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• Out-of-sample prediction of extreme precipitation using nonstationary models. • Significant trends in data of extreme precipitation are insufficient to warrant the selection of a nonstationary model. • Large prediction uncertainty reduces the support for nonstationary models of extreme precipitation. • (Non)stationary model selection should explicitly account for model complexity. Knowledge of the recurrence intervals of precipitation extremes is vital for infrastructure design, risk assessment, and insurance planning. However, trends and shifts in rainfall patterns globally pose challenges to the application of extreme value analysis (EVA) which relies critically on the assumption of stationarity. In this paper, we explore: (1) the suitability of nonstationary (NS) models in the presence of statistically significant trends, and (2) their potential in modeling out-of-sample data to improve frequency analysis of extreme precipitation. We analyze the benefits of using a nonstationary Generalized Extreme Value (GEV) model for annual extreme precipitation records from Southern Brazil. The location of the GEV distribution is allowed to change with time. The unknown GEV model parameters are estimated using Bayesian techniques coupled with Markov chain Monte Carlo simulation. Next, we use GAME sampling to compute the evidence (and their ratios, the so-called Bayes factors) for stationary and nonstationary models of annual maximum precipitation. Our results show that the presence of a statistically significant trend in annual maximum precipitation alone does not justify the use of a NS model. The location parameter of the GEV distribution must also be well defined, otherwise, stationary models of annual maximum precipitation receive more support by the data. These findings reiterate the importance of accounting for GEV model parameters and predictive uncertainty in frequency analysis and hypothesis testing of annual maximum precipitation data records. Furthermore, a meaningful EVA demands detailed knowledge about the origin and persistence of observed changes. [ABSTRACT FROM AUTHOR]

Floods are one of the deadliest natural hazards and are exacerbated by changes in land-use and climate. Urban development decreases infiltration by reducing pervious areas and increases the accumulation of pollutants during dry weather. It also decreases infiltration by reducing pervious areas and increases the accumulation of pollutants during dry periods. During rainy events, there is an increase in pollution concentrations and runoff that may be a source of water supply during drought periods. Modeling the quantity and quality dynamics of stormwater runoff requires a coupled hydrodynamic module capable of estimating the transport and fate of pollutants. In this paper, we evaluate the applicability of a distributed hydrodynamic model coupled with a water quality model (HydroPol2D). First, the model is compared to GSSHA and WCA2D in the V-Tilted catchment, and the limitation of the critical velocity of WCA2D is investigated. We also applied the model in a laboratory wooden board catchment, focusing on the validation of the numerical approach to simulate water quality dynamics. Then, we apply HydroPol2D in the Tijuco Preto catchment, in São Carlos - Brazil, and compare the modeled results with the full momentum solver of the HEC-RAS 2D. This catchment shares similar characteristics with many poorly-gauged and human-impacted catchments worldwide. The implementation of the model, the governing equations, and the estimation of input data are discussed, indicating the challenges and opportunities to scale HydroPol2D into the reality of data scarcity of larger poorly-gauged catchments. For a 1-yr return period of rainfall and antecedent dry days, and assuming an uncertainty of 40% in the water quality parameters, the results indicate that the maximum concentration of total suspended solids (TSS), the maximum load and the mass of the pollutant washed in 30% of the volume are, 456 ± 260 mgL-1km-2, 2. 56 ± 0. 4 kgs-1km-2, and 89 % ± 10 % , respectively. [Display omitted] • A new coupled hydrodynamic and water quality 2D model is developed (HydroPol2D). • The spatial–temporal dynamics of Total Suspended Solids (TSS) is investigated. • We estimate TSS transport rates and first flush for a 1-year return period. • The maximum TSS load is 2. 56 ± 0. 4 kg s − 1 km − 2 for a 40% uncertainty in water quality parameters. • HydroPol2D can also be used for flood inundation mapping, infiltration, and evapotranspiration modeling. [ABSTRACT FROM AUTHOR]

• A dye-based modeling approach was made for the first time in a Neoproterozoic karst hydrosystem. • Geo-speleological features association to develop conceptual models of karst systems. • Spatio-temporal resolutions of flow and transport parameters by equilibrium and non-equilibrium models. • Comparison of hydrodynamic behavior of recent karst systems with Neoproterozoic karst. Brazilian Neoproterozoic carbonate rocks, dating from about 740–590 million years ago, contain the oldest karst-structured terrains on Earth, resulting in groundwater flow pathways in highly heterogeneous and anisotropic conduit networks. Unlike Paleozoic and Mesozoic rocks, in Neoproterozoic karst systems, groundwater circulates and stores practically through dissolution features characterized as tertiary porosity, as the rock's primary porosity is recrystallized, considered negligible. However, studies using hydrodispersive equilibrium and non-equilibrium models to estimate flow and transport parameters to base the hydrodynamic behavior of these areas are not common. This paper proposes this, by a set of techniques involving dye tracer tests and the analysis of breakthrough tracer curves (BTCs) in a highly karstified Neoproterozoic terrain. For this, three karst springsheds, in the east, west, and south areas of the São Miguel river watershed, in Alto São Francisco karst region, Brazil, were choose and studied with dye tracer tests using Rhodamine WT and Uranine during dry and wet seasons, associated with regional/local (hydro)geological-structural, geomorphological, and speleological data. The results identified spatial and seasonal variations of water flow and transport parameters, recharge and discharge zones, and water dynamic and speleogenetic evolutions. BTCs models showed the karst systems are very dynamic with seasonal variations, and heterogeneities (bypass, loops and stagnant zones) control the variation of flow and transport parameters. The hydrodispersive parameters (mean flow velocity, and longitudinal dispersion coefficient) and coefficients of non-equilibrium models (partition, β, and mass transfer, ω) show a direct dependence on hydrogeological and speleogenetic contexts. Furthermore, the comparison with other karst systems around the world showed that Neoproterozoic karst has a more stable hydrodynamic behavior under hydrological conditions. [ABSTRACT FROM AUTHOR]

Hydrological models are useful to support ecosystem services restoration. However, when planning the expansion of Nature-based Solutions and Payments for Ecosystem Services, there are requirements including the principle of additionality, representation of multiple runoff mechanisms and calculation of farm-scale spatial outputs and epistemic uncertainty. While addressing these aspects is important to make future planning more effective (investment costs and water benefits) it is also challenging. This paper integrates, in a single modeling framework, the main requirements highlighted. This allows an improved selection of top priority areas with farm-scale spatial resolution and a deeper understanding of how epistemic modeling uncertainty affects the results, which is relevant to evaluate the risks of overestimating ecosystem services benefits. The modeling approach is demonstrated in a case study watershed in the Atlantic Forest biome (Brazil). The PLANS model is introduced, which uses the design of TOPMODEL to simulate both simulates both saturation-excess and infiltration-excess runoff at the farm-scale resolution. Also, it uses a novel saturation index based in a composition of Height Above the Nearest Drainage and Topographical Wetness Index terrain descriptors. We applied the Generalized Likelihood Uncertainty Estimation method, aided by an evolutionary algorithm, to estimate output epistemic uncertainty. Results show that uncertainty substantially affects priority definition (97% ranking change), and that simulated topographic effects can overcome local effects of land cover and soil type. With better data, uncertainty evaluation indicates that the restoration program in the study case could have the cost of its allocation policy reduced by up to 27%, showing that it can be made more cost- effective with the methods proposed. [Display omitted] [ABSTRACT FROM AUTHOR]

• Recovery of hydrological droughts can be 4 times longer than that of meteorological ones. • Recovery time is longest and more severe in dry regions and regions with high water use. • A multi-indicator approach is key to the proper characterization of drought development and propagation. Meteorological droughts propagate through the hydrological cycle causing hydrological droughts and societal impacts. However, the effects of climate and basin characteristics on hydrologic drought propagation vary regionally and remain largely unclear. In this paper, we characterize meteorological and hydrological droughts in 457 basins in Brazil. Using the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI), we investigate hydrologic drought propagation based on differences in drought onset, the center of mass, and time to peak. Additionally, we estimate the recovery time of meteorological and hydrologic drought events. The results indicate that hydrological droughts are usually more long-lasting, severe, and with a slower recovery time compared to meteorological droughts. While the most severe meteorological droughts are observed in humid regions (e.g., Amazon and Southern Brazil), the most severe and long-lasting hydrological droughts are found in the driest region (i.e., Northeast Brazil) or mostly impacted by human activities (i.e., Southeast Brazil). Hydrological droughts in dry regions can take four times longer to recover than meteorological ones. For most regions, the propagation time was slightly different considering the different approaches. Our results highlight the importance of a multi-indicator approach to fully characterize the mechanisms controlling the development and propagation of droughts through the water cycle. [ABSTRACT FROM AUTHOR]

• Evaporation trends of tropical reservoirs in Brazil were investigated. • Both positive and negative trends in evaporation were observed. • In the industrial region, the negative trend was potentially caused by the impact of pollutant released to the atmosphere. • In the coastal region, the positive trend was related to increasing air temperature. This paper aims to analyze the trends (Mann-Kendall test) of evaporation and climatological variables, including air temperature, relative humidity and wind speed in four reservoirs located in the Brazilian Northeast. The evaporation was estimated through remote sensing using the Surface Energy Balance System for Water (AquaSEBS) model from 1985 to 2018. In addition, it was verified which meteorological parameter has the highest correlation (R2) with the evaporation in order to assess why this process is changing throughout the years in each reservoir. The model performed well, with root mean square error (RMSE) ≤ 1.25 mm/day, percent bias (PBIAS) ≤ 13.70% and coefficient of determination (R2) ≥ 0.51. One reservoir located closer to a coastal zone presented a positive trend (+0.24 mm/34 years), corroborating the measurements of a reference class A pan, and Penman-Monteith equation, while the others, located closer to industrial areas, displayed negative trends (−0.26 to −0.080 mm/34 years). This reduced evaporation was attributed to the impact of industrial pollutant release to the atmosphere, while the increasing effect in the other reservoir was due to its proximity to the coast, which implies an air renewal as the sea breeze contributes for an improvement in the air quality. The meteorological data also presented positive and negative correlations: Temperature exhibited a positive trend (+0.57 °C/34 years), whereas humidity (−4.83%) and wind speed (−0.29 m/s), a negative trend. Evaporation displayed moderate coefficient of determination (R2 > 0.31) with wind speed and humidity. Yet, the reduction of evaporation may be associated with a possible counterbalancing effect of wind speed over humidity. Overall, the results contribute to a better understanding of evaporation trends in a water-scarce region and can be used in a water resources management context as the increasing/reduction of evaporation might significantly impact water availability in this area. [ABSTRACT FROM AUTHOR]