Multicriteria analysis for flood risk map development: a hierarchical method applied to Brazilian cities.

Floods have caused socio-economic and environmental damage globally and, thus, require research. Several factors influence flooding events, such as extreme rainfall, physical characteristics, and local anthropogenic factors; therefore, such factors are essential for mapping flood risk areas and enabling measures that mitigate the damage they cause. This study aimed to map and analyze regions susceptible to flood risk in three different study areas belonging to the same Atlantic Forest biome, in which flood disasters are recurrent. Due to the presence of numerous factors, a multicriteria analysis using the Analytical Hierarchical Process was conducted. First, a geospatial database was composed of layers of elevation, slope, drainage distance, soil drainage, soil hydrological group, precipitation, relief, and land use and cover. Flood risk maps for the study area were then generated, and patterns in the study areas were verified, with the greatest influence being exerted by intense precipitation on consecutive days, elevation at the edges of the channel with low altimetric variation and a flat combination, densely built areas close to the banks of the main river, and an expressive water mass in the main watercourse. The results demonstrate that these characteristics together can indicate the occurrence of flooding events.

Analysis of indicators of surface water pollution in Atlantic Forest preservation areas.

Managing water resources in regions with scarce data, like most developing countries, is still one of the major challenges around the world. Analysis of water quality parameters can provide important information for understanding the current status of water resources and their surroundings, including the changes that have occurred over time. This study aims to evaluate the influence of preservation areas on surface water quality in the Atlantic Forest biome. For this purpose, water quality monitoring sites with a greater number of parameters and longer monitoring time, located in six basins in the Atlantic Forest region of Brazil near preservation areas, were selected. This study employs seven statistical methods, such as cluster and principal component analysis (PCA), and promotes a robust analysis of the pollution of water resources in the Atlantic Forest. The most preserved basins, with more than 87% preservation area, have lower levels of pollution. The second most degraded basin, with 56% preservation area, presents intermediate pollution levels. The most degraded basin has the highest level of pollution. The basin with the lowest area of native vegetation is considered a degraded basin. Finally, non-point sources of pollution from agricultural activities were identified as the main sources of pollution in the region. The cophenetic correlation of 0.97 indicates a good performance of the cluster analysis. In addition, the pre-tests of PCA showed the suitability of the data for performing the test (Bartlett test, < 2.2e-16 and KMO, P= 0.7). The first principal component in the PCA, which accounts for 31.4% of the total variation, is associated with strong ammonia nitrogen and total Kjeldahl nitrogen loads, and moderate biological oxygen demand and nitrite loads. The second component, representing 13.6% of the total variation, indicates periods of self-cleaning of water resources after contamination. The results indicate the importance of maintaining preservation areas in the watershed contribution areas for the improvement of surface water quality in the Atlantic Forest.

The time of concentration application in studies around the world: a review.

The time of concentration (Tc) is the main hydrological parameter used to characterize the response of a given Hydrological Response Unit (HRU) to a precipitation event. Because of its importance, the determining Tc is an integral step in several studies involving runoff. Thus, this work presents an unprecedented review of the application of Tc in different lines of research involving water resources around the world. In this article, 1252 publications were listed, obtained from seven different databases, published by 2020, that presented the expressions "time of concentration," "runoff," and "watershed." The articles and conference papers obtained in this research were classified into 12 topics. The number of publications per topic and per country was measured and a cluster analysis was developed to verify the similarity of the distribution of topics per country. In addition, 125 equations applied in related publications for the estimation of Tc are also listed. Graphical abstract.

Multivariate analysis of factors influencing the peak flow and runoff volume in the Cerrado and Atlantic Forest biomes in Brazil.

This study evaluates the influence of physiographic characteristics on the peak flow to runoff volume ratio in watersheds belonging to the Cerrado and Atlantic Forest biomes, in the Center-South region of Brazil. Specifically, the peak flow and runoff volume values obtained in the outlet section are related to the physiographic characteristics of the watersheds. Using a geographic information system tool, 13 watersheds are delimited, and 38 variables are selected from each watershed. A recursive digital filter is used to separate the direct (surface) flow from base (groundwater) flow. Data are analyzed using multivariate statistics, which allows interpretation of the structure of a data set from the respective correlation matrices. The results indicate that the peak flow and runoff volume are strongly correlated with the physical characteristics of the watersheds and the types of anthropogenic activity in both biomes. Furthermore, the presence of woods and forests reduces the peak flow and runoff volume.

Choosing an appropriate water quality model-a review.

Water quality models are quite complex to use even for scientists, requiring knowledge in different areas such as biology, chemistry, physics, and engineering. Hence, the use of these models by a non-specialist is quite complicated, demanding considerable time and research, particularly to choose which model is the most appropriate for a given situation. In this study, a comparative guide is suggested, which can help users select the appropriate water quality model for certain systems and variables. Five models were considered as follows: AQUATOX, CE-QUAL-W2, Spatially Referenced Regression Model on Watershed Attributes (SPARROW), Soil and Water Assessment Tool (SWAT), and Water Quality Analysis Simulation Program 7 (WASP7), which have been widely used during the last 5 years. All of these selected models are free and easily available. It was verified that each model has its particularities and applications; however, the AQUATOX model has several advantages compared with the other models analyzed. In addition, to illustrate the availability of the proposed comparative guide, a case study was carried out to demonstrating the selection process of the selected models.

Applicability of water quality models around the world-a review.

Water quality models are important tools used in the management of water resources. The models are usually developed for specific regions, with particular climates and physical characteristics. Thus, applying these models in regions other than those they were designed for can generate large simulation errors. With consideration to these discrepancies, the goal of this study is to identify the models employed in different countries and assist researchers in the selection of the most appropriate models for management purposes. Published studies from the last 21 years (1997-2017) that discuss the application of water quality models were selected from three engineering databases: SpringerLink, Web of Science, and Scopus. Seven models for water quality simulations have been widely applied around the world: AQUATOX, CE-QUAL-W2, EFDC, QUALs, SWAT, SPARROW, and WASP. The countries most frequently applying water quality models are the USA, followed by China, and South Korea. SWAT was the most used model, followed by the QUAL group and CE-QUAL-W2. This study provides the opportunity for researchers, who wish to study countries with fewer cases of applied water quality models, to easily identify the work from that region. Furthermore, this work collated central themes of interest and the most simulated parameters for the seven countries that most frequently employed the water quality models.