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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]

The probable rainfall is an excellent climatic parameter of information since it consists of the highest/lowest expected rainfall for a particular period of the year considering a certain level of probability. This study aims to evaluate traditional PDF performance using different goodness-of-fit tests to establish a criterion for choosing them on a monthly rainfall scale, in Mato Grosso do Sul, Brazil. The Cramer-von Misses (CVM) and Anderson–Darling (AD) tests were the most rigorous in rejecting the hypothesis of PFD suitable for monthly rainfall data, while the Kolmogorov–Smirnov (KS) was the least rigorous. The application of stricter goodness-of-fit tests as the CVM implies the use of up to 60% fewer series compared to the KS test. However, suitable series by the KS test presented erroneous estimates of probable monthly rainfall. The CVM and AD tests indicate the PDF with the best statistical performance (higher precision and accuracy between the observed and estimated frequency by the PDF) in more than 60% of situations. The most suitable PDFs for total monthly rainfall by the goodness-of-fit tests was gamma (12 months of the year). The exponential and Generalized Extreme Values (GEV) can be used for both the dry and rainy periods, respectively. The parameters of PDF are correlated with geographical variables, describing the total monthly rainfall distribution such as, for example, the influence of the South Atlantic Subtropical Anticyclone, the South Atlantic Convergence Zone in the rainy period, and the orographic effect in the dry period. [ABSTRACT FROM AUTHOR]

The importance of daily data on reference evapotranspiration (ET0) has increased in recent years due to its relevance in planning and decision making regarding irrigated agriculture, water production, and forest restoration. Facing the scarcity of this information measured in loco, the study of interpolation methods capable of representing ET0 becomes important. Therefore, this study aimed to evaluate the adequacy of the Random Forest (RF) method in the spatialization of ET0 in the watersheds of the Mid-South region of the Espírito Santo State, located within the Atlantic Forest biome, Brazil. From this study, it was found that the RF method is the most suitable one for ET0 spatialization when compared to the Angular distance weighting (ADW) and the inverse distance weighting (IDW) techniques. Also, the spatializations carried out by this method were transformed into databases in a grid format and made available online. Furthermore, the RF database was also compared to other ET0 grid databases, and it was concluded that the RF database also carried out a better performance than the other ones. [ABSTRACT FROM AUTHOR]

The relationship between forest cover and streamflow of watersheds is complex and still controversial in the scientific literature. To investigate such relationship we propose an alternative method which requires the following information for each watershed: percentage of forest cover, annual rainfall, average specific streamflow (qave), and minimum mean specific streamflow in seven consecutive days (q7). As a case study, we analyzed a dataset composed by 25 watersheds located in the Espírito Santo State (ESS), Brazil. We conducted simple and multiple linear regression analyses as well as partial correlation analysis between the above parameters. To reduce the effect of heterogeneity of environmental factors, watersheds with similar characteristics in term of rainfall, drainage area, and both rainfall and drainage area were grouped by cluster analysis, and the above regression and correlation analysis was repeated on each group. Our results using the whole dataset showed that forest cover has a negative relationship with watershed streamflow. The analysis of homogeneous groups of watersheds showed that the average minimum streamflow during seven days (q7) was more sensitive to the presence of forest cover, showing a negative relationship, especially in watersheds with low annual rainfall, while in areas with high precipitation, the annual rainfall showed a strong influence on the hydrological responses of watersheds, masking the effect of forest cover. The proposed method may be easily extended to other areas, and allows the inclusion of other relevant environmental variables according to specific cases. [ABSTRACT FROM AUTHOR]

The application of hydrologic models often needs sets of input parameters related to environmental attributes which are not always available. This leads to the necessity of calibrating the input parameters. However, due to the non-linearity of the hydrologic phenomena, there may be multiple “best” solutions for the calibration. This paper proposes a method for calibrating the DHSVM hydrologic model using the concepts of multiple solutions, multi-site, and parameter transfer among catchments. Eight watersheds were calibrated, resulting in obtaining five sets of “best” parameters (clusters) for each one. Afterward, each watershed was modeled using the parameters of the other catchments in order to verify if the transfer of the calibrated parameters could promote satisfactory modeling of the streamflows. The results show that clusters calibrated for one watershed may be suitable for other catchments. Besdes, the calibrated parameters of the smaller catchments were satisfactory to simulate the streamflow of the bigger catchments. The proposed method can be useful in calibrating and extrapolating the input parameters to regions that do not have information about them [ABSTRACT FROM AUTHOR]

This study aims at fitting polynomial models based on latitude, longitude and altitude coordinates to estimate the monthly and annual mean rainfall in Mato Grosso do Sul state, Midwest region of Brazil. Furthermore, its target is to verify whether hydrologically similar regions provide statistical improvement in the regression fit for rainfall estimation. To create the monthly and annual rainfall for 32 rain gauge stations, there were used at least 15 years long data records for analysis with a percentage of gaps at most 10%. Generally, the monthly and annual rainfall models present suitable statistical validation coefficients. The number of predictor variables enhances the performance of the regression method when estimating monthly and annual rainfall. Fitting regressions in hydrologically similar groups through cluster analysis tends to increase regression performance; however, the limited number of rain gauge stations in Brazil makes this technique difficult to apply because the number of parameters of the regression models may be greater than the number of rain gauge stations in the cluster. The first degree polynomial regression proved to be the most adequate to represent the mean monthly and annual rainfall because of the equivalence between observed and predicted values of rainfall and because of the statistical analysis. Fitting polynomial models presents suitable method for practical applications, forming an important tool for environmental management in the Mato Grasso do Sul State. [ABSTRACT FROM AUTHOR]

This paper describes the assessment of the SWAT hydrological model to reproduce continuous daily streamflow and simulate scenarios of forest management for a small catchment under tropical climate in Aracruz, Brazil. The main land use of the catchment consisted of eucalyptus cultivation. The SWAT parameters were calibrated and validated using daily hydrologic and meteorological data from 1997 to 2004. The statistical indices of SWAT validation (NS = 0.74, PBIAS = -14.34%, RSR = 0.51) show that SWAT performance was satisfactory in this application. Different land use and forest management scenarios were simulated with the aim of assessing their influence over the streamflow. The scenarios were: catchment under eucalyptus cultivation with three different forest managements and catchment under the native forest (Atlantic Rainforest). The scenarios simulations did not show significant changes in the longterm average streamflow. Minimum, maximum, and average annual streamflows were higher for eucalyptus scenarios compared to the native forest scenario. These results should be carefully applied to other watersheds as they reflect soil, landscape, and climate characteristics, as well as the geographic location, size, and use of water of the plantings and other vegetation. [ABSTRACT FROM AUTHOR]

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Copyright of Brazilian Journal of Agricultural Sciences / Revista Brasileira de Ciências Agrárias is the property of Universidade Federal Rural de Pernambuco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Floresta is the property of Revista Floresta and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Brazilian Journal of Agricultural Sciences / Revista Brasileira de Ciências Agrárias is the property of Universidade Federal Rural de Pernambuco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Floresta is the property of Revista Floresta and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)