scholarly journals Establishing Stage–Discharge Rating Curves in Developing Countries: Lake Tana Basin, Ethiopia

Hydrology ◽  
2022 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Teshager A. Negatu ◽  
Fasikaw A. Zimale ◽  
Tammo S. Steenhuis
Keyword(s):  
Developing Countries ◽  
Ecological Research ◽  
Alluvial Channels ◽  
Rating Curve ◽  
Lake Tana ◽  
Discharge Data ◽  
Streamflow Data ◽  
Rating Curves ◽  
Lake Tana Basin ◽  
Discharge Curves

A significant constraint in water resource development in developing countries is the lack of accurate river discharge data. Stage–discharge measurements are infrequent, and rating curves are not updated after major storms. Therefore, the objective is to develop accurate stage–discharge rating curves with limited measurements. The Lake Tana basin in the upper reaches of the Blue Nile in the Ethiopian Highlands is typical for the lack of reliable streamflow data in Africa. On average, one stage–discharge measurement per year is available for the 21 gaging stations over 60 years or less. To obtain accurate and unique stage–discharge curves, the discharge was expressed as a function of the water level and a time-dependent offset from zero. The offset was expressed as polynomial functions of time (up to order 4). The rating curve constants and the coefficients for the polynomial were found by minimizing the errors between observed and predicted fluxes for the available stage–discharge data. It resulted in unique rating curves with R2 > 0.85 for the four main rivers. One of the river bottoms of the alluvial channels increased in height by up to 3 m in 60 years. In the upland channels, most offsets changed by less than 50 cm. The unique rating curves that account for temporal riverbed changes can aid civil engineers in the design of reservoirs, water managers in improving reservoir management, programmers in calibration and validation of hydrology models and scientists in ecological research.

scholarly journals A hydraulic study on the applicability of flood rating curves

2011 ◽  
Vol 42 (1) ◽  
pp. 10-19 ◽  
Author(s):  
Giuliano Di Baldassarre ◽  
Pierluigi Claps
Keyword(s):  
River Flow ◽  
Measurement Range ◽  
Flood Events ◽  
Rating Curve ◽  
Discharge Data ◽  
Discharge Curve ◽  
Rating Curves ◽  
River Po ◽  
Very High ◽  
Discharge Curves

Several hydrological studies have shown that river discharge records are affected by significant uncertainty. This uncertainty is expected to be very high for river flow data referred to flood events, when the stage–discharge rating curve is extrapolated far beyond the measurement range. This study examines the standard methodologies for the construction and extrapolation of rating curves to extreme flow depths and shows the need of proper approaches to reduce the uncertainty of flood discharge data. To this end, a comprehensive analysis is performed on a 16km reach of the River Po (Italy) where five hydraulic models (HEC-RAS) were built. The results of five topographical surveys conducted during the last 50 years are used as geometric input. The application demonstrates that hydraulically built stage–discharge curves for the five cases differ only for ordinary flows, so that a common rating curve for flood discharges can be derived. This result confirms the validity of statistical approaches to the estimation of the so-called ‘flood rating curve’, a unique stage–discharge curve based on data of contemporaneous annual maxima of stage and discharge values, which appears insensitive to marginal changes in river geometry.

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 Budgeting suspended sediment fluxes in tropical monsoonal watersheds with limited data: the Lake Tana basin

2018 ◽  
Vol 66 (1) ◽  
pp. 65-78 ◽  
Author(s):  
Fasikaw A. Zimale ◽  
Mamaru A. Moges ◽  
Muluken L. Alemu ◽  
Essayas K. Ayana ◽  
Solomon S. Demissie ◽  
...  
Keyword(s):  
Management Practices ◽  
Sediment Budget ◽  
Model Parameters ◽  
Lake Tana ◽  
Discharge Data ◽  
Flood Plains ◽  
Sediment Fluxes ◽  
Data Limitations ◽  
Lakes And Reservoirs ◽  
Lake Tana Basin

Abstract Soil erosion decreases soil fertility of the uplands and causes siltation of lakes and reservoirs; the lakes and reservoirs in tropical monsoonal African highlands are especially affected by sedimentation. Efforts in reducing loads by designing management practices are hampered by lack of quantitative data on the relationship of erosion in the watersheds and sediment accumulation on flood plains, lakes and reservoirs. The objective of this study is to develop a prototype quantitative method for estimating sediment budget for tropical monsoon lakes with limited observational data. Four watersheds in the Lake Tana basin were selected for this study. The Parameter Efficient Distributed (PED) model that has shown to perform well in the Ethiopian highlands is used to overcome the data limitations and recreate the missing sediment fluxes. PED model parameters are calibrated using daily discharge data and the occasionally collected sediment concentration when establishing the sediment rating curves for the major rivers. The calibrated model parameters are then used to predict the sediment budget for the 1994-2009 period. Sediment retained in the lake is determined from two bathymetric surveys taken 20 years apart whereas the sediment leaving the lake is calculated based on measured discharge and observed sediment concentrations. Results show that annually on average 34 t/ha/year of sediment is removed from the gauged part of the Lake Tana watersheds. Depending on the up-scaling method from the gauged to the ungauged part, 21 to 32 t/ha/year (equivalent to 24-38 Mt/year) is transported from the upland watersheds of which 46% to 65% is retained in the flood plains and 93% to 96% is trapped on the flood plains and in the lake. Thus, only 4-7% of all sediment produced in the watersheds leaves the Lake Tana Basin.

scholarly journals The Role of the Hydrographer in Rating Curve Development

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Stuart Hamilton ◽  
Marianne Watson ◽  
Robin Pike
Keyword(s):  
Mathematical Form ◽  
Field Observations ◽  
Statistical Regression ◽  
Rating Curve ◽  
Discharge Data ◽  
Data Points ◽  
Rating Curves ◽  
Channel Errors ◽  
Channel Control ◽  
Over Time

Stage-discharge rating curves are used to produce most of the world’s discharge data. The shape of these curves is dependent on the shape of the channel that controls flow. Changes in rating curves occur over time in response to transitory (e.g., vegetation, ice, debris) or persistent (e.g., aggradation/degradation) changes of the rated channel. Errors in rating curve development can result from the mischaracterization of the shape of the curve at a given time, or the misidentification of patterns of change over time. While data-driven methods for rating curve calibration are desirable, conventional statistical regression techniques, unfortunately, require far more data points to fully characterize the patterns of change in the curve shapes than are commonly available. This article discusses the benefits of field observations of the stream channel in support of rating curve development. The mathematical form of the rating curve can be inferred from observations of natural channel control features that link to principles of flow. In this article, the theoretical components of the rating curve equation are discussed with emphasis on how field observations can be used to groundtruth calibrated values for the coefficient, offset, and exponent for each segment of a stage-discharge rating curve. The article also explains how conceptual models developed by the hydrographer add value to the calibration process.

scholarly journals The Role of the Hydrographer in Rating Curve Development

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Stuart Hamilton ◽  
Marianne Watson ◽  
Robin Pike
Keyword(s):  
Mathematical Form ◽  
Field Observations ◽  
Statistical Regression ◽  
Rating Curve ◽  
Discharge Data ◽  
Data Points ◽  
Rating Curves ◽  
Channel Errors ◽  
Channel Control ◽  
Over Time

Stage-discharge rating curves are used to produce most of the world’s discharge data. The shape of these curves is dependent on the shape of the channel that controls flow. Changes in rating curves occur over time in response to transitory (e.g., vegetation, ice, debris) or persistent (e.g., aggradation/degradation) changes of the rated channel. Errors in rating curve development can result from the mischaracterization of the shape of the curve at a given time, or the misidentification of patterns of change over time. While data-driven methods for rating curve calibration are desirable, conventional statistical regression techniques, unfortunately, require far more data points to fully characterize the patterns of change in the curve shapes than are commonly available. This article discusses the benefits of field observations of the stream channel in support of rating curve development. The mathematical form of the rating curve can be inferred from observations of natural channel control features that link to principles of flow. In this article, the theoretical components of the rating curve equation are discussed with emphasis on how field observations can be used to groundtruth calibrated values for the coefficient, offset, and exponent for each segment of a stage-discharge rating curve. The article also explains how conceptual models developed by the hydrographer add value to the calibration process.

scholarly journals Water discharge estimates from large radar altimetry datasets in the Amazon basin

2012 ◽  
Vol 9 (6) ◽  
pp. 7591-7611 ◽  
Author(s):  
A. C. V. Getirana ◽  
C. Peters-Lidard
Keyword(s):  
Data Assimilation ◽  
Amazon Basin ◽  
Water Discharge ◽  
Rating Curve ◽  
Radar Altimetry ◽  
Discharge Data ◽  
Modeling Uncertainties ◽  
The Mean ◽  
Relative Errors ◽  
The Impact

Abstract. In this study, we evaluate the use of a large radar altimetry dataset as a complementary gauging network capable of providing water discharge in ungauged regions within the Amazon basin. A rating-curve-based methodology is adopted to derive water discharge from altimetric data provided by Envisat at 444 virtual stations (VS). The stage-discharge relations at VS are built based on radar altimetry and outputs from a global flow routing scheme. In order to quantify the impact of modeling uncertainties on rating-curve based discharges, another experiment is performed using simulated discharges derived from a simplified data assimilation procedure. Discharge estimates at 90 VS are evaluated against observations during the curve fitting calibration (2002–2005) and evaluation (2006–2008) periods, resulting in mean relative RMS errors as high as 52% and 12% for experiments without and with assimilation, respectively. Without data assimilation, 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 errors (RE) of altimetry-based discharges varied from 15% to 92% for large and small drainage areas, respectively. Rating curves produced a mean RE of 54% versus 68% from model outputs. Assimilating discharge data decreases the mean RE from 68% to 12%. These results demonstrate the feasibility of applying the proposed methodology to the regional or global scales. Also, it is shown the potential of satellite altimetry for predicting water discharge in poorly-gauged and ungauged river basins.

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.

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