Modeling runoff with satellite-based rainfall estimates in the Niger basin

Oyerinde, Ganiyu Titilope; Fademi, I.O.; Denton, O. A.

doi:10.1080/23311932.2017.1363340

Cited by 13 publications

(15 citation statements)

References 26 publications

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“…In the mean time, Jason-3 (launch 2016) continues this data set, and Jason-CS and Sentinel-6 (anticipated launch 2020) will take over in time. Relative altimeter errors (i.e., with respect to an arbitrary vertical reference) are thought to be at the level of a 20-80 cm root-mean-square error (RMSE) for Jason-2, dependent on river width (Papa et al, 2012;Seyler et al, 2013;Tourian et al, 2016). In addition, we used Envisat (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) and SARAL/Altika (2013-present) to benefit from their much higher spatial resolution (about 70 km in the area), but these satellites have repeat cycles of 35 d. Relative errors are believed to be in the 15-70 cm range (Sridevi et al, 2016;Tourian et al, 2016;Bogning et al, 2018).…”

Section: Deriving Altimetric Water Levelsmentioning

confidence: 99%

“…The Niger River, shared by Nigeria, Mali, Niger, Benin, and Guinea, represents the 14th largest river in the world, with a length of 4180 km. The Niger basin covers an area of 2.1 million square kilometers and provides water resources to more than 100 million inhabitants (Oyerinde et al, 2017). Mean annual discharge into the Niger Delta and the tropical Atlantic Ocean amounts to 5600 m 3 s −1 , with peaks during September reaching 27 600 m 3 s −1 and low flow during winter and spring decreasing to 500 m 3 s −1 (Abrate et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…It is thus of obvious importance to water managers, planners, and scientists to better understand and quantify Niger flows, both at short timescales with near-real-time latency and at longer timescales where discharge responds to climate and land use change (Coulthard and Macklin, 2001;Legesse et al, 2003). At the largest spatial scale, discharge measurements would be required to close terrestrial water budgets, with observed or reanalysis precipitation and evapotranspiration data sets and total water storage variations observed with the GRACE satellite mission (Springer et al, 2017), and to improve estimates of freshwater forcing for understanding ocean dynamics (e.g., Papa et al, 2012). However, the gauge observation network along the Niger is not well developed in many locations due to periodical damage during floods, poor funding for maintenance, and armed conflict or unrest in some regions or because data are not automatically transmitted.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Niger discharge from radar altimetry: bridging gaps between gauge and altimetry time series

Schröder

Springer

Kusche

et al. 2019

Hydrol. Earth Syst. Sci.

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Abstract. The Niger River represents a challenging target for deriving discharge from spaceborne radar altimeter measurements, particularly since most terrestrial gauges ceased to provide data during the 2000s. Here, we propose deriving altimetric rating curves by “bridging” gaps between time series from gauge and altimeter measurements using hydrological model simulations. We show that classical pulse-limited altimetry (Jason-1 and Jason-2, Envisat, and SARAL/Altika) subsequently reproduces discharge well and enables continuing the gauge time series, albeit at a lower temporal resolution. Also, synthetic aperture radar (SAR) altimetry picks up the signal measured by earlier altimeters quite well and allows the building of extended time series of higher quality. However, radar retracking is necessary for pulse-limited altimetry and needs to be further investigated for SAR. Moreover, forcing data for calibrating and running the hydrological models must be chosen carefully. Furthermore, stage–discharge relations must be fitted empirically and may need to allow for break points.

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Section: Deriving Altimetric Water Levelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Niger discharge from radar altimetry: bridging gaps between gauge and altimetry time series

Schröder

Springer

Kusche

et al. 2019

Hydrol. Earth Syst. Sci.

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“…The hydrological model assessment and development (hydromad) [11] is a widely used R-based hydrological modeling package [12][13][14][15][16][17][18][19][20][21]. The hydromad package can be used to simulate conceptual hydrological models, optimize parameters, and analyze uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Combining an R-Based Evolutionary Algorithm and Hydrological Model for Effective Parameter Calibration

Shin¹,

Choi

2018

Water

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The hydrological model assessment and development (hydromad) modeling package is an R-based package that can be applied to simulate hydrological models and optimize parameters. As the hydromad package is incompatible with hydrological models outside the package, the parameters of such models cannot be directly optimized. Hence, we proposed a method of optimizing the hydrological-model parameters by combining the executable (EXE) file of the hydrological model with the shuffled complex evolution (SCE) algorithm provided by the hydromad package. A physically based, spatially distributed, grid-based rainfall–runoff model (GRM) was employed. By calibrating the parameters of the GRM, the performance of the model was found to be reasonable. Thus, the hydromad can be used to optimize the hydrological-model parameters outside the package if the EXE file of the hydrological model is available. The time required to optimize the parameters depends on the type of event, even for the same catchment area.

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“…While the IHACRES-CMD model has three soil moisture accounting parameters (Table 1), the GR4J model has four parameters, and the Sacramento model has thirteen parameters ( Table 1). IHACRES-CMD and GR4J were selected due to their wide usage and acceptability in hydrological studies in the Niger basin [9,[22][23][24]. The Sacramento model was added to the two well-known models in the region because of its robust parameterisation.…”

Section: Hydrological Modelsmentioning

confidence: 99%

Influence of Parameter Sensitivity and Uncertainty on Projected Runoff in the Upper Niger Basin under a Changing Climate

Oyerinde

Diekkrüger

2017

Climate

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Hydro-climatic projections in West Africa are attributed with high uncertainties that are difficult to quantify. This study assesses the influence of the parameter sensitivities and uncertainties of three rainfall runoff models on simulated discharge in current and future times using meteorological data from eight Global Climate Models (GCM). The IHACRES Catchment Moisture Deficit (IHACRES-CMD) model, the GR4J, and the Sacramento model were chosen for this study. During the model evaluation, 10,000 parameter sets were generated for each model and used in a sensitivity and uncertainty analysis using the Generalized Likelihood Uncertainty Estimation (GLUE) method. Out of the three models, IHACRES-CMD recorded the highest Nash-Sutcliffe Efficiency (NSE) of 0.92 and 0.86 for the calibration (1997)(1998)(1999)(2000)(2001)(2002)(2003) and the validation (2004)(2005)(2006)(2007)(2008)(2009)(2010) period, respectively. The Sacramento model was able to adequately predict low flow patterns on the catchment, while the GR4J and IHACRES-CMD over and under estimated low flow, respectively. The use of multiple hydrological models to reduce uncertainties caused by model approaches is recommended, along with other methods for sustainable river basin management.

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Modeling runoff with satellite-based rainfall estimates in the Niger basin

Cited by 13 publications

References 26 publications

Niger discharge from radar altimetry: bridging gaps between gauge and altimetry time series

Niger discharge from radar altimetry: bridging gaps between gauge and altimetry time series

Combining an R-Based Evolutionary Algorithm and Hydrological Model for Effective Parameter Calibration

Influence of Parameter Sensitivity and Uncertainty on Projected Runoff in the Upper Niger Basin under a Changing Climate

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