Tools for communicating agricultural drought over the Brazilian Semiarid using the soil moisture index

Soil moisture over the Brazilian semiarid region is presented in different visualizations that highlight spatial, temporal and short-term agricultural risk. The analysis used the Soil Moisture Index (SMI), which is based on a normalization of soil moisture by field capacity and wilting point. The index was used to characterize the actual soil moisture conditions into categories from severe drought to very wet. In addition, the temporal evolution of SMI was implemented to visualize recent trends in short-term drought and response to rainfall events at daily time steps, as new data are available. Finally, a visualization of drought risk was developed by considering a critical value of SMI (assumed as 0.4), below which water stress is expected to be triggered in plants. A novel index based on continuous exposure to critical SMI was developed to help bring awareness of real time risk of water stress over the region: the Index of Stress in Agriculture (ISA). The index was tested during a drought over the region and successfully identified locations under water stress for periods of three days or more. The monitoring tools presented here help to describe the real time conditions of drought over the region using daily observations. The information from those tools support decisions on agricultural management such as planting dates, triggering of irrigation, or harvesting.Peer ReviewedPostprint (published version

Use of SMOS L3 soil moisture data: validation and drought assessment for Pernambuco State, Northeast Brazil

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.Peer ReviewedPostprint (published version

Remote Sensing as a Tool for Agricultural Drought Alert Over the South Region of Brazil

In this study the estimative of the Combined Drought Index (CDI) to identify agricultural drought over Southern Brazil is introduced. This combined drought index is based on a combination of three indicators: Standardized Precipitation Index (SPI), Soil Moisture Anomalies (SMA) and Vegetation Health Index (VHI). The proposed CDI has four levels, watch, warning, alert I and alert II, thus benefiting an increasing degrees of severity. This CDI was applied during the first 6 months of 2020 to different study sites over Southern Brasil, representative of the crop areas. The performance of the CDI levels was assessed by comparison with risk areas. Observations show a good match between these areas and the CDI. Important crop drought events in 2020 were correctly predicted by the proposed CDI in all areas

Impact of soil moisture on crop yields over Brazilian semiarid

The objective of this work was to investigate the relationship between soil water content and rainfall with rice, beans, cassava and corn yields in the semiarid region of Northeast Brazil. Precipitation and modeled soil water content were compared to yields recorded at the county levels in this region. The results were also integrated over the area of the nine States that lie within the officially recognized region of semiarid climate in Brazil. The influence of water balance components was quantified by calculating their correlation coefficient with yields of the different crop species over the municipalities of the region. It was found that rainfall had higher correlation to crop yields over most of the region, while soil water content had lower values of correlation. This result is consistent with the fact that average root depth is 40 cm, lower than the layer of soil used in the model used to estimate soil water content (100 cm). Plants respond better to the precipitation in the top layers of soil, while the water storage in the deep layer of soil might be important only in other temporal and spatial scales of the hydrological cycle.Peer ReviewedPostprint (published version

Estudo de Sensibilidade do Esquema de Superfície SSB a Partir de dados Micrometeorológicos e Biofísicos Obtidos em Área de Caatinga no Nordeste do Brasil

Estudo de sensibilidade do esquema de superfície SSiB apartir de dados micrometeorológicos e biofísicos obtidosem área de caatinga no Nordeste do Brasi

Impactos dos Parâmetros Biofísicos da Vegetação Derivados do Sensor Modis/terra nas Simulações do Balanço de Energia em Área de Caatinga

Considerando a complexa variabilidade sazonal do bioma caatingano Nordeste do Brasil (NEB), torna-se importante, no contextode modelagem da interação biosfera-atmosfera para o NEB, uma caracterizaçãoaprimorada dos parâmetros biofísicos sazonais da vegetação referentesa essa classe da vegetação. Tais parâmetros afetam as interaçõesentre a biosfera terrestre e a atmosfera. Posto isto, o objetivo principaldeste trabalho foi obter uma representação mais realista dos parâmetrosÍndice de Área Foliar e Fração de Cobertura Vegetal para o bioma caatingapor meio de imagens do sensor MODIS/TERRA e avaliar o impactodesses parâmetros nas simulações do balanço de energia na superfície

Calibration of the simplified simple biosphere model (SSiB) for Amazonian pasture and forest sites using LBA data

The parameters of the Simplified Simple Biosphere Model - SSiB were validated and subsequently calibrated for the Fazenda Nossa Senhora Aparecida (62º22'W; 10º45'S) pasture site and the Reserva Biológica do Jaru (62º22'W; 10º45'S) forest site, both located in the state of Rondônia. Micrometeorological and hydrological data collected during the dry period of 2001, as part of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia - LBA, were used. The results showed that the model simulated well the net radiation, both at the pasture and at the forest. The latent heat flux was super-estimated in both sites. The model sub-estimated the sensible heat flux at the pasture and at the forest, mainly during the night period; notwithstanding, the values for the forest were nearer to the observed ones. With the calibrated parameters, the model generated better estimations of the latent and the sensible heat fluxes, thus better representing the energy partition both at the forest and at the pasture.", 'enOs parâmetros do "Simplified Simple Biosphere Model"-SSiB foram validados e posteriormente calibrados para os sítios de pastagem da Fazenda Nossa Senhora Aparecida (62º22\'W; 10º45\'S) e de floresta da Reserva Biológica do Jaru (62º22\'W; 10º45\'S), ambos situados no estado de Rondônia. Foram utilizadas medidas micrometeorológicas e hidrológicas obtidas durante o período seco de 2001, como parte do Experimento de Grande Escala da Biosfera-Atmosfera na Amazônia - LBA. Os resultados indicam que o modelo simulou bem o saldo de radiação, tanto na pastagem quanto na floresta. O fluxo de calor latente foi superestimado nos dois sítios nos períodos de simulação, o que deve estar relacionado aos parâmetros utilizados no cálculo dessa variável. O modelo subestimou o fluxo de calor sensível na pastagem e na floresta, principalmente no período noturno; porém, para a floresta, os valores foram mais próximos daqueles observados. Com os parâmetros ajustados, melhores estimativas dos fluxos de calor latente e de calor sensível foram geradas e, conseqüentemente, representou melhor as partições de energia na floresta e na pastagem

Drought Between 1963 and 2017 in the Federal District, Brazil

Drought is a climatic extreme caused by the precipitation deficit, which results in low water availability for different human activities. The drought characterization regarding of its duration and severity is still little explored, especially in regions where drought is not recurrent in a short time scale. With that in mind, this study presents a quantitative evaluation of the drought events occurred between 1964 and 2017 in the Federal District, with an emphasis on the last drought of 2016-2017. For this, the Standardized Precipitation Index (SPI) was used to evaluate the duration and severity of drought events and the Vegetation Supply Water Index (VSWI) for the spatial analysis of the drought impacts on vegetation. According to the SPI, the longest and most severe drought event, occurred in 1998. The most recent drought 2016-2017 started in April, beginning of the dry period, but remained throughout the wet season (October 2016 to March 2017). Considering ranking of duration and severity, among all the longest and severe events occurred in Brasilia, since 1963, this recent drought event can be positioned in sixth and in fourth position respectively, emphasizing its study importance in scientific community. According to VSWI, in the last drought event, the areas impacted by drought reached 75% of the Federal Distric

The challenges of Consolidation of a Drought-Related Disaster Risk Warning System to Brazil

In Brazil, droughts are widespread and recurrent in the semiarid region, mainly due to its water vulnerability. Approximately 28 million people live in the region, which concentrates the highest proportion of people living in poverty in Brazil. If drought occurs intensively and extensively in densely populated areas, it can result in disaster when local capacities are insufficient to avoid significant damage. The risks associated with drought are related to the natural hazard, local vulnerabilities, response capacity, and mitigation policies. This study presents the challenges for the consolidation of a drought risk warning system in Brazil and proposes an initial structure for assigning responsibilities among the national institutions involved in the theme in order to guide actions for the risk mitigation.No Brasil, a seca é um fenômeno caracterizado pela sua ampla cobertura espacial e recorrência na região semiárida, principalmente devido à sua vulnerabilidade hídrica. Aproximadamente 28 milhões de pessoas vivem na região, a qual concentra a maior parte da população mais pobre do Brasil. Assim, a seca é uma ameaça natural à medida que ocorre de forma intensiva e extensiva em áreas densamente povoadas, podendo resultar em desastre quando as capacidades locais são insuficientes para evitar danos significativos. O risco de um desastre associado à seca está relacionado com a ameaça física, as vulnerabilidades locais, a capacidade de resposta e com as políticas de mitigação. O presente estudo apresenta os desafios para a consolidação de um sistema de alerta de risco de desastres associados às secas no Brasil e propõe uma estrutura inicial de atribuição de responsabilidades entre as instituições nacionais envolvidas com a temática com a finalidade de guiar ações para a mitigação dos riscos