Banca de QUALIFICAÇÃO: PAULO ANDRÉ DA SILVA MARTINS

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : PAULO ANDRÉ DA SILVA MARTINS
DATE: 19/08/2024
TIME: 08:30
LOCAL: Plataforma do Google meet
TITLE:

Estimates and Space-Time Distribution of Erosivity Resulting from Rainfall in the State of Rondônia

KEY WORDS:

El30, Spatialization, precipitation, Northern Region

PAGES: 80
BIG AREA: Ciências Exatas e da Terra
AREA: Geociências
SUBÁREA: Geografia Física
SPECIALTY: Climatologia Geográfica
SUMMARY:

Soil erosion is a phenomenon triggered by erosive agents. This process is mainly driven by precipitation, which acts as the driving force behind water erosion. The energy released during precipitation is crucial as it directly influences the intensity, frequency, and duration of erosive events in different regions or locations. The detachment and transport of sediments by surface runoff are direct consequences of these elements, significantly impacting soil erosion dynamics. The objectives include: 1- Evaluating the El30 Erosivity Index, providing a value for the "R" factor 2- Characterising the rainfall hydrological pattern in the state of Rondônia 3- Estimating erosive potential and assessing the frequency and intensity of precipitation. This study aims to demonstrate the variation of the Erosivity Index associated with differences in precipitation and its kinetic energy across the state of Rondônia, aiming to show that the variation of the Erosivity Index is related to differences in seasons as well as seasonality. The study area encompasses the state of Rondônia, located in Brazil, situated between the geographical coordinates 7.98– 13.69°S and 59.77–66.81°W. This region covers an area of 243,000 km², representing a significant portion of the 5,000,000 km² that make up the Brazilian Legal Amazon. The study will utilise precipitation data from the years 1980 to 2020 from 30 fluviographic stations of the National Water Agency (ANA) in the state of Rondônia, and data from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation estimates product for the same period. The CHIRPS data has been validated against surface data, and the Erosivity Index has been calculated. Validation will be conducted using statistics based on monthly and annual averages. The relationship between measured and estimated values will be assessed using the Pearson correlation coefficient "r". The Pearson correlation coefficient (r) measures the degree of linear correlation between two quantitative variables. Accuracy analysis will be conducted using the Willmott index "d," which relates the distance of estimated values compared to observed values, ranging between 0 for no match and 1 for a perfect match. The Root Mean Square Error (RMSE) will also be analysed to indicate discrepancies between the presented model of estimated and measured values, along with the Mean Absolute Error (MAE) showing the average absolute distance (deviation) between estimated and measured values. In both errors, values should be close to zero. After data validation, the Fourier equation relating to the average monthly precipitation, annual precipitation, and annual total values of erosivity will be used to find the monthly values. The data will be classified according to Carvalho's proposal (2008), which creates classes for erosivity based on the values: R < 2452 Low; and R > 9812 very strong. The results indicate significant differences in precipitation data between monthly and annual measurements throughout the state of Rondônia. The highest overestimation was 30% at station c9, while the lowest was 14.1% at station c3. The annual estimates followed a similar pattern, with station c9 having a 44.3% overestimation, while station c18 had the lowest at 10.5%. These results highlight the variability in CHIRPS estimates across different stations and underscore the importance of considering these discrepancies for more accurate analyses related to precipitation in the state of Rondônia. Monthly estimates showed significant correlations ranging from weak (0.3 to 0.5) to strong (0.7 to 0.9). The Wilmont coefficient yielded a result of 0.87 with lower RMSE errors of 87.97mm and 89.23mm. The determination scale (R2) above 0.5 indicates that over 50% of the variation in measured precipitation can be explained by the variation in precipitation estimated by CHIRPS. This study assessed significant differences in CHIRPS precipitation estimates compared to monthly and annual measurements across the state of Rondônia, highlighting the importance of monitoring the quality of surface data due to potential meteorological challenges such as issues in collection, transmission, and storage that may lead to disruptions in data continuity and integrity.

COMMITTEE MEMBERS:
Presidente - 396929 - DORISVALDER DIAS NUNES
Interno - 3102827 - JOAO PAULO ASSIS GOBO
Interno - 2313615 - MICHEL WATANABE
Externo à Instituição - CARLOS ALEXANDRE SANTOS QUERINO - UFAM
Externa à Instituição - JULIANE KAYSE ALBUQUERQUE DA SILVA QUERINO - UFAM
Externa à Instituição - TAMIRES CUNHA DE AGUIAR