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Recently, there has been an increase in the number of natural disasters caused by extreme events, which are enhanced by climate change and anthropogenic interference. Therefore, understanding the hydrological behavior in areas with high vulnerability to floods and water scarcity is essential to capably manage water resources. In this context the study aimed to analyze the streamflow trend in the Piranga river basin, as well as to evaluate the determining factors in the streamflow variation regime in the watershed. For this reason, historical series of seven stream gauging stations were analyzed, adopting the base period of studies from 1975 to 2018. In order to identify the trend in maximum, average and minimum streamflow data, the Mann–Kendall, Pettitt and Spearman correlation tests were used. To understand the possible causes of streamflow trends, precipitation data, land use and occupation, and water demand were analyzed. It was observed that all stations showed some significant trend of streamflow reduction, especially in the dry season, having reduced from 10 to 35% comparing to the historical series average. On an annual scale, significant trends of reduction in average and minimum streamflow were detected. The change in streamflow behavior was not related to the distribution of precipitation over the years in the watershed. The cause of streamflow reduction may be related to the increase in water demand and with changes in land use and occupation, mainly characterized by the increase in planted forest, forest formation and urban areas and the reduction of areas destined to agriculture. The methodology proposed in this study can be adapted to other watersheds in the world, aiming to assist in the planning of water resources. [ABSTRACT FROM AUTHOR]

Disasters caused by rainfall extremes represent social challenges in several sectors, especially in climate change scenarios. Along with changes in land use and land cover, this relationship may become more complex. Thus, the present study aimed to detect recent trends in the pattern of rainfall indicators and associate them with records of natural disasters and the evolution of changes in land use and land cover for the state of Espírito Santo, southeastern Brazil. Daily rainfall data from 77 rain gauge stations from 1970 to 2018 were used to analyze climate trends in different rainfall indicators obtained using the RClimDex software. Records of natural disasters from 1991 to 2020 in the state of Espírito Santo were gathered from the Brazilian Integrated Disaster Information System. Additionally, land use and land cover data from 1985 and 2019 were also used. The Mann–Kendall (MK) test and the Sen slope were used to detect and quantify trends. In the Litoral Norte Espírito-santense and Noroeste Espírito-santense mesoregions of the State, trends of drought intensification are expected mainly in the regions further north. Associated with the great recent agricultural expansion in the region, this trend is concerning. The Central Espírito-santense and Sul Espírito-santense mesoregions tend to become wetter, which explains the recent increase in floods and heavy rainfall. No significant trends were found in the other regions studied. The approach adopted in this study has the potential to assist decision-making, implement mitigation and/or adaptation measures, and reduce the impacts of natural disasters in different regions of the world. [ABSTRACT FROM AUTHOR]

In Brazil, specifically in the Doce River basin, there is still a great lack of studies on temporal and spatial trends in water quality, since the water quality in the monitoring campaigns is basically evaluated when it comes down to the concentrations of monitored variables. In this sense, the objective of this work was to perform a temporal and spatial trend analysis of water quality data in the Minas Gerais portion of the Doce River basin, Brazil. For this, the Mann–Kendall, seasonal Mann–Kendall and Spearman correlation tests were used in the temporal analysis and the cluster analysis in the spatial analysis. In the analysis of temporal trends, the analyses were performed using the values of the National Sanitation Foundation Water Quality Index (NSFWQI) and the variables that compose it. In the analysis of spatial trends, the stations were evaluated only based on the WQI. With the results of the analysis of temporal trend, it was identified that most stations did not present a statistically significant trend for the WQI. In the stations that presented trends of quality reduction, most of them are in densely populated areas, demonstrating the strong influence of the poor sanitary conditions of the municipalities to the water quality of the basin. When analyzing the variables that compose the WQI, the results found for nitrate demonstrated that water quality deterioration is also affected by the diffuse pollution originating from farming areas. The results for Escherichia coli reinforced the impact of the discharge of domestic effluents and demonstrated the absence of a significative trend is still of concern because it can represent the maintenance of a degradation state in the water bodies. In the spatial trend analysis, the CA grouped the monitoring stations into six clusters based on their similarity among the WQI values, and, together with the results of the other analyses, it was verified that the Caratinga River basin (UGRH5 Caratinga) presented the highest degree of pollution. It was also possible to identify five stations that can be reallocated or deactivated since they have similarities with other stations located in the same watercourse. [ABSTRACT FROM AUTHOR]

The objective of the present study was to evaluate the water quality data in the Minas Gerais portion of the Doce River basin in order to analyze the current monitoring network by identifying the main variables to be maintained in the network, their possible sources of pollution, and the best sampling frequency. Multivariate statistical techniques (factor analysis/principal components analysis, FA/PCA and cluster analysis, CA) complemented by the analysis of violation of the framing classes were used for this purpose. Water quality variables common to 64 monitoring sites were analyzed for the base period from 2010 to 2017. The water quality variables were analyzed considering the different monitoring campaigns: (a) partial campaigns; (b) total campaigns; and (c) monthly campaigns. It was identified from the FA/PCA results, that, when the partial campaign data were analyzed, the variables selected represent the high susceptibility that the basin presents to erosion and the release of domestic effluents in its water bodies. When the data of total campaigns were evaluated, representative variables of the contamination by heavy metals from industrial and mining activities were included. Therefore, the analysis of violation of the framing classes made possible to identify five critical variables: thermotolerant coliforms, dissolved iron, total phosphorus, and total manganese, which reinforced the results obtained in FA/PCA. Based on the results of the analyses, it was recommended to include variables associated with heavy metal contamination in the partial campaigns, prioritizing the dissolved iron and total manganese, as well as total chloride sampling only for the total campaigns. The evaluated data from the monthly campaigns, the CA showed that although the quarterly monitoring frequency is satisfactory, the monthly monitoring is more appropriate for the monitoring of water quality in the Minas Gerais portion of the Doce River basin. [ABSTRACT FROM AUTHOR]

Land use and land cover have a direct influence on the hydrological regime. Urbanization and deforestation are accountable for reducing the water infiltration and consequent runoff's increase. These modifications lead to high peak flows responsible for catastrophic events. Thus, this work analyzed the impact of land use and land cover's change on the hydrological regime in a Brazilian southeastern urbanized watershed; considering current and future scenarios. The hydrological model HEC–HMS was used to estimate stream flow and aided in the search for suitable solutions. Using the Land Change Modeler tool made possible to design 2030's land use and land cover in Grande river watershed. Hydrological simulations were carried out for 2030 using HEC–HMS. Some of the forested areas were replaced by agriculture and pasture. The agricultural areas were the ones that showed greater expansion. Such changes contributed to a mean increase of 52% in the stream flow hydrograph when compared to the watershed's current scenario. After the use of best management practices, the stream flow hydrograph had a mean reduction of 44%. The structures considered were bio-retention cells, rain gardens, infiltration trenches, and permeable pavements for urban areas. For rural areas, the practices suggested were level terraces, no-till farming, and contour farming. All structures were applied in a distributed manner throughout the watershed. Therefore, it is concluded that land use and land cover's change in Grande river watershed significantly influence the stream flow regime, and the use of best management practices proved efficient in reducing floods. [ABSTRACT FROM AUTHOR]