Adriano Rolim da Paz

A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

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.

Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin

Abstract 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. Editor D. Koutsoyiannis; Associate editor T. Wagener Citation Ruhoff, A.L., Paz, A.R., Aragao, L.E.O.C., Mu, Q., Malhi, Y., Collischonn, W., Rocha, H.R., and Running, S.W., 2013. Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin. Hydrological Sciences Journal, 58 (8), 1658–1676.

Errors in river lengths derived from raster digital elevation models

Length of river reaches is one of the most important characteristics of stream networks when applying hydrological or environmental simulation models. A common method of obtaining estimates of river lengths is based on deriving flow directions, accumulated area and drainage lines from raster digital elevation models (DEM). This method leads to length estimates with variable accuracy, which depends on DEM horizontal resolution, flatness of terrain, DEM vertical accuracy, the algorithm used to obtain flow directions and the way by which distances are calculated over raster structures. We applied an automatic river length extraction method for eight river reaches in the River Uruguay Basin (206000km^2), in Southern Brazil, and compared its results to the lengths obtained from drainage vector lines digitalized over satellite images. Our results show that relative errors can be higher than 30% in flat regions with relatively low DEM resolution. Preprocessing of DEM by the method known as stream burning greatly improves results, reducing errors to the range 1.9-7.4%. Further improved estimates were obtained by applying optimized values for the length of orthogonal and diagonal steps called distance transforms, reducing the errors to the range -2.0-3.3%.

Large-Scale Hydrodynamic Modeling of a Complex River Network and Floodplains

This paper presents a one-dimensional hydrodynamic modeling of a large-scale river network and floodplains. The study site comprises the Upper Paraguay River and its main tributaries (a total of 4,800 km of river reaches) in South American central area, including a complex river network flowing along the Pantanal wetland. The main issues are related to preparing input data for the hydraulic model in a consistent and georeferenced database and to representing different flow regimes. Geographic information systems-based automatic procedures were developed in order to produce cross-sectional profiles that encompass the large floodplains and to link hydraulic data and spatial location. The marked seasonal flow regime and relative smooth hydrographs of Paraguay River were quite well reproduced by the hydraulic model. For the tributaries, it must be mentioned the model’s ability to simulate both cases when the hydrograph does not present a marked peak flow, due to water loss for the floodplain, and when the hyd...

Improvements in large‐scale drainage networks derived from digital elevation models

[1] This paper presents an improved algorithm for deriving drainage networks for coarse-gridded distributed hydrological models based on relatively fine resolution digital elevation models. The proposed algorithm aims to reproduce actual drainage networks more closely when applied in regions with meandering rivers running in parallel and for cell sizes of the order of 10 kilometers. To achieve this goal, the COTAT algorithm of Reed (2003) was improved, introducing another parameter related to the minimum upstream flow path into the cell besides the area threshold. The proposed algorithm was tested by applying it to the catchments of the rivers Tapajos (530,000 km 2 ) and Grande (145,000 km 2 ) in South America. Results show that drainage networks are generally improved by the proposed algorithm, needing only minor manual corrections.

Incorporating Forecasts of Rainfall in Two Hydrologic Models Used for Medium-Range Streamflow Forecasting

This study reports on the performance of two medium-range streamflow forecast models: (1) a multilayer feed-forward artificial neural network; and (2) a distributed hydrologic model. Quantitative precipitation forecasts were used as input to both models. The Furnas Reservoir on the Rio Grande River was selected as a case study, primarily because of the availability of quantitative precipitation forecasts from the Brazilian Center for Weather Prediction and Climate Studies and due to its importance in the Brazilian hydropower generating system. Streamflow forecasts were calculated for a drainage area of about 51,900 km(2), with lead times up to 12 days, at daily intervals. The Nash-Sutcliffe efficiency index, the root-mean-square error, the mean absolute error, and the mean relative error were used to assess the relative performance of the models. Results showed that the performance of streamflow forecasts was strongly dependent on the quality of quantitative precipitation forecasts used. The artificial neural network (ANN) method seemed to be less sensitive to precipitation forecast error relative to the distributed hydrological model. Hence, the latter presented a better skill in flow forecasting when using the more accurate perfect precipitation forecast. The conceptual hydrological model also demonstrates better forecast skill than ANN models for longer lead times, when the representation of the rainfall-runoff process and of the water storage in the watershed becomes more important than the flow routing along the drainage network. In addition, results obtained by incorporating a quantitative precipitation forecast in both models performed better than the current streamflow obtained by the Brazilian national electric system operator using statistical models which do not utilize information on precipitation, whether observed or forecast. (Less)

Estimativa de área agrícola por meio de séries temporais Modis NDVI no Estado do Mato Grosso

The objective of this work was to evaluate a simple, semi‑automated methodology for mapping cropland areas in the state of Mato Grosso, Brazil. A Fourier transform was applied over a time series of vegetation index products from the moderate resolution imaging spectroradiometer (Modis) sensor. This procedure allows for the evaluation of the amplitude of the periodic changes in vegetation response through time and the identification of areas with strong seasonal variation related to crop production. Annual cropland masks from 2006 to 2009 were generated and municipal cropland areas were estimated through remote sensing. We observed good agreement with official statistics on planted area, especially for municipalities with more than 10% of cropland cover (R2 = 0.89), but poor agreement in municipalities with less than 5% crop cover (R2 = 0.41). The assessed methodology can be used for annual cropland mapping over large production areas in Brazil.

Geotecnologias aplicadas à avaliação de parâmetros biofísicos do Pantanal

The objective of this work was to evaluate surface biophysical parameters of the Pantanal biome, Brazil, by the application of geotechnologies. The Sebal algorithm, Modis imagery, and land use and land cover map were used. The obtained results for NDVI, surface temperature, albedo, daily sensible heat flux, daily net radiation and daily actual evapotranspiration were consistent with literature data for the different land use and land cover classes, and corroborate the analytical and synoptic capacity of Sebal estimates. These results show the potential of geotechnologies in the implementation of models or algorithms developed for the understanding of biophysical process dynamics related to the soil‑plant‑atmosphere interactions in Pantanal.

Avaliação de estimativas de campos de precipitação para modelagem hidrológica distribuída

There is an increasing availability and application of precipitation fields estimated by remote sensing or calculated by atmospheric circulation models, which are frequently used as input for distributed hydrological models. The spatial distribution of the estimated precipitation fields is extremely important and must be verified against observed precipitation fields. This paper proposes a method for spatiotemporal comparison between observed and estimated precipitation fields based on a pixel by pixel comparison and on contingency tables. Two distinct approaches are carried out: (i) the spatial integrated analysis produces skill scores denoting the ability of the estimated precipitation field in reproducing the occurrence of observed precipitation along the time; (ii) the time integrated analysis generates maps of skill scores showing the reliability of the precipitation estimates in each pixel. As an example of application, the estimated precipitation climatology of the CPTEC/COLA global circulation model over the Rio Grande basin is assessed. Using five different skill scores, the proposed method identified seasonal variations and spatial patterns in the performance of the estimated precipitation fields in relation to precipitation fields derived from pluviometers measurement.

Análise da evolução e estimativa futura da massa coletada de resíduos sólidos domiciliares no município de João Pessoa e relação com outros indicadores de consumo

This paper has the general purpose of analyzing the spatiotemporal variation of the amount of collected domestic solid waste (DSW) in Joao Pessoa districts between 2003 and 2010. The methodology accomplished a preliminary consistency analysis of DSW data, followed by determining per capita of DSW, annual variation rates of absolute values and per capita of DSW, correlation analysis for the year 2010 between DSW per capita and variables representing income, education, energy and water per capita consumption, and three future scenarios of DSW collection were traced until 2030. It was estimated an increase of 32.4% for the total DSW collected in the period 2003-2010, reaching in 2010 an equivalent to 0.806 kg.person-1.day -1, which is coherent with an earlier study that has monitored three single-family residences in the city. Such an increase is consequence not only of the population growth (15.1%), but also due to intensification in goods consumption. The relationship between DSW production and consumption patterns was highlighted by the strong correlation found between per capita of collected DSW and per capita of energy consumption, education and income variables. This corroborates the need of a cultural change regarding consumption, misuse and discard of solid waste towards environmental sustainability. If the rate of solid waste generation keeps growing, it is projected between 0.85 and 1.88 kg.person-1.day -1 about 2030, which will increase the challenge of collecting the DSW, landfill disposing and management, and the need of actions to mitigate potential environmental impacts.