law method was compared to the at-many-stations hydraulic geometry (AMHG) method; in addition, a novel AHG machine-learning (ML) method was introduced to estimate water discharge at three gauging stations in the Tisza (Szeged and Algyő) and Maros (Makó) Rivers in Hungary. The surface reflectance of Sentinel-2 images was correlated to in situ suspended sediment concentration (SSC) by support vector machine (SVM), random forest (RF), artificial neural network (ANN), and combined algorithms. The best performing water discharge and SSC models were employed to estimate the Qs. Our novel AHG ML method gave the best estimations of water discharge (Szeged: R2 = 0.87; Algyő: R2 = 0.75; Makó: R2 = 0.61). Furthermore, the RF (R2 = 0.9) and combined models (R2 = 0.82) showed the best SSC estimations for the Maros and Tisza Rivers. The highest Qs were detected during floods; however, there is usually a clockwise hysteresis between the SSC and water discharge, especially in the Tisza River.

Roughness into the Channel Create the Flood Situation - A Case Study at Lower Reach of Shilabati River Basin, Paschim Medinipur, West Bengal

Roughness into the channel of streams and rivers determines several important hydraulic parameters must be properly represented in models for estimating water discharge and sediment transport. Hydraulic parameters mainly gradient, hydraulic radius, width, width-depth ratio, wetted perimeter and cross sectional area are considered for analysing the ability of channels to carry discharge but resisting forces are opposing component of this movement. This paper reviews to evaluate the different approaches used to identify the roughness and to understanding of how flow resistance is created by roughness in open channel flows. The Shilabati river basin embraces a portion of the eastern fringe of the Chotonagpur plateau. South west monsoon is the principal source of rainfall in this area. After the heavy storm, the low lying depression in the lower reach of this catchment attracts huge flood water and sediments from it upper catchment, sub-tributaries and larger catchments of neighbouring rivers mainly Damodar, Darakeswar, and Kangsabati. The upper courses are steeper (0.84) and rocky facilitating easy drainage, that gradually concentrates at lower reach as it lost its capacity due to sudden reduction of gradient (Gadghat, 0.08; Bandar, 0.02). In the Shilabati river the cross sectional area changes through time in response to fluctuations in discharge. Channel slopes near these gauging stations are surveyed, that shows continuously decreasing tendency towards lower catchment. Capacity of channel is measured by conveyance of flow. Roughness coefficient value at three gauging station (Banka 0.50, Gadghat near Ghatal 0.82 and at estuary, Banka,1) measuring by the Manning’s equation depicts that the resistance to flow increases steadily at downstream. Channel substrate mainly vegetation and netting also influences the boundary roughness and flow resistance. Friction from sediment load mainly grain roughness are responsible for generating resistance which steadily declines movement and create jamming of water which ultimately leads to flood and water storage situation.

Estimating River Sediment Discharge in the Upper Mississippi River Using Landsat Imagery

With the decline of operational river gauges monitoring sediments, a viable means of quantifying sediment transport is needed. In this study, we address this issue by applying relationships between hydraulic geometry of river channels, water discharge, water-leaving surface reflectance (SR), and suspended sediment concentration (SSC) to quantify sediment discharge with the aid of space-based observations. We examined 5490 Landsat scenes to estimate water discharge, SSC, and sediment discharge for the period from 1984 to 2017 at nine gauging sites along the Upper Mississippi River. We used recent advances in remote sensing of fluvial systems, such as automated river width extraction, Bayesian discharge inference with at-many-stations hydraulic geometry (AMHG), and SSC-SR regression models. With 621 Landsat scenes available from all the gauging sites, the results showed that the water discharge and SSC retrieval from Landsat imagery can yield reasonable sediment discharge estimates along the Upper Mississippi River. An overall relative bias of −25.4, mean absolute error (MAE) of 6.24 × 104 tonne/day, relative root mean square error (RRMSE) of 1.21, and Nash–Sutcliffe Efficiency (NSE) of 0.49 were obtained for the sediment discharge estimation. Based on these statistical metrics, we identified three of the nine gauging sites (St. Louis, MO; Chester, IL; and Thebes, IL), which were in the downstream portion of the river, to be the best locations for estimating water and sediment discharge using Landsat imagery.

A high space–time resolution dataset linking meteorological forcing and hydro-sedimentary response in a mesoscale Mediterranean catchment (Auzon) of the Ardèche region, France

Abstract. A comprehensive hydrometeorological dataset is presented spanning the period 1 January 2011–31 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradient channels of bedrock rivers which promotes the transfer of suspended solids downstream. The number of observed variables, the various sensors involved (both in situ and remote) and the space–time resolution ( ∼ km2, ∼ min) of this comprehensive dataset make it a unique contribution to research communities focused on hydrometeorology, surface hydrology and erosion. Given that rainfall is highly variable in space and time in this region, the observation system enables assessment of the hydrological response to rainfall fields. Indeed, (i) rainfall data are provided by rain gauges (both a research network of 21 rain gauges with a 5 min time step and an operational network of 10 rain gauges with a 5 min or 1 h time step), S-band Doppler dual-polarization radars (1 km2, 5 min resolution), disdrometers (16 sensors working at 30 s or 1 min time step) and Micro Rain Radars (5 sensors, 100 m height resolution). Additionally, during the special observation period (SOP-1) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). (ii) Other meteorological data are taken from the operational surface weather observation stations of Météo-France (including 2 m air temperature, atmospheric pressure, 2 m relative humidity, 10 m wind speed and direction, global radiation) at the hourly time resolution (six stations in the region of interest). (iii) The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations estimate water discharge at a 2–10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity) and water samples are collected automatically during floods, allowing further geochemical characterization of water and suspended solids. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously measures water level and water temperature in headwater subcatchments (from 0.17 to 116 km2) at a time resolution of 2–5 min. A network of soil moisture sensors enables the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, concomitant observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. Finally, this dataset is considered appropriate for understanding the rainfall variability in time and space at fine scales, improving areal rainfall estimations and progressing in distributed hydrological and erosion modelling. DOI of the referenced dataset: doi:10.6096/MISTRALS-HyMeX.1438.

Evaluating the temporal variability of concentrations of POPs in a glacier-fed stream food chain using a combined modeling approach

Falling snow acts as an efficient scavenger of contaminants from the atmosphere and, accumulating on the ground surface, behaves as a temporary storage reservoir; during snow aging and metamorphosis, contaminants may concentrate and be subject to pulsed release during intense snow melt events. In high-mountain areas, firn and ice play a similar role. The consequent concentration peaks in surface waters can pose a risk to high-altitude ecosystems, since snow and ice melt often coincide with periods of intense biological activity. In such situations, the role of dynamic models can be crucial when assessing environmental behavior of contaminants and their accumulation patterns in aquatic organisms. In the present work, a dynamic fate modeling approach was combined to a hydrological module capable of estimating water discharge and snow/ice melt contributions on an hourly basis, starting from hourly air temperatures. The model was applied to the case study of the Frodolfo glacier-fed stream (Italian Alps), for which concentrations of a number of persistent organic pollutants (POPs), such as polychlorinated biphenyl (PCBs) and p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE) in stream water and four macroinvertebrate groups were available. Considering the uncertainties in input data, results showed a satisfying agreement for both water and organism concentrations. This study showed the model adequacy for the estimation of pollutant concentrations in surface waters and bioaccumulation in aquatic organisms, as well as its possible role in assessing the consequences of climate change on the cycle of POPs.

Estimating water discharge from large radar altimetry datasets

Abstract. The objective of this study is to evaluate the potential of large altimetry datasets as a complementary gauging network capable of providing water discharge in ungauged regions. A rating curve-based methodology is adopted to derive water discharge from altimetric data provided by the Envisat satellite at 475 virtual stations (VS) within the Amazon basin. From a global-scale perspective, the stage–discharge relations at VS are built based on radar altimetry and outputs from a modeling system composed of a land surface model and a global river routing scheme. In order to quantify the impact of model uncertainties on rating-curve based discharges, a second experiment is performed using outputs from a simulation where daily observed discharges at 135 gauging stations are introduced in the modeling system. Discharge estimates at 90 VS are evaluated against observations during the curve fitting calibration (2002–2005) and evaluation (2006–2008) periods, resulting in mean normalized RMS errors as high as 39 and 15% for experiments without and with direct insertion of data, respectively. Without direct insertion, uncertainty of discharge estimates can be mostly attributed to forcing errors at smaller scales, generating a positive correlation between performance and drainage area. Mean relative streamflow volume errors (RE) of altimetry-based discharges varied from 15 to 84% for large and small drainage areas, respectively. Rating curves produced a mean RE of 51% versus 68% from model outputs. Inserting discharge data into the modeling system decreases the mean RE from 51 to 18%, and mean NRMSE from 24 to 9%. These results demonstrate the feasibility of applying the proposed methodology to the continental or global scales.

고정식 표면영상유속계 (FSIV)를 이용한 실시간 하천 유량 산정

표면영상유속계(SIV)는 영상 분석 기법을 이용하여 하천의 표면유속을 측정하고, 이를 토대로 유량을 산정하는 시스템이다. 본 연구에서는 고정식 표면영상유속계(FSIV) 시스템을 달천 수전교에 설치하여 실시간으로 연속적인 유량 측정을 실시하였다. 수전교에 적용된 FSIV의 하드웨어 시스템은 영상 획득을 위한 2대의 디지털 카메라와 컴퓨터, 그리고 수위 측정을 위한 초음파 수위계로 구성된다. 이 현장 장비들에서 획득된 실시간 영상과 수위 자료는 무선인터넷을 이용하여 실시간으로 홈페이지에 전송되며, 표면영상유속분석 소프트웨어를 이용하여 유량을 산정한다. FSIV에 의한 유량산정 결과는 직상류의 괴산댐 방류량과 FSIV와 동일한 지점에 설치된 Acoustic Doppler Velocity Meter (ADVM)를 설치한 후 유속지수법으로 산정된 유량과 비교하여 검토하였다. 댐 방류량과 비교한 결과 30<TEX>$m^3/s$</TEX> 이상의 유량에서는 대부분 5~10%의 오차를 보였으며, ADVM을 이용하여 측정된 유량과 비교한 결과는 약 200<TEX>$m^3/s$</TEX> 이상의 유량에서는 오차가 약 5 % 이내로 확인되었다. FSIV의 설치 경비와 운용에 드는 비용과 인력을 감안한다면, FSIV는 실시간으로 유량을 관측할 수 있는 좋은 대안이 될 것으로 판단된다. Surface Image Velocimetry (SIV) is a recently-developed discharge measurement instrument. It uses image processing techniques to measure the water surface velocity and estimate water discharge with given cross section. The present study aims to implement a FSIV (Fixed-type Surface Image Velocimetry) at Soojeon Bridge in the Dalcheon. The hardware system consists of two digital cameras, a computer, and a pressure-type water stage gauge. The images taken with the hardware system are sent to a server computer via a wireless internet, and analyzed with a image processing software (SIV software). The estimated discharges were compared with the observed discharges through Goesan dam spillway and index velocity method using ADVM. The computed results showed a good agreement with the observed one, except for the night time. The results compared with discharges through Goesan dam spillway reached around 5~10% in the case of discharge over 30 m3/s, and the results compared with discharges through index velocity method using ADVM reached around 5% in the case of discharge over 200 <TEX>$m^3/s$</TEX>. Considering the low cost of the system and the visual inspection of the site situation with the images, the SIV would be fairly good way to measure water discharge in real time.

Global coastal segmentation and its river catchment contributors: A new look at land‐ocean linkage

Here we present the COSCATs global database of 151 catchments in exorheic areas. The catchments connect to oceans through coastal segments according to three sets of criteria: natural limits (continents, oceans, regional seas, major capes, and bays), continental shelf topography (sills, basins, island chains), and geophysical dynamics (climate, ocean currents and tectonics). The COSCATs segmentation scheme is designed to improve Earth System analysis and to harmonize reporting of global riverine transfers from land to oceans. Each COSCAT is characterized by its coastal segment limits and length (median 2 400 km), by its catchment characteristics, including area (median 0.45 M km2), width, latitudinal range, runoff average value and direction, including its related physiographic units (n = 500). We apply the COSCAT segmentation to all 151 basins to estimate water discharge and total nitrogen impacts to oceans and find that the average runoff (mm/yr) and N yields (YN in kg km−2 yr−1) range over more than 3 orders of magnitude at this coarse resolution, and that their average population density ranges over 2 orders of magnitude. Hyperactive regions, defined as segments with 5 to 10 times the world average yield (river transfers per unit area of land), are differentially placed for water runoff and total contemporary nitrogen. COSCATs have been designed to facilitate the budget reporting and the analysis of global scale heterogeneity for riverine fluxes and can be applied to other material, such as suspended solids, carbon species or other nutrients, particularly for areas draining into regional seas.