Abstract
The regionalised characteristics of a sub-basin's long-term hydrological behaviour are used as multiple constraint filters for constraining hydrological model simulations in the Congo Basin using the monthly time step Pitman model. The results suggest that the constraints are appropriate in many sub-basins (≥ 20 gauging stations), but not all. Detailed examination of these results suggested that the effects of high slopes (> 7%) could increase the runoff ratio and Q90/MMQ (low flow index) constraint values and that implementing an adjustment factor based on slope did improve some of the very poor results. The percentage points on the FDC falling within the simulated uncertainty band has increased from 0% to 59.6% and 2.4% to 39.9% for the Rift valley and Batéké plateaux regions, respectively. Future studies ideally need a range of different rainfall products to quantify the uncertainties related to the inappropriateness of the CRU rainfall data in some parts of the Congo Basin.
Highlights
Adequate quantification of hydrological information across different spatial and temporal scales is essential to ensure sustainable management of water resources (Quesada-Montano et al, 2018)
Necessary to resort to hydrological modelling approaches that can realistically quantify the uncertainty associated with water resources estimations (Ndzabandzaba and Hughes, 2017; QuesadaMontano et al, 2018)
Since the original MMR values are model dependent, it was expected that their use in this modelling exercise would constitute one of the major sources of uncertainty associated with low flows
Summary
Adequate quantification of hydrological information across different spatial and temporal scales is essential to ensure sustainable management of water resources (Quesada-Montano et al, 2018). The data are not very useful for quantifying regional patterns of response in headwater areas (Kabuya et al, 2020b) This presents a serious limitation to hydrological modelling and makes it difficult to quantify model behavioural parameters (those generating hydrological responses that match observed conditions) for the individual upstream sub-basins (Hughes, 2016). It is, necessary to resort to hydrological modelling approaches that can realistically quantify the uncertainty associated with water resources estimations (Ndzabandzaba and Hughes, 2017; QuesadaMontano et al, 2018). This means that water resources decision-making processes have to allow for this uncertainty (McMillan et al, 2017; Hughes, 2019)
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