the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Hydrological regime shifts in Sahelian watersheds: an investigation with a simple dynamical model driven by annual precipitation
Abstract. The Sahel, the semi-arid fringe south of the Sahara, experienced severe meteorological droughts in the '70s–'80s. Since these droughts, watersheds in the Central Sahel have experienced an increase in the annual runoff coefficient (annual runoff normalized by annual precipitation). We hypothesize that these increases correspond to regime shifts. To investigate the timing of these regime shifts, we introduce a lumped model that represents feedbacks between soil, water and vegetation at the watershed scale and the annual time step. This model relies on runoff coefficient as a constraint for the state variable and precipitation as unique external forcing. Four watersheds (Gorouol, Dargol, Nakanbé and Sirba), with pluri-decennial observations ('50s–2010s), are modeled. For each watershed, one million parameterizations of this model are sampled and run, and an ensemble of one thousand best parameterizations is selected based on observed runoff coefficients. Our results show that this model can reproduce the trend of runoff coefficients. For all watersheds, almost all selected parameterizations from the ensemble are bistable, and can be utilized to define two alternative runoff coefficient regimes: a low and a high regime. Most ensemble members undergo regime shifts: simulated runoff coefficients belong to the low regime in 1965 and to the high regime in 2014. Finally, we find that the year of the regime shift, defined as the first year with more than 50 % of ensemble members in the high regime, was 1968, 1976, 1977, 1987 for the Gorouol, Dargol, Nakanbé and Sirba watershed, respectively. This article proposes several simple ideas toward improving the modelling and characterization of hydrological regime shifts.
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CC1: 'Comment on egusphere-2025-1965', Roland Yonaba, 05 Jun 2025
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Publisher’s note: the content of this comment was removed on 11 June 2025 since the comment was posted by mistake.
Citation: https://doi.org/10.5194/egusphere-2025-1965-CC1 -
RC1: 'Comment on egusphere-2025-1965', Roland Yonaba, 05 Jun 2025
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Dear Authors,
I have carefully reviewed your manuscript entitled "Hydrological regime shifts in Sahelian watersheds: an investigation with a simple dynamical model driven by annual precipitation." This study presents a novel, parsimonious modelling approach to investigate regime shifts in Sahelian runoff dynamics, a particularly relevant topic given the hydroclimatic complexity of the West African drylands. The manuscript is based on a clear and well-motivated hypothesis—the Sahelian paradox as a manifestation of hydrological regime shifts—and it advances a simple yet insightful dynamical model incorporating precipitation and runoff feedbacks. The combination of lumped modelling, ensemble simulation, and bifurcation analysis is commendably applied to long-term observational datasets.
However, there are some areas that require improvement before this work can be considered for publication.
Lines 45–50:
You introduce a model with precipitation as the sole external forcing. While conceptual simplicity is appreciated, the omission of known key drivers like land use changes (e.g., deforestation, cropland expansion, crust formation) and rainfall intensity is somehow concerning. Given existing knowledge on Sahelian hydrology, this simplification may lead to misleading causal inferences. The rationale for excluding these variables needs to be better justified, and at minimum, the implications of this omission must be critically discussed earlier. Also, not all readers are familiar with the term “attraction basin”, which needs explaination beforehand.Lines 100–110 (Eq. 1 and surrounding text):
The functional form used to relate S, P, and K is not adequately justified from a physical or empirical standpoint. For instance, the role of the parameters aa and bb in shaping the runoff response curve requires clearer explanation. Why not explore more physically based alternatives or benchmark this against empirical runoff-precipitation relationships?Lines 105–110 (Eq. 2):
The formulation of the “indicator of wetness” I is intuitive, but its dependence on the parameter f introduces confusion, especially since ff also appears in Eq. 1. The choice to divide by f in this context is not well motivated—wouldn't this imply higher f leads to lower wetness, contrary to physical intuition?Lines 109–115 (Eq. 3):
Equation 3 includes a third term µ(1-S) that is introduced as a stabilizer. This is acceptable, but it remains ad hoc and may significantly affect long-term trajectories of the model. Please include a sensitivity analysis of this parameter or offer more detailed justification of its value and range.Lines 115–125 (Model calibration):
While you cite equifinality to justify using an ensemble, you could improve the reproducibility of your methodology by clarifying the basis for choosing the “top 1,000” parameter sets. Why not explore a weighted ensemble or Bayesian approach to deal with parameter uncertainty more formally?Lines 125–135:
You define bistability based on attractor separation, but the use of arbitrary thresholds like 2000 mm precipitation and 10,000-year simulations raises concerns. These choices might significantly affect the classification of parameter sets. You should evaluate how sensitive the bistability classification is to these design choices.Lines 145–155 (Eq. 4 and definition of regime):
The operationalization of regime shifts via S=(↑S+↓S)/2 is a critical assumption. This midpoint criterion might not capture the actual dynamics of transition in transient regimes. Alternative definitions (e.g. basins of attraction) or at least a justification for this heuristic are needed.Figure 5 / Lines 155–170:
The mismatch between observed runoff coefficients and the simulated ensemble spread—especially for the Sirba and Nakanbé basins—is troubling. It casts doubt on whether the model can adequately capture year-to-year variability or nonlinear transitions. Please provide a quantitative assessment of performance beyond RMSE (e.g., Nash-Sutcliffe efficiency, bias).Lines 180–190 and Figure 7:
The definition of the “regime shift year” as the first time when more than 50% of ensemble members enter the high regime seems arbitrary. Why not use a probabilistic or statistical breakpoint analysis? The current criterion could lead to inconsistencies in estimating regime shift timing, as seen in the Gorouol case.Lines 200–220 (Discussion):
You rightly acknowledge that the model underrepresents interannual variability and that precipitation alone is insufficient. However, this admission seems to undercut the core claim that the model can meaningfully identify regime shifts. This contradiction should be addressed more transparently. Can regime shifts truly be inferred from such a limited model?Lines 205–210 (Gorouol case):
The early regime shift in the Gorouol basin (before observed droughts) is indeed counterintuitive. It may reflect model artefacts from initialization, especially since 40% of ensemble members already start in the “high” regime. This undermines the claim of detecting shifts dynamically. Please explore whether this result is robust or an artefact of initial conditions.Lines 215–220:
The interpretation of monostable vs. bistable ensemble members is important, but underdeveloped. If 10% of simulations do not undergo regime shifts, does this reflect real watershed variability or model limitations? Some exploration of this heterogeneity would enrich the discussion.A minor and general comment: the writing is generally clear, but at times overly dense with jargon. Consider simplifying key explanations, especially around dynamical systems concepts, to enhance accessibility for a broader hydrological audience. Also, Figures (in general) are informative, though Figures 4 and 6 could benefit from clearer legends and a brief description of axis choices (e.g. why is S bounded between 0–0.7?).
Citation: https://doi.org/10.5194/egusphere-2025-1965-RC1
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