Use of SMOS L3 Soil Moisture Data: Validation and Drought Assessment for Pernambuco State, Northeast Brazil

Souza, Alzira G. S. S.; Neto, Alfredo Ribeiro; Rossato, Luciana; Alvalá, Regina Célia dos Santos; Souza, Laio Lucas de

doi:10.3390/rs10081314

Cited by 28 publications

(19 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Several evaluations and comparisons of remote SM have been made using observations from in situ measurements [14]. They are fairly accurate for point-based measurements, however inadequate to perform SM evaluation on larger scales [15].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Soil Moisture Variability in Poland from SMOS Satellite Observations

2019

View full text Add to dashboard Cite

Soil moisture (SM) data play an important role in agriculture, hydrology, and climate sciences. In this study, we examined the spatial-temporal variability of soil moisture using Soil Moisture Ocean Salinity (SMOS) satellite measurements for Poland from a five-year period (2010–2014). SMOS L2 v. 551 datasets (latitudinal rectangle 1600 × 840 km, centered in Poland) averaged for quarterly (three months corresponding to winter, spring, summer, and autumn) and yearly values were used. The results were analysed with the use of classical statistics and geostatistics (using semivariograms) to acquire information about the nature of anisotropy and the lengths and directions of spatial dependences. The minimum (close to zero) and maximum soil moisture values covered the 0.5 m3 m−3 range. In particular quarters, average soil moisture did not exceed 0.2 m3 m−3 and did not drop below 0.12 m3 m−3; the corresponding values in the study years were 0.171 m3 m−3 and 0.128 m3 m−3. The highest variability of SM occurred generally in winter (coefficient of variation, CV, up to 40%) and the lowest value was recorded in spring (around 23%). The average CV for all years was 32%. The quarterly maximum (max) soil moisture contents were well positively correlated with the average soil moisture contents (R2 = 0.63). Most of the soil moisture distributions (histograms) were close to normal distribution and asymmetric data were transformed with the square root to facilitate geostatistical analysis. Isotropic and anisotropic empirical semivariograms were constructed and the theoretical exponential models were well fitted (R2 > 0.9). In general, the structural dependence of the semivariance was strong and moderate. The nugget (C0) values slightly deceased with increasing soil moisture while the sills (C0 + C) increased. The effective ranges of spatial dependence (A) were between 1° and 4° (110–440 km of linear distance). Generally, the ranges were greater for drier than moist soils. Anisotropy of the SM distribution exhibited different orientation with predominance from north-west to south-east in winter and spring and changed for from north-east to south-west or from north to south in the other seasons. The fractal dimension values showed that the distribution of the soil moisture pattern was less diverse (smoother) in the winter and spring, compared to that in the summer and autumn. The soil moisture maps showed occurrence of wet areas (soil moisture > 0.25 m3 m−3) in the north-eastern, south-eastern and western parts and dry areas (soil moisture < 0.05 m3 m−3) mainly in the central part (oriented towards the south) of Poland. The spatial distribution of SM was attributed to soil texture patterns and associated with water holding capacity and permeability. The results will help undertake appropriate steps to minimize susceptibility to drought and flooding in different regions of Poland.

show abstract

Section: Introductionmentioning

confidence: 99%

Evaluation of Soil Moisture Variability in Poland from SMOS Satellite Observations

2019

View full text Add to dashboard Cite

show abstract

“…The state of Pernambuco is in the Northeast region of Brazil, between the coordinates 7° S and 10° S and 34° W and 42° W. It extends considerably from east to west, with 80% of its territory in the Semiarid region (CONDEPE/FIDEM, 2006;Souza et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…Several studies have been conducted to evaluate the droughts from 2012 to 2017 using rainfall data series and vegetation indexes (Brito et al, 2017;Cunha et al, 2017;. Soil moisture is an essential climatic variable to monitor droughts, which is considered an important variable for establishing the severity of drought (Pablos et al, 2017;Rossato et al, 2017;Souza et al, 2018). This is an important variable to establish the severity of droughts that is used mainly to monitor droughts for agricultural purposes (Pablos et al, 2017;Paredes-Trejo & Barbosa, 2017;Souza et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Soil moisture obtained through remote sensing to assess drought events

Inocêncio

Neto

Souza

2020

Rev. bras. eng. agríc. ambient.

View full text Add to dashboard Cite

The sequence of drought events in the Northeast of Brazil in recent decades raises attention to the importance of studying this phenomenon. The objective of this study was to evaluate the duration and severity of drought events from 1988 to 2018 in hydrographic basins of the state of Pernambuco, Brazil, using two drought indexes: Standardized Soil Moisture Index and Soil Moisture Condition Index, calculated based on data of the Soil Moisture Project of the European Space Agency’s Climate Change Initiative. The duration of the droughts was determined considering the months between their beginning and end, and their severity was based on the area formed in the graph between the curve of the index and the x-axis. The soil moisture database showed to be a promising tool for the analysis and monitoring of drought events in the Northeast region of Brazil, mainly for analysis and monitoring of drought events. The indexes allowed the evaluation of the drought phenomenon over the 30-year period, showing increases from 2012, which were more pronounced in the Semiarid region. The hydrographic basins responded differently to a same event, depending on the climate characteristics of the region in which they are located. Consecutive years with rainfall below the historical mean increased the magnitude of the droughts, as found for the 2012-2017 period, in which the indexes presented delays to return to more favorable values, showing the effect that one drought year has on the following year.

show abstract

“…Two applications in Brazil are discussed in this Special Issue. Souza et al [5] discussed the evaluation of SMOS soil moisture data in the state of Pernambuco in Brazil, including in situ sensors, both in forest and arid regions; showing a net decrease of performances from arid to forest regions. They also showed that the use of SMOS data provides additional information to precipitation data that allows the monitoring of drought periods.…”

Section: Applications For Drought Assessment and Rainfall And Evaporamentioning

confidence: 99%

Soil Moisture Remote Sensing across Scales

et al. 2019

View full text Add to dashboard Cite

show abstract

Use of SMOS L3 Soil Moisture Data: Validation and Drought Assessment for Pernambuco State, Northeast Brazil

Cited by 28 publications

References 48 publications

Evaluation of Soil Moisture Variability in Poland from SMOS Satellite Observations

Evaluation of Soil Moisture Variability in Poland from SMOS Satellite Observations

Soil moisture obtained through remote sensing to assess drought events

Soil Moisture Remote Sensing across Scales

Contact Info

Product

Resources

About