scholarly journals River Discharge Estimation based on Satellite Water Extent and Topography: An Application over the Amazon

2019 ◽  
Vol 20 (9) ◽  
pp. 1851-1866 ◽  
Author(s):  
Dinh Thi Lan Anh ◽  
Filipe Aires
Keyword(s):  
River Discharge ◽  
Amazon Basin ◽  
Water Cycle ◽  
Large River ◽  
Water Volume ◽  
Discharge Estimation ◽  
Three Rivers ◽  
Storage Change

Abstract River discharge (RD) estimates are necessary for many applications, including water management, flood risk, and water cycle studies. Satellite-derived long-term GIEMS-D3 surface water extent (SWE) maps and HydroSHEDS data, at 90-m resolution, are here used to estimate several hydrological quantities at a monthly time scale over a few selected locations within the Amazon basin. Two methods are first presented to derive the water level (WL): the “hypsometric curve” and the “histogram cutoff” approaches at an 18 km × 18 km resolution. The obtained WL values are interpolated over the whole water mask using a bilinear interpolation. The two methods give similar results and validation with altimetry is satisfactory, with a correlation ranging from 0.72 to 0.89 in the seven considered stations over three rivers (i.e., Wingu, Negro, and Solimoes Rivers). River width (RW) and water volume change (WVC) are also estimated. WVC is evaluated with GRACE total water storage change, and correlations range from 0.77 to 0.88. A neural network (NN) statistical model is then used to estimate the RD based on four predictors (SWE, WL, WVC, and RW) and on in situ RD measurements. Results compare well to in situ measurements with a correlation of about 0.97 for the raw data (and 0.84 for the anomalies). The presented methodologies show the potential of historical satellite data (the combination of SWE with topography) to help estimate RD. Our study focuses here on a large river in the Amazon basin at a monthly scale; additional analyses would be required for other rivers, including smaller ones, in different environments, and at higher temporal scale.

scholarly journals Long-term Total Water Storage Change from a SAtellite Water Cycle (SAWC) reconstruction over large south Asian basins

2019 ◽  
Author(s):  
Victor Pellet ◽  
Filipe Aires ◽  
Fabrice Papa ◽  
Simon Munier ◽  
Bertrand Decharme
Keyword(s):  
Water Resources ◽  
Climate Variability ◽  
Water Cycle ◽  
Water Storage ◽  
Anthropogenic Pressure ◽  
Total Water ◽  
Storage Change ◽  
Discharge Measurements

Abstract. The Total Water Storage Change (TWSC) over land is a major component of the global water cycle, with a large influence on climate variability, sea level budget and water resources availability for human life. Its first estimates at large-scale were made available with GRACE observations for the 2002–2016 period, followed since 2018 by the launch of GRACE-FO mission. In this paper, using an approach based on the water mass conservation rule, we proposed to merge satellite-based observations of precipitation and evapotranspiration along with in situ river discharge measurements to estimate TWSC over longer time periods (typically from 1980 to 2016), compatible with climate studies. We performed this task over five major Asian basins, subject to both large climate variability and strong anthropogenic pressure for water resources, and for which long term record of in situ discharge measurements are available. Our SAtellite Water Cycle (SAWC) reconstruction provides TWSC estimates very coherent in terms of seasonal and interannual variations with independent sources of information such as (1) TWSC GRACE-derived observations (over the 2002–2015 period), (2) ISBA-CTRIP model simulations (1980–2015), and (3) multi-satellite inundation extent (1993–2007). This analysis shows the advantages of the use of multiple satellite-derived data sets along with in situ data to perform hydrologically coherent reconstruction of missing water component estimate. It provides a new critical source of information for long term monitoring of TWSC and to better understand their critical role in the global and terrestrial water cycle.

scholarly journals Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins

2020 ◽  
Vol 24 (6) ◽  
pp. 3033-3055
Author(s):  
Victor Pellet ◽  
Filipe Aires ◽  
Fabrice Papa ◽  
Simon Munier ◽  
Bertrand Decharme
Keyword(s):  
Climate Variability ◽  
Water Cycle ◽  
Critical Role ◽  
Water Storage ◽  
Anthropogenic Pressure ◽  
Total Water ◽  
Storage Change ◽  
Discharge Measurements

Abstract. The total water storage change (TWSC) over land is a major component of the global water cycle, with a large influence on the climate variability, sea level budget and water resource availability for human life. Its first estimates at a large scale were made available with GRACE (Gravity Recovery and Climate Experiment) observations for the 2002–2016 period, followed since 2018 by the launch of the GRACE-FO (Follow-On) mission. In this paper, using an approach based on the water mass conservation rule, we propose to merge satellite-based observations of precipitation and evapotranspiration with in situ river discharge measurements to estimate TWSC over longer time periods (typically from 1980 to 2016), compatible with climate studies. We performed this task over five major Asian basins, subject to both large climate variability and strong anthropogenic pressure for water resources and for which long-term records of in situ discharge measurements are available. Our Satellite Water Cycle (SAWC) reconstruction provides TWSC estimates very coherent in terms of seasonal and interannual variations with independent sources of information such as (1) TWSC GRACE-derived observations (over the 2002–2015 period), (2) ISBA-CTRIP (Interactions between Soil, Biosphere and Atmosphere CNRM – Centre National de Recherches Météorologiques – Total Runoff Integrating Pathways) model simulations (1980–2015) and (3) the multi-satellite inundation extent (1993–2007). This analysis shows the advantages of the use of multiple satellite-derived datasets along with in situ data to perform a hydrologically coherent reconstruction of a missing water component estimate. It provides a new critical source of information for the long-term monitoring of TWSC and to better understand its critical role in the global and terrestrial water cycle.

scholarly journals Using modelled discharge to develop satellite-based river gauging: a case study for the Amazon Basin

2018 ◽  
Author(s):  
Jiawei Hou ◽  
Albert I. J. M. van Dijk ◽  
Luigi J. Renzullo ◽  
Robert A. Vertessy
Keyword(s):  
Surface Water ◽  
River Discharge ◽  
Water Resource Management ◽  
Amazon Basin ◽  
Water Cycle ◽  
Detection System ◽  
Optical Data ◽  
Large Area ◽  
Discharge Measurements

Abstract. River discharge measurements have proven invaluable to monitor the global water cycle, assess flood risk, and guide water resource management. However, there is a delay and overall decline in the availability of gauging data and stations are highly unevenly distributed globally. While not a substitute for river discharge measurement, remote sensing is a cost-effective technology to acquire information on river dynamics. The general approach has been to relate satellite observation to discharge measured in situ, which prevents its use for ungauged rivers. Alternatively, hydrological models are now available that can be used to estimate river discharge globally. While subject to greater errors and biases than measurements, model estimates of river discharge do expand the options for applying satellite-based discharge monitoring in ungauged rivers. Our aim was to test this approach. We used gridded surface water extent information from two sources: (1) Global Flood Detection System (GFDS) passive microwave data; and (2) MODIS optical data. The data were available for the common period of 2000–2014. The hydrological model used was the World-Wide Water (W3) model version 2, providing river discharge from 1980 to 2014. We designed and compared two methods to relate simulated storage and discharge to MODIS and GFDS surface water extent fraction for developing satellite gauging reaches (SGRs), and applied the best performing method to construct SGRs across the Amazon Basin. River discharge estimates from MODIS SGRs, GFDS SGRs, and the W3 model were evaluated with in situ river discharge measurements. The results showed SGRs can be successfully established over a large area using MODIS and GFDS water extent and modelled discharge, and used to estimate river discharge at both gauged and ungauged sites.

scholarly journals Using modelled discharge to develop satellite-based river gauging: a case study for the Amazon Basin

2018 ◽  
Vol 22 (12) ◽  
pp. 6435-6448 ◽  
Author(s):  
Jiawei Hou ◽  
Albert I. J. M. van Dijk ◽  
Luigi J. Renzullo ◽  
Robert A. Vertessy
Keyword(s):  
River Discharge ◽  
Water Resource Management ◽  
Large Scale ◽  
Amazon Basin ◽  
Water Cycle ◽  
Detection System ◽  
Grid Cell ◽  
Cost Effective ◽  
Satellite Observation ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. River discharge measurements have proven invaluable to monitor the global water cycle, assess flood risk, and guide water resource management. However, there is a delay, and ongoing decline, in the availability of gauging data and stations are highly unevenly distributed globally. While not a substitute for river discharge measurement, remote sensing is a cost-effective technology to acquire information on river dynamics in situations where ground-based measurements are unavailable. The general approach has been to relate satellite observation to discharge measured in situ, which prevents its use for ungauged rivers. Alternatively, hydrological models are now available that can be used to estimate river discharge globally. While subject to greater errors and biases than measurements, model estimates of river discharge do expand the options for applying satellite-based discharge monitoring in ungauged rivers. Our aim was to test whether satellite gauging reaches (SGRs), similar to virtual stations in satellite altimetry, can be constructed based on Moderate Resolution Imaging Spectroradiometer (MODIS) optical or Global Flood Detection System (GFDS) passive microwave-derived surface water extent fraction and simulated discharge from the World-Wide Water (W3) model version 2. We designed and tested two methods to develop SGRs across the Amazon Basin and found that the optimal grid cell selection method performed best for relating MODIS and GFDS water extent to simulated discharge. The number of potential river reaches to develop SGRs increases from upstream to downstream reaches as rivers widen. MODIS SGRs are feasible for more river reaches than GFDS SGRs due to its higher spatial resolution. However, where they could be constructed, GFDS SGRs predicted discharge more accurately as observations were less affected by cloud and vegetation. We conclude that SGRs are suitable for automated large-scale application and offer a possibility to predict river discharge variations from satellite observations alone, for both gauged and ungauged rivers.

scholarly journals Past terrestrial water storage (1980–2008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data

2011 ◽  
Vol 15 (2) ◽  
pp. 533-546 ◽  
Author(s):  
M. Becker ◽  
B. Meyssignac ◽  
L. Xavier ◽  
A. Cazenave ◽  
R. Alkama ◽  
...  
Keyword(s):  
Large Scale ◽  
Amazon Basin ◽  
Hydrological Modeling ◽  
Water Cycle ◽  
Southern Oscillation ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Direct Estimate ◽  
Terrestrial Water

Abstract. Terrestrial water storage (TWS) composed of surface waters, soil moisture, groundwater and snow where appropriate, is a key element of global and continental water cycle. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) space gravimetry mission provides a new tool to measure large-scale TWS variations. However, for the past few decades, direct estimate of TWS variability is accessible from hydrological modeling only. Here we propose a novel approach that combines GRACE-based TWS spatial patterns with multi-decadal-long in situ river level records, to reconstruct past 2-D TWS over a river basin. Results are presented for the Amazon Basin for the period 1980–2008, focusing on the interannual time scale. Results are compared with past TWS estimated by the global hydrological model ISBA-TRIP. Correlations between reconstructed past interannual TWS variability and known climate forcing modes over the region (e.g., El Niño-Southern Oscillation and Pacific Decadal Oscillation) are also estimated. This method offers new perspective for improving our knowledge of past interannual TWS in world river basins where natural climate variability (as opposed to direct anthropogenic forcing) drives TWS variations.

scholarly journals Rationale for Monitoring Discharge on the Ground

2012 ◽  
Vol 13 (6) ◽  
pp. 1977-1986 ◽  
Author(s):  
Balázs M. Fekete ◽  
Ulrich Looser ◽  
Alain Pietroniro ◽  
Richard D. Robarts
Keyword(s):  
Remote Sensing ◽  
River Discharge ◽  
Hydrological Cycle ◽  
Water Cycle ◽  
In Situ Monitoring ◽  
Water Fluxes ◽  
Earth Observations ◽  
Discharge Monitoring ◽  
Earth’S Climate

Abstract The hydrological cycle is receiving increasing attention both as an essential natural resource for humans and ecosystems and as a critical component controlling the earth’s climate system. Better understanding of the water cycle and its interaction with changing climate will require improved monitoring of the various water fluxes and storages in hydrological processes. River discharge is a unique component reflecting an integrated hydrological signal over larger regions. Existing in situ monitoring solutions to monitor discharge are often considered too expensive and the difficulties in data sharing are viewed as insurmountable obstacles, which has led to growing interest in finding an alternative. This paper argues that in situ monitoring is far less expensive than claimed and the obstacles are not necessarily as insurmountable as often stated and a conscious effort to revitalize in situ monitoring will be needed. This paper demonstrates that there is no substitute for in situ discharge monitoring, but there should be a synergy between in situ monitoring and remote sensing since they are truly complementary. This paper primarily focuses on river discharge, but the conclusions are relevant for a host of other earth observations (particularly water quality) that would greatly benefit from a reconsidered balance between in situ and remote sensing observations.

scholarly journals The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

2011 ◽  
Vol 8 (1) ◽  
pp. 1609-1663 ◽  
Author(s):  
W. A. Dorigo ◽  
W. Wagner ◽  
R. Hohensinn ◽  
S. Hahn ◽  
C. Paulik ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Water Cycle ◽  
Soil Moisture Data ◽  
The North ◽  
Time Period ◽  
Different Depths ◽  
Operational Networks

Abstract. In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status January 2011), the ISMN contains data of 16 networks and more than 500 stations located in the North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

Estimation of River Discharge using Multi-Mission Satellite Altimetry and Optical Remote Sensing Imagery

2020 ◽  
Author(s):  
Daniel Scherer ◽  
Christian Schwatke ◽  
Denise Dettmering
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Water Level ◽  
River Discharge ◽  
Water Surface ◽  
Satellite Altimetry ◽  
Remote Sensing Data ◽  
Sensing Data

<p>Despite increasing interest in monitoring the global water cycle, the availability of in-situ discharge time series is decreasing. However, this lack of ground data can be compensated by using remote sensing techniques to observe river discharge.</p><p>In this contribution, a new approach for estimating the discharge of large rivers by combining various long-term remote sensing data with physical flow equations is presented. For this purpose, water levels derived from multi-mission satellite altimetry and water surface extents extracted from optical satellite images are used, both provided by DGFI-TUM’s “Database of Hydrological Time series of Inland Waters” (DAHITI, https://dahiti.dgfi.tum.de). The datasets are combined by fitting a hypsometric curve in order to describe the stage-width relation, which is then used to derive the water level for each acquisition epoch of the long-term multi-spectral remote sensing missions. In this way, the chance of detecting water level extremes is increased and a bathymetry can be estimated from water surface extent observations. Below the minimum hypsometric water level, the river bed elevation is estimated using an empirical width-to-depth relationship in order to determine the final cross-sectional geometry. The required flow gradient is computed based on a linear adjustment of river surface slope using all altimetry-observed water level differences between synchronous measurements at various virtual stations along the river. The roughness coefficient is set based on geomorphological features quantified by adjustment factors. These are chosen using remote sensing data and a literature decision guide.</p><p>Within this study, all parameters are estimated purely based on remote sensing data, without using any ground data. In-situ data is only used for the validation of the method at the Lower Mississippi River. It shows that the presented approach yields best results for uniform and straight river sections. The resulting normalized root mean square error for those targets varies between 10% to 35% and is comparable with other studies.</p>

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