## 5 Discussion
This uncertainty can be methodological, epistemic or associated with data sources and boundary conditions [10]. Probabilistic cartography has a number of advantages over cartography that could be called classic or conventional. The main advantage is its versatility, because it makes it possible to incorporate a wide range of errors and uncertainties onto the probabilistic intervals in the estimation of the variables involved in the cartographic production. This means that it is easy to adapt the cartographic result to future changes or hypotheses, such as climate change scenarios, geomorphological evolution or land-use evolution models [15]. Therefore, probabilistic cartography is ideal for future forecast maps, such as the \"Flood Factor\" maps of the First Street Foundation [48], which generate risk cartography for past, present and future time horizons (within 30 years). This versatility allows the incorporation of novel methodologies based on decision making under uncertainty theories, in particular \"Value of Information\" (VOI) as proposed by [PERSON] et al. [11]. From an applied point of view, this advantage of probability mapping allows this versatility to be transferred to flood risk management and the adoption of mitigation measures and strategies. For example, in the field of insurance and reinsurance, probabilistic cartographies reach their maximum development, as they allow the correlation of risk in coverage with the probability of risk of loss [49], and the adjustment of insurance policies with confidence intervals, following more conservative or more entrepreneurial policies, replacing the classic FEMA \"Flood Insurance Rate Map\" (FIRM) [50]. Another field of application where probability maps could be very useful is in territorial and urban planning since the different land classifications (urban, rural, and protected) and land-use restrictions (residential, industrial, recreational, and services) could be associated not so much with the probability of the phenomenon occurring as with the uncertainty of its estimation. This would avoid the so-called \"border or edge effects\" in landscape and urban planning, associated with abrupt zoning limits, which are so damaging to risk management, and would encourage a greater progressive gradation in classes, types of uses and use restrictions in the territory [51; 52; 53]. Finally, a flood risk analysis for critical infrastructures, such as nuclear power plants, large reservoir dams, industrial poles and the like, requires cartographies that make it possible to remain on the safety side, using the maximum magnitude and minimum probability confidence intervals when selecting their location, design and dimensioning [54; 55]. However, not all are advantages in the use of probability mapping over conventional flood hazard and risk mapping. In the legislative field, and specifically in administrative and criminal law, the diffuse limits associated with statistical probabilities generate problems of interpretation and application [56; 57]. If technical and legal problems already exist when legislation establishes the zoning of activities based on return periods--as in Spain, where the floodable zone is defined as that flooded by the 500-year return period [58]--the legal difficulties are extended by cartographies that add uncertainties and confidence intervals, which are difficult to incorporate into legislation and regulatory development. Despite these legal and other methodological limitations, the different comparative analyses between deterministic and probabilistic maps for case studies [47] have demon strated the usefulness of the latter maps, especially if they are used as an element of relative comparison, as is the case in this work. The probabilistic cartography produced for Zamora city can also be used as a peak flow uncertainty measure. So, for the 500-year return period, this uncertainty is about 36.5% when you compare the quantile and the 99% confidence interval peak flow values.