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Towards a framework of catchment classification for hydrologic predictions and water resources management in the ungauged basin of the Congo River: An a priori approach
  • +8
  • Raphael Tshimanga,
  • Gode Bola,
  • Pierre Kabuya,
  • Landry Nkaba,
  • Jeffery Neal,
  • Mark Trigg,
  • Paul Bates,
  • Denis Hughes,
  • Alain Laraque,
  • Ross Woods,
  • Thorsten Wagener
Raphael Tshimanga
Congo Basin Water Resources Research Center (CRREBaC) & Dpt. Natural Resources Management

Corresponding Author:[email protected]

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Gode Bola
Congo Basin Water Resources Research Center (CRREBaC) & Dpt. Natural Resources Management
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Pierre Kabuya
Congo Basin Water Resources Research Center (CRREBaC) & Dpt. Natural Resources Management
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Landry Nkaba
Congo Basin Water Resources Research Center (CRREBaC) & Dpt. Natural Resources Management, University of Kinshasa
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Jeffery Neal
School of Geographical Sciences, University of Bristol
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Mark Trigg
School of Civil Engineering, University of Leeds
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Paul Bates
School of Geographical Sciences, University of Bristol
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Denis Hughes
Institute for Water Research, Rhodes University
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Alain Laraque
CNRS/IRD
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Ross Woods
Department of Civil Engineering, University of Bristol
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Thorsten Wagener
Department of Civil Engineering, University of Bristol
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Abstract

The Congo Basin exhibits tremendous heterogeneities, out of which it emerges as an intricate system where complexity will vary consistently over time and space. Increased complexity in the absence of adequate knowledge will always result in increased uncertainties. One way of simplifying this complexity is through an understanding of organisational relationships of the landscape features, which is termed here as catchment classification. The need for a catchment classification framework for the Congo Basin is obvious given the basin’s inherent heterogeneities, the ungauged nature of the basin, and the pressing needs for water resources management that include the quantification of current and future supplies and demands, which also encompass the impacts of future changes associated with climate and land use, as well as water resources operational policies. The need is also prompted by many local-scale management concerns within the basin. This study uses an a priori approach to determine homogenous climatic-physiographic regions that are expected to underline dominant hydrological processes characteristics. A set of 1740 catchment units are partitioned across the whole basin, based on a set of comprehensive criteria, including natural break of the elevation gradient (199 units), inclusion of socio-economic and anthropogenic systems (204 units), and water management units based on traditional nomenclature of the rivers within the basin (1337 units). The identified catchment units are used to assess existing datasets of the basin physical properties, necessary to derive descriptors of the catchments characteristics. An unsupervised classification, based on Hierarchical Agglomerative Cluster algorithm is used, that yields 11 homogenous groups that are consistent with the current perceptual understanding of the Congo Basin physiographic and climatic settings. These regions represent therefore an a priori classification that will be further used to derive functional relationships of the catchments, necessary to enable hydrological prediction and water management in the basin.
25 Feb 2022Published in Congo Basin Hydrology, Climate, and Biogeochemistry on pages 469-498. 10.1002/9781119657002.ch24