Nonlinear hydro-climatic controls on an arid-region lake: Evidence from 40 years of remote sensing
Abstract. Accurate measurement of lake surface area is essential for understanding eco-hydrological processes in arid regions, yet long-term records are often limited by cloud contamination, seasonal ice cover, and data gaps. In this study, we developed an optimized extraction framework that integrates seasonal index selection, adaptive thresholding, maximum connectivity analysis, and mutual information – based gap filling to construct a continuous monthly lake area series for Bahannao Lake from 1984 to 2024. This method effectively addressed common challenges in remote sensing water extraction and provided reliable long-term lake dynamics in a data-scarce desert region. Based on the reconstructed time series, we examined the multi-factor drivers of lake evolution using an XGBoost model combined with climatic and energy-balance variables. Results reveal pronounced interannual and seasonal variability: precipitation dominates lake expansion in spring and summer, while shortwave radiation is the main driver of evaporation in autumn and winter, even under cold conditions. Long-term trends indicate a shift in controlling mechanisms – from humidity and precipitation decline (1984–1999), to increased radiation and humidity variability (2000–2014), and finally to intensified sensible heat flux and potential evapotranspiration (2015–2024).Our findings highlight the nonlinear and evolving interactions between hydro-climatic factors regulating arid-region lakes. The proposed framework provides a robust approach for generating long-term lake records, advancing understanding of eco-hydrological responses to climate change, and offering scientific support for water resources management and adaptation in arid regions.
Lakes in arid and semi-arid regions are good indicators for the regional environmental changes. The manuscript develops a series of technologies to construct a continuous monthly record of Bahannao Lake based on remote sensing data, further reveals the temporal shifts and nonlinear controls of hydro-climatic drivers on lake dynamics with the help of multi-factor analysis using the XGBoost model. A large number of data analysis have been carried out; the methods are sound and the results are reliable. However, there are shortcomings in the presentation and interpretation of the results, which prohibit the publication of this manuscript in the current version.
Overall, the manuscript offers significant value and is suitable for publication in HESS. The topic is of interest and fits the journal scope, but I have several suggestions and comments before publication in HESS.
Major comments:
Minor comments: