Improving environmental sustainability involves measuring indices that show responses to different production processes and management types. Suspended sediment concentration (SSC) in water bodies is a parameter of great importance, as it is related to watercourse morphology, land use and occupation in river basins, and sediment transport and accumulation. Although already established, the methods used for acquiring such data in the field are costly. This hinders extrapolations along water bodies and reservoirs. Remote sensing is a feasible alternative to remedy these obstacles, as changes in suspended sediment concentrations are detectable by satellite images. Therefore, satellite image reflectance can be used to estimate SSC spatially and temporally. We used Sentinel-2 A and B imagery to estimate SSC for the Teles Pires River in Brazil’s Amazon. Sensor images used were matched to the same days as field sampling. Google Earth Engine (GEE), a tool that allows agility and flexibility, was used for data processing. Access to several data sources and processing robustness show that GEE can accurately estimate water quality parameters via remote sensing. The best SSC estimator was the reflectance of the B4 band corresponding to the red range of the visible spectrum, with the exponential model showing the best fit and accuracy.
Objetivou-se determinar as vazões líquidas, as concentrações de sedimentos em suspensão e a turbidez em uma seção fluviométrica, na região central da microbacia hidrográfica do rio Caiabi (MBHRC), localizada na transição da floresta Amazônica e do Cerrado. Foram estabelecidas curvas-chaves para as vazões líquidas e sólidas, além de estimativas da turbidez. O monitoramento a campo ocorreu entre dezembro de 2020 e dezembro de 2021, com mensuração mensal de vazões líquidas e coletas de amostras de água e sedimentos. Os resultados adquiridos possibilitaram ajustes da curva-chave líquida com índice de Nash-Sutcliffe (NSE) de 0,9928, coeficiente de determinação (R²) de 0,9964 e do desvio médio absoluto (D%) de 3,7264. Por meio de ajuste de relações entre as variáveis avaliadas, observou-se que a descarga líquida pode explicar cerca de 80% da descarga de sedimentos na MBHRC, enquanto, a concentração de sedimentos em suspensão pode explicar cerca de 70% da descarga total de sedimentos. Os valores de turbidez medidos por turbidímetro foram correlacionados com a concentração de sedimentos em suspensão e com as descargas sólidas em suspensão, resultando em valores de R² de até 0,8807 (NTU x Css) e R² de até 0,7185 (NTU x Qss). Palavras-chave: hidrossedimentologia; turbidímetro; concentração de sedimentos; correlação. Net flow, suspended sediments and turbidity in the Caiabi River microbasin, in the Cerrado-Amazon ecotono ABSTRACT: The objective was to determine the liquid flows, the suspended sediment concentrations and the turbidity in a fluviometric section, in the central region of the Caiabi River microbasin (MBHRC), located in the transition between the Amazon forest and the Cerrado. Key curves were established for liquid and solid flows, in addition to turbidity estimates. Field monitoring took place between December 2020 and December 2021, with monthly measurement of liquid flows and collection of water and sediment samples. The acquired results made it possible to adjust the net key curve with a Nash-Sutcliffe index (NSE) of 0.9928, coefficient of determination (R²) of 0.9964 and absolute mean deviation (D%) of 3.7264. By adjusting the relationships between the variables evaluated, it was observed that the net discharge can explain about 80% of the sediment discharge in the MBHRC, while the concentration of suspended sediments can explain about 70% of the total discharge. of sediment. The turbidity values measured by Turbidimeter were correlated with the concentration of suspended sediments and with the total solid discharges, resulting in R² values up to 0.8807 (NTU X Qss) and R² values up to 0.7185 (NTU x Css). Keywords: hydrosedimentology; turbidimeter; sediment concentration; correlation.
O desenvolvimento da região Centro-Oeste do Brasil aconteceu de forma rápida e expressiva, integrando a região à economia nacional e internacional, passando a ser considerada a principal região geradora de produtos agropecuários exportáveis. Como todo processo de produção tende a causar impactos ambientais, estes sistemas tendem a aumentar a erosão natural do solo e consequente sedimentação em rios. Para verificar esses impactos e possibilitar o planejamento de medidas mitigadoras, é importante o estudo hidrossedimentológico de bacias hidrográficas, pois servem como base de dados para ajustar modelos que possam auxiliar na predição de cenários de acordo com uso e ocupação do solo, bem como o regime da disponibilidade hídrica. Desta forma objetivou-se avaliar a produção de sedimentos na microbacia hidrográfica do rio Caiabi, localizada nas cidades de Sinop e Vera, região Norte do estado do Mato Grosso, por meio do ajuste e análise da MUSLE. Ao verificar uma superestimação da produção de sedimentos utilizando os coeficientes de localização originais do modelo matemático MUSLE, fez-se necessário a calibração e a validação do modelo. Por meio de dados de curva-chave sólida obtidos por medições a campo, e utilizando-se três metodologias diferentes de ajuste do modelo, bem como três arranjos de dados para calibração e validação, obteve-se novos valores para a e b. Os testes estatísticos identificaram que o método dos mínimos quadrados apresentou os melhores valores de NSE para todos os arranjos utilizados, acima de 0,80, e o melhor conjunto de valores para os índices estatísticos utilizados (NSE, MAE, RMSE, R2, PBIAS) foi o método dos mínimos quadrados utilizando um arranjo de 50% dos dados tanto para calibração como 50% de dados para validação, apresentando coeficientes de localização 0,0044 e 0,8774, respectivamente para os coeficientes a e b.Palavras-chave: erosão; modelagem; curva-chave; coeficientes regionais. Evaluation of soil losses by MUSLE in a watershed in the Cerrado-Amazon ecotone A B S T R A C TThe development of the Center-West region of Brazil happened quickly and expressively, integrating the region to the national and international economy, becoming considered the main region that generates exportable agricultural products. As every production process tends to cause environmental impacts, these systems tend to increase the natural erosion of the soil and consequent sedimentation in rivers. In order to verify these impacts and enable the planning of mitigating measures, the hydrosedimentological study of hydrographic basins is important, as they serve as a database for adjusting models that can help in the prediction of scenarios according to land use and occupation, as well as the water availability regime. Thus, the objective was to evaluate the production of sediments in the hydrographic microbasin of the Caiabi River, located in the cities of Sinop and Vera, in the northern region of the state of Mato Grosso. When verifying an overestimation of sediment production using the original location coefficients of the MUSLE mathematical model, it was necessary to calibrate and validate the model. Using solid rating curve data obtained from field measurements, and using three different model fitting methodologies, as well as three data arrays for calibration and validation, new values were obtained for a and b. The statistical tests identified that the least squares method presented the best NSE values for all the arrangements used, above 0.80, and the best set of values for the statistical indices used (NSE, MAE, RMSE, R2, PBIAS) was the least squares method using an array of 50% of the data for both calibration and 50% of data for validation, showing location coefficients 0.0044 and 0.8774, respectively for coefficients a and bKeywords: erosion; modeling; rating curve; regional coefficients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.