Droughts in São Paulo: challenges and lessons for a water-adaptive society

Souza, Felipe Augusto Arguello; Mohor, Guilherme Samprogna; Arias, Diego Alejandro Guzmán; Buarque, Ana Carolina Sarmento; Taffarello, Denise; Mendiondo, Eduardo Mário

doi:10.1080/1573062x.2022.2047735

Cited by 5 publications

(2 citation statements)

References 67 publications

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“…Water-related disasters (both droughts and floods) have acquired global attention due to their impacts on vulnerable communities and their increasing occurrence in the face of climate change [26,27], and this is also observed in Brazil [28][29][30]. According to Souza et al [31], there are over 40,000 areas at risk of hydrological disasters in Brazil, which together encompass around 120 million people and are responsible for 60% of the gross domestic product. Despite national regulations, local efforts to build resilience to floods, landslides, droughts, biodiversity loss, and energy consumption are slow.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Time Series Models for Mean Discharge Modeling and Forecasting in a Sub-Basin of the Paranaíba River, Brazil

Costa,

Menezes Filho,

Canales

et al. 2023

Hydrology

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Stochastic modeling to forecast hydrological variables under changing climatic conditions is essential for water resource management and adaptation planning. This study explores the applicability of stochastic models, specifically SARIMA and SARIMAX, to forecast monthly average river discharge in a sub-basin of the Paranaíba River near Patos de Minas, MG, Brazil. The Paranaíba River is a vital water source for the Alto Paranaíba region, serving industrial supply, drinking water effluent dilution for urban communities, agriculture, fishing, and tourism. The study evaluates the performance of SARIMA and SARIMAX models in long-term discharge modeling and forecasting, demonstrating the SARIMAX model’s superior performance in various metrics, including the Nash–Sutcliffe coefficient (NSE), the root mean square error (RMSE), and the mean absolute percentage error (MAPE). The inclusion of precipitation as a regressor variable considerably improves the forecasting accuracy, and can be attributed to the multivariate structure of the SARIMAX model. While stochastic models like SARIMAX offer valuable decision-making tools for water resource management, the study underscores the significance of employing long-term time series encompassing flood and drought periods and including model uncertainty analysis to enhance the robustness of forecasts. In this study, the SARIMAX model provides a better fit for extreme values, overestimating peaks by around 11.6% and troughs by about 5.0%, compared with the SARIMA model, which tends to underestimate peaks by an average of 6.5% and overestimate troughs by approximately 76.0%. The findings contribute to the literature on water management strategies and mitigating risks associated with extreme hydrological events.

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Section: Introductionmentioning

confidence: 99%

Assessment of Time Series Models for Mean Discharge Modeling and Forecasting in a Sub-Basin of the Paranaíba River, Brazil

Costa,

Menezes Filho,

Canales

et al. 2023

Hydrology

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“…GIS and remote sensing techniques and methods are essential tools for mapping and monitoring flood hazards (Bisht et al, 2016;Antzoulatos et al, 2022;Katipoğlu and Acar, 2022; Pinos and Quesada-Román, 2022; Souza et al, 2022). Currently, the development of flood hazard models has become feasible on a continental and global scale, and their application can be extremely useful for preparing the population and implicitly for reducing the catastrophic impact of these phenomena (Dottori et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Flood Risk of Grasslands in the Mountain Area of Western Romania

MAGUREANU,

SFIRCOCI,

COPACEAN

et al. 2023

LSSD

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Floods, some of the most destructive natural phenomena, are occurring with increasing frequency, against the backdrop of climate change in recent years. Floods affect both built spaces and natural areas, implicitly the lands used as grasslands. In the context outlined above, the purpose of this study is to identify grasslands susceptible to being affected by floods and to group and map them according to the intensity of the manifestation of the flood risk. For the flood risk assessment, both for the entire analyzed area and for the grassland areas, in the GIS environment, seven factors (spatialized in raster format) determining the occurrence of floods were taken into account: land use, altitude, slope, drainage density, rainfall, distance to rivers and distance to roads. The flood vulnerability map of the analyzed territory, implicitly of the grassland areas, obtained by summing up and the weighted participation of the seven variables, was reclassified into five risk classes/areas: no risk or very low risk, low risk, medium risk, high risk and very high risk. It has been shown that the most vulnerable are the surfaces located on land with low slopes, located at low altitudes and in the proximity of water courses. Regarding the areas of grasslands, 50% fall into the classes without flood risk, with very low and low risk, 28% in the moderate risk class, 16% present a high risk and 6% of the grasslands are classified in the risk class very high to floods. From the point of view of practical applicability, it is important to identify and map the grasslands at risk of flooding, so that measures can be taken to mitigate the destructive effects.

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Space-time variations of hydrological drought severities and trends in the semi-arid Euphrates Basin, Turkey

Katipoğlu

Acar²

2022

Stoch Environ Res Risk Assess

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Droughts in São Paulo: challenges and lessons for a water-adaptive society

Cited by 5 publications

References 67 publications

Assessment of Time Series Models for Mean Discharge Modeling and Forecasting in a Sub-Basin of the Paranaíba River, Brazil

Assessment of Time Series Models for Mean Discharge Modeling and Forecasting in a Sub-Basin of the Paranaíba River, Brazil

Flood Risk of Grasslands in the Mountain Area of Western Romania

Space-time variations of hydrological drought severities and trends in the semi-arid Euphrates Basin, Turkey

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