ABSTRACT The goal of this paper was to apply a method for the delineation of vegetation homogeneous zones (HZs) to map the profitability of cotton ( Gossypium sp.) using NDVI (Normalized Difference Vegetation Index) data from RPA imagery. Two irrigated cotton crops, at the FAU (103 ha) and FRP farms (106 ha), located in the western region of Bahia State, Brazil, were studied. The NDVI images were classified into three HZs: “high”, “medium” and “low” plant vigor; using the k-means clustering method. In each HZ the yield was measured, and the profitability estimated. In FAU we found that the lower the HZ’s NDVI values, the lower its profitability, because there was profit in the “high vigor” HZ, of US$ 829.40 ha-1, and loss in the “low vigor” HZ, of about US$ ‒1.256.09 ha-1 (‒251.44% compared with the “high vigor”). In the FRP plantation, the lower the NDVI values, the lower the loss of the plantation, as there were losses in all HZs: from “high” to “low vigor” HZ, the percentage difference in profitability was ‒343.43%. Thus, the use of a low-cost modified near-infrared Canon S100 on an RPA enabled the mapping of crop profitability, aiding the search for the factors behind yield variability.

Abstract The knowledge of the frequency and magnitude of low flow events is necessary to mitigate social, economic and ecological impacts inside the basin. However, the measurement network in Brazil is still restricted to large drainage areas, while basins with less than 300 km2 remain ungauged. Among different flow estimation methods, we used a rainfall-runoff model designed specifically to estimate flow rates during the dry season in small ungauged basins: the Silveira Method (SM). We tested the model performance for the São Bartolomeu river basin (Minas Gerais, Brazil), a small ungauged basin that experienced severe droughts and water supply shortages in 2014-2016. We tested eleven different scenarios based on the time and duration of drought periods used to estimate the model parameters. In the best scenario, the model underestimated low flow rates by 31% for Q95 and was considered suitable to predict local low flow. Finally, the model results suggest that a water volume higher than the river can support has been granted concession during the dry season, which may lead to an unsustainable water supply scenario soon. This result showed the capacity of SM as a complementary tool for the evaluation of water potential in small basins.

ABSTRACT This study aimed to use global sensitivity analysis (GSA) methods to evaluate the sensitivity of the SAC-SMA hydrologic model parameters in the estimation of daily flows of the Piracicaba river basin. The study was carried out in three sections of flow monitoring of the Piracicaba river basin, with an area of 5,304.0 km2 and located in the State of Minas Gerais, Brazil. For the global sensitivity analysis of the SAC-SMA model, the Morris and Sobol methods were used. The model parameters showing high sensitivity were UZFWM, which represents the free water depth in the upper zone of the soil and interferes with the subsurface flow and groundwater aquifer recharge; ADIMP, which represents the additional impermeable area of the basin and interferes with the direct runoff generation; and LZPK, LZSK, LZFPM, and LZFSM, which are related to the base flow of the basin. The results showed that most of the SAC-SMA model parameters do not provide expressive variations in the output variable, most of the SAC-SMA model parameters with high sensitivity are the intervenient in the base flow, and the Morris method should be used as a preliminary analysis to the use of the Sobol method.

Abstract: In order to characterize the occurrence and intensity of droughts in the Doce River Basin, as well as to develop a system for its classification, four different drought indexes were evaluated: Percent of Normal Precipitation (PNP), Deciles Method (DM), Rainfall Anomaly Index (RAI) and Standardized Precipitation Index (SPI). The indices were calculated annually, based on precipitation data from 89 rainfall stations of the Brazilian National Water Agency (ANA). Nine analysis units (AUs) were determined in the basin and the Thiessen Polygons method was used to obtain the average precipitation in the respective drainage areas. The indices were calculated for each AU and then related to the drought intensity classes. An overall classification of the indices was proposed for the drought classification system for a 30-year base period, from 1985 to 2015. The most critical hydrological years of the Doce River Basin in relation to the drought were 1994/1995, 2000/2001 and 2014/2015, the latter being the most critical of the last 30 years. The results show that the annual drought classification system proved to be efficient in the identification of events, allowing to verify that the Doce River Basin presents a severe climatic drought condition, on average, every seven years.

ABSTRACT Evaporation rates in reservoirs influence the volume of water available for multiple uses. Thus, the objective of this study was to estimate the evaporation rates and the evaporated volumes per unit time in the Tucuruí-PA and Lajeado-TO reservoirs based on the methods in Linacre (1993), Kohler et al. (1955), Morton (1983), Bruin & Keijman (1979) and Penman (1948) method was adopted as the standard. The mean annual evaporation rates in the Tucuruí and Lajeado reservoirs, estimated by the Penman method, were similar, with values of 1,784 mm and 1,882 mm, respectively. None of the alternative analyzed methods could be used to estimate the mean annual evaporation in the Tucuruí and Lajeado reservoirs and could not replace the Penman method. However, the Linacre (1993) and Bruin & Keijman (1979) methods could be used to estimate monthly evaporation during the dry season in Tucuruí. The mean evaporated volume per unit time and the mean net evaporated volume per unit time in the Tucuruí reservoir correspond to 120% and 50%, respectively, of the total water demand in the Tocantins-Araguaia region, while the mean evaporated volume per unit time and the mean net evaporated volume per unit time in the Lajeado reservoir correspond to 120% and 50%, respectively, of the total water demand in the basin.

Dentre as características da precipitação aquela que expressa sua capacidade em promover a erosão do solo é denominada erosividade das chuvas (R), sendo comumente representada pelos índices EI30 e KE>25. A determinação destes indices requer a disponibilidade de series de dados pluviográficos, que são de difícil acesso no Brasil. O presente artigo descreve o uso de séries sintéticas de dados pluviográficos para calcular os índices EI30 e KE>25 no Estado do Espírito Santo (Brasil). Redes neurais artificiais (ANNs) também foram desenvolvidas para promover a interpolação espacial dos valores de R no Espírito Santo. Os valores calculados para os índices EI30 e KE>25 foram próximos àqueles encontrados em áreas pluviométricamente homegêneas próximas, indicando a aplicabilidade do uso de séries sintéticas de dados pluviográficos. As redes neurais artificiais consistiram em interpoladores espacial melhores que os métodos de inverso da potência da distância e krigagem para a espacialização dos índices de erosividade no Espírito Santo.

The rainfall parameter that expresses the capacity to promote soil erosion is called rainfall erosivity (R), and is commonly represented by the indexes EI30 and KE>25. The calculations of these indexes requires pluviographical records, that are difficult to obtain in Brazil. This paper describes the use of synthetic rainfall series to compute EI30 and KE>25 in Espírito Santo State (Brazil). Artificial neural networks (ANNs) were also developed to spatially interpolate R values in Espírito Santo. EI30 and KE>25 indexes values were close to those calculated on a homogeneous area according to the similarity of rainfall distribution; indicating the applicability of the use of synthetic rainfall series to estimate the R factor. ANNs had a better performance than Inverse Distance Weighted and Kriging to spatially interpolate rainfall erosivity values in the State of Espírito Santo.

Desenvolveu-se um programa computacional que permite a aplicação da metodologia para geração de séries sintéticas de precipitação desenvolvida por OLIVEIRA (2003). O desenvolvimento do aplicativo foi viabilizado pela elaboração de um algoritmo computacional em ambiente de programação "Borland Delphi 6.0". Os dados de entrada necessários são provenientes de banco de dados no formato padronizado pela Agência Nacional de Águas (ANA) com registros pluviométricos diários provenientes de estações meteorológicas. A partir dessas informações, o programa computacional é capaz de gerar séries sintéticas de precipitação diária contendo o total precipitado em milímetros, a duração do evento em horas, o tempo padronizado de ocorrência da intensidade máxima instantânea e a intensidade máxima instantânea padronizada. A série sintética gerada é armazenada em arquivos no formato "Texto" que podem ser acessados posteriormente por outros aplicativos e/ou planilhas eletrônicas. Além dos arquivos, são apresentadas várias informações na forma de gráficos e quadros, facilitando a avaliação do desempenho da metodologia desenvolvida.

A computational model was developed to generate synthetic series of rainfall using the method developed by OLIVEIRA (2003). The software was developed in Borland Delphi 6.0 environment. The input data come from the daily precipitation data in the standardized format of the National Water Agency (ANA). The software is capable to generate synthetic series of daily rainfall containing the amount and the duration of the rainfall, and the standardized event time of the maximum instantaneous intensity. The generated synthetic series are stored in text-formatted files that may be accessed by others softwares and/or electronic datasheets. There were also presented graphs and tables format, to easily evaluate the performance of the method developed.