Key Points
Remote sensing validation of a hydrologic‐hydrodynamic model of the Amazon
Uncertainty of precipitation and river‐floodplain parameters cause model errors
Importance of floodplains and ...backwater effects on flood waves traveling
In this paper, a hydrologic/hydrodynamic modeling of the Amazon River basin is presented using the MGB‐IPH model with a validation using remotely sensed observations. Moreover, the sources of model errors by means of the validation and sensitivity tests are investigated, and the physical functioning of the Amazon basin is also explored. The MGB‐IPH is a physically based model resolving all land hydrological processes and here using a full 1‐D river hydrodynamic module with a simple floodplain storage model. River‐floodplain geometry parameters were extracted from the SRTM digital elevation model, and the model was forced using satellite‐derived rainfall from TRMM3B42. Model results agree with observed in situ daily river discharges and water levels and with three complementary satellite‐based products: (1) water levels derived from ENVISAT altimetry data; (2) a global data set of monthly inundation extent; and (3) monthly terrestrial water storage (TWS) anomalies derived from the Gravity Recovery and Climate Experimental mission. However, the model is sensitive to precipitation forcing and river‐floodplain parameters. Most of the errors occur in westerly regions, possibly due to the poor quality of TRMM 3B42 rainfall data set in these mountainous and/or poorly monitored areas. In addition, uncertainty in river‐floodplain geometry causes errors in simulated water levels and inundation extent, suggesting the need for improvement of parameter estimation methods. Finally, analyses of Amazon hydrological processes demonstrate that surface waters govern most of the Amazon TWS changes (56%), followed by soil water (27%) and ground water (8%). Moreover, floodplains play a major role in stream flow routing, although backwater effects are also important to delay and attenuate flood waves.
Radar-based satellite altimetry is well recognized for oceanographic applications. For continental hydrology, its use is complicated by a number of environmental factors such as river width and ...shape, land cover type in the vicinity of the river banks, and the topography of the relief. These factors make precision vary significantly. Locations where the satellites cross the river can be used as “virtual gauging stations” that can complement the existing network of in situ stations. This article describes processing techniques that take some of these environmental factors (river shape and width) into account to improve the precision of altimetry measurements of the water level. These techniques are based on some a priori information about the river banks and on modeling a phenomenon called “off-nadir hooking”. This approach is tested on the São Francisco River in Brazil, which for most of its path is considered narrow for satellite altimetry applied to hydrology. Data from Envisat cover the period 2002–2010 while the recently launched SARAL satellite provided data for 2013. The results show that the accuracy varies significantly depending on a number of environmental factors some of which are discussed in depth. In about one-half of the 16 satellite water gauging stations, the RMS errors are lower than 60cm and in some cases better than 30cm. These variations could not be directly related to the river width, but appear to be mostly related to the land cover and to the processing chain that often extracts altimetry points from an off-nadir location. All processing is fully described and the results are presented for both the Envisat/RA-2 and SARAL/Altika altimeters.
•We successfully measured water level in a mid-size river using satellite altimetry.•We developed three original processing approaches to improve measurement accuracy.•We analyzed environmental factors to help understand of how they affect accuracy.•We compared results from Envisat and SARAL satellites.•We present results for 16 sites of varying width and environmental context.
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.
Being one of the most vulnerable regions in the world, the Ganges–Brahmaputra–Meghna delta presents a major challenge for climate change adaptation of nearly 200 million inhabitants. It is often ...considered as a delta mostly exposed to sea-level rise and exacerbated by land subsidence, even if the local vertical land movement rates remain uncertain. Here, we reconstruct the water-level (WL) changes over 1968 to 2012, using an unprecedented set of 101 water-level gauges across the delta. Over the last 45 y, WL in the delta increased slightly faster (∼3 mm/y), than global mean sea level (∼2 mm/y). However, from 2005 onward, we observe an acceleration in the WL rise in the west of the delta. The interannual WL fluctuations are strongly modulated by El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) variability, with WL lower than average by 30 to 60 cm during co-occurrent El Niño and positive IOD events and higher-than-average WL, by 16 to 35 cm, during La Niña years. Using satellite altimetry and WL reconstructions, we estimate that the maximum expected rates of delta subsidence during 1993 to 2012 range from 1 to 7 mm/y. By 2100, even under a greenhouse gas emission mitigation scenario (Representative Concentration Pathway RCP 4.5), the subsidence could double the projected sea-level rise, making it reach 85 to 140 cm across the delta. This study provides a robust regional estimate of contemporary relative WL changes in the delta induced by continental freshwater dynamics, vertical land motion, and sea-level rise, giving a basis for developing climate mitigation strategies.
This work presents a practical approach to reconstructing past and present discharge and water depth time series for operational monitoring of small-sized ungauged watersheds using remotely sensed ...and freely accessible datasets in conjunction with hydrological models. The methodology was applied to the Tsiribihina watershed in Madagascar. Mostly, satellite data are used, such as water levels from satellite altimetry missions and rainfall from the African Rainfall Climatology 2 product. In contrast, the Modelo de Grandes Bacias is calibrated using historical discharge measurements to simulate distributed discharge in the basin. Rating curves are computed by crossing the altimetry information of water height with the simulated discharge outputs. These rating curves enable the conversion of water levels, discharge and depth interchangeably. Present-day discharge and depth can thus be estimated in near real time with any update of satellite rainfall data and/or water level gained by altimetry missions currently flying in operational mode.
This study sets out to analyze the stages of water bodies in the Amazon basin derived from the processing of ERS-2 and ENVISAT satellite altimetry data. For ENVISAT, GDR measurements for both Ice-1 ...and Ice-2 tracking algorithms were tested. For ERS-2, the Ice-2 data produced by the OSCAR project was used. Water level time series over river segments of very different width, from several kilometers to less than a hundred of meters, were studied. The water level time series that can be derived from narrow riverbeds are enhanced by off-nadir detections. Conversely, the off-nadir effect may degrade the series over large bodies if not properly accounted for. Comparison at crossovers and with in situ gauges shows that the quality of the series can be highly variable, from 12cm in the best cases and 40cm in most cases to several meters in the worse cases. Cautious data selection is clearly a key point to achieve high quality series. Indeed, low quality series mostly result from inclusion of outliers in the data set finally retained for the computation of the series. Ice-2 and Ice-1 tracking algorithms in the ENVISAT data perform almost equally well. ENVISAT altimetry is clearly an improvement on ERS-2 altimetry.
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.
Since the launch of the ENVISAT satellite in 2002, the Radar Altimetry Mission provides systematic observations of the Earth topography. Among the different goals of the ENVISAT Mission, one directly ...concerns land hydrology: the monitoring of the water levels of lakes, wetlands, and rivers. The ENVISAT Geophysical Data Records products contain, over different type of surfaces, altimeter ranges derived from four specialized algorithms or retrackers. However, none of the retrackers are intended to the processing of the radar echoes over continental waters. A validation study is necessary to assess the performances of the different ENVISAT-derived water levels to monitor inland waters. We have selected four test-zones over the Amazon basin to achieve this validation study. We compare first the performances of these retracking algorithms to deliver reliable water levels for land hydrology. Comparisons with in-situ gauge stations showed that Ice-1 algorithm, based on the Offset Centre of Gravity technique, provides the more accurate water stages. Second, we examine the potentiality to combine water levels derived from different sensors (Topex/Poseidon, ERS-1 and -2, GFO).
In this study, rating curves (RCs) were determined by applying satellite altimetry to a poorly gauged basin. This study demonstrates the synergistic application of remote sensing and watershed ...modeling to capture the dynamics and quantity of flow in the Amazon River Basin, respectively. Three major advancements for estimating basin‐scale patterns in river discharge are described. The first advancement is the preservation of the hydrological meanings of the parameters expressed by Manning's equation to obtain a data set containing the elevations of the river beds throughout the basin. The second advancement is the provision of parameter uncertainties and, therefore, the uncertainties in the rated discharge. The third advancement concerns estimating the discharge while considering backwater effects. We analyzed the Amazon Basin using nearly one thousand series that were obtained from ENVISAT and Jason‐2 altimetry for more than 100 tributaries. Discharge values and related uncertainties were obtained from the rain‐discharge MGB‐IPH model. We used a global optimization algorithm based on the Monte Carlo Markov Chain and Bayesian framework to determine the rating curves. The data were randomly allocated into 80% calibration and 20% validation subsets. A comparison with the validation samples produced a Nash‐Sutcliffe efficiency (
Ens) of 0.68. When the MGB discharge uncertainties were less than 5%, the
Ens value increased to 0.81 (mean). A comparison with the in situ discharge resulted in an
Ens value of 0.71 for the validation samples (and 0.77 for calibration). The
Ens values at the mouths of the rivers that experienced backwater effects significantly improved when the mean monthly slope was included in the RC. Our RCs were not mission‐dependent, and the
Ens value was preserved when applying ENVISAT rating curves to Jason‐2 altimetry at crossovers. The cease‐to‐flow parameter of our RCs provided a good proxy for determining river bed elevation. This proxy was validated against Acoustic Doppler current profiler (ADCP) cross sections with an accuracy of more than 90%. Altimetry measurements are routinely delivered within a few days, and this RC data set provides a simple and cost‐effective tool for predicting discharge throughout the basin in nearly real time.
Key Points:
Discharge can be obtained in near‐real‐time from altimetry and rating curve
Including slope in rating curve allows adequate estimate of discharge in backwater conditions
Rating curve parameters provide meaningful information on rivers characteristics
In 2015, an emergency state was declared in Bolivia when Poopó Lake dried up. Climate variability and the increasing need for water are potential factors responsible for this situation. Because field ...data are missing over the region, no statements are possible about the influence of mentioned factors. This study is a preliminary step toward the understanding of Poopó Lake drought using remote sensing data. First, atmospheric corrections for Landsat (FLAASH and L8SR), seven satellite derived indexes for extracting water bodies, MOD16 evapotranspiration, PERSIANN-CDR and MSWEP rainfall products potentiality were assessed. Then, the fluctuations of Poopó Lake extent over the last 26 years are presented for the first time jointly, with the mean regional annual rainfall. Three main droughts are highlighted between 1990 and 2015: two are associated with negative annual rainfall anomalies in 1994 and 1995 and one associated with positive annual rainfall anomaly in 2015. This suggests that other factors than rainfall influenced the recent disappearance of the lake. The regional evapotranspiration increased by 12.8% between 2000 and 2014. Evapotranspiration increase is not homogeneous over the watershed but limited over the main agriculture regions. Agriculture activity is one of the major factors contributing to the regional desertification and recent disappearance of Poopó Lake.
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