scholarly journals Estimating uncertainties in hydraulicallymodelled rating curves for discharge time series assessment

2018 ◽  
Vol 40 ◽  
pp. 06013
Author(s):  
Valentin Mansanarez ◽  
Ida K. Westerberg ◽  
Steve W. Lyon ◽  
Norris Lam
Keyword(s):  
Time Series ◽  
Hydraulic Model ◽  
Observation Data ◽  
Rating Curve ◽  
Hydraulic Modelling ◽  
Discharge Time ◽  
High Flows ◽  
Rating Curves ◽  
Hydrometric Station ◽  
The Impact

Establishing a reliable stage-discharge (SD) rating curve for calculating discharge at a hydrological gauging station normally takes years of data collection. Estimation of high flows is particularly difficult as they occur rarely and are often difficult to gauge in practice. At a minimum, hydraulicallymodelled rating curves could be derived with as few as two concurrent SD and water-surface slope measurements at different flow conditions. This means that a reliable rating curve can, potentially, be developed much faster via hydraulic modelling than using a traditional rating curve approach based on numerous stage-discharge gaugings. In this study, we use an uncertainty framework based on Bayesian inference and hydraulic modelling for developing SD rating curves and estimating their uncertainties. The framework incorporates information from both the hydraulic configuration (bed slope, roughness, vegetation) using hydraulic modelling and the information available in the SD observation data (gaugings). Discharge time series are estimated by propagating stage records through the posterior rating curve results. Here we apply this novel framework to a Swedish hydrometric station, accounting for uncertainties in the gaugings and the parameters of the hydraulic model. The aim of this study was to assess the impact of using only three gaugings for calibrating the hydraulic model on resultant uncertainty estimations within our framework. The results were compared to prior knowledge, discharge measurements and official discharge estimations and showed the potential of hydraulically-modelled rating curves for assessing uncertainty at high and medium flows, while uncertainty at low flows remained high. Uncertainty results estimated using only three gaugings for the studied site were smaller than ±15% for medium and high flows and reduced the prior uncertainty by a factor of ten on average and were estimated with only 3 gaugings.

scholarly journals Stormflow and suspended sediment routing through a small detention pond with uncertain discharge rating curves

2018 ◽  
Vol 50 (4) ◽  
pp. 1177-1188 ◽  
Author(s):  
Adam Krajewski ◽  
Kazimierz Banasik ◽  
Anna E. Sikorska
Keyword(s):  
Sediment Concentration ◽  
Rating Curve ◽  
Discharge Time ◽  
Urban Catchment ◽  
Detention Ponds ◽  
Sediment Routing ◽  
Detention Pond ◽  
Huge Impact ◽  
Rating Curves ◽  
The Impact

Abstract Ratings curves are commonly used for computing discharge time series from recorded water stages or for hydrograph and sediment graph routing through detention ponds. Numerous studies have demonstrated that these rating curves are often linked with significant uncertainty. Nevertheless, the uncertainty related to the use of these rating curves in sediment estimates has not been investigated so far. Hence, in this work, we assess the impact of using such uncertain discharge rating curves on the estimation of the pond outflow (discharge, sediment concentration and load) from a small detention pond located in a small urban catchment in Poland. Our results indicate that the uncertainty in rating curves has a huge impact on estimates of discharge and sediment fluxes in the outlet from the reservoir, wherein the uncertainty in the inlet rating curve plays a more important role than the uncertainty in the outlet rating curve. Poorly estimated rating curve(s) may thus lead to serious errors and biased conclusions in the estimates and designs of detention ponds. To reduce this uncertainty, more efforts should be made to construct the rating curves at the pond inlet and to gather more data in extreme conditions.

Comparison of rating-curve uncertainty estimation using hydraulic modelling and power-law methods

2020 ◽  
Author(s):  
Ida Westerberg ◽  
Valentin Mansanarez ◽  
Steve Lyon ◽  
Norris Lam
Keyword(s):  
Power Law ◽  
Cost Effective ◽  
Uncertainty Estimation ◽  
Hydraulic Model ◽  
Lower Probability ◽  
Rating Curve ◽  
Hydraulic Modelling ◽  
Probability Of Occurrence ◽  
Rating Curves ◽  
Low Uncertainty

<p>Establishing reliable rating curves and thereby reliable streamflow monitoring records is fundamental to much of hydrological science and water management practice. Cost-effective methods that enable rapid rating curve estimation with low uncertainty are needed given diminishing monitoring resources and increasing human-driven changes to the water cycle. Traditional power-law rating curves rely on numerous gaugings to estimate rating curves and their associated uncertainty. Hydraulically-modelled rating curves are a promising alternative to power-law methods as they rely on fewer gaugings, but they are associated with additional uncertainty sources in the hydraulic knowledge (bed slope, roughness, topography and vegetation), which need to be assessed.</p><p>Our aim with this study was to compare power-law and hydraulic-model based methods for estimating rating curves and their uncertainty. We focused on assessing their accuracy as well as the costs and time required for establishing rating curves. We compared the Rating curve Uncertainty estimation using Hydraulic Modelling (RUHM) framework with the Bayesian power-law method BaRatin. The RUHM framework combines a one-dimensional hydraulic model with Bayesian inference to incorporate information from both hydraulic knowledge and the calibration gauging data. We applied both methods to the 584 km<sup>2</sup> River Röån station in Sweden under nine different gauging strategies associated with different costs. The gauging strategies differed in the number and flow magnitude of the gaugings used as well as the probability of observing the gauged flows.</p><p>We found that rating curves with low uncertainty could be modelled with fewer gaugings using the RUHM framework compared to BaRatin. As few as three gaugings were needed for RUHM if these gaugings covered low and medium flows, making the estimation both cost effective and time efficient. When using all the gaugings available (i.e. a high-cost gauging strategy), the uncertainty for RUHM and BaRatin was similar at the Röån station. Furthermore, we found that BaRatin needed gaugings with lower probability of occurrence (i.e. covering a larger part of the flow range) than needed when using hydraulic modelling (low and middle flow gaugings with high probability of occurrence gave good results). The results for this Swedish site show that hydraulic rating curve uncertainty estimation is a promising tool for quickly estimating rating curves and their uncertainties. In particular, it is useful for previously ungauged or remote sites, or at stations where there have been major temporal changes to the stage–discharge relation.</p>

scholarly journals Modelling the Mara River Basin with data uncertainty using water levels for calibration

2017 ◽  
Author(s):  
Petra Hulsman ◽  
Thom A. Bogaard ◽  
Hubert H. G. Savenije
Keyword(s):  
Time Series ◽  
Water Level ◽  
River Basin ◽  
Hydrological Model ◽  
Water Levels ◽  
Rating Curve ◽  
Discharge Time ◽  
Discharge Data ◽  
Single Station ◽  
Rating Curves

Abstract. Hydrological models play an important role in Water Resources Management. In hydrological modelling, discharge data is generally required for calibration. To obtain continuous time series, water levels are usually converted into discharge by using a rating curve. However with this methodology, uncertainties are introduced in the discharge data due to insufficient observations, inadequate rating curve fitting procedures, extrapolation or temporal changes in the river geometry. Unfortunately, this is often the case in many African river basins. In this study, a semi-distributed rainfall runoff model has been applied to the Mara River Basin for the assessment of the water availability. To reduce the effect of discharge uncertainties in this model, water levels instead of discharge time series were used for calibration. In this model, seven sub-catchments are distinguished and four hydrological response units: forest, shrubs, cropland and grassland. To calibrate the model on water level data, modelled discharges have been converted into water levels using cross-section observations and the Strickler formula. In addition, new geometric rating curves have been obtained based on modelled discharge, observed water level and the Strickler formula. This procedure resulted in good and consistent model results during calibration and validation. The hydrological model was able to reproduce the water depths for the entire basin as well as for the Nyangores sub-catchment in the north. The geometric and recorded (i.e. existing) rating curves were significantly different at Mines, the catchment outlet, probably due to uncertainties in the recorded discharge time series. At Nyangores however, the geometric and recorded discharge were almost identical. In addition, it has been found that the precipitation estimation methodology influenced the model results significantly. Application of a single station for each sub-catchment resulted in flashier responses whereas Thiessen averaged precipitation resulted in more dampened responses. In conclusion, by using water level time series for calibrating the hydrological model of the Mara River Basin promising model results were obtained. For this river basin, the main limitation for obtaining an accurate hydrograph representation was the inadequate knowledge on the spatial distribution of the precipitation.

scholarly journals Rainfall-runoff modelling using river-stage time series in the absence of reliable discharge information: a case study in the semi-arid Mara River basin

2018 ◽  
Vol 22 (10) ◽  
pp. 5081-5095 ◽  
Author(s):  
Petra Hulsman ◽  
Thom A. Bogaard ◽  
Hubert H. G. Savenije
Keyword(s):  
Time Series ◽  
Water Level ◽  
River Basin ◽  
Calibration Method ◽  
Water Levels ◽  
Rainfall Runoff ◽  
Rating Curve ◽  
Discharge Time ◽  
Rating Curves ◽  
Semi Arid

Abstract. Hydrological models play an important role in water resources management. These models generally rely on discharge data for calibration. Discharge time series are normally derived from observed water levels by using a rating curve. However, this method suffers from many uncertainties due to insufficient observations, inadequate rating curve fitting procedures, rating curve extrapolation, and temporal changes in the river geometry. Unfortunately, this problem is prominent in many African river basins. In this study, an alternative calibration method is presented using water-level time series instead of discharge, applied to a semi-distributed rainfall-runoff model for the semi-arid and poorly gauged Mara River basin in Kenya. The modelled discharges were converted into water levels using the Strickler–Manning formula. This method produces an additional model output; this is a “geometric rating curve equation” that relates the modelled discharge to the observed water level using the Strickler–Manning formula and a calibrated slope-roughness parameter. This procedure resulted in good and consistent model results during calibration and validation. The hydrological model was able to reproduce the water levels for the entire basin as well as for the Nyangores sub-catchment in the north. The newly derived geometric rating curves were subsequently compared to the existing rating curves. At the catchment outlet of the Mara, these differed significantly, most likely due to uncertainties in the recorded discharge time series. However, at the “Nyangores” sub-catchment, the geometric and recorded discharge were almost identical. In conclusion, the results obtained for the Mara River basin illustrate that with the proposed calibration method, the water-level time series can be simulated well, and that the discharge-water-level relation can also be derived, even in catchments with uncertain or lacking rating curve information.

scholarly journals Future shifts in extreme flow regimes in Alpine regions

2019 ◽  
Vol 23 (11) ◽  
pp. 4471-4489 ◽  
Author(s):  
Manuela I. Brunner ◽  
Daniel Farinotti ◽  
Harry Zekollari ◽  
Matthias Huss ◽  
Massimiliano Zappa
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Flow Regimes ◽  
High Flow ◽  
Discharge Time ◽  
Climate Conditions ◽  
Flow Duration ◽  
High Flows ◽  
Flow Duration Curves ◽  
Extreme Flow

Abstract. Extreme low and high flows can have negative economic, social, and ecological effects and are expected to become more severe in many regions due to climate change. Besides low and high flows, the whole flow regime, i.e., annual hydrograph comprised of monthly mean flows, is subject to changes. Knowledge on future changes in flow regimes is important since regimes contain information on both extremes and conditions prior to the dry and wet seasons. Changes in individual low- and high-flow characteristics as well as flow regimes under mean conditions have been thoroughly studied. In contrast, little is known about changes in extreme flow regimes. We here propose two methods for the estimation of extreme flow regimes and apply them to simulated discharge time series for future climate conditions in Switzerland. The first method relies on frequency analysis performed on annual flow duration curves. The second approach performs frequency analysis of the discharge sums of a large set of stochastically generated annual hydrographs. Both approaches were found to produce similar 100-year regime estimates when applied to a data set of 19 hydrological regions in Switzerland. Our results show that changes in both extreme low- and high-flow regimes for rainfall-dominated regions are distinct from those in melt-dominated regions. In rainfall-dominated regions, the minimum discharge of low-flow regimes decreases by up to 50 %, whilst the reduction is 25 % for high-flow regimes. In contrast, the maximum discharge of low- and high-flow regimes increases by up to 50 %. In melt-dominated regions, the changes point in the other direction than those in rainfall-dominated regions. The minimum and maximum discharges of extreme regimes increase by up to 100 % and decrease by less than 50 %, respectively. Our findings provide guidance in water resource planning and management and the extreme regime estimates are a valuable basis for climate impact studies. Highlights Estimation of 100-year low- and high-flow regimes using annual flow duration curves and stochastically simulated discharge time series Both mean and extreme regimes will change under future climate conditions. The minimum discharge of extreme regimes will decrease in rainfall-dominated regions but increase in melt-dominated regions. The maximum discharge of extreme regimes will increase and decrease in rainfall-dominated and melt-dominated regions, respectively.

Discharge estimation and monitoring extreme events by satellite altimetry

2020 ◽  
Author(s):  
Rossella Belloni ◽  
Stefania Camici ◽  
Angelica Tarpanelli
Keyword(s):  
Time Series ◽  
Water Level ◽  
River Discharge ◽  
Satellite Altimetry ◽  
Global Scale ◽  
Discharge Time ◽  
Discharge Data ◽  
The World ◽  
Daily Discharge ◽  
Rating Curves

<p>In view of recent dramatic floods and drought events, the detection of trends in the frequency and magnitude of long time series of flood data is of scientific interest and practical importance. It is essential in many fields, from climate change impact assessment to water resources management, from flood forecasting to drought monitoring, for the planning of future water resources and flood protection systems. <br>To detect long-term changes in river discharge a dense, in space and time, network of monitoring stations is required. However, ground hydro-meteorological monitoring networks are often missing or inadequate in many parts of the world and the global supply of the available river discharge data is often restricted, preventing to identify trends over large areas.  <br>The most direct method of deriving such information on a global scale involves satellite earth observation. Over the last two decades, the growing availability of satellite sensors, and the results so far obtained in the estimation of river discharge from the monitoring of the water level through satellite radar altimetry has fostered the interest on this subject.  <br>Therefore, in the attempt to overcome the lack of long continuous observed time series, in this study satellite altimetry water level data are used to set-up a consistent, continuous and up-to-date daily discharge dataset for different sites across the world. Satellite-derived water levels provided by publicly available datasets (Podaac, Dahiti, River& Lake, Hydroweb and Theia) are used along with available ground observed river discharges to estimate rating curves. Once validated, the rating curves are used to fill and extrapolate discharge data over the whole period of altimetry water level observations. The advantage of using water level observations provided by the various datasets allowed to obtain discharge time series with improved spatio-temporal coverages and resolutions, enabling to extend the study on a global scale and to efficiently perform the analysis even for small to medium-sized basins.  <br>Long continuous discharge time series so obtained are used to perform a global trend analysis on extreme flood and drought events. Specifically, annual maximum discharge and peak-over threshold values are extracted from the simulated daily discharge time series, as proxy variables of independent flood events. For flood and drought events, a trend analysis is carried out to identify changes in the frequency and magnitude of extreme events through the Mann-Kendall (M-K) test and a linear regression model between time and the flood magnitude.  <br>The analysis has permitted to identify areas of the world prone to floods and drought, so that appropriate actions for disaster risk mitigation and continuous improvement in disaster preparedness, response, and recovery practices can be adopted. </p>

scholarly journals Hydraulic scale modelling of the rating curve for a gauging station with challenging geometry

2019 ◽  
Vol 50 (3) ◽  
pp. 825-836 ◽  
Author(s):  
Øyvind Pedersen ◽  
Jochen Aberle ◽  
Nils Rüther
Keyword(s):  
Complex Geometry ◽  
Field Measurements ◽  
Numerical Control ◽  
Control Technique ◽  
Scale Model ◽  
Rating Curve ◽  
Scale Modelling ◽  
High Flows ◽  
Rating Curves ◽  
Gauging Station

Abstract Direct discharge measurements during flood events can be challenging from a technical as well as from a safety point of view. Therefore, flood discharges are often estimated by extrapolating a rating curve. Extrapolations far outside the range of the directly measured discharges are common, although the associated errors can be large. In this article, a novel method to determine suitable stage measurement locations and derive rating curves using a hydraulic scale model is presented. A hydraulic scale model for a natural gauging station site is produced with a computer numerical control technique, making a detailed representation of the prototype topography and bathymetry. The site is characterized by a complex geometry, and the results of the scale model study reveal that the current location of stage measurement is not suitable for determining the rating curve for high flows. The scale model is used to identify potential locations for future stage measurements, and a flood rating curve is constructed based on field measurements for low flows and scale model data for high flows. The study shows how hydraulic scale modelling can be used to provide more reliable rating curves for large discharges and evaluate new or existing gauging stations located at sites with challenging measurement conditions.

scholarly journals Assessing rating-curve uncertainty and its effects on hydraulic model calibration

2012 ◽  
Vol 16 (4) ◽  
pp. 1191-1202 ◽  
Author(s):  
A. Domeneghetti ◽  
A. Castellarin ◽  
A. Brath
Keyword(s):  
Cross Section ◽  
River Flow ◽  
Hydraulic Model ◽  
Rating Curve ◽  
Flow Measurements ◽  
Curve Estimation ◽  
Natural Streams ◽  
Rating Curves ◽  
River Po

Abstract. This study considers the overall uncertainty affecting river flow measurements and proposes a framework for analysing the uncertainty of rating-curves and its effects on the calibration of numerical hydraulic models. The uncertainty associated with rating-curves is often considered negligible relative to other approximations affecting hydraulic studies, even though recent studies point out that rating-curves uncertainty may be significant. This study refers to a ~240 km reach of River Po and simulates ten different historical flood events by means of a quasi-twodimensional (quasi-2-D) hydraulic model in order to generate 50 synthetic measurement campaigns (5 campaigns per event) at the gauged cross-section of interest (i.e. Cremona streamgauge). For each synthetic campaign, two different procedures for rating-curve estimation are applied after corrupting simulated discharges according to the indications reported in the literature on accuracy of discharge measurements, and the uncertainty associated with each procedure is then quantified. To investigate the propagation of rating-curve uncertainty on the calibration of Manning's roughness coefficients further model simulations are run downstream Cremona's cross-section. Results highlight the significant role of extrapolation errors and how rating-curve uncertainty may be responsible for estimating unrealistic roughness coefficients. Finally, the uncertainty of these coefficients is analysed and discussed relative to the variability of Manning's coefficient reported in the literature for large natural streams.

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