Explore the vast range of titles available.

Land surface models (LSMs) are widely used to study the continental part of the water cycle. However, even though their accuracy is increasing, inherent model uncertainties can not be avoided. In the meantime, remotely sensed observations of the continental water cycle variables such as soil moisture, lakes and river elevations are more frequent and accurate. Therefore, those two different types of information can be combined, using data assimilation techniques to reduce a model's uncertainties in its state variables or/and in its input parameters. The objective of this study is to present a data assimilation platform that assimilates into the large-scale ISBA-CTRIP LSM a punctual river discharge product, derived from ENVISAT nadir altimeter water elevation measurements and rating curves, over the whole Amazon basin. To deal with the scale difference between the model and the observation, the study also presents an initial development for a localization treatment that allows one to limit the impact of observations to areas close to the observation and in the same hydrological network. This assimilation platform is based on the ensemble Kalman filter and can correct either the CTRIP river water storage or the discharge. Root mean square error (RMSE) compared to gauge discharges is globally reduced until 21 % and at Óbidos, near the outlet, RMSE is reduced by up to 52 % compared to ENVISAT-based discharge. Finally, it is shown that localization improves results along the main tributaries.

The Amazon river basin has been recently affected by extreme climatic events, such as the exceptional drought of 2005, with significant impacts on human activities and ecosystems. In spite of the importance of monitoring freshwater stored and moving in such large river basins, only scarce measurements of river stages and discharges are available and the signatures of extreme drought conditions on surface freshwater dynamics at the basin scale are still poorly known. Here we use continuous multisatellite observations of inundation extent and water levels between 2003 and 2007 to monitor monthly variations of surface water storage at the basin scale. During the 2005 drought, the amount of water stored in the river and floodplains of the Amazon basin was ∼130 km3 (∼70%) below its 2003-7 average. This represents almost a half of the anomaly of minimum terrestrial water stored in the basin as estimated using the Gravity Recovery and Climate Experiment (GRACE) data.

In the Congo Basin, the elevated vulnerability of food security and the water supply implies that sustainable development strategies must incorporate the effects of climate change on hydrological regimes. However, the lack of observational hydro-climatic data over the past decades strongly limits the number of studies investigating the effects of climate change in the Congo Basin. We present the largest altimetry-based dataset of water levels ever constituted over the entire Congo Basin. This dataset of water levels illuminates the hydrological regimes of various tributaries of the Congo River. A total of 140 water level time series are extracted using ENVISAT altimetry over the period of 2003 to 2009. To improve the understanding of the physical phenomena dominating the region, we perform a K-means cluster analysis of the altimeter-derived river level height variations to identify groups of hydrologically similar catchments. This analysis reveals nine distinct hydrological regions. The proposed regionalization scheme is validated and therefore considered reliable for estimating monthly water level variations in the Congo Basin. This result confirms the potential of satellite altimetry in monitoring spatio-temporal water level variations as a promising and unprecedented means for improved representation of the hydrologic characteristics in large ungauged river basins.

In the Amazon basin, the recently released SRTM Global 1 arc-second (SRTMGL1) remains the best topographic information for hydrological and hydrodynamic modeling purposes. However, its accuracy is hindered by errors, partly due to vegetation, leading to erroneous simulations. Previous efforts to remove the vegetation signal either did not account for its spatial variability or relied on a single assumed percentage of penetration of the SRTM signal. Here, we propose a systematic approach over an Amazonian floodplain to remove the vegetation signal, addressing its heterogeneity by combining estimates of vegetation height and a land cover map. We improve this approach by interpolating the first results with drainage network, field and altimetry data to obtain a hydrological conditioned DEM. The averaged interferometric and vegetation biases over the forest zone were found to be −2.0 m and 7.4 m, respectively. Comparing the original and corrected DEM, vertical validation against Ground Control Points shows a RMSE reduction of 64%. Flood extent accuracy, controlled against Landsat and JERS-1 images, stresses improvements in low and high water periods (+24% and +18%, respectively). This study also highlights that a ground truth drainage network, as a unique input during the interpolation, achieves reasonable results in terms of flood extent and hydrological characteristics.

O presente estudo teve como objetivo principal, a validação de informações geomorfológicas na bacia do rio Madeira utilizando dados de sensores remotos. Com base nas informações geradas pelo estudo espera-se contribuir para o monitoramento hidrológico da região da bacia do rio Madeira, uma vez que em toda a extensão da bacia Amazônica existem problemas relacionados ao monitoramento hidrológico, o que acaba gerando impactos negativos na gestão de recursos hídricos da região. A validação das informações geomorfológicas, mais especificamente a variável profundidade, foi feita com base na elaboração de uma curva chave produzida com dados de vazão simulada pelo Modelo de Grandes Bacias – MGB e pelas cotas altimétricas oriundas de dados do satélite Sentinel 3A durante o período de 2016 a 2019. Esses dados relacionados as informações geomorfológicas de profundidade foram validados, usando como referência as medidas de profundidade provenientes da batimetria da área de estudo analisada. Esta batimetria foi realizada pelo Serviço de Sinalização Náutica – SSN-9 que é responsável pela segurança da navegação dentro da bacia Amazônica. A validação das informações geomorfológicas relacionadas a variável profundidade pode indicar um caminho para novas alternativas no monitoramento hidrológico da bacia Amazônica, onde é possível, utilizar dados de modelagem hidrológica e cotas altimétricas provenientes de satélites para fazer um monitoramento seguro e com alta resolução temporal e espacial.

The present study aimed to validate depth data obtained through the key curve equation elaborated based on data from the Large Basin Hydrological Model (MGB) and Spatial Altimetry (Sentinel 3A). Using as a comparison for validation, depth data obtained through bathymetry. The values found in relation to the parameters of the key curve are coefficient A (250.074); coefficient B (1.738) and the Coefficient Z0 (13.788). The simulated flows produced consistent and applicable results for the study, thus making model calibration unnecessary. The percentage of confidence presented by the key curve was (95%). Values can be explained by section geometry. It was possible to identify the existence of uniformity in the data set, which indicates a good fit of the key curve. The difference between the data obtained by the key curve (MGB/Spatial Altimetry) and (in situ) related to the average depth was (1.17m). When compared, the values found related to the standard deviation, it was possible to identify a difference of (0.76 cm). The validation of geomorphological information related to variable depth can help create new alternatives for the hydrological monitoring of the Amazon basin.

The hydrological observation network in the Amazon basin is made of conventional rainfall and water level stations presently maintained by the Agência Nacional de Águas (ANA), the National Agency for Waters. The water level network has long been plagued by difficulties associated with spatial coverage, timely delivery and data errors. Satellite observations are important means for providing hydrologic data with acceptable spatial and temporal resolution, and radar altimeters embarked onboard successive satellites since the early 1970s collect measurements of water level over rivers in a well-defined geodetic reference frame and can be used to address some of these problems. Nowadays, satellite altimetry can be used to collect the time variations of the water levels over many rivers throughout the word, as long as the reach are several hundred meters wide. This ability is particularly interesting in ungauge basins but it can also be used as an independent source of information to cross-check existing gauge series. In the present study, we focus on examples from the Amazon basin where radar altimetry has been used to provide an independent dataset that can be used to support the management of hydrological observation networks by including new data together with conventional field data,

The present study aimed to validate depth data obtained through the key curve equation elaborated based on data from the Large Basin Hydrological Model (MGB) and Spatial Altimetry (Sentinel 3A). Using as a comparison for validation, depth data obtained through bathymetry. The values found in relation to the parameters of the key curve are coefficient A (250.074); coefficient B (1.738) and the Coefficient Z0 (13.788). The simulated flows produced consistent and applicable results for the study, thus making model calibration unnecessary. The percentage of confidence presented by the key curve was (95%). Values can be explained by section geometry. It was possible to identify the existence of uniformity in the data set, which indicates a good fit of the key curve. The difference between the data obtained by the key curve (MGB/Spatial Altimetry) and (in situ) related to the average depth was (1.17m). When compared, the values found related to the standard deviation, it was possible to identify a difference of (0.76 cm). The validation of geomorphological information related to variable depth can help create new alternatives for the hydrological monitoring of the Amazon basin. Keywords: Spatial altimetry; Rating curve; Hydrological monitoring; Madeira river. O presente estudo teve como objetivo validar dados de profundidade obtidos por intermedio da equacao da curva chave elaborada com base em dados do Modelo Hidrologico de Grandes Bacias (MGB) e Altimetria Espacial (Sentinel 3A). Utilizando como comparativo para validacao, dados de profundidade obtidos por intermedio de batimetria. Os valores encontrados com relacao aos parametros da curva chave sao coeficiente A (250,074); coeficiente B (1,738) e o Coeficiente Z0 (13,788). As vazoes simuladas produziram resultados consistentes e aplicaveis para o estudo, tornando assim desnecessaria a calibracao do modelo. O percentual de confianca apresentado pela curva chave foi de (95%). Os valores podem ser explicados pela geometria da secao. Foi possivel identificar a existencia de uniformidade no conjunto de dados o que indica um bom ajuste da curva chave. A diferenca existente entre os dados obtidos pela curva chave (MGB/Altimetria Espacial) e (in situ) relacionados a profundidade media foi de (1,17m). Quando comparados, os valores encontrados relacionados ao desvio padrao, foi possivel identificar uma diferenca de (0,76 cm). A validacao de informacoes geomorfologicas relacionadas a variavel profundidade, podem auxiliar na criacao de novas alternativas para o monitoramento hidrologico da bacia Amazonica. Palavras-chave: Altimetria espacial; Curva chave; Monitoramento hidrologico; Rio Madeira. El presente estudio tuvo como objetivo validar los datos de profundidad obtenidos a traves de la ecuacion de la curva clave elaborada a partir de datos del Modelo Hidrologico de Gran Cuenca (MGB) y Altimetria Espacial (Sentinel 3A). Utilizando como comparacion para la validacion, los datos de profundidad obtenidos mediante batimetria. Los valores encontrados en relacion a los parametros de la curva clave son el coeficiente A (250.074); coeficiente B (1,738) y el coeficiente Z0 (13,788). Los flujos simulados produjeron resultados consistentes y aplicables para el estudio, haciendo innecesaria la calibracion del modelo. El porcentaje de confianza presentado por la curva clave fue (95%). Los valores se pueden explicar mediante la geometria de la seccion. Fue posible identificar la existencia de uniformidad en el conjunto de datos, lo que indica un buen ajuste de la curva clave. La diferencia entre los datos obtenidos por la curva clave (MGB / Altimetria espacial) y (in situ) relacionados con la profundidad media fue de (1,17 m). Al comparar los valores encontrados relacionados con la desviacion estandar, fue posible identificar una diferencia de (0,76 cm). La validacion de informacion geomorfologica relacionada con la variable profundidad puede ayudar a crear nuevas alternativas para el monitoreo hidrologico de la cuenca del Amazonas. Palabras clave: Altimetria espacial; Curva clave; Monitoreo hidrologico; Rio Madeira.