scholarly journals Informing a hydrological model of the Ogooué with multi-mission remote sensing data

2017 ◽  
Author(s):  
Cecile M. M. Kittel ◽  
Karina Nielsen ◽  
Christian Tøttrup ◽  
Peter Bauer-Gottwein
Keyword(s):  
Remote Sensing ◽  
Hydrological Model ◽  
Water Storage ◽  
Remote Sensing Data ◽  
Total Water ◽  
Support Tool ◽  
River Stage ◽  
Satellite Missions ◽  
Sar Imagery ◽  
Storage Change

Abstract. Remote sensing provides a unique opportunity to inform and constrain a hydrological model and to increase its value as a decision-support tool. In this study, we applied a multi-mission approach to force, calibrate and validate a hydrological model of the ungauged Ogooué river basin in Africa with publicly available and free remote sensing observations. We used a rainfall–runoff model based on the Budyko framework coupled with a Muskingum routing approach. We parametrized the model using the SRTM DEM, and forced it using precipitation from two satellite-based rainfall estimates, FEWS-RFE and TRMM 3B42 v.7, and temperature from ECMWF ERA-Interim. We combined three different datasets to calibrate the model using an aggregated objective function with contributions from: (1) historical in-situ discharge observations from the period 1953-1984 at 6 locations in the basin, (2) radar altimetry measurements of river stages by Envisat and Jason-2 at 12 locations in the basin and (3) GRACE total water storage change. Additionally, we extracted CryoSat-2 observations throughout the basin using a Sentinel-1 SAR imagery water mask and used the observations for validation of the model. The use of new satellite missions, including Sentinel-1 and CryoSat-2, increased the spatial characterization of river stage. Throughout the basin, we achieved good agreement between observed and simulated discharge and river stage, with a RMSD between simulated and observed water amplitudes at virtual stations of 0.74 m for the TRMM forced model and 0.87 m for the FEWS-RFE forced model. The hydrological model also generally captures total water storage change patterns, although the amplitude of storage change is generally underestimated. By combining hydrological modelling with multi-mission remote sensing from ten different satellite missions, we obtain new information on an otherwise unstudied basin. The proposed model is the best current baseline characterisation of hydrological conditions in the Ogooué in light of the available observations.

scholarly journals Informing a hydrological model of the Ogooué with multi-mission remote sensing data

2018 ◽  
Vol 22 (2) ◽  
pp. 1453-1472 ◽  
Author(s):  
Cecile M. M. Kittel ◽  
Karina Nielsen ◽  
Christian Tøttrup ◽  
Peter Bauer-Gottwein
Keyword(s):  
Remote Sensing ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Water Storage ◽  
Total Water ◽  
Support Tool ◽  
River Stage ◽  
Satellite Missions ◽  
Storage Change

Abstract. Remote sensing provides a unique opportunity to inform and constrain a hydrological model and to increase its value as a decision-support tool. In this study, we applied a multi-mission approach to force, calibrate and validate a hydrological model of the ungauged Ogooué river basin in Africa with publicly available and free remote sensing observations. We used a rainfall–runoff model based on the Budyko framework coupled with a Muskingum routing approach. We parametrized the model using the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) and forced it using precipitation from two satellite-based rainfall estimates, FEWS-RFE (Famine Early Warning System rainfall estimate) and the Tropical Rainfall Measuring Mission (TRMM) 3B42 v.7, and temperature from ECMWF ERA-Interim. We combined three different datasets to calibrate the model using an aggregated objective function with contributions from (1) historical in situ discharge observations from the period 1953–1984 at six locations in the basin, (2) radar altimetry measurements of river stages by Envisat and Jason-2 at 12 locations in the basin and (3) GRACE (Gravity Recovery and Climate Experiment) total water storage change (TWSC). Additionally, we extracted CryoSat-2 observations throughout the basin using a Sentinel-1 SAR (synthetic aperture radar) imagery water mask and used the observations for validation of the model. The use of new satellite missions, including Sentinel-1 and CryoSat-2, increased the spatial characterization of river stage. Throughout the basin, we achieved good agreement between observed and simulated discharge and the river stage, with an RMSD between simulated and observed water amplitudes at virtual stations of 0.74 m for the TRMM-forced model and 0.87 m for the FEWS-RFE-forced model. The hydrological model also captures overall total water storage change patterns, although the amplitude of storage change is generally underestimated. By combining hydrological modeling with multi-mission remote sensing from 10 different satellite missions, we obtain new information on an otherwise unstudied basin. The proposed model is the best current baseline characterization of hydrological conditions in the Ogooué in light of the available observations.

scholarly journals REMOTE SENSING OF WATER BALANCE IN PANTANAL

2019 ◽  
Vol 46 (3) ◽  
pp. 20
Author(s):  
Adriana Aparecida Moreira ◽  
Alice César Fassoni-Andrade ◽  
Anderson Luis Ruhoff ◽  
Rodrigo Cauduro Dias de Paiva
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Water Storage ◽  
Remote Sensing Data ◽  
Northern Region ◽  
Sensing Data ◽  
In Situ Data ◽  
Storage Change ◽  
Hydrological Variables

Pantanal, located in the Upper Paraguay basin, is the world’s largest tropical wetland. The maintenance of this ecosystem depends on the water balance since precipitation is seasonal and high losses of water occur due to the high evapotranspiration. Water balance assessment using in situ data is still a challenge due to the large extension of the area and the complexity to be represented. In this study, the water balance in the Upper Paraguay basin was investigated based on hydrological variables derived from remote sensing data. Precipitation, evapotranspiration, and water storage change data were estimated with accuracy by the water balance, but the same was not possible for the discharge. However, high uncertainties in the estimates were verified, mainly during the rainy season. The remote sensing data allowed the identification of the seasonality of hydrological variables in the Pantanal system and in the different regions of the basin: Chaco, Pantanal and Planalto. Water deficit in the basin was observed from March/April to September as well as a positive water balance due to precipitation during the rest of the year. The spatial analysis of the basin showed that in the northern region, the precipitation, the evapotranspiration, and the water storage variation are higher than in the southern region. Results demonstrated that remote sensing data can help in the comprehension of hydrological systems operation, especially in large wetland regions.

Stepwise improvement of hydrological models using satellite-based evaporation and total water storage estimations

2021 ◽  
Author(s):  
Markus Hrachowitz ◽  
Petra Hulsman ◽  
Hubert Savenije
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Model Development ◽  
Water Storage ◽  
Spatiotemporal Variability ◽  
Model Structure ◽  
Hydrological Models ◽  
Total Water ◽  
Spatiotemporal Model ◽  
Multiple Variables

<p>Hydrological models are often calibrated with respect to flow observations at the basin outlet. As a result, flow predictions may seem reliable but this is not necessarily the case for the spatiotemporal variability of system-internal processes, especially in large river basins. Satellite observations contain valuable information not only for poorly gauged basins with limited ground observations and spatiotemporal model calibration, but also for stepwise model development. This study explored the value of satellite observations to improve our understanding of hydrological processes through stepwise model structure adaption and to calibrate models both temporally and spatially. More specifically, satellite-based evaporation and total water storage anomaly observations were used to diagnose model deficiencies and to subsequently improve the hydrological model structure and the selection of feasible parameter sets. A distributed, process based hydrological model was developed for the Luangwa river basin in Zambia and calibrated with respect to discharge as benchmark. This model was modified stepwise by testing five alternative hypotheses related to the process of upwelling groundwater in wetlands, which was assumed to be negligible in the benchmark model, and the spatial discretization of the groundwater reservoir. Each model hypothesis was calibrated with respect to 1) discharge and 2) multiple variables simultaneously including discharge and the spatiotemporal variability in the evaporation and total water storage anomalies. The benchmark model calibrated with respect to discharge reproduced this variable well, as also the basin-averaged evaporation and total water storage anomalies. However, the evaporation in wetland dominated areas and the spatial variability in the evaporation and total water storage anomalies were poorly modelled. The model improved the most when introducing upwelling groundwater flow from a distributed groundwater reservoir and calibrating it with respect to multiple variables simultaneously. This study showed satellite-based evaporation and total water storage anomaly observations provide valuable information for improved understanding of hydrological processes through stepwise model development and spatiotemporal model calibration.</p>

Estimating the water balance and uncertainty bounds in a highly groundwater-dependent and data-scarce areas: An example for the upper Citarum basin

2021 ◽  
Author(s):  
Steven Reinaldo Rusli ◽  
Albrecht Weerts ◽  
Victor Bense
Keyword(s):  
Water Balance ◽  
Water Storage ◽  
Total Water ◽  
Groundwater Abstraction ◽  
Water Balance Components ◽  
Groundwater Storage ◽  
Actual Evaporation ◽  
Basin Scale ◽  
Basin Water ◽  
Storage Change

<p>In this study, we estimate the water balance components of a highly groundwater-dependent and hydrological data-scarce basin of the upper reaches of the Citarum river in West Java, Indonesia. Firstly, we estimate the groundwater abstraction volumes based on population size and a review of literature (0.57mm/day). Estimates of other components like rainfall, actual evaporation, discharge, and total water storage changes are derived from global datasets and are simulated using a distributed hydrological wflow_sbm model which yields additional estimates of discharge, actual evaporation, and total water storage change. We compare each basin water balance estimate as well as quantify the uncertainty of some of the components using the Extended Triple Collocation (ETC) method.</p><p>The ETC application on four different rainfall estimates suggests a preference of using the CHIRPS product as the input to the water balance components estimates as it delivers the highest r<sup>2</sup>  and the lowest RMSE compared to three other sources. From the different data sources and results of the distributed hydrological modeling using CHIRPS as rainfall forcing, we estimate a positive groundwater storage change between 0.12 mm/day - 0.60 mm/day. These results are in agreement with groundwater storage change estimates based upon GRACE gravimetric satellite data, averaged at 0.25 mm/day. The positive groundwater storage change suggests sufficient groundwater recharge occurs compensating for groundwater abstraction. This conclusion seems in agreement with the observation since 2005, although measured in different magnitudes. To validate and narrow the estimated ranges of the basin water storage changes, a devoted groundwater model is necessary to be developed. The result shall also aid in assessing the current and future basin-scale groundwater level changes to support operational water management and policy in the Upper Citarum basin.</p>

scholarly journals Spatial pattern evaluation of a calibrated national hydrological model – a remote sensing based diagnostic approach

2017 ◽  
Author(s):  
Gorka Mendiguren ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Hydrological Model ◽  
Remote Sensing Data ◽  
Driving Mechanism ◽  
Distributed Hydrological Model ◽  
Eof Analysis ◽  
Sensing Data ◽  
Spatio Temporal

Abstract. Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two source energy balance model (TSEB) driven mainly by satellite remote sensing data. The main hypothesis of the study is that while both approaches are essentially estimates, the spatial patterns of the remote sensing based approach are explicitly driven by observed land surface temperature and therefore represent the most direct spatial pattern information of ET; enabling its use for distributed hydrological model evaluation. Ideally the hydrological model simulation and remote sensing based approach should present similar spatial patterns and driving mechanism of ET. However, the spatial comparison showed that the differences are significant and indicating insufficient spatial pattern performance of the hydrological model. The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in 6 domains that are calibrated independently from each other, as it is often the case for large scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of Leaf Area Index (LAI), root depth (RD) and Crop coefficient (Kc) for each land cover type. This zonal approach of model parametrization ignores the spatio-temporal complexity of the natural system. To overcome this limitation, the study features a modified version of the DK-Model in which LAI, RD, and KC are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatio-temporal variability and spatial consistency between the 6 domains. The effects of these changes are analyzed by using the empirical orthogonal functions (EOF) analysis to evaluate spatial patterns. The EOF-analysis shows that including remote sensing derived LAI, RD and KC in the distributed hydrological model adds spatial features found in the spatial pattern of remote sensing based ET.

scholarly journals Geometric Accuracy Improvement Method for High-Resolution Optical Satellite Remote Sensing Imagery Combining Multi-Temporal SAR Imagery and GLAS Data

2020 ◽  
Vol 12 (3) ◽  
pp. 568
Author(s):  
Quansheng Zhu ◽  
Wanshou Jiang ◽  
Ying Zhu ◽  
Linze Li
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Geometric Accuracy ◽  
Laser Altimetry ◽  
Multi Temporal ◽  
Improvement Method ◽  
Optical Imagery ◽  
Sar Imagery

With the widespread availability of satellite data, a single region can be described using multi-source and multi-temporal remote sensing data, such as high-resolution (HR) optical imagery, synthetic aperture radar (SAR) imagery, and space-borne laser altimetry data. These have become the main source of data for geopositioning. However, due to the limitation of the direct geometric accuracy of HR optical imagery and the effect of the small intersection angle of HR optical imagery in stereo pair orientation, the geometric accuracy of HR optical imagery cannot meet the requirements for geopositioning without ground control points (GCPs), especially in uninhabited areas, such as forests, plateaus, or deserts. Without satellite attitude error, SAR usually provides higher geometric accuracy than optical satellites. Space-borne laser altimetry technology can collect global laser footprints with high altitude accuracy. Therefore, this paper presents a geometric accuracy improvement method for HR optical satellite remote sensing imagery combining multi-temporal SAR Imagery and GLAS data without GCPs. Based on the imaging mechanism, the differences in the weight matrix determination of the HR optical imagery and SAR imagery were analyzed. The laser altimetry data with high altitude accuracy were selected and applied as height control point in combined geopositioning. To validate the combined geopositioning approach, GaoFen2 (GF2) optical imagery, GaoFen6 (GF6) optical imagery, GaoFen3 (GF3) SAR imagery, and the Geoscience Laser Altimeter System (GLAS) footprint were tested. The experimental results show that the proposed model can be effectively applied to combined geopositioning to improve the geometric accuracy of HR optical imagery. Moreover, we found that the distribution and weight matrix determination of SAR images and the distribution of GLAS footprints are the crucial factors influencing geometric accuracy. Combined geopositioning using multi-source remote sensing data can achieve a plane accuracy of 1.587 m and an altitude accuracy of 1.985 m, which is similar to the geometric accuracy of geopositioning of GF2 with GCPs.

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.

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