Marcelo Curtarelli

Assessment of Spatial Interpolation Methods to Map the Bathymetry of an Amazonian Hydroelectric Reservoir to Aid in Decision Making for Water Management

The generation of reliable information for improving the understanding of hydroelectric reservoir dynamics is fundamental for guiding decision-makers to implement best management practices. In this way, we assessed the performance of different interpolation algorithms to map the bathymetry of the Tucurui hydroelectric reservoir, located in the Brazilian Amazon, as an aid to manage and operate Amazonian reservoirs. We evaluated three different deterministic and one geostatistical algorithms. The performance of the algorithms was assessed through cross-validation and Monte Carlo Simulation. Finally, operational information was derived from the bathymetric grid with the best performance. The results showed that all interpolation methods were able to map important bathymetric features. The best performance was obtained with the geostatistical method (RMSE = 0.92 m). The information derived from the bathymetric map (e.g., the level-area and level-volume diagram and the three-dimensional grid) will allow for optimization of operational monitoring of the Tucurui hydroelectric reservoir as well as the development of three-dimensional modeling studies.

Field measurements of the backscattering coefficient in a cascading reservoir system: first results from Nova Avanhandava and Barra Bonita Reservoirs (São Paulo, Brazil)

ABSTRACT In this study, a data set of total suspended matter (TSM), chlorophyll-a (Chl-a), total backscattering coefficient (bb) and the remote sensing reflectance (Rrs) were measured in the euphotic zone of two hydroelectric reservoirs at 71 stations during field surveys in the wet and dry seasons. These two reservoirs are located in a cascading system in Tietê River, São Paulo State, Brazil. The limnological and optical data were interpolated using the ordinary kriging technique to map their spatial distribution. The differences in TSM, Chl-a and in bb in space and time were investigated. The profiling data from bb were analysed. All these data were used to explain the resulting Rrs spectra in these two reservoirs. For both reservoirs, the inorganic fraction of TSM was responsible for the bb variability and therefore modulates the Rrs spectra. The seasonally difference in the optical data will help to understand how the inherent optical properties and the apparent optical properties changes in a cascading reservoir system.

Performance analysis of MODIS 500-m spatial resolution products for estimating chlorophyll-a concentrations in oligo- to meso-trophic waters case study: Itumbiara reservoir, Brazil

Monitoring chlorophyll-a (chl-a) concentrations is important for the management of water quality, because it is a good indicator of the eutrophication level in an aquatic system. Thus, our main purpose was to develop an alternative technique to monitor chl-a in time and space through remote sensing techniques. However, one of the limitations of remote sensing is the resolution. To achieve a high temporal resolution and medium space resolution, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m reflectance product, MOD09GA, and limnological parameters from the Itumbiara Reservoir. With these data, an empirical (O14a) and semi-empirical (O14b) algorithm were developed. Algorithms were cross-calibrated and validated using three datasets: one for each campaign and a third consisting of a combination of the two individual campaigns. Algorithm O14a produced the best validation with a root mean square error (RMSE) of 30.4%, whereas O14b produced an RMSE of 32.41% using the mixed dataset calibration. O14a was applied to MOD09GA to build a time series for the reservoir for the year of 2009. The time-series analysis revealed that there were occurrences of algal blooms in the summer that were likely related to the additional input of nutrients caused by rainfall runoff. During the winter, however, the few observed algal blooms events were related to periods of atmospheric meteorological variations that represented an enhanced external influence on the processes of mixing and stratification of the water column. Finally, the use of remote sensing techniques can be an important tool for policy makers, environmental managers and the scientific community with which to monitor water quality.

Evaluation of the Tropical Rainfall Measuring Mission 3B43 product over an inland area in Brazil and the effects of satellite boost on rainfall estimates

Abstract The main objective of this study was to evaluate the monthly mean areal rainfall estimated using the Tropical Rainfall Measuring Mission (TRMM) 3B43 version 7 product over an inland area in Central Brazil. Furthermore, we investigated the effect of TRMM orbit boost (in August 2001) over the 3B43 estimates. The TRMM 3B43 estimates were compared to reference rainfall data, collected at 67 rain gauge stations irregularly distributed in the study area. The results showed a good agreement between the TRMM 3B43 areal monthly mean rainfall estimations and reference data ( r > 0.97 ). The error analysis showed that the TRMM 3B43 product tends to overestimate the areal monthly mean rainfall at approximately 1.24%. The root-mean-square error (RMSE) for the entire period was 19.66     mm   month − 1 (15.75%). A Monte Carlo simulation and Wilcoxon statistical test showed that the RMSE increased significantly ( p -value < 0.01 ) after the boost, rising from 15.20 to 23.06     mm   month − 1 . However, the increase in the RMSE does not preclude the use of the TRMM 3B43 product for estimating the monthly mean areal rainfall over the Upper Paraná watershed. The impacts of boost on TRMM 3B43 estimates were observed only for rainfall rates higher than 250     mm   month − 1 .

Interactive Correlation Environment (ICE) — A Statistical Web Tool for Data Collinearity Analysis

Web tools for statistical investigation with an interactive and friendly interface enable users without programming knowledge to conduct their analyses. We develop an Interactive Correlation Environment (ICE) in an open access platform to perform spectral collinearity analysis for biogeochemical activity retrieval. We evaluate its performance on different browsers and applied it to retrieve chlorophyll-a (chl-a) concentration in a tropical reservoir. The use of ICE to retrieve water chl-a concentration got a Root Mean Square Error (RMSE) lower than 7% for seasonal datasets, enhancing ICEs ability to adapt it within season. An RMSE of 17% was found for the mixed dataset with a large range of chl-a concentrations. We conclude that the use of ICE is recommended, due to its quick response, easily manipulation, high accuracy, and empirical adaptation to seasonal variability. Its use is enhanced by the development of hyperspectral sensors, which allow the identification of several biogeochemical components, such as chl-a, phycocyanin (PC), soil salinity, soil types, leaf nitrogen, and leaf chl-a concentration.

Mean diel variability of surface energy fluxes over Manso Reservoir

Abstract Mean diel cycle of latent (E), sensible (H), net longwave (Lwnet), net shortwave (Sw), and net surface heat flux balance (S) were estimated from hourly meteorological and subsurface water temperature time series acquired for ~1 month during mid-austral autumn by a buoy system in a large tropical reservoir in Brazil. E and H were in phase and had their maximum (E = 163 Wm−2; H = 39 Wm−2) at early morning and minimum (E = 112 Wm−2; H = 6 Wm−2) midafter-noon, resulting in Bowen ratios of 0.24 and 0.06, respectively. Heat loss by evaporation therefore dominates over sensible heat used to warm surface atmosphere. Atmospheric instability was present almost all the time, increasing latent and sensible heat flux exchange coefficients by ~50% over their neutral values (from 1.4 × 10−3 to 2.2 × 10−3). Mean Lwnet varied from 76 at late afternoon to 89 Wm−2 at early morning, indicating its importance in the overall surface heat flux balance. All 3 fluxes (E, H, and Lwnet) were positive (reservoir losing energy) throughout the day. The integrated daily average net energy budget S (net short wave radiation minus E + H + Lwnet) was ~ −60 Wm−2; nighttime energy loss exceeded daytime gain, with consequent cooling of the reservoir. A mean temperature drop of about −0.1 °C d−1 was obtained by fitting a linear trend line to observed daily mean surface temperatures. In a qualitative way, diel time variations of surface water temperature were consistent to the time variability of S, indicating the dominant role of the surface heat budget in modulating surface layer temperatures of the reservoir.

Influence of summertime mesoscale convective systems on the heat balance and surface mixed layer dynamics of a large Amazonian hydroelectric reservoir

We evaluated the impacts of summertime mesoscale convective systems (MCS) on the heat balance and diel surface mixed layer (SML) dynamics of the Brazilian Amazons Tucurui Hydroelectric Reservoir (THR). We used a synergistic approach that combines in situ data, remote sensing data, and three-dimensional (3-D) modeling to investigate the typical behavior of the components of the heat balance and the SML dynamics. During the study period (the austral summer of 2012–2013), 22 days with MCS activity were identified. These events occurred approximately every 4 days, and they were most frequent during January (50% of the observations). An analysis of local meteorological data showed that when MCS occur, the environmental conditions at THR change significantly (p-value < 0.01). The net longwave flux, which was the heat balance component most strongly impacted by MCS, increased more than 32% on days with MCS activity. The daily integrated heat balance became negative (−54 W m−2) on MCS days, while the balance was positive (19 W m−2) on non-MCS days. In response to the changes in the heat balance, the SML dynamics changed when a MCS was over the THR. The SML depth was typically 28% higher on the days with MCS (∼1.6 m) compared with the days without MCS (∼1.3 m). The results indicate that MCS are one of the main meteorological disturbances driving the heat balance and the mixing dynamics of Amazonian hydroelectric reservoirs during the summer. These events may have implications for the water quality and greenhouse gas emissions of Amazonian reservoirs.

Carbon dioxide emissions from Tucuruí reservoir (Amazon biome): New findings based on three-dimensional ecological model simulations.

We used a three-dimensional model to assess the dynamics of diffusive carbon dioxide flux (F(CO2)) from a hydroelectric reservoir located at Amazon rainforest. Our results showed that for the studied periods (2013 summer/wet and winter/dry seasons) the surface averaged F(CO2) presented similar behaviors, with regular emissions peaks. The mean daily surface averaged F(CO2) showed no significant difference between the seasons (p>0.01), with values around -1338mg Cm-2day-1 (summer/wet) and -1395mg Cm-2day-1 (winter/dry). At diel scale, the F(CO2) was large during the night and morning and low during the afternoon in both seasons. Regarding its spatial distribution, the F(CO2) showed to be more heterogeneous during the summer/wet than during the winter/dry season. The highest F(CO2) were observed at transition zone (-300mg Cm-2h-1) during summer and at littoral zone (-55mg Cm-2h-1) during the winter. The total CO2 emitted by the reservoir along 2013 year was estimated to be 1.1Tg C year-1. By extrapolating our results we found that the total carbon emitted by all Amazonian reservoirs can be around 7Tg C year-1, which is 22% lower than the previous published estimate. This significant difference should not be neglected in the carbon inventories since the carbon emission is a key factor when comparing the environmental impacts of different sources of electricity generation and can influences decision makers in the selection of the more appropriate source of electricity and, in case of hydroelectricity, the geographical position of the reservoirs.

Spatiotemporal total suspended matter estimation in Itumbiara reservoir with Landsat-8/OLI images

ABSTRACT The transparency of water is affected by the amount of sunlight available, suspended particles and dissolved solids such as colored dissolved organic material present in the water column. High concentrations of total suspended matter (TSM) reduce water clarity, which can affect photosynthesis of submerged aquatic vegetation, thereby affecting oxygen production which is essential to aquatic organisms at upper levels in the food chain. The aim of this work is to evaluate the use of Landsat-8 Operational Land Imager (OLI) sensor to estimate TSM concentrations in the Itumbiara hydroelectric reservoir, Midwest Brazil (18°25′ S, 49°06′ W). Concurrent proximal remote-sensing and limnological data were collected in May and September 2009, acquired between 10:00 and 14:00 (Brazil time UTC-3) to provide representative daily readings. In situ above-water radiometric data were used to simulate remote-sensing reflectance (Rrs) for the Landsat-8/OLI spectral bands. TSM empirical models were derived from Landsat-8/OLI simulated spectral bands. The data set acquired in September 2009 was used to derive the models and the data collected in May 2009 was used for validation. To assess the similarities and differences between measured and model derived TSM concentrations, two statistical indicators were calculated. The model with lowest error was applied to selected Landsat-8/OLI images. Preliminary results showed that the model with lowest error was calibrated using Rrs from bands 2 and 3 as index. The results obtained here show that Landsat-8/OLI sensor has enough sensibility to estimate TSM concentrations in inland waters in Brazil.

Estimating total suspended matter using the particle backscattering coefficient: results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)

ABSTRACT In this study, a quasi-analytical algorithm (QAA)-based model was parameterized using remote-sensing reflectance (Rrs, units in sr−1), total absorption coefficient (at) and total suspended matter (TSM) concentration. The model was based on the particle backscattering at 561 nm (bbp(561)) and was derived from the QAA and TSM concentration. The aim of this work was to parameterize a QAA-based model to estimate the TSM concentration using the Landsat-8 Operational Land Imager (OLI) sensor in the Itumbiara hydroelectric reservoir, Brazil. The results demonstrated that the calibrated model, TSM = , had a coefficient of determination of R2 = 0.70 and that the validation had an R2 = 0.82, RMSE = 41.39% and a mean bias of 0.074 mg l−1. The primary observation using the TSM and bbp(561) maps is that waters with lower bbp(561) values have lower TSM concentrations; there is a direct correlation between bbp(561) and TSM concentration.