Although the single threshold is still considered a suitable and easy-to-do technique to extract water features in spatiotemporal analysis, it leads to unavoidable errors. This paper uses an enumerative search to optimize thresholds over satellite-derived modified normalized difference water index (MNDWI). We employed a cross-validation approach and treated accuracy as a random variable in order to: (a) investigate uncertainty related to its application; (b) estimate non-optimistic errors involving single thresholding; (c) investigate the main factors that affect the accuracy’s model, and (d) compare satellite sensors performance. We also used a high-resolution digital elevation model to extract water elevations values, making it possible to remove topographic effects and estimate non-optimistic errors exclusively from orbital imagery. Our findings evidenced that there is a region where thresholds values can vary without causing accuracy loss. Moreover, by constraining thresholds variation between these limits, accuracy is dramatically improved and outperformed the Otsu method. Finally, the number of scenes employed to optimize a single threshold drastically affects the accuracy, being not appropriate using a single scene once it leads to overfitted threshold values. More than three scenes are recommended.

As mudanças no uso e na ocupação do solo, provocadas pelas ações antrópicas, têm gerado grandes impactos nas paisagens. Esses impactos podem ser mitigados através do monitoramento do uso e da cobertura do solo utilizando-se informações espaço-temporais das modificações ocorridas na paisagem. Este trabalho apresenta uma análise espaço-temporal detalhada da dinâmica do uso e ocupação do solo da bacia hidrográfica do riacho São Paulo, localizada na região semiárida do Estado de Pernambuco, entre os anos de 1991 e 2010. Partindo da classificação de três imagens de satélite dos anos de 1991, 2000 e 2010, foram utilizadas matrizes de transição, associadas à álgebra de mapas e métricas da paisagem. Os resultados mostraram que durante o período estudado as classes de uso e ocupação do solo passaram por uma grande transição, com a substituição progressiva das áreas de vegetação de caatinga aberta por áreas com pastagem/agricultura. Junto com o rápido crescimento da classe pastagem/agricultura, a paisagem predominante de vegetação nativa foi sendo substituída por uma paisagem cada vez mais devastada, heterogênea e fragmentada, como mostraram os índices das métricas da paisagem.

The goal of this study was to validate soil moisture data from Soil Moisture Ocean Salinity (SMOS) using two in situ databases for Pernambuco State, located in Northeast Brazil. The validation process involved two approaches, pixel-station comparison and areal average, for three regions in Pernambuco with different climatic characteristics. After validation, the SMOS data were used for drought assessment by calculating soil moisture anomalies for the available period of data. Four statistical criteria were used to verify the quality of the satellite data: Pearson correlation coefficient, Willmott index of agreement, BIAS, and root mean squared difference (RMSD). The average RMSD calculated from the daily time series in the pixel and the areal assessment were 0.071 m³m⁻³ and 0.04 m³m⁻³, respectively. Those values are near to the expected 0.04 m³m⁻³ accuracy of the SMOS mission. The analysis of soil moisture anomalies enabled the assessment of the dry period between 2012 and 2017 and the identification of regions most impacted by the drought. The driest year for all regions was 2012, when the anomaly values achieved −50% in some regions. The use of SMOS data provided additional information that was used in conjunction with the precipitation data to assess drought periods. This may be particularly relevant for planning in agriculture and supporting decision makers and farmers.

Water availability for a range of human uses will increasingly be affected by climate change, especially in the arid and semiarid tropics. The main objective of this study is to evaluate the infrastructure sufficiency in meeting water demand under climate-induced socio-hydrological transition in the Capibaribe River basin (CRB). The basin has experienced spatial and sectoral (agriculture-to-urban) reconfiguration of water demands. Human settlements that were once dispersed, relying on intermittent sources of surface water, are now larger and more spatially concentrated, which increases water-scarcity effects. Based on the application of linked hydrologic and water-resources models using precipitation and temperature projections of the IPCC SRES (Special Report: Emissions Scenarios) A1B scenario, a reduction in rainfall of 26.0% translated to streamflow reduction of 60.0%. We used simulations from four members of the HadCM3 (UK Met Office Hadley Centre) perturbed physics ensemble, in which a single model structure is used and perturbations are introduced to the physical parameterization schemes in the model (Chou et al., 2012). We considered that the change of the water availability in the basin in the future scenarios must drive the water management and the development of adaptation strategies that will manage the water demand. Several adaptive responses are considered, including water-loss reductions, wastewater collection and reuse, and rainwater collection cisterns, which together have potential to reduce future water demand by 23.0%. This study demonstrates the vulnerabilities of the infrastructure system during socio-hydrological transition in response to hydroclimatic and demand variabilities in the CRB and also indicates the differential spatial impacts and vulnerability of multiple uses of water to changes over time. The simulations showed that the measures proposed and the water from interbasin transfer project of the São Francisco River had a positive impact over the water supply in the basin, mainly for human use. Industry and irrigation will suffer impact unless other measures are implemented for demand control.