| 26 Sep 2025
Spatiotemporal assessment of landslide risk over large areas: A case study of the Valencian Community (1950–2021)
Abstract. The risk posed by natural hazards has gained growing attention in recent decades, largely due to the intensification and recurrence of extreme events, with the climate crisis identified as the primary driver. Landslide risk is no exception, although its impacts are generally less evident than those of floods or, particularly, severe droughts. In both cases, urban expansion has further exacerbated the problem, especially since the mid-twentieth century in more developed regions. This residential growth often took place in poorly regulated settings, particularly during its early stages, leading to the occupation of areas that were environmentally, culturally, or from a landscape perspective unsuitable, and frequently exposed to natural hazards. In fact, the risk of landslides affecting buildings located on susceptible terrain can largely be attributed to ineffective land management, often resulting from the absence of specific regulations. This study introduces a set of risk indices that serve as objective tools for the dynamic assessment of landslide risk in extensive and spatially fragmented territories divided into local entities. Based on these indices, criteria are proposed to evaluate the degree of risk and the adequacy of its management within each local entity, considering the evolution of urban development. Finally, a classification system is presented that organizes all cases according to their severity, offering a decision-support tool for public authorities tasked with ensuring effective land management.
This paper presents a comprehensive spatiotemporal assessment of landslide risk in the Valencian Community (Spain) from 1950 to 2021. The authors propose a multidimensional risk evaluation framework that integrates geological susceptibility, cadastral data, and economic exposure through the Risk Index (RI), Risk Quality Index (RQI), Risk Sensitivity Index (RSI), and Modified Risk Quality Index (mRQI). The topic is timely and relevant, addressing an essential research gap between susceptibility modeling and actionable risk management. The dataset is extensive, and the results have clear implications for regional land-use planning and risk mitigation.
Recommendation: Major Revision.
Major Comments：
The manuscript frequently claims that the proposed framework is particularly suitable for large, spatially heterogeneous regions such as the Valencian Community, yet it does not clearly explain why such regions are challenging for landslide risk assessment or how the proposed methodology addresses those challenges. Large and heterogeneous areas are typically characterized by strong geological and geomorphological variability, uneven spatial distribution of landslide inventories, inconsistent resolution of socioeconomic data, and mismatch between geological and administrative boundaries—all of which can undermine comparability and accuracy of regional risk models. The authors should explicitly discuss these challenges and clarify how the RQI, RSI, and mRQI frameworks overcome them, for instance by integrating multi-source datasets, applying normalization to reduce bias among different scales, coupling physical and socioeconomic factors across scales, and using dynamic indicators to capture temporal evolution of risk. Expanding this discussion would convincingly demonstrate the framework’s innovation and justify its claimed applicability to spatially dispersed regions.
Minor comments：
1. The methodological innovation of the RQI, RSI, and mRQI indices relative to existing risk assessment frameworks should be stated more clearly. A concise comparison with earlier studies (e.g., Guzzetti et al., 2005; Pereira et al., 2020; Segoni & Caleca, 2021) would help readers understand the conceptual advancement of this work.
2. The relationships and calculation logic of the indices—particularly the variables Gaj, Faj, LM, and DV—need clearer description. Including a schematic diagram summarizing index derivation, weighting, and normalization would enhance transparency and reproducibility.
3. The study would benefit from a brief uncertainty or sensitivity analysis to evaluate how variations in data inputs (e.g., susceptibility classification or economic valuation) affect risk index results. Even a qualitative discussion would strengthen confidence in the robustness of the findings.
4. Although the dataset spans more than seven decades, temporal changes in landslide risk are not well illustrated. Incorporating a time-series trend, decade-based comparison, or discussion of major shifts in risk drivers would make the “spatiotemporal” aspect of the study more convincing.
5. The discussion of socioeconomic influences such as tourism and urban expansion remains qualitative. Integrating basic quantitative indicators—such as land-use change, population growth, or infrastructure density—would provide stronger empirical support for the interpretation.
6. The manuscript would benefit from editorial refinement. Ensure consistent terminology throughout (e.g., unify “risk zone,” “susceptibility zone,” and “management class”), verify incomplete references, and standardize equation formatting and figure captions for clarity and professionalism.