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

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.

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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

Hydrology and Earth System Sciences ◽

10.5194/hess-22-5081-2018 ◽

2018 ◽

Vol 22 (10) ◽

pp. 5081-5095 ◽

Cited By ~ 4

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.

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Discharge estimation and monitoring extreme events by satellite altimetry

10.5194/egusphere-egu2020-8020 ◽

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

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.&#160; 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. &#160; 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. &#160; 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. &#160; 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. &#160; 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.&#160;

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Estimating uncertainties in hydraulicallymodelled rating curves for discharge time series assessment

E3S Web of Conferences ◽

10.1051/e3sconf/20184006013 ◽

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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Using radar altimetry to update a large-scale hydrological model of the Brahmaputra river basin

Hydrology Research ◽

10.2166/nh.2013.191 ◽

2013 ◽

Vol 45 (1) ◽

pp. 148-164 ◽

Cited By ~ 13

Author(s):

Flemming Finsen ◽

Christian Milzow ◽

Richard Smith ◽

Philippa Berry ◽

Peter Bauer-Gottwein

Keyword(s):

Real Time ◽

River Basin ◽

Large Scale ◽

Hydrological Model ◽

Water Levels ◽

Hydrological Models ◽

Altimetry Data ◽

Brahmaputra River ◽

Radar Altimetry ◽

Rating Curves

Measurements of river and lake water levels from space-borne radar altimeters (past missions include ERS, Envisat, Jason, Topex) are useful for calibration and validation of large-scale hydrological models in poorly gauged river basins. Altimetry data availability over the downstream reaches of the Brahmaputra is excellent (17 high-quality virtual stations from ERS-2, 6 from Topex and 10 from Envisat are available for the Brahmaputra). In this study, altimetry data are used to update a large-scale Budyko-type hydrological model of the Brahmaputra river basin in real time. Altimetry measurements are converted to discharge using rating curves of simulated discharge versus observed altimetry. This approach makes it possible to use altimetry data from river cross sections where both in-situ rating curves and accurate river cross section geometry are not available. Model updating based on radar altimetry improved model performance considerably. The Nash–Sutcliffe model efficiency increased from 0.77 to 0.83. Real-time river basin modelling using radar altimetry has the potential to improve the predictive capability of large-scale hydrological models elsewhere on the planet.

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

Hydrology Research ◽

10.2166/nh.2018.131 ◽

2018 ◽

Vol 50 (4) ◽

pp. 1177-1188 ◽

Cited By ~ 4

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.

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A Zonal Watershed Hydrological Model Considering Land use and Land Cover Change and its Application

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.405-408.2201 ◽

2013 ◽

Vol 405-408 ◽

pp. 2201-2207 ◽

Cited By ~ 1

Author(s):

Xi Nan Li ◽

Ping Xie ◽

Yong Zhu

Keyword(s):

Land Use ◽

Water Resources ◽

Land Cover ◽

Land Cover Change ◽

River Basin ◽

Hydrological Model ◽

Daily Rainfall ◽

Scientific Basis ◽

Annual Runoff ◽

Discharge Data

In order to evaluate quantitatively the hydrology and water resources effects of land use and land cover change (LUCC), a zonal watershed hydrological model considering land use and land cover change (ZWHM-LUCC) was developed. According to the daily rainfall, evaporation and discharge data of Wuding River Basin during 1980~2000, the parameters of the model were calibrated and verified. The results show that coefficient of water balance (R) is 1.004 and the qualified rate of annual runoff depth (DR) is86.67% during calibration period 1986~2000 and the R is 0.938 and the DR is 66.67% during calibration verification 1980~1985. The calculated results indicate that this model has good adaptability in Wuding River Basin. The different scenarios of land use/land cover were analyzed by the model, with 2000 year as base year, 13 scenarios were designed, which be helpful to study water-economy-ecology interactions and natural-social dualistic, and provide the scientific basis for Wuding river basin water and soil conservation planning and water resources planning.

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Characterising hillslope–stream connectivity with a joint event analysis of stream and groundwater levels

Hydrology and Earth System Sciences ◽

10.5194/hess-24-5713-2020 ◽

2020 ◽

Vol 24 (12) ◽

pp. 5713-5744

Author(s):

Daniel Beiter ◽

Markus Weiler ◽

Theresa Blume

Keyword(s):

Time Series ◽

Water Level ◽

Groundwater Level ◽

Stream Water ◽

Water Levels ◽

Joint Analysis ◽

Strong Increase ◽

Groundwater Levels ◽

The Relationship ◽

Insight Into

Abstract. Hillslope–stream connectivity controls runoff generation, during events and during baseflow conditions. However, assessing subsurface connectivity is a challenging task, as it occurs in the hidden subsurface domain where water flow can not be easily observed. We therefore investigated if the results of a joint analysis of rainfall event responses of near-stream groundwater levels and stream water levels could serve as a viable proxy for hillslope–stream connectivity. The analysis focuses on the extent of response, correlations, lag times and synchronicity. As a first step, a new data analysis scheme was developed, separating the aspects of (a) response timing and (b) extent of water level change. This provides new perspectives on the relationship between groundwater and stream responses. In a second step we investigated if this analysis can give an indication of hillslope–stream connectivity at the catchment scale. Stream water levels and groundwater levels were measured at five different hillslopes over 5 to 6 years. Using a new detection algorithm, we extracted 706 rainfall response events for subsequent analysis. Carrying out this analysis in two different geological regions (schist and marls) allowed us to test the usefulness of the proxy under different hydrological settings while also providing insight into the geologically driven differences in response behaviour. For rainfall events with low initial groundwater level, groundwater level responses often lag behind the stream with respect to the start of rise and the time of peak. This lag disappears at high antecedent groundwater levels. At low groundwater levels the relationship between groundwater and stream water level responses to rainfall are highly variable, while at high groundwater levels, above a certain threshold, this relationship tends to become more uniform. The same threshold was able to predict increased likelihood for high runoff coefficients, indicating a strong increase in connectivity once the groundwater level threshold was surpassed. The joint analysis of shallow near-stream groundwater and stream water levels provided information on the presence or absence and to a certain extent also on the degree of subsurface hillslope–stream connectivity. The underlying threshold processes were interpreted as transmissivity feedback in the marls and fill-and-spill in the schist. The value of these measurements is high; however, time series of several years and a large number of events are necessary to produce representative results. We also find that locally measured thresholds in groundwater levels can provide insight into the connectivity and event response of the corresponding headwater catchments. If the location of the well is chosen wisely, a single time series of shallow groundwater can indicate if the catchment is in a state of high or low connectivity.

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Assimilation of Piezometric Data to Calibrate Parsimonious Daily Hydrological Models

Water ◽

10.3390/w13172342 ◽

2021 ◽

Vol 13 (17) ◽

pp. 2342

Author(s):

Axel Flinck ◽

Nathalie Folton ◽

Patrick Arnaud

Keyword(s):

Time Series ◽

River Flow ◽

Hydrological Model ◽

Water Levels ◽

Model Parameters ◽

Rainfall Time Series ◽

Time Step ◽

Processing Methods ◽

Analysis System ◽

Set Up

Low water levels are a seasonal phenomenon, which can be long, short, and more or less intense, affecting entire watercourses. This phenomenon has become a concern for many countries who seek better understanding of the processes that affect it and learn how to optimally manage water resources (pumping, irrigation). Consequently, a lumped rainfall model at daily time step (GR) has been defined, calibrated, and regionalised over French territories. The input data come from SAFRAN, the distributed mesoscale atmospheric analysis system, which provides daily solid and liquid precipitation and temperature data throughout the French territory. This model could be improved, in particular to more accurately simulate the hydrological response of watersheds interacting with groundwater. The idea is to use piezometric data from the ADES bank, available in France, and to use it for the calibration phase of the hydrological model. The analysis was carried out across ten French catchments that are representative of various hydrometeorological behaviours and are located in a diverse hydrogeological context. Each catchment must be represented by a piezometer that closely represents the main aquifer that interacts with the basin. This piezometer is located on part of the watershed that is most covered in terms of its drainage network, and closest to its outlet. Different signal processing methods are used to characterise the relationship between the fluctuation of river flow, piezometric levels and rainfall time series. Potential processing methods will be carried out in the temporal domain. To quantify groundwater table inertia and that of the catchment area, correlograms were calculated from daily chronicles of flows and piezometric levels. A cross-correlatory analysis was set up to see, in more detail, the correlations between the flow rates (especially base flows) and piezometric level time series. This type of analysis makes it possible to study relationships between various observations, and tests were carried out to take this information into account during the phase of the calibration of hydrological model parameters. These different analyses will hopefully help us to use piezometric data to consolidate the quality and robustness of the modelling.

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Automatic flood extent mapping using long time series of SAR imagery and water levels or discharge data

10.5194/egusphere-egu2020-16811 ◽

2020 ◽

Author(s):

Tomasz Berezowski

Keyword(s):

Time Series ◽

Groundwater Discharge ◽

Threshold Value ◽

Water Levels ◽

Backscatter Coefficient ◽

Discharge Data ◽

River Flooding ◽

Long Time Series ◽

Long Time ◽

Sar Imagery

Long time series of flood extent mapping are valuable for flooding frequency analysis, wetlands monitoring and hydrological model validation. In this study an automatic algorithm for flood extent mapping using long time series of synthetic aperture radar (SAR) imagery and observed water levels or discharge is presented. The key assumption of this algorithm is that the flooding extent is correlated to these two observed variables and the highest correlation is obtained when the flood/no flood threshold value of SAR backscatter coefficient is optimal. This study is conducted in the Biebrza River floodplain (approximately 220km2) located in NE Poland. The floodplain is a natural wetland, relatively untouched by human, with complex inundation that involves not only river flooding, but also groundwater discharge and rain or snowmelt local inundation. In order to map 2014-2018 flooding series the automatic thresholding algorithm is run on Sentinel 1 data from one relative orbit, yielding 161 SAR scenes. The estimated 2014-2018 &#160;water line match well water levels from independent water gauge and the inundation maps agree with the MODIS 500m reflectance image. This approach was unable to identify inundation in remote parts of the floodplain except very intensive groundwater discharge events. This behavior may have several reasons, of which the most probable are that the dense vegetation obscuring inundated ground and that groundwater, snowmelt or rainfall inundation is not correlated to the variables recorded at a water gauge located in the river.

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