Southeast Brazil Research Articles

Specialization in Ciidae-host fungi communities in two Atlantic forest remnants of Southeast Brazil

Mycophagy, the practice of feeding on fungal structures or plant material decomposed by fungal enzymes, is one of the oldest feeding habits of beetles. A notable family of beetles with a strict association with fungi throughout their life cycle is Ciidae. Members of this family use fungi as shelter, food, and sites for copulation and oviposition, making them true mycetobionts. The fungi associated with ciids belong to the phylum Basidiomycota and play a crucial role in nutrient cycling by degrading wood and decomposing cellulose, hemicellulose, and lignin. Ciids contribute significantly to the degradation of these basidiomes, thereby preventing their accumulation and enhancing nutrient availability in forest ecosystems. Although interactions between Ciidae beetles and their host fungi have been relatively well-studied, research on these interactions in the neotropics remains scarce. In this study, we investigated the interactions between ciids and their host fungi in two forest remnants of the Atlantic Forest biome. Using ecological network analysis, we assessed the frequency of occurrence of ciid species and calculated key indices for describing community structure: connectance, web asymmetry, links per species, nestedness, robustness, and specialization. This allowed us to compare the structural patterns of the two Ciidae-fungi networks. Our results revealed that the main host fungal species were the same in both communities, but differences in host usage by ciids were observed, reflecting the availability of fungal basidiomes. These differences led to distinct network structures. Most Ciidae species were found to be generalists, exploiting host fungi according to their availability.

Rare Pleurotus species with veiled basidiomata from the Neotropics: neotypification of Pleurotus magnificus and epityfication of Pleurotus rickii

Knowledge of Pleurotus in Brazil dates back to the 19th century, when European mycologists studied and described numerous Neotropical taxa. Some of these long-described species remain poorly known, mostly due to the lack of recent records, detailed morphological descriptions, and molecular data. During field surveys in Southeast and Southern Brazil, specimens of two rare Pleurotus species with veiled basidiomata, i.e. P. magnificus and P. rickii, were collected. These species are recorded for the first time in the state of Santa Catarina, Brazil, and P. magnificus for the first time in the states of Minas Gerais, Paraná and São Paulo. Updated and detailed morphological descriptions are provided. DNA sequences of the ITS and nLSU molecular markers were obtained for both species, and phylogenetic analyses were conducted to explore their relationships within Pleurotus. A neotype is designated for P. magnificus, and a lectotype and epitype are designated for P. rickii.

Multi-Criteria Analysis for Geospatialization of Potential Areas for Water Reuse in Irrigated Agriculture in Hydrographic Regions

As the climate crisis progresses, droughts and the seasonal availability of fresh water are becoming increasingly common in different regions of the world. One solution to tackle this problem is the reuse of treated wastewater in agriculture. This study was carried out in two significant hydrographic regions located in the southeast of Brazil (Mogi Guaçu River Water Management Unit—UGRHI-09 and Piracicaba River Basin—PRB) that have notable differences in terms of land use and land cover. The aim of this study was to carry out a multi-criteria analysis of a set of environmental attributes in order to classify the areas under study according to their levels of soil suitability and runoff potential. The integrated analysis made it possible to geospatialize prospective regions for reuse, under two specified conditions. In the UGRHI-09, condition 1 corresponds to 3373.24 km2, while condition 2 comprises 286.07 km2, located mainly in the north-western and central-eastern portions of the unit. In the PRB, condition 1 was also more expressive in occupational terms, corresponding to 1447.83 km2; and condition 2 was perceptible in 53.11 km2, predominantly in the central region of the basin. The physical characteristics of the areas studied were decisive in delimiting the areas suitable for the reuse of treated wastewater.

The Emergence of Cat-Transmitted Sporotrichosis Driven by Sporothrix brasiliensis in Piauí, Brazil.

In Brazil, the emergence of feline sporotrichosis, a neglected subcutaneous mycosis primarily transmitted by cats and caused by the fungus Sporothrix brasiliensis, has been monitored via molecular tools. This approach underscores the geographic expansion of this disease and highlights the critical role of molecular surveillance in understanding its epidemiology and guiding public health interventions. We investigated three domestic cats (Felis catus) with multiple skin lesions in Picos, Piauí, Brazil. The cats were examined, and samples were collected for laboratory diagnosis, including cytological evaluation, fungal culture, and molecular characterisation. The molecular analysis involved a one-tube multiplex probe-based qPCR assay for the diagnosis of Sporothrix species, mating-type determination, and amplified fragment length polymorphism (AFLP, EcoRI-GA/MseI-AG) to assess genetic similarity and potential origin. All three cats were diagnosed with sporotrichosis caused by the hypervirulent S. brasiliensis. A probable case of zoonotic transmission has been reported in a 12-year-old girl who developed Parinaud oculoglandular syndrome after contact with one of the cats with sporotrichosis. The molecular analysis revealed that the cat isolates were MAT 1-2 and formed a single cluster according to the AFLP analysis, suggesting direct transmission (cat-cat) and a potential founder effect. The isolates were also closely related to strains from Pernambuco and Southeast Brazil, indicating a possible introduction from these regions. Identifying S. brasiliensis in Piauí emphasises the need for increased awareness and control measures to prevent further spread. The predominance of the MAT1-2 idiomorphs and the genetic similarity among outbreak isolates suggest clonal expansion, which could have significant implications for public health and veterinary practices. Considering its zoonotic potential and environmental adaptability, a One Health approach is crucial for managing and controlling the spread of cat-transmitted sporotrichosis.

Diversity of Diptera and their parasitoids associated with Inga vera Willd. (1806) (Fabaceae) with new host record in Minas Gerais, Brazil

Diptera belonging to four different families, as well as four associated parasitoids were reared from fruits of Inga vera Willd. (Fabaceae) in Lavras, Minas Gerais, southeast Brazil. We collected 450 fruits from five trees of I. vera between 2020 and 2021 in various localities situated within the University Federal of Lavras. We reared specimens belonging to four different dipteran families: Anastrepha distincta Greene (Tephritidae), Asteromyia sp. (Cecidomyiidae), Drosophila zottii Vilela (Drosophilidae), and Neosilba pendula (Bezzi) (Lonchaeidae). Lopheucoilasp.(Hymenoptera: Figitidae) probably is a parasitoid of N. pendulawhereas Eupelmus sp. (Hymenoptera: Eupelmidae), and two species of Sycophila (Hymenoptera, Eurytomidae) appear to be parasitoids of Asteromyia sp.. We additionally conducted molecular characterization using the DNA barcoding locus for the majority of the species reared in this study. This study provides valuable insights into the biology and ecology of frugivorous flies in Brazil, and sheds light on potential biological control agents, enabling better management practices.

Spatiotemporal Evolution of the Yellow Fever Epidemic in Southeast Brazil from 2016 to 2019.

Background: Yellow fever (YF) is a zoonotic disease transmitted by mosquitoes among humans and nonhuman primates. Although urban YF is eradicated, the sylvatic YF has reemerged in some areas of Brazil in the twenty-first century. From 2016 to 2019, a sylvatic YF epidemic occurred in Southeast Brazil, where it had been eradicated in the 1940s. Methods: This study's objective was to describe the epidemic in the states of the Southeast region, based on descriptive, cluster, and mobility analyses. Results: Both the descriptive and cluster analyses showed that the YF cases spread from the state of Minas Gerais southward, causing peaks in cases during the summer months. None of the state capitals was included in the clusters, but the connectivity between the municipalities in Greater Metropolitan São Paulo highlighted potential paths of spread. Despite differences in sociodemographic profiles between the Southeast and North of Brazil (the latter region considered endemic), the epidemiological profile was similar, except for patients' occupation, which was not related to rural work in the Southeast. Conclusion: The results contributed to our understanding of the paths by which YF spread across Southeast Brazil and the epidemiological profile in an area that had gone decades without autochthonous cases.

Protocol for an ambidirectional cohort study on long COVID and the healthcare needs, use and barriers to access health services in a large city in Southeast Brazil

IntroductionPost-COVID-19 condition, or syndrome, also known as long COVID, is an infection-associated chronic condition that can develop after a SARS-CoV-2 infection and last at least 3 months to years. Despite...

Excess mortality associated with chikungunya epidemic in Southeast Brazil, 2023

The chikungunya virus (CHIKV) was first detected in Brazil in 2014 and has since caused major epidemics. In 2023, a major chikungunya epidemic occurred in Minas Gerais, one of the most populous states in the country. We analyzed the North and Northeast Health Macroregions of Minas Gerais, with 2.5 million inhabitants. The study used epidemiological data from the Ministry of Health’s laboratory surveillance, disease notification and mortality systems. A robust Poisson regression model was constructed to estimate expected monthly mortality. Excess deaths were calculated by comparing observed deaths with model estimates during the epidemic period. During the epidemic, there were 890 excess deaths attributed to chikungunya, translating into a mortality rate of 35.1/100,000 inhabitants. The excess mortality rate was significantly 60 times higher than the deaths reported by surveillance, with only 15 confirmed deaths. The correlation between excess deaths and laboratory-confirmed chikungunya cases was strong, while the correlation with dengue and COVID-19 was not statistically significant. The results highlighted the serious underestimation of chikungunya mortality by epidemiological surveillance. During the same year, only 420 chikungunya deaths were reported by all PAHO member countries. Routine epidemiological surveillance systems cannot capture the full impact of this disease. Excess mortality is a key measure for understanding the impact of epidemics, as demonstrated by COVID-19 and influenza pandemics. The study highlights the need for complementary tools to traditional surveillance to better assess impacts on morbidity and mortality and support priority setting in public health interventions.

Comparison of the Performance of Commercially Available Quantitative Viral Load Assays Using Clinical Samples from Patients from Regions Where Distinct HIV-1 Subtypes Co-Circulate: Potential Implications for Patient Management.

HIV RNA plasma viral load (VL) is the standard surrogate marker to monitor response to antiretroviral treatment (ART). We compared the linearity, repeatability, and concordance of six commercially available HIV RNA VL platforms using clinical samples from patients from Brazilian sites where different HIV-1 subtypes co-circulate. A total of 150 plasma samples from each city were collected in Curitiba, Southern Brazil (subtype C), São Paulo (subtype B), and Santos (BF recombinants), Southeast Brazil. Platforms were VERSANT® Siemens HIV RNA 1.0 (kPCR); VERSANT® Siemens HIV-1 RNA 3.0 (bDNA); Abbott Real-Time HIV-1; NucliSens EasyQ® HIV-1 v2.0 Biomerieux; COBAS® TaqMan®, Roche; and artus HIV Virus-1 RT-PCR, QIAGEN. OptiQuant HIV-1 RNA quantification panel was used to compare VL linearity, using samples containing 50, 500,5,000, 50,000, 500,000, and 5,000,000 HIV copies/mL. HIV RNA panels with subtypes A, B, C, D, F, G, H, circulating recombinant form (CRF)1, and CRF2 were utilized. A high degree of linearity and repeatability was demonstrated for all platforms. When compared with a subtype B reference sample, 17 of 54 (31.48%) samples diverged by more than 0.5 log10 copies/mL. Except for the Roche platform, all platforms underestimated subtype C VLs. A total of 743 (82.6%) valid results were obtained with samples from São Paulo, 707 (78.6%) from Santos, and 673 (74.8%) from Curitiba (São Paulo vs. Santos, p = .03; São Paulo vs. Curitiba, p = .00006; Santos vs. Curitiba, p = .06). The number of discordant samples between different methodologies when VL was undetectable in one method and detectable in the other ranged from 1.25% (Abbot vs. Siemens) to 44.8% (Abbott vs. Biomerieux). Finding samples with undetectable VL in one method and a high VL in another might have important individual and public health consequences. Standardization of VL measurements, particularly for non-B subtypes infections, especially subtype C, is necessary to maximize the individual and public health benefits of ART globally.

Enhancing forensic applications through the mineralogy of clays in surface soil horizon: A case study of baixada fluminense, Southeast Brazil

Clay minerals possess chemical, mineralogical, and crystallographic characteristics that make them potential forensic markers, as they can reflect geochemical and weathering processes on a detailed scale. Therefore, this study aims to use the mineralogy of the clay fraction to distinguish samples from the surface soil horizons in four municipalities in Brazil, to assess the possibility of geographical tracking for forensic applications. Studies characterizing clays in environments with a variety of soil types in forensic pedology are necessary but still in their early stages. Furthermore, due to the high incidence of homicides involving the displacement of bodies in the region and the low resolution of these crimes, this research is crucial for geoscientific applications, with the potential for global replication. The samples were separated by centrifugation and analyzed using X-ray diffractometry, X-ray fluorescence, and thermogravimetry. Minerals were determined through quantitative mineralogical analyses using Rietveld and Biscaye methods. Additionally, in conjunction with the crystallographic parameters of kaolinite (Full Width at Half Maximum – FWHM), it was possible to form 8 Clay Mineral Assemblages and Gibbsite (CMAG), whose geographical delimitation considered geological and hydrographic aspects. The determination of CMAGs is based on mineralogy and is defined as follows: CMAG 1: kaolinite+(illite); CMAG 2: kaolinite+(gibbsite); CMAG 3: kaolinite + illite + montmorillonite; CMAG 4: kaolinite + illite+(gibbsite); CMAG 5: ordered kaolinite+(illite)+(gibbsite); CMAG 6: kaolinite + gibbsite+(illite); CMAG 7: disordered kaolinite + illite + gibbsite; CMAG 8: kaolinite+(illite)+(chlorite). The results indicate that the quantification of clay minerals in samples from surface soil horizons, FWHM, and the % of Al in goethite can represent valuable tools for forensic pedology. Moreover, through the characterization of iron and titanium (hydr)oxides, it was possible to distinguish samples with a distance of 335 m between them, further expanding the capability to identify the geographical origin of samples, making them potential forensic markers.

Machine Learning Models for the Spatial Prediction of Gully Erosion Susceptibility in the Piraí Drainage Basin, Paraíba Do Sul Middle Valley, Southeast Brazil

Soil erosion is a global issue—with gully erosion recognized as one of the most important forms of land degradation. The purpose of this study is to compare and contrast the outcomes of four machine learning models, Classification and Regression (CART), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Machine (SVM), used for mapping susceptibility to soil gully erosion. The controlling factors of gully erosion in the Piraí Drainage Basin, Paraíba do Sul Middle Valley were analysed by image interpretation in Google Earth and gully erosion samples (n = 159) were used for modelling and spatial prediction. The XGBoost and RF models achieved identical results for the area under the receiver operating characteristic curve (AUROC = 88.50%), followed by the SVM and CART models, respectively (AUROC = 86.17%; AUROC = 85.11%). In all models analysed, the importance of the main controlling factors predominated among Lineaments, Land Use and Cover, Slope, Elevation and Rainfall, highlighting the need to understand the landscape. The XGBoost model, considering a smaller number of false negatives in spatial prediction, was considered the most appropriate, compared to the Random Forest model. It is noteworthy that the XGBoost model made it possible to validate the hypothesis of the study area, for susceptibility to gully erosion and identifying that 9.47% of the Piraí Drainage Basin is susceptible to gully erosion. Furthermore, replicable methodologies are evidenced by their rapid applicability at different scales.

Anurans in the ecotone between the Atlantic Forest and Cerrado in the Campos das Vertentes, southeast Brazil

Knowing the biodiversity of anurans in poorly studied regions, especially those in biomes declining in areaas a result of human activities, such as the Campos das Vertentes in Minas Gerais, Brazil, is essential for developing andimplementing management and conservation strategies for the biota and for monitoring environmental quality. Ourobjective was to inventory the anurans of forest remnants in an ecotonal area between Atlantic Forest and Cerrado inBarroso and Prados Municipalities, Minas Gerais, Brazil. From October 2020 to March 2021, four researchers sampledanurans during three nighttime hours over 24 days for a total of 168 person-hours. We recorded 26 anuran species (16in the Family Hylidae) in 13 genera and seven families. Forest fragments, such as those sampled, are important for theprotection of anurans but are disappearing rapidly, mostly due to conversion to agricultural activities. Reduction oreven local extinctions of anuran populations renders conservation actions urgent.

The influence of major faults and fractures on the development of non-matrix porosity system in a pre-salt carbonate reservoir, Santos Basin – Brazil

Faults and fractures are central for characterizing the permeability distribution in carbonate reservoirs since they act as pathways for diagenetic fluids that often favor intense rock dissolution and permeability. Usually, high permeability zones and fractures are not easily recognized in seismic data due to limited resolution and they are often associated with higher concentrations of hydrocarbons or even significant fluid losses during drilling, thus creating a challenge for hydrocarbon exploration. In the Santos Basin, southeast Brazil, the pre-salt carbonate reservoirs from the Barra Velha Formation (BVE) are the main hydrocarbon producers in Brazilian Atlantic margin and well-known for being extremely heterogeneous, exhibiting complex dual-porosity systems. In this study, we built a conceptual model of these fracture zones and non-matrix porosity formation that helped narrowing the understanding of these complex systems. The characterization of faults and fractures was carried out using seismic, well-logs, and borehole image data to understand the influence of these structures in the porosity formation along the Barra Velha Formation. In the study area, three fault sets were defined (F1, F2, and F3) from seismic data. F1 represents to the larger faults, while the F3 fault set represents the smaller faults related to the reactivation of F1; both sets being oriented NE-SW. The F2 fault set is associated with the rift formation and is oriented to NNE-SSW. These three fault sets compartmentalized the studied area into different domains, each exhibiting distinct fracture sets. The natural open fractures were formed during the reactivation of rift faults and are oriented mainly NW, NNE-NNW, NE, and ENE and were identified across the entire study area, but with different intensity values. The fracture intensity closely relates to the distance from major faults where the wells with the highest fracture intensity occurs located 150–590 m from the larger F1 fault set. Scan-lines were conducted throughout the area to determine the fault width, and an average value of 1.2 km was established. Seven non-matrix porosity classes were characterized and classified into stratigraphically concordant and discordant non-matrix pore types at well scale through borehole image interpretation. The Barra Velha Formation exhibit higher occurrence of stratigraphically discordant non-matrix porosity related to fractured zones while stratigraphically concordant non-matrix porosity is mainly controlled by the paleotopography of the study area. Overall, non-matrix porosity formation tends to follow an orientation that suggests a preferential dissolution flow towards NE and ENE directions. Intervals with higher silica content shows a positive correlation with both fracture intensity and stratigraphically discordant non-matrix porosities. This work provides a conceptual model about the fractures and non-matrix porosity distribution in pre-salt carbonate rocks that can help address some of associated structural and stratigraphic uncertainties during field appraisal and development.

New evidence for superposition of two major Precambrian orogens in southeast Brazil

New evidence for superposition of two major Precambrian orogens in southeast Brazil

Incorporating sex and gender into health research funded by the Brazilian Ministry of Health: lessons learned in 15 years and prospects for change

Incorporating sex and gender differences into health research demonstrates the inequalities in the health of women, men and intersex people. This study analyzed funding provided by the Brazilian Ministry of Health’s Department of Science and Technology (Decit/MS) for research incorporating sex and gender in Brazil between 2004 and 2018, stratified by year, region, funding format, and type of research. This is a descriptive retrospective study based on public secondary data provided by Decit/MS. A total of 171 studies were funded, with a value of 30.5 million PPP$, most conducted in educational and research institutions in Southeast Brazil (78.4%). Stratified analysis revealed no significant difference in the amount of funding provided under different government administrations. The largest investment was for national research funding (57.9%). Ten institutions received most of the financial resources provided (82.8%). The most funded research was on population and public health (62%). The most studied topic was chronic noncommunicable diseases (CNCD) (29%). Investments in research were insufficient and unequally distributed among regions, receiving institutions, and types of research. Government and funding agencies need to implement specific action plans to encourage understanding of sex and gender disparities in the Brazilian health sector.

Sedentary Behavior and Ultra-Processed Food Consumption Associated to BMI Changes in Brazilian Students During COVID-19.

University students experienced significant changes in their routines with the implementation of remote learning during Covid-19 pandemic, including increase in sedentary behavior (SB) time and ultra-processed foods (UPF's) consumption, which may have influenced changes in body mass index (BMI). To evaluate the association between the variation in SB time and UPF's consumption with the variation in BMI, before and during the pandemic, in university students. This is a cross-sectional study, conducted between November 2020 and February 2021, with students from a public university of Southeast of Brazil, who answered an online questionnaire with questions regarding to the period before and during the pandemic. SB was assessed through questions about time spent on TV and electronic devices. A score of the frequency of UPF's consumption was estimated based on the Brazilian Food Guide. Self-reported information on height and body mass was used to calculate BMI. The sample comprised 3390 university students, with an average age of 28.7 (± 10.0) years. Among them, 65.4% were undergraduates, and 66.9% were women. SB time, UPF score, and BMI increased significantly during the pandemic, compared to the previous period. In this population, there was a significant association between increased SB time (β = 0.06; SE = 0.01; p < 0.001) and UPF score (β = 0.08; SE = 0.01; p < 0.001) with an increase in BMI. Changes in SB time and UPF score were associated with an increase in BMI before and during the COVID-19 pandemic in students from a Brazilian University.

Machine learning approaches for mapping and predicting landslide-prone areas in São Sebastião (Southeast Brazil)

This study employs machine learning techniques to map and predict landslide-prone areas in São Sebastião, Brazil, a region susceptible to landslides due to its steep terrain and intense rainfall. We compared five algorithms: Random Forest, Gradient Boosting, Support Vector Machine, Artificial Neural Network, and k-Nearest Neighbors, using various environmental factors as inputs. The Gradient Boosting model performed best, achieving an AUC-ROC of 0.963 and an accuracy of 99.6%. Slope degree, soil moisture index, and relief dissection emerged as the most influential factors in predicting landslide susceptibility. Analysis of land use and land cover changes between 1985 and 2021 revealed significant increases in forest cover and urban areas, with implications for landslide risk distribution. The resulting susceptibility map shows predominantly low-risk areas with scattered high-risk zones, providing crucial information for targeted risk management. This research demonstrates the effectiveness of machine learning in landslide susceptibility mapping and offers valuable insights for disaster risk reduction and urban planning in coastal mountainous regions.

Predicting the drivers of Bothrops snakebite incidence across Brazil: A Spatial Analysis

Snakebite envenoming poses a significant public health challenge on a global basis, affecting millions of people annually and leading to complications that may result in fatalities. Brazil stands as one of the countries most impacted by snakebite envenoming, with snakes of the Bothrops genus being responsible for most bites. The current study aimed to identify the determinants of Bothrops snakebite incidence across different regions of Brazil. An ecological study was conducted using municipality-aggregated data, with snakebite incidence as the dependent variable. The study period comprised the years 2015–2021. We constructed Species Distribution Models (SDMs) for Bothrops species, and information was collected on precipitation, runoff, maximum and minimum temperatures, native forest, historical forest loss, agriculture, and pasture in each Brazilian municipality. These data were employed to assess the association between snakebite incidence and biotic, climatic, and landscape factors. The data were analyzed using Generalized Least Squares (GLS) regression. The SDMs demonstrated good performance. The average annual snakebite incidence during the study period ranged from zero to 428.89 per 100,000 inhabitants, depending on the municipality. Higher incidence rates were concentrated primarily in municipalities in the northern region of the country. In this study, we found that nationwide, areas with extensive native forests and those that have historically experienced significant loss of forest cover exhibited higher snakebite incidence rates. Additionally, areas with higher temperatures and precipitation levels, as well as greater climatic suitability for the species B. jararaca, showed significantly higher snakebite incidence rates in the South and Southeast of Brazil, respectively. These associations may be linked to increased snake abundance and active behavior, as well as to engagement in activities favoring human-snake contact in these areas. The findings of this study can contribute to the improvement of prevention and control strategies for this public health issue in Brazil.

Physical and chemical indicators of soil quality in gully environments, State of Rio de Janeiro (Southeast Brazil)

Physical and chemical indicators of soil quality in gully environments, State of Rio de Janeiro (Southeast Brazil)

Development of DRIP - drought representation index for CMIP climate model performance, application to Southeast Brazil

With the escalating impacts of drought events driven by climate change, reducing the uncertainty of drought projections becomes critical for enhancing risk management and adaptation strategies. This study aimed to develop an index for assessing the performance of CMIP6 Global Climate Models in simulating meteorological drought scenarios across regional hydrological systems, intended to provide more reliable information for management purposes. Named the ‘Drought Representation Index for CMIP Climate Model Performance’ (DRIP), this index evaluates CMIP models' performance to represent drought severity, duration, and return period. DRIP was used to select CMIP models and create an ensemble of the best-performing models (E-DRIP) to improve the reliability of drought projections. E-DRIP was then compared with a general ensemble of available CMIP6 models (E-CMIP). We applied this method in Southeast Brazil, a region known for its climate uncertainties and low predictability; specifically, it was implemented within the Paraíba do Sul River Basin, a nationally strategic watershed in a highly populated and industrialized area, which has recently faced unprecedented drought-related water crises. Results showed that DRIP effectively assessed the individual performance of CMIP models, which exhibited considerable variability, and identified the top-performing models for a multi-model ensemble. Additionally, the E-DRIP ensemble significantly reduced uncertainties in drought projections, achieving an average reduction of 63 % in the study area compared to E-CMIP. Furthermore, the proposed method enables evaluations across any standardized drought index scale, reference period, or threshold, and can be readily adapted to other hydrological systems.