Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Dembélé, Moctar; Schaefli, Bettina; Giesen, Nick van de; Mariethoz, Grégoire

doi:10.5194/hess-24-5379-2020

Cited by 72 publications

(49 citation statements)

References 219 publications

(210 reference statements)

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“…They recommended the use of CHIRPS for flood and drought studies undertaken in Burkina Faso and Mozambique by Dembélé and Zwart (2016) and Toté et al (2015), respectively. Dembélé et al (2020b) also evaluated the suitability of 17 available gridded rainfall datasets for large-scale hydrological modelling in the Volta River basin and showed that CHIRPS is one of the best-performing datasets for streamflow simulation. The study also established that none of the rainfall datasets they tested consistently performed well in reproducing the spatiotemporal rainfall variability.…”

Section: Observation-based Driving Datamentioning

confidence: 99%

How might climate change affect river flows across West Africa?

et al. 2021

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West Africa and its semi-arid Sahelian region are one of the world’s most vulnerable regions to climate change with a history of extreme climate variability. There is still considerable uncertainty as to how projected climate change will affect precipitation at local and regional scales and the consequent impact on river flows and water resources across West Africa. Here, we aim to address this uncertainty by configuring a regional-scale hydrological model to West Africa. The model (hydrological modelling framework for West Africa—HMF-WA) simulates spatially consistent river flows on a 0.1° × 0.1° grid (approximately 10 km × 10 km) continuously across the whole domain and includes estimates of anthropogenic water use, wetland inundation, and local hydrological features such as endorheic regions. Regional-scale hydrological simulations driven by observed weather data are assessed against observed flows before undertaking an analysis of the impact of projected future climate scenarios from the CMIP5 on river flows up to the end of the twenty-first century. The results indicate that projected future changes in river flows are highly spatially variable across West Africa, particularly across the Sahelian region where the predicted changes are more pronounced. The study shows that median peak flows are projected to decrease by 23% in the west (e.g. Senegal) and increase by 80% in the eastern region (e.g. Chad) by the 2050s. The projected reductions in river flows in western Sahel lead to future droughts and water shortages more likely, while in the eastern Sahel, projected increases lead to future frequent floods.

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Section: Observation-based Driving Datamentioning

confidence: 99%

How might climate change affect river flows across West Africa?

et al. 2021

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“…spheric reanalysis for environmental studies. Several intercomparison studies have been done (e.g., Beck et al, 2017;Essou et al, 2017), including over Africa (Satgé et al, 2020;Dembélé et al, 2020). These studies outline a complex picture in which performance depends on scale, climate and data source and for which no dataset consistently outperforms all of the others.…”

Section: Discussionmentioning

confidence: 99%

“…The GRDC is arguably the most complete global discharge database providing free access to river discharge data (Fekete and Vörösmarty, 2007). The database provides streamflow records collected from 9213 stations across the globe, with an average temporal coverage of 42 years per station (Do et al, 2017). It is operated under the World Meteorological Organization (WMO) umbrella to provide broad hydrological data to support the scientific research community.…”

Section: Observed Streamflow Datamentioning

confidence: 99%

Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies

Mostafa

Brissette²,

Arsenault³

2021

Hydrol. Earth Syst. Sci.

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Abstract. Climate change impact studies require a reference climatological dataset providing a baseline period to assess future changes and post-process climate model biases. High-resolution gridded precipitation and temperature datasets interpolated from weather stations are available in regions of high-density networks of weather stations, as is the case in most parts of Europe and the United States. In many of the world's regions, however, the low density of observational networks renders gauge-based datasets highly uncertain. Satellite, reanalysis and merged product datasets have been used to overcome this deficiency. However, it is not known how much uncertainty the choice of a reference dataset may bring to impact studies. To tackle this issue, this study compares nine precipitation and two temperature datasets over 1145 African catchments to evaluate the dataset uncertainty contribution to the results of climate change studies. These deterministic datasets all cover a common 30-year period needed to define the reference period climate. The precipitation datasets include two gauge-only products (GPCC and CPC Unified), two satellite products (CHIRPS and PERSIANN-CDR) corrected using ground-based observations, four reanalysis products (JRA55, NCEP-CFSR, ERA-I and ERA5) and one merged gauged, satellite and reanalysis product (MSWEP). The temperature datasets include one gauged-only (CPC Unified) product and one reanalysis (ERA5) product. All combinations of these precipitation and temperature datasets were used to assess changes in future streamflows. To assess dataset uncertainty against that of other sources of uncertainty, the climate change impact study used a top-down hydroclimatic modeling chain using 10 CMIP5 (fifth Coupled Model Intercomparison Project) general circulation models (GCMs) under RCP8.5 and two lumped hydrological models (HMETS and GR4J) to generate future streamflows over the 2071–2100 period. Variance decomposition was performed to compare how much the different uncertainty sources contribute to actual uncertainty. Results show that all precipitation and temperature datasets provide good streamflow simulations over the reference period, but four precipitation datasets outperformed the others for most catchments. They are, in order, MSWEP, CHIRPS, PERSIANN and ERA5. For the present study, the two-member ensemble of temperature datasets provided negligible levels of uncertainty. However, the ensemble of nine precipitation datasets provided uncertainty that was equal to or larger than that related to GCMs for most of the streamflow metrics and over most of the catchments. A selection of the four best-performing reference datasets (credibility ensemble) significantly reduced the uncertainty attributed to precipitation for most metrics but still remained the main source of uncertainty for some streamflow metrics. The choice of a reference dataset can therefore be critical to climate change impact studies as apparently small differences between datasets over a common reference period can propagate to generate large amounts of uncertainty in future climate streamflows.

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“…mHM has successfully been applied for several West African basins using a variety of forcing data and observational data as calibration targets [12,[30][31][32]. In our model setup for the Senegal River basin, elevation was retrieved from the Shuttle Radar Topographic Mission.…”

Section: Hydrological Modelmentioning

confidence: 99%

“…The robustness of the calibration experiments and the effectiveness of the proposed normalization strategy should be investigated in more detail. Ideally by means of an ensemble approach containing different precipitation forcing data sources as well as an ensemble of ET references [31,32].…”

Section: Calibration Strategymentioning

confidence: 99%

Climate Normalized Spatial Patterns of Evapotranspiration Enhance the Evaluation of Hydrological Models

Koch¹,

Demirel²,

Stisen³

2021

Preprint

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Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement was supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET are often characterized by an underlying climate gradient, and with this study, we argue that gradient dominated patterns may hamper the potential of spatial pattern-oriented evaluation frameworks. We hypothesize that the climate control of spatial patterns of ET overshadows the effect model parameters have on the simulated variability. To solve this limitation, we propose a climate normalization strategy. This is demonstrated for the Senegal River basin as modeling case study, where the dominant north-south precipitation gradient is the main driver of the observed hydrological variability. Two multi-objective calibration experiments investigate the effect of climate normalization. Both calibrations utilize observed discharge (Q) in combination with remote sensing ET data, where one is based on the original ET pattern and the other utilizes the normalized ET pattern. We identify parameter sets that balance the tradeoffs between the two independent observations and find that the calibration using the normalized ET pattern does not compromise the spatial patern performance of the original pattern. However, vice versa, this is not necessarily the case, since the calibration using the original ET pattern showed a poorer performance for the normalized pattern. Both calibrations reached comparable performance of Q. With this study, we identified a general shortcoming of spatial pattern-oriented model evaluations using ET in basins dominated by a climate gradient, but we argue that this also applies to other variables such as, soil moisture or land surface temperature.

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Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Cited by 72 publications

References 219 publications

How might climate change affect river flows across West Africa?

How might climate change affect river flows across West Africa?

Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies

Climate Normalized Spatial Patterns of Evapotranspiration Enhance the Evaluation of Hydrological Models

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