The recently published work by Liu et al. [1] introduced the Stepwise Ecological Restoration (STERE) framework, offering an innovative, systematic and modular methodology for ecological restoration. As ecosystem degradation continues to pose a significant global threat to biodiversity, ecosystem services, and human well-being, traditional restoration methods often fail to account for the complexities and levels of degradation encountered in different ecosystems. The STERE framework represents a groundbreaking solution by providing a systematic theory that adapts restoration efforts to the unique conditions and specific needs of an ecosystem.

Adaptation of ecosystems’ root zones to climate change critically affects drought resilience and vegetation productivity. However, a global quantitative assessment of this mechanism is missing. In this study, we analyzed high-quality observation-based data to find that the global average root zone water storage capacity (S_R) increased by 11%, from 182 to 202 mm in 1982–2020. The total increase of S_R equals to 1652 billion m³ over the past four decades. S_R increased in 9 out of 12 land cover types, while three relatively dry types experienced decreasing trends, potentially suggesting the crossing of ecosystems’ tipping points. Our results underscore the importance of accounting for root zone dynamics under climate change to assess drought impacts.

Reading landscapes and developing calibration-free runoff generation models that adequately reflect land surface heterogeneities remains the focus of much hydrological research. In this study, we report a novel and simple topography-driven runoff generation parameterization – the HAND-based Storage Capacity curve (HSC), which uses a topographic index (HAND, Height Above the Nearest Drainage) to identify hydrological similarity and the extent of saturated areas in catchments. The HSC can be used as a module in any conceptual rainfall–runoff model. Further, coupling the HSC parameterization with the mass curve technique (MCT) to estimate root zone storage capacity (SuMax), we developed a calibration-free runoff generation module, HSC-MCT. The runoff generation modules of HBV and TOPMODEL were used for comparison purposes. The performance of these two modules (HSC and HSC-MCT) was first checked against the data-rich Bruntland Burn (BB) catchment in Scotland, which has a long time series of field-mapped saturation area extent. We found that HSC, HBV and TOPMODEL all perform well to reproduce the hydrograph, but the HSC module performs better in reproducing saturated area variation, in terms of correlation coefficient and spatial pattern. The HSC and HSC-MCT modules were subsequently tested for 323 MOPEX catchments in the US, with diverse climate, soil, vegetation and geological characteristics. In comparison with HBV and TOPMODEL, the HSC performs better in both calibration and validation, particularly in the catchments with gentle topography, less forest cover, and arid climate. Despite having no calibrated parameters, the HSC-MCT module performed comparably well with calibrated modules, highlighting the robustness of the HSC parameterization to describe the spatial distribution of the root zone storage capacity and the efficiency of the MCT method to estimate SuMax. This novel and calibration-free runoff generation module helps to improve the prediction in ungauged basins and has great potential to be generalized at the global scale.