Articles | Volume 377
https://doi.org/10.5194/piahs-377-19-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/piahs-377-19-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Regionalising MUSLE factors for application to a data-scarce catchment
Institute for Water Research, Rhodes University, P.O. Box 94, Grahamstown, Eastern Cape, South Africa
Andrew Slaughter
CORRESPONDING AUTHOR
Institute for Water Research, Rhodes University, P.O. Box 94, Grahamstown, Eastern Cape, South Africa
Denis Hughes
Institute for Water Research, Rhodes University, P.O. Box 94, Grahamstown, Eastern Cape, South Africa
Sukhmani Mantel
Institute for Water Research, Rhodes University, P.O. Box 94, Grahamstown, Eastern Cape, South Africa
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Yves Tramblay, Nathalie Rouché, Jean-Emmanuel Paturel, Gil Mahé, Jean-François Boyer, Ernest Amoussou, Ansoumana Bodian, Honoré Dacosta, Hamouda Dakhlaoui, Alain Dezetter, Denis Hughes, Lahoucine Hanich, Christophe Peugeot, Raphael Tshimanga, and Patrick Lachassagne
Earth Syst. Sci. Data, 13, 1547–1560, https://doi.org/10.5194/essd-13-1547-2021, https://doi.org/10.5194/essd-13-1547-2021, 2021
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This dataset provides a set of hydrometric indices for about 1500 stations across Africa with daily discharge data. These indices represent mean flow characteristics and extremes (low flows and floods), allowing us to study the long-term evolution of hydrology in Africa and support the modeling efforts that aim at reducing the vulnerability of African countries to hydro-climatic variability.
Andrew R. Slaughter and Saman Razavi
Earth Syst. Sci. Data, 12, 231–243, https://doi.org/10.5194/essd-12-231-2020, https://doi.org/10.5194/essd-12-231-2020, 2020
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Water management faces the challenge of non-stationarity in future flows. To extend flow datasets beyond the gauging data, this study presents a method of generating an ensemble of weekly flows from tree-ring reconstructed flows to represent uncertainty that can overcome certain long-standing data challenges with paleo-reconstruction. An ensemble of 500 flow time series were generated for the four sub-basins of the Saskatchewan River basin, Canada, for the period 1600–2001.
Nadia Oosthuizen, Denis A. Hughes, Evison Kapangaziwiri, Jean-Marc Mwenge Kahinda, and Vuyelwa Mvandaba
Proc. IAHS, 378, 11–16, https://doi.org/10.5194/piahs-378-11-2018, https://doi.org/10.5194/piahs-378-11-2018, 2018
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Input data (and model parameters) are significant sources of uncertainty that should be quantified. In southern Africa, water use data are among the most unreliable sources of model input data because available databases generally consist of only licensed information and actual use is generally unknown. The study assesses how uncertainty impacts the estimation of surface water resources of the Mogalakwena and Shashe sub-basins when using the databases that are currently available.
Vuyelwa Mvandaba, Denis Hughes, Evison Kapangaziwiri, Jean-Marc Mwenge Kahinda, and Nadia Oosthuizen
Proc. IAHS, 378, 17–22, https://doi.org/10.5194/piahs-378-17-2018, https://doi.org/10.5194/piahs-378-17-2018, 2018
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Channel transmission losses play a significant role in the water balance of the Limpopo River Basin, therefore understanding loss processes and quantifying the impact on water resources is integral for advancing knowledge and improving water resource management. Using three functions of the Pitman Model, loss simulations were conducted and results indicate that all three functions are able to simulate losses,albeit with differing magnitudes. Better quantification requires reliable observed data.
Andrew R. Slaughter and Sukhmani K. Mantel
Proc. IAHS, 377, 25–33, https://doi.org/10.5194/piahs-377-25-2018, https://doi.org/10.5194/piahs-377-25-2018, 2018
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WQSAM is a water quality model designed specifically for South Africa as it relies on flow data generated by South African-specific flow models. However, many of the characteristics of WQSAM would make it suitable for other developing semi-arid countries. This study attempted to adapt WQSAM to take in flow data from the globally-applied WEAP flow model so that WQSAM can be applied elsewhere. WQSAM could effectively use the flow data from the WEAP model as demonstrated on a case-study catchment.
Demetris Koutsoyiannis, Günter Blöschl, András Bárdossy, Christophe Cudennec, Denis Hughes, Alberto Montanari, Insa Neuweiler, and Hubert Savenije
Hydrol. Earth Syst. Sci., 20, 1081–1084, https://doi.org/10.5194/hess-20-1081-2016, https://doi.org/10.5194/hess-20-1081-2016, 2016
D. A. Hughes
Proc. IAHS, 371, 23–28, https://doi.org/10.5194/piahs-371-23-2015, https://doi.org/10.5194/piahs-371-23-2015, 2015
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Flow regimes of rivers will be different in the future, but how different is uncertain. Water resources decisions will rely on practical simulation tools that are sensitive to changes, can assimilate change information and flexible enough to accommodate new understanding. This paper presents some tools that can address these issues in southern Africa. Appropriate tools are available but we need more reliable forcing and model validation data and methods for making decisions with uncertain data.
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Short summary
The paper investigates the use of GIS to come up with model parameters. This is part of a process of simplifying model use. The findings show that existing GIS data can be used for estimating model parameters as the outcomes of the research show that model outputs are consistent with previously estimated measures. This research is part of a development of a model which can estimate soil loss and sediment delivery at broad spatial and temporal scales to improve catchment management.
The paper investigates the use of GIS to come up with model parameters. This is part of a...