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The objective of this research is to select the best orbital sensor for rainfall estimates (monthly and annual scales) and to analyze the frequency and magnitude of extreme rainfall events and their trends and disruptions based on the use of satellite rainfall product data for the Cananeia–Iguape Coastal System (CICS). Data from four satellite rainfall products were used to identify the correspondence with seven points on the surface of the study area. Statistical metrics were used to identify the best satellite rainfall product. After identifying the sensor with the best performance in estimating orbital precipitation, extreme events were identified by the Standardized Precipitation Index (SPI) on a one-month (SPI-1), three-month (SPI-3), and twelve-month (SPI-12) scale. Trend and rupture detection in the time series were performed using different statistical techniques (Mann–Kendall, Pettitt, Standard Normal Homogeneity Test, or Buishand test). Among the satellite rainfall products, CHIRPS had the best measurements for the analyzed points on the surface. The year 1983 was characterized as very rainy, also marked by the occurrence of El Niño, and was marked by the rupture of the rains at all points (IDs 1, 2, 3, 4, 5, 6, and 7) analyzed in the month of June. The decrease in monthly rainfall was more significant in the months of February (at points IDs 1, 2, 3, 5, and 7) and April (IDs 1, 3, 5, and 7). Decreased rainfall may cause CICS mangrove shrinkage. These results showed the importance of studying rainfall in an area with mangroves in order to understand the dynamics of vegetation in the face of climate change. [ABSTRACT FROM AUTHOR]

We applied the informational approach of the Fisher‐Shannon method to study the time series of Standardized Precipitation Index (SPI) derived from monthly rainfall data at 133 gauging stations in Northeast (NE) Brazil. The climate in the study region ranges from tropical humid in the coastal area Zona de Mata to tropical semiarid inland Sertão, passing through a sub‐humid transition region Agreste. The time span is from 1962 to 2012, and SPI was calculated for 1, 3, 6, and 12 ‐ month time scales. We calculate information quantifiers Shannon entropy power (SEP) and Fisher information measure (FIM) that quantify signal disorder and structural organization, respectively, and define its position in the Fisher Shannon plane (FS). We find that the SPI‐1 series that describes short term dry/wet conditions display a higher degree of organization (higher FIM) and a lower degree of disorder (lower SEP) than SPI's that describe medium and long term conditions (SPI‐3, SPI‐6, and SPI‐12). By analysing the spatial distribution of information quantifiers, we find that short term dry/wet conditions (SPI‐1) show the lowest disorder and highest organization degree in the deep inland Sertão region and highest disorder and lowest organization degree in the coastal Zona de Mata region, while long term conditions (SPI‐12) show the opposite trend. For medium‐term conditions (SPI‐3 and SPI‐6), the SEP is highest and FIM lowest in the transition sub‐humid Agreste region. Our findings indicate that information theory‐based methods, particularly FS have the potential to discriminate among different climatic regimes. [ABSTRACT FROM AUTHOR]

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Droughts are natural events that can cause water scarcity and can consequently have undesired environmental, social and political effects. Because droughts are related to land use and land cover modifications, satellite images are used to monitor and identify drought episodes through indices as Standardized Precipitation Index based on rainfall data and vegetation-based indices as Normalized Difference Vegetation Index (NDVI). Changes in vegetation cover have as impact the increasing of the land surface temperature (LST) that is a significant indicative of drought occurrence. This work explored the NDVI-LST relation through the Vegetation Health Index (VHI) in a tropical environment in Tietê River, State of São Paulo, Brazil, in order to assess changes in vegetation condition in two periods (2000 and 2014). Results showed that stressed areas are coincident with areas presenting high rate of modification in land cover; this areas presented low values of VHI and high values of LST. The worst conditions are verified in 2014, the same period of the most severe drought occurrence that reduced storage capacity in reservoirs in Tietê River. [ABSTRACT FROM AUTHOR]

The proper isolation of climate effects over the water resources needs accurate knowledge of the precipitation regime. The Urubupungá Hydroelectric Cascade catchment area (UHC) overlaps more than half Itaipu Hydroelectric Plant catchment area in the Paraná River, in Brazil, which recently faced its first ever predicted water emergency. This study determines the spatiotemporal patterns of both droughts and excessive precipitations in the UHC catchment area with the principal component analysis (PCA) and constant wavelet analysis (CWT) and their global teleconnections with composite analysis and cross-wavelet analysis (XWT). The precipitation data used include 166 rain gauges with 42 years length (1976–2017) and were indexed by the Standardized Precipitation Index (SPI) during the dry season, the wet season and the water year. The rotation of Empirical Orthogonal Functions (EOF) with the varimax method revealed five sub-regions of temporal patterns in the study area. The dry season was the only that showed consistent EOF in all sub-regions, whose temporal pattern showed gradual and instant changes both concentrated northern and instant changes mostly in the 1990 decade. The composite analysis presented both positive and negative anomalies directly related with precipitations over two atmospheric indices, which are the Pacific Decadal Ocean and the Atlantic Multidecadal Ocean. The teleconnections of UHC with atmospheric indices of the Antarctic continent oscillations should be deeply investigated, since it had strong influence in XWT analysis but a slightly behavior in the composite analysis. • The dry season over the upper Parana River basin has five distinct sub-regions of patterns and teleconnections. • The Northern sub-region concentrates the significant precipitation losses. • The Atlantic Ocean teleconnections strongly dictates the intensity of the convergence zone system over the study area. • The Atlantic Ocean teleconnections most pairedly dictates precipitations all over the study area. [ABSTRACT FROM AUTHOR]

The objective of the present study is to characterize the drought occurrences in a region comprising Paraguay, southern Brazil and northeastern Argentina. To recognize the drought occurrences the standardized precipitation index at the time-scales of 3 and 6 months was applied to the rainfall records from 1961 to 2011 at 51 rain gauges located in that region. After a drought regionalization using principal component analysis, a new approach, the Kernel occurrence rate estimation method coupled with bootstrap confidence band was used to quantify yearly drought occurrence rates. The study also includes the results of an additional and new approach based on rainfall threshold surfaces aimed at recognizing and monitoring the drought occurrence at the early stages of their development. For both time-scales, the study allowed identification of some spatial homogeneous regions regarding the severe droughts. In some of those regions, trends in the severe drought frequency occurrence were identified. The rainfall threshold surfaces, besides providing an adequate interpretation of the meaning of the standard precipitation index, can be quite easily and reliably utilized to identify the drought episodes. [ABSTRACT FROM AUTHOR]

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We analyze trend and persistence in Standardized Precipitation Index (SPI) time series derived from monthly rainfall data at 133 gauging stations in Pernambuco state, Brazil, using a suite of complementary methods to address the spatially explicit tendencies, and persistence. SPI was calculated for 1-, 3-, 6-, and 12-month time scales from 1950 to 2012. We use Mann–Kendall test and Sen's slope to determine sign and magnitude of the trend, and detrended fluctuation analysis (DFA) method to quantify long-term correlations. For all time scales significant negative trends are obtained in the Sertão (deep inland) region, while significant positive trends are found in the Agreste (intermediate inland), and Zona da Mata (coastal) regions. The values of DFA exponents show different scaling behavior for different time scales. For short-term conditions described by SPI-1 the DFA exponent is close to 0.5 indicating weak persistency and low predictability, while for medium-term conditions (SPI-3 and SPI-6) DFA exponents are greater than 0.5 and increase with time scale indicating stronger persistency and higher predictability. For SPI-12 that describes long-term precipitation patterns, the values of DFA exponents for inland regions are around 1, indicating strong persistency, while in the shoreline the value of the DFA exponent is between 1.0 and 1.5, indicating anti-persistent fractional Brownian motion. These results should be useful for agricultural planning and water resource management in the region. [ABSTRACT FROM AUTHOR]

This study aimed to understand the perception of drought among farmers, in order to support decision-making in the water allocation process. This study was carried out in the Tabuleiro de Russas irrigated perimeter, in northeast Brazil, over the drought period of 2012–2018. Two analyses were conducted: (i) drought characterization, using the Standardized Precipitation Index (SPI) based on drought duration and frequency criteria; and (ii) analysis of farmers' perceptions of drought via selection of explanatory variables using the Random Forest (RF) and the Decision Tree (DT) methods. The 2012–2018 drought period was defined as a meteorological phenomenon by local farmers; however, an SPI evaluation indicated that the drought was of a hydrological nature. According to the RF analysis, four of the nine study variables were more statistically important than the others in influencing farmers' perception of drought: number of cultivated land plots, farmer's age, years of experience in the agriculture sector, and education level. These results were confirmed using DT analysis. Understanding the relationship between these variables and farmers' perception of drought could aid in the development of an adaptation strategy to water deficit scenarios. Farmers' perception can be beneficial in reducing conflicts, adopting proactive management practices, and developing a holistic and efficient early warning drought system. [ABSTRACT FROM AUTHOR]