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Anderson Ruhoff
Instituto de Pesquisas Hidráulicas (IPH), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre 91501-970, Brazil

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Journal article
Published: 18 August 2021 in Remote Sensing
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Hydrological models are useful tools for water resources studies, yet their calibration is still a challenge, especially if aiming at improved estimates of multiple components of the water cycle. This has led the hydrologic community to look for ways to constrain models with multiple variables. Remote sensing estimates of soil moisture are very promising in this sense, especially in large areas for which field observations may be unevenly distributed. However, the use of such data to calibrate hydrological models in a synergistic way is still not well understood, especially in tropical humid areas such as those found in South America. Here, we perform multiple scenarios of multiobjective model optimization with in situ discharge and the SMOS L4 root zone soil moisture product for the Upper Paraná River Basin in South America (drainage area > 900,000 km²), for which discharge data for 136 river gauges are used. An additional scenario is used to compare the relative impacts of using all river gauges and a small subset containing nine gauges only. Across the basin, the joint calibration (CAL-DS) using discharge and soil moisture leads to improved precision and accuracy for both variables. The discharges estimated by CAL-DS (median KGE improvement for discharge was 0.14) are as accurate as those obtained with the calibration with discharge only (median equal to 0.14), while the CAL-DS soil moisture retrieval is practically as accurate (median KGE improvement for soil moisture was 0.11) as that estimated using the calibration with soil moisture only (median equal to 0.13). Nonetheless, the individual calibration with discharge rates is not able to retrieve satisfactory soil moisture estimates, and vice versa. These results show the complementarity between these two variables in the model calibration and highlight the benefits of considering multiple variables in the calibration framework. It is also shown that, by considering only nine gauges instead of 136 in the model optimization, the model is able to estimate reasonable discharge and soil moisture, although relatively less accurately and with less precision than for the entire dataset. In summary, this study shows that, for poorly gauged tropical basins, the joint calibration of SMOS soil moisture and a few in situ discharge gauges is capable of providing reasonable discharge and soil moisture estimates basin-wide and is more preferable than performing only a discharge-oriented optimization process.

ACS Style

Ayan Santos Fleischmann; Ahmad Al Bitar; Aline Meyer Oliveira; Vinícius Alencar Siqueira; Bibiana Rodrigues Colossi; Rodrigo Cauduro Dias de Paiva; Yann Kerr; Anderson Ruhoff; Fernando Mainardi Fan; Paulo Rógenes Monteiro Pontes; Walter Collischonn. Synergistic Calibration of a Hydrological Model Using Discharge and Remotely Sensed Soil Moisture in the Paraná River Basin. Remote Sensing 2021, 13, 3256 .

AMA Style

Ayan Santos Fleischmann, Ahmad Al Bitar, Aline Meyer Oliveira, Vinícius Alencar Siqueira, Bibiana Rodrigues Colossi, Rodrigo Cauduro Dias de Paiva, Yann Kerr, Anderson Ruhoff, Fernando Mainardi Fan, Paulo Rógenes Monteiro Pontes, Walter Collischonn. Synergistic Calibration of a Hydrological Model Using Discharge and Remotely Sensed Soil Moisture in the Paraná River Basin. Remote Sensing. 2021; 13 (16):3256.

Chicago/Turabian Style

Ayan Santos Fleischmann; Ahmad Al Bitar; Aline Meyer Oliveira; Vinícius Alencar Siqueira; Bibiana Rodrigues Colossi; Rodrigo Cauduro Dias de Paiva; Yann Kerr; Anderson Ruhoff; Fernando Mainardi Fan; Paulo Rógenes Monteiro Pontes; Walter Collischonn. 2021. "Synergistic Calibration of a Hydrological Model Using Discharge and Remotely Sensed Soil Moisture in the Paraná River Basin." Remote Sensing 13, no. 16: 3256.

Journal article
Published: 15 June 2021 in Remote Sensing
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Soil heat flux (G) is an important component for the closure of the surface energy balance (SEB) and the estimation of evapotranspiration (ET) by remote sensing algorithms. Over the last decades, efforts have been focused on parameterizing empirical models for G prediction, based on biophysical parameters estimated by remote sensing. However, due to the existing models’ empirical nature and the restricted conditions in which they were developed, using these models in large-scale applications may lead to significant errors. Thus, the objective of this study was to assess the ability of the artificial neural network (ANN) to predict mid-morning G using extensive remote sensing and meteorological reanalysis data over a broad range of climates and land covers in South America. Surface temperature (Ts), albedo (α), and enhanced vegetation index (EVI), obtained from a moderate resolution imaging spectroradiometer (MODIS), and net radiation (Rn) from the global land data assimilation system 2.1 (GLDAS 2.1) product, were used as inputs. The ANN’s predictions were validated against measurements obtained by 23 flux towers over multiple land cover types in South America, and their performance was compared to that of existing and commonly used models. The Jackson et al. (1987) and Bastiaanssen (1995) G prediction models were calibrated using the flux tower data for quadratic errors minimization. The ANN outperformed existing models, with mean absolute error (MAE) reductions of 43% and 36%, respectively. Additionally, the inclusion of land cover information as an input in the ANN reduced MAE by 22%. This study indicates that the ANN’s structure is more suited for large-scale G prediction than existing models, which can potentially refine SEB fluxes and ET estimates in South America.

ACS Style

Bruno de Andrade; Olavo Pedrollo; Anderson Ruhoff; Adriana Moreira; Leonardo Laipelt; Rafael Kayser; Marcelo Biudes; Carlos dos Santos; Debora Roberti; Nadja Machado; Higo Dalmagro; Antonio Antonino; José Lima; Eduardo de Souza; Rodolfo Souza. Artificial Neural Network Model of Soil Heat Flux over Multiple Land Covers in South America. Remote Sensing 2021, 13, 2337 .

AMA Style

Bruno de Andrade, Olavo Pedrollo, Anderson Ruhoff, Adriana Moreira, Leonardo Laipelt, Rafael Kayser, Marcelo Biudes, Carlos dos Santos, Debora Roberti, Nadja Machado, Higo Dalmagro, Antonio Antonino, José Lima, Eduardo de Souza, Rodolfo Souza. Artificial Neural Network Model of Soil Heat Flux over Multiple Land Covers in South America. Remote Sensing. 2021; 13 (12):2337.

Chicago/Turabian Style

Bruno de Andrade; Olavo Pedrollo; Anderson Ruhoff; Adriana Moreira; Leonardo Laipelt; Rafael Kayser; Marcelo Biudes; Carlos dos Santos; Debora Roberti; Nadja Machado; Higo Dalmagro; Antonio Antonino; José Lima; Eduardo de Souza; Rodolfo Souza. 2021. "Artificial Neural Network Model of Soil Heat Flux over Multiple Land Covers in South America." Remote Sensing 13, no. 12: 2337.

Preprint content
Published: 14 April 2021
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Evapotranspiration (ET) is a key process linking surface and atmospheric energy budgets, yet its drivers and patterns across wetlandscapes are poorly understood worldwide. Here we assess the ET dynamics in 12 wetlands complexes across South America, revealing major differences under temperate, tropical, and equatorial climates. While net radiation is a dominant driver of ET seasonality in most environments, flooding also contributes strongly to ET in tropical and equatorial wetlands, especially in meeting the evaporative demand. Moreover, significant water losses through wetlands and ET differences between wetlands and uplands occur in temperate, water-limited environments and in highly flooded areas such as the Pantanal, where slow river flood propagation drives the ET dynamics. Finally, floodplain forests produce the greatest ET in all environments except the Central Amazon, where upland forests sustain high rates year round. Our findings highlight the unique hydrological functioning and ecosystem services provided by wetlands on a continental scale.

ACS Style

Ayan Fleischmann; Leonardo Laipelt; Fabrice Papa; Anderson Ruhoff; Rodrigo Paiva; Marcelo Biudes; Rafael Kayser; Catherine Prigent; Eric Cosio; Nadja Machado; Walter Collischonn. Patterns and drivers of evapotranspiration in South American wetlands. 2021, 1 .

AMA Style

Ayan Fleischmann, Leonardo Laipelt, Fabrice Papa, Anderson Ruhoff, Rodrigo Paiva, Marcelo Biudes, Rafael Kayser, Catherine Prigent, Eric Cosio, Nadja Machado, Walter Collischonn. Patterns and drivers of evapotranspiration in South American wetlands. . 2021; ():1.

Chicago/Turabian Style

Ayan Fleischmann; Leonardo Laipelt; Fabrice Papa; Anderson Ruhoff; Rodrigo Paiva; Marcelo Biudes; Rafael Kayser; Catherine Prigent; Eric Cosio; Nadja Machado; Walter Collischonn. 2021. "Patterns and drivers of evapotranspiration in South American wetlands." , no. : 1.

Article
Published: 08 March 2021 in Environmental Monitoring and Assessment
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Subtropical coastal shallow lakes (SCSL) are sensitive ecosystems. The lake-skin-water temperature (LSWT) is an average lake temperature proxy and responds to changes in surroundings, affecting biological and physical lake processes. In this study, M*D11A1 products are used to develop daytime and nighttime LSWT time series for 20 SCSL in South America. The influence of climatic (air temperature, surface net solar radiation, wind speed, and wind direction) and non-climatic (latitude, lake area, perimeter, width, length, and morphology) factors are evaluated from 2001 to 2017. Pearson’s coefficients (ρ) and auto- and cross-correlations are used to establish the relation between LWST and the selected factors. We identify that the dynamic of LSWT is sensitive to geomorphological factors (latitude and lake width) throughout the year, especially in summer. In winter, the LSTW regime is mainly affected by wind direction (ρ = -0.66, p value < 0.01). Linear models are fitted to the temperature series to check the trend changes in the inflection points and the warming or cooling trend for LSWT. Considering the complete series, the maximum warming rate of LSWT is 0.25 °C per decade (°C/dec). The analysis of the identified sub-periods reveals that warming and cooling can occur (significantly) in shorter periods. The average trends within sub-periods for skin temperature-daytime (± 0.0105 °C/dec), skin temperature-nighttime (0.0041 °C/dec), and air temperature (− s0.006 °C/dec; 0.007 °C/dec) are estimated. Our approach has the potential to be applied in future studies due to the expansion of knowledge about the behavior of SCSL and the understanding of the current and potential effects of climate change in association with physical and geomorphological traits.

ACS Style

Itzayana González Ávila; Matheus Henrique Tavares; Cayo Lopes Bezerra Chalegres; Andres Mauricio Munar; Carlos Ruberto Fragoso; David da Motta-Marques; Anderson Ruhoff. Southern coastal subtropical shallow lakes skin temperature driven by climatic and non-climatic factors. Environmental Monitoring and Assessment 2021, 193, 1 -16.

AMA Style

Itzayana González Ávila, Matheus Henrique Tavares, Cayo Lopes Bezerra Chalegres, Andres Mauricio Munar, Carlos Ruberto Fragoso, David da Motta-Marques, Anderson Ruhoff. Southern coastal subtropical shallow lakes skin temperature driven by climatic and non-climatic factors. Environmental Monitoring and Assessment. 2021; 193 (4):1-16.

Chicago/Turabian Style

Itzayana González Ávila; Matheus Henrique Tavares; Cayo Lopes Bezerra Chalegres; Andres Mauricio Munar; Carlos Ruberto Fragoso; David da Motta-Marques; Anderson Ruhoff. 2021. "Southern coastal subtropical shallow lakes skin temperature driven by climatic and non-climatic factors." Environmental Monitoring and Assessment 193, no. 4: 1-16.

Journal article
Published: 28 February 2021 in Remote Sensing
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The lack of measurement of precipitation in large areas using fine-resolution data is a limitation in water management, particularly in developing countries. However, Version 6 of the Integrated Multi-satellitE Retrievals for GPM (IMERG) has provided a new source of precipitation information with high spatial and temporal resolution. In this study, the performance of the GPM products (Final run) in the state of Paraná, located in the southern region of Brazil, from June 2000 to December 2018 was evaluated. The daily and monthly products of IMERG were compared to the gauge data spatially distributed across the study area. Quantitative and qualitative metrics were used to analyze the performance of IMERG products to detect precipitation events and anomalies. In general, the products performed positively in the estimation of monthly rainfall events, both in volume and spatial distribution, and demonstrated limited performance for daily events and anomalies, mainly in mountainous regions (coast and southwest). This may be related to the orographic rainfall in these regions, associating the intensity of the rain, and the topography. IMERG products can be considered as a source of precipitation data, especially on a monthly scale. Product calibrations are suggested for use on a daily scale and for time-series analysis.

ACS Style

Jéssica G. Nascimento; Daniel Althoff; Helizani C. Bazame; Christopher M. U. Neale; Sergio N. Duarte; Anderson L. Ruhoff; Ivo Z. Gonçalves. Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Paraná State, Brazil. Remote Sensing 2021, 13, 906 .

AMA Style

Jéssica G. Nascimento, Daniel Althoff, Helizani C. Bazame, Christopher M. U. Neale, Sergio N. Duarte, Anderson L. Ruhoff, Ivo Z. Gonçalves. Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Paraná State, Brazil. Remote Sensing. 2021; 13 (5):906.

Chicago/Turabian Style

Jéssica G. Nascimento; Daniel Althoff; Helizani C. Bazame; Christopher M. U. Neale; Sergio N. Duarte; Anderson L. Ruhoff; Ivo Z. Gonçalves. 2021. "Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Paraná State, Brazil." Remote Sensing 13, no. 5: 906.

Journal article
Published: 31 March 2020 in Remote Sensing
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Evapotranspiration ( E T ) provides a strong connection between surface energy and hydrological cycles. Advancements in remote sensing techniques have increased our understanding of energy and terrestrial water balances as well as the interaction between surface and atmosphere over large areas. In this study, we computed surface energy fluxes using the Surface Energy Balance Algorithm for Land (SEBAL) algorithm and a simplified adaptation of the CIMEC (Calibration using Inverse Modeling at Extreme Conditions) process for automated endmember selection. Our main purpose was to assess and compare the accuracy of the automated calibration of the SEBAL algorithm using two different sources of meteorological input data (ground measurements from an eddy covariance flux tower and reanalysis data from Modern-Era Reanalysis for Research and Applications version 2 (MERRA-2)) to estimate the dry season partitioning of surface energy and water fluxes in a transitional area between tropical rainforest and savanna. The area is located in Brazil and is subject to deforestation and cropland expansion. The SEBAL estimates were validated using eddy covariance measurements (2004 to 2006) from the Large-Scale Biosphere-Atmosphere Experiment in the Amazon (LBA) at the Bananal Javaés (JAV) site. Results indicated a high accuracy for daily ET, using both ground measurements and MERRA-2 reanalysis, suggesting a low sensitivity to meteorological inputs. For daily ET estimates, we found a root mean square error (RMSE) of 0.35 mm day−1 for both observed and reanalysis meteorology using accurate quantiles for endmembers selection, yielding an error lower than 9% (RMSE compared to the average daily ET). Overall, the ET rates in forest areas were 4.2 mm day−1, while in grassland/pasture and agricultural areas we found average rates between 2.0 and 3.2 mm day−1, with significant changes in energy partitioning according to land cover. Thus, results are promising for the use of reanalysis data to estimate regional scale patterns of sensible heat (H) and latent heat (LE) fluxes, especially in areas subject to deforestation.

ACS Style

Leonardo Laipelt; Anderson Luis Ruhoff; Ayan Fleischmann; Rafael Henrique Bloedow Kayser; Elisa De Mello Kich; Humberto Ribeiro Da Rocha; Christopher Michael Usher Neale. Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil. Remote Sensing 2020, 12, 1108 .

AMA Style

Leonardo Laipelt, Anderson Luis Ruhoff, Ayan Fleischmann, Rafael Henrique Bloedow Kayser, Elisa De Mello Kich, Humberto Ribeiro Da Rocha, Christopher Michael Usher Neale. Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil. Remote Sensing. 2020; 12 (7):1108.

Chicago/Turabian Style

Leonardo Laipelt; Anderson Luis Ruhoff; Ayan Fleischmann; Rafael Henrique Bloedow Kayser; Elisa De Mello Kich; Humberto Ribeiro Da Rocha; Christopher Michael Usher Neale. 2020. "Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil." Remote Sensing 12, no. 7: 1108.

Preprint content
Published: 23 March 2020
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Evapotranspiration (ET) is a key variable to terrestrial climate system, transferring water from the surface to the atmosphere, regulating air temperature and carbon exchanges, thus, linking the water, carbon and water cycles. Despite its great importance, ET patterns in tropical biomes are not fully understood yet. Studies with eddy covariance (EC) ET measurements and remote sensing models demonstrated a huge importance over ET drivers and limiting factors. In this context, this study aimed to assess the ET process in the tropics, from local to basin scale, using EC measurements (from the LBA project) and remote sensing models (MOD16 and GLEAM). At local scale, measurements and estimates were evaluated against net radiation, precipitation and vegetation index (EVI), in order to assess how these drivers control ET patterns. Then, a Budyko approach was applied at basin scale to calculate how water and energy constrain ET in large basins, including Amazon, Solimões, Purus, Medeira, Tapajós, and Xingu rivers. Our results demonstrated disagreements between models to represent maximum and minimum ET rates at tropical forest vegetation (at K43, K67 and K83 sites), with ET measurements peaking during the dry season, in a pattern coincident with annual net radiation cycle. Moreover, deep rooting of well-established rainforests, available soil moisture and increased solar radiation allow ET processes to be maintained during the dry season. ET estimates from MOD16 algorithm agree with these patterns, however, estimates from GLEAM indicates maximum ET rates during the rainy season. At cropland/pasture vegetation (at K77 site), also located in central Amazon, EC measurements showed moderate negative agreement with net radiation (R² = -0.48) and positive with precipitation (R² = 0.53), with decreasing ET rates during the dry season. GLEAM showed ET rates reduction in dry months, but also showed a peak in during wet season, while increasing ET estimates are observed for MOD16, both presented similar behavior as in tropical forest sites. Furthermore, measurements in the southwest part (RJA and FNS sites) did not show clear seasonal patterns, and both MOD16 and GLEAM algorithms, agree with decreasing ET rates during the dry season, showing a significant relationship with precipitation and vegetation indices. Results based on the Budyko approach indicated agreement between the models, indicating a predominant energy-limited condition when evaluated whole basin (at Óbidos station), or basins located in the northern and western parts of Amazon (in Amazon, Purus, and Negro basins), which corroborates with other studies, where ET has limited energy availability. However, our results also demonstrated disagreements in basins located in the southern and eastern parts (in Madeira, Tapajós and Xingu basins), where MOD16 showed some water-limited conditions, whilst it was not observed for GLEAM algorithm. Whether the models agree in terms of seasonality and water and energy limitations, they also disagree between them and ground measurements. This study highlighted the importance to understand limitations of multi-models and multi-scale ET processes for hydroclimatological studies in the tropics.

ACS Style

Adriana Aparecida Moreira; Anderson Luis Ruhoff. Assessing evapotranspiration drivers and patterns at multiple scale in the Amazon basin. 2020, 1 .

AMA Style

Adriana Aparecida Moreira, Anderson Luis Ruhoff. Assessing evapotranspiration drivers and patterns at multiple scale in the Amazon basin. . 2020; ():1.

Chicago/Turabian Style

Adriana Aparecida Moreira; Anderson Luis Ruhoff. 2020. "Assessing evapotranspiration drivers and patterns at multiple scale in the Amazon basin." , no. : 1.

Journal article
Published: 26 February 2020 in Remote Sensing of Environment
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Scarcity of water temperature data in rivers may limit a diversity of studies considering this property, which regulates many physical, chemical, and biological processes. We present a robust method to generate a consistent, continuous daily river water temperature (RWT) data series for medium and large rivers using the combined techniques of remote sensing and water temperature modelling. In order to validate our approach, we divided this study into two parts: (i) we evaluated methods to derive RWT from Landsat 7 ETM+ and Landsat 8 TIRS imagery; and (ii) we evaluated the calibration and validation of river temperature models, using these data, to generate the continuous RWT data series. A 1.2 km section of the White River located near Hazleton, IN, USA, was selected to assess this method mainly due to river width and data availability. We tested three methods to retrieve RWT from Landsat 7 and four from Landsat 8, and we also applied a simple thermal sharpening technique. For Landsat 7, the methods showed bias and RMSE of 0.01–0.46 °C and 1.32–1.84 °C, while for Landsat 8, the methods showed bias and RMSE of 0.08–1.27 °C and 1.74–2.17 °C, and in both cases, the best results were found applying the radiative transfer equation with NASA's Atmospheric Correction Parameter Calculator. For the second part of the validation process, we compared a stochastic model and a hybrid model, air2stream, using as input two datasets: the RWT data derived from Landsat 7 only, and a combined dataset of both Landsat 7 and 8 derived RWT. The air2stream model outperformed the stochastic model when calibrated with Landsat 7 data only, with RMSE of 1.83 °C, but both models showed similar results when calibrated with the combined Landsat data, when air2stream showed RMSE of 1.58 °C. Due to its physical basis, better calibration procedure, and higher consistency, air2stream was considered the best model for deriving the continuous RWT data series. When compared to the measured daily mean RWT data, there was no observed tendency in under or overestimating the RWT in low or high temperature conditions by the modelled series. While further tests are needed in order to evaluate if our approach can be applied to analyse past behaviour and present trends, and the impacts of climate change on the temperature of rivers, the consistent results indicate that this approach has the potential to be applied in rivers with no measured temperature data, for example, in the spatial modelling of longitudinal profiles of rivers and the modelling of tributary river temperatures.

ACS Style

Matheus Henrique Tavares; Augusto Hugo Farias Cunha; David Da Motta Marques; Anderson Luis Ruhoff; Carlos Ruberto Fragoso; Andrés Mauricio Munar; Marie-Paule Bonnet. Derivation of consistent, continuous daily river temperature data series by combining remote sensing and water temperature models. Remote Sensing of Environment 2020, 241, 111721 .

AMA Style

Matheus Henrique Tavares, Augusto Hugo Farias Cunha, David Da Motta Marques, Anderson Luis Ruhoff, Carlos Ruberto Fragoso, Andrés Mauricio Munar, Marie-Paule Bonnet. Derivation of consistent, continuous daily river temperature data series by combining remote sensing and water temperature models. Remote Sensing of Environment. 2020; 241 ():111721.

Chicago/Turabian Style

Matheus Henrique Tavares; Augusto Hugo Farias Cunha; David Da Motta Marques; Anderson Luis Ruhoff; Carlos Ruberto Fragoso; Andrés Mauricio Munar; Marie-Paule Bonnet. 2020. "Derivation of consistent, continuous daily river temperature data series by combining remote sensing and water temperature models." Remote Sensing of Environment 241, no. : 111721.

Journal article
Published: 01 January 2020 in RBRH
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In this paper we synthesize the special sessions of the XXIII Brazilian Water Resources Symposium 2019 in order to understand the major advances and challenges in the water sciences in Brazil. We analyzed more than 250 papers and presentations of 16 special sessions covering topics of Climate Variability and Change, Disasters, Modeling, Large Scale Hydrology, Remote Sensing, Education, and Water Resources Management. This exercise highlighted the unique diversity of natural and human water features in Brazil, that offers a great opportunity for understanding coupled hydrological and societal systems. Most contributions were related to methods and the quantification of water phenomena, therefore, there is a clear necessity for fostering more research on phenomena comprehension. There is a vast network of co-authorship among institutions but mostly from academia and with some degree of regional fragmentation. The ABRhidro community now has the challenge to enhance its collaboration network, the culture of synthesis analysis, and to build a common agenda for water resources research. It is also time for us to be aligned with the international water science community and to use our experiences to actively contribute to the tackling of global water issues.

ACS Style

Rodrigo Cauduro Dias de Paiva; Pedro Luiz Borges Chaffe; Jamil Alexandre Ayach Anache; Andrea Sousa Fontes; Ligia Maria Nascimento de Araujo; Anderson Nascimento de Araujo; Daniel Bartiko; Tobias Bleninger; Pablo Borges de Amorim; Diogo Costa Buarque; Tomas Carlotto; Walter Collischonn; Daniel Henrique Marco Detzel; Fernando Mainardi Fan; Rosa Maria Formiga-Johnsson; Masato Kobiyama; Michael Mannich; Guilherme Marques; Gean Paulo Michel; Debora Yumi de Oliveira; Paulo Tarso Sanches de Oliveira; Adilson Pinheiro; Anderson Ruhoff; Vinicius Alencar Siqueira; Rutineia Tassi; Franciele Zanandrea. Advances and challenges in the water sciences in Brazil: a community synthesis of the XXIII Brazilian Water Resources Symposium. RBRH 2020, 25, 1 .

AMA Style

Rodrigo Cauduro Dias de Paiva, Pedro Luiz Borges Chaffe, Jamil Alexandre Ayach Anache, Andrea Sousa Fontes, Ligia Maria Nascimento de Araujo, Anderson Nascimento de Araujo, Daniel Bartiko, Tobias Bleninger, Pablo Borges de Amorim, Diogo Costa Buarque, Tomas Carlotto, Walter Collischonn, Daniel Henrique Marco Detzel, Fernando Mainardi Fan, Rosa Maria Formiga-Johnsson, Masato Kobiyama, Michael Mannich, Guilherme Marques, Gean Paulo Michel, Debora Yumi de Oliveira, Paulo Tarso Sanches de Oliveira, Adilson Pinheiro, Anderson Ruhoff, Vinicius Alencar Siqueira, Rutineia Tassi, Franciele Zanandrea. Advances and challenges in the water sciences in Brazil: a community synthesis of the XXIII Brazilian Water Resources Symposium. RBRH. 2020; 25 ():1.

Chicago/Turabian Style

Rodrigo Cauduro Dias de Paiva; Pedro Luiz Borges Chaffe; Jamil Alexandre Ayach Anache; Andrea Sousa Fontes; Ligia Maria Nascimento de Araujo; Anderson Nascimento de Araujo; Daniel Bartiko; Tobias Bleninger; Pablo Borges de Amorim; Diogo Costa Buarque; Tomas Carlotto; Walter Collischonn; Daniel Henrique Marco Detzel; Fernando Mainardi Fan; Rosa Maria Formiga-Johnsson; Masato Kobiyama; Michael Mannich; Guilherme Marques; Gean Paulo Michel; Debora Yumi de Oliveira; Paulo Tarso Sanches de Oliveira; Adilson Pinheiro; Anderson Ruhoff; Vinicius Alencar Siqueira; Rutineia Tassi; Franciele Zanandrea. 2020. "Advances and challenges in the water sciences in Brazil: a community synthesis of the XXIII Brazilian Water Resources Symposium." RBRH 25, no. : 1.

Journal article
Published: 04 October 2019 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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An adequate estimate of the radiation components on the earth’s surface may help reveal many important interactions between the earth’s surface and the atmosphere. In-situ measurements of radiation components are sparse, and remote sensing is one way to overcome this limitation. The clouds and the earth’s radiant energy system (CERES) provides a long-term estimate of shortwave and longwave radiation over the entire globe. This article compared and evaluated all components of the surface radiation, estimated using CERES SYN1deg Ed3A and SYN1deg Ed4A data (shortwave up and down, longwave up and down, and photosynthetically active radiation) against measurements for 15 sites located in Brazil. Our results indicated that CERES SYN1deg estimates are accurate for all variables evaluated, with the SYN1deg Ed4A version increasing the $R^{2}$ and decreasing the RMSE from the SYN1deg Ed3A version. We also evaluated the main driving factors controlling the variability of the surface radiation components, using cluster analysis and multiple linear regression. The results showed that surface temperature and total precipitable water vapor are the main driving factors affecting the variability of the different radiation components. The results also highlighted the influence of climate conditions and biome features on the estimates of surface radiation components by CERES. The radiation data provided by CERES SYN1deg Ed4A proved to be a promising alternative for large regions where meteorological information is unavailable or sparse.

ACS Style

Glaucia Dos Santos Nascimento; Anderson Ruhoff; J. Rafael Cavalcanti; David Da Motta Marques; Debora Regina Roberti; Humberto Ribeiro Da Rocha; Andres Mauricio Munar; Carlos Ruberto Fragoso; Maria Betania Leal De Oliveira. Assessing CERES Surface Radiation Components for Tropical and Subtropical Biomes. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2019, 12, 3826 -3840.

AMA Style

Glaucia Dos Santos Nascimento, Anderson Ruhoff, J. Rafael Cavalcanti, David Da Motta Marques, Debora Regina Roberti, Humberto Ribeiro Da Rocha, Andres Mauricio Munar, Carlos Ruberto Fragoso, Maria Betania Leal De Oliveira. Assessing CERES Surface Radiation Components for Tropical and Subtropical Biomes. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2019; 12 (10):3826-3840.

Chicago/Turabian Style

Glaucia Dos Santos Nascimento; Anderson Ruhoff; J. Rafael Cavalcanti; David Da Motta Marques; Debora Regina Roberti; Humberto Ribeiro Da Rocha; Andres Mauricio Munar; Carlos Ruberto Fragoso; Maria Betania Leal De Oliveira. 2019. "Assessing CERES Surface Radiation Components for Tropical and Subtropical Biomes." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12, no. 10: 3826-3840.

Journal article
Published: 13 September 2019 in Water
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Evapotranspiration (ET) is an important component of the hydrological cycle. Understanding the ET process has become of fundamental importance given the scenario of global change and increasing water use, especially in the agricultural sector. Determining ET over large agricultural areas is a limiting factor due to observational data availability. In this regard, remote sensing data has been used to estimate ET. In this study, we evaluated the Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface ET product estimates (hereafter MOD16 ET – MODIS Global Terrestrial Evapotranspiration Product) over two rice paddy areas in Southern Brazil, through the ET measured using the eddy covariance technique (hereafter EC). The energy balance components were evaluated during fallow and flooded seasons showing latent heat flux dominates in both seasons. The results showed that MOD16 ET underestimated EC measurements. Overall, the RMSE (root mean square error) ranged between 13.40 and 16.35 mm 8-day−1 and percent bias (PBIAS) ranged between −33.7% and −38.7%. We also assessed the ET (measured and estimated) main drivers, with EC yielding higher correlation against observed net radiation (Rn) and global radiation (Rg), followed by air temperature (Temp) and vapor pressure deficit (VPD), whilst MOD16 ET estimates yielded higher correlation against leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR). The MOD16 algorithm was forced with meteorological measurements but the results did not improve as expected, suggesting a low sensitivity to meteorological inputs. Our results indicated when a water layer was present over the soil surface without vegetation (LAI around zero), the largest differences between EC measurements and MOD16 ET were found. In this period, the expected domain of soil evaporation was not observed in MOD16 ET physical processes partition, indicating the algorithm was not able to detect areas with high soil moisture. In general, the MOD16 ET product presented low accuracy when compared against experimental measurements over flooded rice paddy, suggesting more studies are necessary, in order to reduce uncertainties associated to the land cover conditions.

ACS Style

Vanessa De Arruda Souza; Débora Regina Roberti; Anderson Luis Ruhoff; Tamíres Zimmer; Daniela Santini Adamatti; Luis Gustavo G. De Gonçalves; Marcelo Bortoluzzi Diaz; Rita De Cássia Marques Alves; Osvaldo L. L. De Moraes. Evaluation of MOD16 Algorithm over Irrigated Rice Paddy Using Flux Tower Measurements in Southern Brazil. Water 2019, 11, 1911 .

AMA Style

Vanessa De Arruda Souza, Débora Regina Roberti, Anderson Luis Ruhoff, Tamíres Zimmer, Daniela Santini Adamatti, Luis Gustavo G. De Gonçalves, Marcelo Bortoluzzi Diaz, Rita De Cássia Marques Alves, Osvaldo L. L. De Moraes. Evaluation of MOD16 Algorithm over Irrigated Rice Paddy Using Flux Tower Measurements in Southern Brazil. Water. 2019; 11 (9):1911.

Chicago/Turabian Style

Vanessa De Arruda Souza; Débora Regina Roberti; Anderson Luis Ruhoff; Tamíres Zimmer; Daniela Santini Adamatti; Luis Gustavo G. De Gonçalves; Marcelo Bortoluzzi Diaz; Rita De Cássia Marques Alves; Osvaldo L. L. De Moraes. 2019. "Evaluation of MOD16 Algorithm over Irrigated Rice Paddy Using Flux Tower Measurements in Southern Brazil." Water 11, no. 9: 1911.

Articles
Published: 17 February 2019 in Hydrological Sciences Journal
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It has been proposed that linear regression curves can be used to estimate monthly climate variables from observed precipitation. This approach is explored by applying the MGB hydrological model to the Paraná Basin (Brazil). Linear regressions were obtained for 54 climate gauges, and showed that most of them had at least six months of significant correlation between monthly climate variables (sunlight hours and relative humidity) and precipitation. The regression equations were applied to 5201 raingauges to estimate monthly climate variables and evapotranspiration, and the results were compared with a scenario using long-term climate averages only. Main differences occurred in wetter periods, where negative correlations between monthly precipitation and evapotranspiration were obtained when using precipitation as a proxy. Long-term changes in hydrological regime were assessed, and showed that the effect of precipitation on climate variables did not contribute expressively to the alterations observed in river discharge in Paraná Basin.

ACS Style

Ayan Fleischmann; Fernando Fan; Bruno Collischonn; Walter Collischonn; Paulo Rógenes Pontes; Anderson Ruhoff. Precipitation as a proxy for climate variables: application for hydrological modelling. Hydrological Sciences Journal 2019, 64, 361 -379.

AMA Style

Ayan Fleischmann, Fernando Fan, Bruno Collischonn, Walter Collischonn, Paulo Rógenes Pontes, Anderson Ruhoff. Precipitation as a proxy for climate variables: application for hydrological modelling. Hydrological Sciences Journal. 2019; 64 (3):361-379.

Chicago/Turabian Style

Ayan Fleischmann; Fernando Fan; Bruno Collischonn; Walter Collischonn; Paulo Rógenes Pontes; Anderson Ruhoff. 2019. "Precipitation as a proxy for climate variables: application for hydrological modelling." Hydrological Sciences Journal 64, no. 3: 361-379.

Journal article
Published: 18 January 2019 in Water
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Water temperature regulates many processes in lakes; therefore, evaluating it is essential to understand its ecological status and functioning, and to comprehend the impact of climate change. Although few studies assessed the accuracy of individual sensors in estimating lake-surface-water temperature (LSWT), comparative analysis considering different sensors is still needed. This study evaluated the performance of two thermal sensors, MODIS and Landsat 7 ETM+, and used Landsat methods to estimate the SWT of a large subtropical lake. MODIS products MOD11 LST and MOD28 SST were used for comparison. For the Landsat images, the radiative transfer equation (RTE), using NASA’s Atmospheric Correction Parameter Calculator (AtmCorr) parameters, was compared with the single-channel algorithm in different approaches. Our results showed that MOD11 obtained the highest accuracy (RMSE of 1.05 ° C), and is the recommended product for LSWT studies. For Landsat-derived SWT, AtmCorr obtained the highest accuracy (RMSE of 1.07 ° C) and is the recommended method for small lakes. Sensitivity analysis showed that Landsat-derived LSWT using the RTE is very sensitive to atmospheric parameters and emissivity. A discussion of the main error sources was conducted. We recommend that similar tests be applied for Landsat imagery on different lakes, further studies on algorithms to correct the cool-skin effect in inland waters, and tests of different emissivity values to verify if it can compensate for this effect, in an effort to improve the accuracy of these estimates.

ACS Style

Matheus Henrique Tavares; Augusto Hugo Farias Cunha; David Motta-Marques; Anderson Luís Ruhoff; J. Rafael Cavalcanti; Jr. Carlos Ruberto Fragoso; Juan Martín Bravo; Andrés Mauricio Munar; Fernando Mainardi Fan; Lucia Helena Ribeiro Rodrigues. Comparison of Methods to Estimate Lake-Surface-Water Temperature Using Landsat 7 ETM+ and MODIS Imagery: Case Study of a Large Shallow Subtropical Lake in Southern Brazil. Water 2019, 11, 168 .

AMA Style

Matheus Henrique Tavares, Augusto Hugo Farias Cunha, David Motta-Marques, Anderson Luís Ruhoff, J. Rafael Cavalcanti, Jr. Carlos Ruberto Fragoso, Juan Martín Bravo, Andrés Mauricio Munar, Fernando Mainardi Fan, Lucia Helena Ribeiro Rodrigues. Comparison of Methods to Estimate Lake-Surface-Water Temperature Using Landsat 7 ETM+ and MODIS Imagery: Case Study of a Large Shallow Subtropical Lake in Southern Brazil. Water. 2019; 11 (1):168.

Chicago/Turabian Style

Matheus Henrique Tavares; Augusto Hugo Farias Cunha; David Motta-Marques; Anderson Luís Ruhoff; J. Rafael Cavalcanti; Jr. Carlos Ruberto Fragoso; Juan Martín Bravo; Andrés Mauricio Munar; Fernando Mainardi Fan; Lucia Helena Ribeiro Rodrigues. 2019. "Comparison of Methods to Estimate Lake-Surface-Water Temperature Using Landsat 7 ETM+ and MODIS Imagery: Case Study of a Large Shallow Subtropical Lake in Southern Brazil." Water 11, no. 1: 168.

Research article
Published: 18 September 2018 in Hydrology and Earth System Sciences
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Providing reliable estimates of streamflow and hydrological fluxes is a major challenge for water resources management over national and transnational basins in South America. Global hydrological models and land surface models are a possible solution to simulate the terrestrial water cycle at the continental scale, but issues about parameterization and limitations in representing lowland river systems can place constraints on these models to meet local needs. In an attempt to overcome such limitations, we extended a regional, fully coupled hydrologic–hydrodynamic model (MGB; Modelo hidrológico de Grandes Bacias) to the continental domain of South America and assessed its performance using daily river discharge, water levels from independent sources (in situ, satellite altimetry), estimates of terrestrial water storage (TWS) and evapotranspiration (ET) from remote sensing and other available global datasets. In addition, river discharge was compared with outputs from global models acquired through the eartH2Observe project (HTESSEL/CaMa-Flood, LISFLOOD and WaterGAP3), providing the first cross-scale assessment (regional/continental × global models) that makes use of spatially distributed, daily discharge data. A satisfactory representation of discharge and water levels was obtained (Nash–Sutcliffe efficiency, NSE > 0.6 in 55 % of the cases) and the continental model was able to capture patterns of seasonality and magnitude of TWS and ET, especially over the largest basins of South America. After the comparison with global models, we found that it is possible to obtain considerable improvement on daily river discharge, even by using current global forcing data, just by combining parameterization and better routing physics based on regional experience. Issues about the potential sources of errors related to both global- and continental-scale modeling are discussed, as well as future directions for improving large-scale model applications in this continent. We hope that our study provides important insights to reduce the gap between global and regional hydrological modeling communities.

ACS Style

Vinícius A. Siqueira; Rodrigo C. D. Paiva; Ayan S. Fleischmann; Fernando M. Fan; Anderson L. Ruhoff; Paulo R. M. Pontes; Adrien Paris; Stéphane Calmant; Walter Collischonn. Toward continental hydrologic–hydrodynamic modeling in South America. Hydrology and Earth System Sciences 2018, 22, 4815 -4842.

AMA Style

Vinícius A. Siqueira, Rodrigo C. D. Paiva, Ayan S. Fleischmann, Fernando M. Fan, Anderson L. Ruhoff, Paulo R. M. Pontes, Adrien Paris, Stéphane Calmant, Walter Collischonn. Toward continental hydrologic–hydrodynamic modeling in South America. Hydrology and Earth System Sciences. 2018; 22 (9):4815-4842.

Chicago/Turabian Style

Vinícius A. Siqueira; Rodrigo C. D. Paiva; Ayan S. Fleischmann; Fernando M. Fan; Anderson L. Ruhoff; Paulo R. M. Pontes; Adrien Paris; Stéphane Calmant; Walter Collischonn. 2018. "Toward continental hydrologic–hydrodynamic modeling in South America." Hydrology and Earth System Sciences 22, no. 9: 4815-4842.

Preprint content
Published: 02 May 2018
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ACS Style

Vinícius A. Siqueira; Rodrigo C. D. Paiva; Ayan S. Fleischmann; Fernando M. Fan; Anderson L. Ruhoff; Paulo R. M. Pontes; Adrien Paris; Stéphane Calmant; Walter Collischonn. Supplementary material to "Toward continental hydrologic–hydrodynamic modeling in South America". 2018, 1 .

AMA Style

Vinícius A. Siqueira, Rodrigo C. D. Paiva, Ayan S. Fleischmann, Fernando M. Fan, Anderson L. Ruhoff, Paulo R. M. Pontes, Adrien Paris, Stéphane Calmant, Walter Collischonn. Supplementary material to "Toward continental hydrologic–hydrodynamic modeling in South America". . 2018; ():1.

Chicago/Turabian Style

Vinícius A. Siqueira; Rodrigo C. D. Paiva; Ayan S. Fleischmann; Fernando M. Fan; Anderson L. Ruhoff; Paulo R. M. Pontes; Adrien Paris; Stéphane Calmant; Walter Collischonn. 2018. "Supplementary material to "Toward continental hydrologic–hydrodynamic modeling in South America"." , no. : 1.

Preprint content
Published: 02 May 2018
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Providing reliable estimates of streamflow and hydrological fluxes is a major challenge for water resources management over national and transnational basins in South America. Global hydrological models and land surface models are a possible solution to simulate the terrestrial water cycle at the continental scale, but issues on parameterization and limitations in representing lowland river systems put into question their utility for basin-scale analysis and to deliver daily discharges to meet local needs. In an attempt to overcome such limitations, we extended a regional, fully coupled hydrologic–hydrodynamic model (MGB) to the continental domain of South America and assessed its performance using daily river discharges, water levels from independent sources (in situ, satellite altimetry), estimates of terrestrial water storage (TWS) and evapotranspiration (ET) from remote sensing and other available global datasets. In addition, river discharges were compared with outputs from global models acquired through the eartH2Observe project (HTESSEL/CaMa-Flood, LISFLOOD and WaterGAP3), providing the first cross-scale assessment (regional/continental × global models) that makes use of spatially consistent daily discharge data. A satisfactory representation of discharges and water levels was obtained (NSE > 0.6 in 55 % of the cases) and MGB was able to capture patterns of seasonality and magnitude of TWS and ET especially over the largest basins of South America. Continental-scale modeling significantly improved discharge estimates when compared with global models, which resulted in a large number of gauges with negative (or close to 0) NSE values. Models were largely affected by positive bias mainly over East/Northeast Brazil and Argentina as well as over regions of Sao Francisco and Parnaiba basins, while major issues on flow timing were observed in regions affected by floodplain processes such as the Amazon, La Plata, Tocantins–Araguaia, Orinoco and Magdalena basins. We state that efforts in calibrating rainfall-runoff parameters within large basins are necessary to simulate daily river discharges appropriately in this continent, but implementing a hydrodynamic routing component is also important. We hope that our study provides further insights about hydrological simulation in South America, helping to reduce the gap between global and regional hydrological modeling communities.

ACS Style

Vinícius A. Siqueira; Rodrigo C. D. Paiva; Ayan S. Fleischmann; Fernando M. Fan; Anderson L. Ruhoff; Paulo R. M. Pontes; Adrien Paris; Stéphane Calmant; Walter Collischonn. Toward continental hydrologic–hydrodynamic modeling in South America. 2018, 2018, 1 -50.

AMA Style

Vinícius A. Siqueira, Rodrigo C. D. Paiva, Ayan S. Fleischmann, Fernando M. Fan, Anderson L. Ruhoff, Paulo R. M. Pontes, Adrien Paris, Stéphane Calmant, Walter Collischonn. Toward continental hydrologic–hydrodynamic modeling in South America. . 2018; 2018 ():1-50.

Chicago/Turabian Style

Vinícius A. Siqueira; Rodrigo C. D. Paiva; Ayan S. Fleischmann; Fernando M. Fan; Anderson L. Ruhoff; Paulo R. M. Pontes; Adrien Paris; Stéphane Calmant; Walter Collischonn. 2018. "Toward continental hydrologic–hydrodynamic modeling in South America." 2018, no. : 1-50.

Journal article
Published: 22 March 2018 in Ciência e Natura
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This study aims to evaluate the performance of MOD16 and GLEAM evapotranspiration (ET) datasets in nine eddy covariance monitoring sites. Data from both ET products were downloaded and its daily means calculated. Evapotranspiration estimations were then compared to the observed ET in the eddy covariance monitoring sites from the Large-Scale Biosphere-Atmosphere Experiment in the Amazon (LBA). We performed a statistical analysis using the correlation coefficient (R), the root mean square error (RMSE) and BIAS. Results indicate that, in general, both products can represent the observed ET in the eddy covariance flux towers. MOD16 and GLEAM showed similar values to the calculated statistics when ET estimates were compared to observed ET. Model estimates and eddy covariance flux towers are subject to uncertainties that influence the analysis of remotely-sensed ET products.

ACS Style

Adriana Aparecida Moreira; Daniela Santini Adamatti; Anderson Luis Ruhoff. Avaliação dos produtos de evapotranspiração baseados em sensoriamento remoto MOD16 e GLEAM em sítios de fluxos turbulentos do Programa LBA. Ciência e Natura 2018, 40, 112 -118.

AMA Style

Adriana Aparecida Moreira, Daniela Santini Adamatti, Anderson Luis Ruhoff. Avaliação dos produtos de evapotranspiração baseados em sensoriamento remoto MOD16 e GLEAM em sítios de fluxos turbulentos do Programa LBA. Ciência e Natura. 2018; 40 ():112-118.

Chicago/Turabian Style

Adriana Aparecida Moreira; Daniela Santini Adamatti; Anderson Luis Ruhoff. 2018. "Avaliação dos produtos de evapotranspiração baseados em sensoriamento remoto MOD16 e GLEAM em sítios de fluxos turbulentos do Programa LBA." Ciência e Natura 40, no. : 112-118.

Original articles
Published: 17 October 2013 in Hydrological Sciences Journal
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Remote sensing is considered the most effective tool for estimating evapotranspiration (ET) over large spatial scales. Global terrestrial ET estimates over vegetated land surfaces are now operationally produced at 1-km spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the MOD16 algorithm. To evaluate the accuracy of this product, ground-based measurements of energy fluxes obtained from eddy covariance sites installed in tropical biomes and from a hydrological model (MGB-IPH) were used to validate MOD16 products at local and regional scales. We examined the accuracy of the MOD16 algorithm at two sites in the Rio Grande basin, Brazil, one characterized by a sugar-cane plantation (USE), the other covered by natural savannah vegetation (PDG) for the year 2001. Inter-comparison between 8-day average MOD16 ET estimates and flux tower measurements yielded correlations of 0.78 to 0.81, with root mean square errors (RMSE) of 0.78 and 0.46 mm d-1, at PDG and USE, respectively. At the PDG site, the annual ET estimate derived by the MOD16 algorithm was 19% higher than the measured amount. For the average annual ET at the basin-wide scale (over an area of 145 000 km2), MOD16 estimates were 21% lower than those from the hydrological model MGB-IPH. Misclassification of land use and land cover was identified as the largest contributor to the error from the MOD16 algorithm. These estimates improve significantly when results are integrated into monthly or annual time intervals, suggesting that the algorithm has a potential for spatial and temporal monitoring of the ET process, continuously and systematically, through the use of remote sensing data.

ACS Style

A. L. Ruhoff; A. R. Paz; L. E. O. C. Aragao; Q. Mu; Y. Malhi; Walter Collischonn; H. R. Rocha; S. W. Running. Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin. Hydrological Sciences Journal 2013, 58, 1658 -1676.

AMA Style

A. L. Ruhoff, A. R. Paz, L. E. O. C. Aragao, Q. Mu, Y. Malhi, Walter Collischonn, H. R. Rocha, S. W. Running. Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin. Hydrological Sciences Journal. 2013; 58 (8):1658-1676.

Chicago/Turabian Style

A. L. Ruhoff; A. R. Paz; L. E. O. C. Aragao; Q. Mu; Y. Malhi; Walter Collischonn; H. R. Rocha; S. W. Running. 2013. "Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin." Hydrological Sciences Journal 58, no. 8: 1658-1676.

Journal article
Published: 12 March 2012 in Remote Sensing
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Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r 2= 0.64 and r2 = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r 2 = 0.76 and r2 = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km2 (r2= 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Rn). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.

ACS Style

Anderson L. Ruhoff; Adriano R. Paz; Walter Collischonn; Luiz E.O.C. Aragao; Humberto R. Rocha; Yadvinder S. Malhi. A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas. Remote Sensing 2012, 4, 703 -725.

AMA Style

Anderson L. Ruhoff, Adriano R. Paz, Walter Collischonn, Luiz E.O.C. Aragao, Humberto R. Rocha, Yadvinder S. Malhi. A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas. Remote Sensing. 2012; 4 (3):703-725.

Chicago/Turabian Style

Anderson L. Ruhoff; Adriano R. Paz; Walter Collischonn; Luiz E.O.C. Aragao; Humberto R. Rocha; Yadvinder S. Malhi. 2012. "A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas." Remote Sensing 4, no. 3: 703-725.

Journal article
Published: 01 August 2010 in Revista Brasileira de Ciência do Solo
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Métodos de representação espacial para o cálculo do fator topográfico (LS) da Equação Universal de Perda de Solo Revisada (RUSLE) têm sido utilizados para estimar a erosão do solo e a produção de sedimentos em bacias hidrográficas. Esses procedimentos baseiam-se nas equações tradicionalmente empregadas para determinação do fator LS e em informações que caracterizam a forma das vertentes derivadas do modelo numérico de elevação (MNE). Neste estudo foram analisados dois métodos de representação espacial utilizados no cálculo do fator LS em modelos matemáticos de erosão e produção de sedimentos em bacias hidrográficas. A análise foi realizada em quatro bacias rurais de relevo movimentado. Os valores de LS obtidos pelos métodos de representação espacial foram comparados entre si e com valores de LS determinados pelo método tradicional com levantamento em campo. Resultados mostraram que os valores de LS gerados pelos métodos de representação espacial apresentam diferenças significativas entre si, sendo dependentes do procedimento de cálculo e do método utilizado para determinar a direção de fluxo no MNE. Também foi verificado que os valores numéricos do fator LS determinados pelos métodos de representação espacial apresentam diferenças em relação àqueles estimados pelo método tradicional.

ACS Style

Jean Paolo Gomes Minella; Gustavo Henrique Merten; Anderson Luis Ruhoff. Utilização de métodos de representação espacial para cálculo do fator topográfico na equação universal de perda de solo revisada em bacias hidrográficas. Revista Brasileira de Ciência do Solo 2010, 34, 1455 -1462.

AMA Style

Jean Paolo Gomes Minella, Gustavo Henrique Merten, Anderson Luis Ruhoff. Utilização de métodos de representação espacial para cálculo do fator topográfico na equação universal de perda de solo revisada em bacias hidrográficas. Revista Brasileira de Ciência do Solo. 2010; 34 (4):1455-1462.

Chicago/Turabian Style

Jean Paolo Gomes Minella; Gustavo Henrique Merten; Anderson Luis Ruhoff. 2010. "Utilização de métodos de representação espacial para cálculo do fator topográfico na equação universal de perda de solo revisada em bacias hidrográficas." Revista Brasileira de Ciência do Solo 34, no. 4: 1455-1462.