| 24 Sep 2025
A simplified model to investigate the hydrological regimes of temporary wetlands: the case study of Doñana marshland (Spain)
Abstract. Natural and pristine ecosystems, such as wetlands, are being either directly or indirectly threatened by a multiplicity of drivers, which include anthropogenic activities and the impacts they have on the use of natural resources. Strategies oriented to a sustainable management of natural resources (in particular, water) are therefore urgently needed, considering also the increasing effects of climate change. Despite their ecological importance, wetlands remain underrepresented in hydrological modelling studies, especially regarding their specific water needs under changing environmental conditions and different scenarios. This study aims to estimate the water requirements of a temporary wetland through a simple hydrological balance model, ultimately facilitating the identification of strategies for its long-term sustainable management. The pilot case study is the Doñana National Park, SW Spain, one of the case studies of the European project LENSES (PRIMA Call 2020). The model ('WetMAT') is calibrated and validated using historical time series of key hydrological variables (Maximum Flooded Area and Hydroperiod) taken from the literature, to describe the hydrological processes in the wetland. The model is then used for a scenario analysis focused on the assessment of climate change impacts on the state of the wetland and for assessing the ecological water demand of the wetland in a dynamic way, helping to quantify the water needs of such a fragile ecosystem. The results highlight the urgency and importance of developing tools that can help integrating environmental needs into water resources planning and management.
This manuscript employs a streamlined, simplified model to reproduce wetland inundated area and hydroperiod, and it stands out for its attempt to use the integrated IPI metric to inform management strategy development. However, the manuscript’s credibility would be strengthened by empirical evidence of external applicability, clearer justification of key equation coefficients, and a more explicit rationale for parameter bounds and the calibration design.
comments
1) Since Section 1 mentions that WetMAT can be applied to other regions, please present actual external applications and their outcomes. Specify which metrics (e.g., MFA, hydroperiod) were used for calibration/validation, how they were evaluated, and the achieved performance levels.
2) In Section 2.2.1, Eq. (6) directly computes MFA, but the basis for the exponent 0.2 is not clear. Please provide supporting prior studies and the empirical fitting procedure, along with a sensitivity analysis over alternative ranges (e.g., 0.15–0.30).
3) In Section 2.2.2, when applying WetMAT to the Doñana marshland, what are the specific reasons for neglecting river inflow (l_w) and groundwater inflow (G_w) in Eq. (1)? Also explain why, in the simplified balance (Eq. 7), evapotranspiration over water (ET_w) becomes the dominant term.
4) In Section 2.2.3, describing parameter upper/lower bounds as merely “reasonable” is insufficient. Please cite the basis for each value (field observation ranges, literature values, or data statistics) and explain how these sources informed the final choices.
5) In Section 3.1, both θ_WP and θ_FC are highly sensitive for maximum MFA, yet the trends differ: MFA increases as θ_WP increases, while MFA decreases as θ_FC increases. Please provide the physical explanation for these opposite tendencies.
6) For nine WetMAT parameters, 100 calibration runs appear insufficient to identify the optimum robustly. Please justify why limiting calibration to 100 runs is adequate for global exploration.
7) In Section 3.2, state that “As the only datasets available for the maximum MFA and hydroperiod variables are those used in this study, with no other relevant literature providing comparable datasets.” but relying on a single metric is limiting. Why was KGE used alone? Please add auxiliary metrics (e.g., R², NSE) and specify threshold/interpretation criteria from the literature.
8) For maximum MFA, please explain the hydrological rationale for why achieving KGE = 0.85 required setting θ_WP at the upper bound and K at the lower bound. In addition, please provide literature that supports the final chosen parameter values.
9) The Inundation Persistence Index (IPI), which combines maximum MFA and hydroperiod, appears to be the key metric of this study. However, the background and definition of IPI are not sufficiently explained in the manuscript. Please supplement this in the Introduction or Section 3.3.
10) The statements in Section 3.3 that “The annual precipitation goes above the 400 mm there is a good correlation between the two variables.” and that “There is no direct correlation between the 50th percentile of both series.” appear contradictory. To substantiate the findings, please present quantile-based correlations to verify whether the relationship holds only beyond the threshold. Also provide a clear rationale for setting the threshold at 400 mm.
11) Section 3.4 presents a climate-change analysis but lacks discussion. Please clarify which factor—changes in precipitation, temperature/PET, or model structure—drives the reductions in MFA and hydroperiod. If framed as future work, outline a brief quantitative plan to assess future IPI changes so the purpose of the section is clear.