Marcus Nobrega Gomes Junior

Disaster inventories assign one hazard to each record, which can obscure interactions among hazards co-occurring. This structure makes it difficult to determine whether municipalities face a range of hazards over time and whether specific combinations are associated with greater impacts. We combined 76,191 municipal records from the Brazilian Digital Atlas of Disasters (1991–2025) with climate, land-cover, topographic, and soil data and examined the dataset on two scales. At the municipal scale, we measured the diversity of hazards accumulated over two multi-year periods. At the event scale, we classified short-duration municipal events according to their compound configurations: whether they occurred after a dry month (preconditioning), during locally extreme three-day rainfall, or together with another short-duration hazard (co-occurrences). Among 1,695 municipalities initially dominated by one hazard, 372 (21.9%) later qualified a municipal multi-hazard profile. At least one compound condition occurred in 35.8% of 40,464 classified events and these events accounted for 36.8% of recorded economic losses. Events with locally extreme rainfall (21.8%) showed higher recorded material damage, economic loss, homelessness, displacement, and affected populations than events without any compound component. Events with antecedent drought only (9.9%) showed no comparable elevation in damage metrics. Recorded hazards aligned with environmental conditions: rainfall-related records occurred under wetter conditions, and drought, wildfire, and heat-wave records under hotter, drier ones. Long-term municipal hazard diversity and short-duration compound conditions thus provide different information that is lost when hazards are counted separately. We also developed PRISMA Brazil: an open platform for municipal disaster records, socio-environmental indicators, and multi-hazard analysis.

Infiltration-based low-impact development (LID) practices are widely implemented to mitigate urban runoff impacts; however, their design is commonly guided by volumetric water-quality criteria that obscure critical trade-offs among hydrologic performance, geometry, soil properties, and cost. This study introduces the LID-design atlas (LIDA), a physics-based design database that systematically maps hydrologic performance and life cycle cost trade-offs across a broad space of infiltration-based LID configurations. LIDA is populated using thousands of numerical simulations generated with the Darcy–Richards analysis of infiltration in nature-based low-impact development (DRAIN-LID) model, which resolves one-dimensional variably saturated vertical flow through engineered media using a mixed-form Darcy–Richards formulation coupled with synthetic runoff inflow hydrographs. Three numerical design scenarios, spanning residential and roadside retrofit applications, are used to demonstrate how LIDA enables rapid screening of feasible designs based on peak-flow reduction, time-to-peak delay, detention time, ponding depth, and cost constraints. The results reveal strong threshold behavior in system response, with feasible design regions governed by interactions among footprint, media depth, and soil hydraulic conductivity rather than by storage volume alone. In space-constrained settings, increases in media depth are shown to be a more cost-efficient lever than footprint expansion, whereas lower-permeability media substantially restrict feasible design space. By explicitly resolving the temporal redistribution of runoff and exposing cost–performance trade-offs that are not captured by volume-based sizing methods, LIDA provides a transparent and computationally efficient framework for early-stage screening and comparison of infiltration-based LID designs.

Cost-effective water distribution network (WDN) design is crucial for reliable urban water supply. This paper introduces the open-source Excel for Water system Hydraulic Analysis Tool (X-WHAT) for WDN simulation and preliminary design. Unlike traditional spreadsheet approaches based on Hardy-Cross iteration, X-WHAT uses Excel’s built-in Generalised Reduced Gradient (GRG) solver with a direct matrix formulation, requiring no mass-conservative initial estimates or iterative flow corrections. The mathematical framework covers network topology, mass and energy conservation, and a multi-component cost function including tank material, structural foundation, and pumping energy costs. X-WHAT supports educational and preliminary engineering applications without coding expertise, while enabling sensitivity analysis for demand, configuration, cost, and hydraulic-performance changes. Three case studies, validated against EPANET and published literature, demonstrate the tool’s effectiveness. A tentative class organisation and unit design following the Understanding by Design (UbD) approach are also proposed. Through optimization, X-WHAT achieved a cost reduction of 151,790 USD (9.8% of total network cost) compared to standard design in a network serving 44,416 people. Supplementary material provides a step-by-step guide.

This study evaluates the hydrological and water quality performance of four permeable pavement (PP) types, namely, permeable interlocking concrete pavers, permeable grid, permeable asphalt ...

Accurate representation of closure relationships, such as subsurface storage‐discharge, is essential for hydrologic modeling at the hillslope scale, but remains challenging due to the nonlinear state‐dependent nature of soil hydraulic behavior. We investigate the state dependence of such parameters and closure relationships at the hillslope scale by developing a data assimilation framework that couples a 2D Boussinesq groundwater model with a simplified explicit unsaturated zone reservoir, avoiding the need to solve the full 1D Richards equation. A sequential particle filter (PF) is applied to dynamically update model states and parameters using observed seepage discharge and groundwater depth from the Landscape Evolution Observatory (LEO), the world's largest controlled artificial hillslope facility. Compared to a time‐invariant calibrated model (Kling–Gupta Efficiency, KGE = 0.85), the PF achieves significantly higher KGEs of 0.94, 0.94, and 0.96 for ensembles of 25, 100, and 400 particles, respectively, demonstrating robustness and computational efficiency. Correlation analysis reveals that parameter evolution is strongly state‐dependent: saturated hydraulic conductivity shows consistent negative correlation with groundwater levels (up to , ), reflecting compensatory behavior for unmodeled lateral unsaturated flow; van Genuchten parameters and evolve in opposing directions to regulate retention behavior; and specific yield , derived from , , and pressure head, acts as a dynamic closure variable that declines with rising water table. These results provide a demonstration of temporally evolving parameters and closure relationships in a first‐order catchment and underscore the ability of PFs to reveal emergent hydrologic behavior while preserving model tractability.

Climate change is increasing the extreme precipitation frequency and magnitude, intensifying river flood risk. Additionally, population growth in flood-prone zones within urban areas can exacerbate flood disaster risks. This study evaluates flood vulnerability in São Paulo's Aricanduva River watershed under current and future demographic and climate conditions. Non-stationary IDF curves derived from historical data and RCP4.5/8.5 models were employed to generate Huff design precipitation for 2-, 5-, 10-, 25-, 50-, and 100-year return periods. Population and household density were determined from IBGE census data; their projections utilized discrete logistic (population) and declining growth rate (households) models. HydroPol2D, a hydrological-hydraulic model, simulated the events to generate the flood maps. The analyses encompass socio-environmental dimensions and are presented in three factors: total affected population, affected population during the event, and affected households by income level. Results showed that a 100-year flood could affect 3.5\% of the population and 3.3\% of households in 2022. By 2099, under RCP4.5 and RCP8.5, impacts on population could increase by 29.3\%, and on households, by 21.6\%, demonstrating increasing risk over time. Shapley decomposition identified population growth (increased exposure), as the main driver in comparison with climate change conditions (increased hazard) for the affected population. For affected households, the influence of housing growth and climate change conditions varied across return periods. This study offers a flood vulnerability assessment reference for developing-country urban areas, supporting the development of effective prevention/control strategies. Such actions align with SDGs 6, 9, 11, and 13 in mitigating urban flooding impacts.

Reliable urban stormwater design under nonstationary rainfall is becoming increasingly important, yet quantitative links between floods occurrence, updated design requirements, and associated costs remain limited. This study (i) characterizes the evolution and impacts of flood-related events in São Paulo State, Brazil (1991–2024), and (ii) quantifies how nonstationary rainfall projections (CMIP6 SSP2-4.5 and SSP5-8.5) affect culvert sizing and construction costs across municipalities for standardized hypothetical catchments, across multiple return periods and future horizons. Observations indicate an increase in flood occurrence, from an average of 7.8 events per year in the 1990s to 72.9 events per year in the 2010s. In the immediate future (2015–2055), SSP2-4.5 projected costs remain close to the baseline for most municipalities (for return periods ≤ 25 years, 68% show increases up to 10%), whereas for the distant future (2056–2100) 86% exceed 10% under SSP5-8.5. However, under SSP5-8.5 in the immediate future (2015–2055), and for RP > 25 years, approximately 46% of municipalities exceed 10% additional costs. Design discharges generally rise by 9–43% in the immediate future, with stronger increases under SSP5-8.5 toward the late century. Mapping required hydraulic area to commercially available nominal sizes discretizes upgrades and creates threshold behavior, with larger basins crossing size classes more often. These findings challenge the assumption of stationary design and support the adoption of nonstationary adaptation strategies to reduce the long-term probability of structural failure.

This study presents an integrated approach for the design of lot-scale micro-reservoirs that considers the spatial variability of runoff generation within a catchment. Traditional reservoir sizing methods often neglect the cumulative, catchment-scale hydrological effects, which can lead to unintended synchronization of hydrograph peaks and localized flooding. The proposed methodology introduces a novel design criterion based on the upstream hydrological contribution and the position of each lot within the catchment. Using the Rational Method for runoff estimation, the SCS–CN method for infiltration and abstraction losses, and the PULS method for hydraulic routing, an open-source Excel–VBA tool was developed to automate the modeling and design process. Three case studies demonstrate the framework's ability to distinguish design requirements for lots with identical geometries but varying catchment positions. Results show that reference flow constraints derived from upstream characteristics significantly influence the required storage volume and outlet configuration. The tool supports optimization and performance analysis through dimensionless indicators that characterize peak attenuation, time-to-peak delay, storage performance, and mass balance.