Generation and analysis of stage-fall-discharge laws from coupled hydrological-hydraulic river network model integrating sparse multi-satellite data

Malou, Thibault; Garambois, Pierre‐André; Paris, Adrien; Monnier, Jérôme

doi:10.1016/j.jhydrol.2021.126993

Cited by 14 publications

(15 citation statements)

References 59 publications

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“…-Coupling to hydraulic models of the DassFlow variational data assimilation platform (Monnier et al, 2016) also recently wrapped in python, adapted to use satellite datasets either with 1D network model (Brisset et al, 2018 Pujol et al, 2020;Malou et al, 2021) or a multi-D model with fine 2D zooms (Pujol et al, 2022) with regularizations taylored for hydrological-hydraulic inverse problems.…”

Section: Discussionmentioning

confidence: 99%

Adjoint-based spatially distributed calibration of a grid GR-based parsimonious hydrological model over 312 French catchments with SMASH platform

Colleoni

Garambois

Javelle

et al. 2022

Preprint

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Abstract. Reducing uncertainty and improving robustness and spatio-temporal extrapolation capabilities remain key challenges in hydrological modeling especially for flood forecasting over large areas. Parsimonious model structures and effective optimization strategies are crucially needed to tackle the difficult issue of distributed hydrological model calibration from sparse integrative discharge data, that is in general high dimensional inverse problems. This contribution presents the first evaluation of Variational Data Assimilation (VDA), very well suited to this context but still rarely employed in hydrology because of high technicality, and successfully applied here to the spatially distributed calibration of a newly taylored grid-based parsimonious model structure and corresponding adjoint, over a large sample. It is based on the Variational Data Assimilation (VDA) framework of SMASH (Spatially distributed Modelling and ASsimilation for Hydrology) platform, underlying the French national flash flood forecasting system Vigicrues Flash. It proposes an upgraded distributed hourly rainfall-runoff model structure employing GR-based operators, including a non-conservative flux, and its adjoint obtained by automatic differentiation for VDA. The performances of the approach are assessed over annual, seasonal and floods timescales via standard performance metrics and in spatio-temporal validation. The gain of using the proposed non-conservative 6-parameters model structure is highlighted in terms of performance and robustness, compared to a simpler 3-parameters structure. Spatially distributed calibrations lead to a significant gain in terms of reaching high performances in calibration and temporal validation on the catchments sample, with median efficiencies respectively of NSE = 0.88 (resp. 0.85) and NSE = 0.8 (resp. 0.79) over the total time window on period p2 (resp. p1). Simulated signatures in temporal validation over 1443 (resp. 1522) flood events on period p2 (resp. p1) are quite good with median flood (NSE; KGE) of (0.63; 0.59) (resp. (0.55; 0.53)). Spatio-temporal validations, i.e. on pseudo ungauged cases, lead to encouraging performances also. Moreover, the influence of certain catchment characteristics on model performance and parametric sensitivity is analyzed. Best performances are obtained for Oceanic and Mediterranean basins whereas it performs less well over Uniform basins with significant influence of multi-frequency hydrogeological processes. Interestingly, regional sensitivity analysis revealed that the non conservative water exchange parameter and the production parameter, impacting the simulated runoff amount, are the most sensitive parameters along with the routing parameter especially for faster responding catchments. This study is a first step in the construction of a flexibe and versatile multi-model and optimization framework with hydbrid methods for regional hydrological modeling with multi-source data assimilation.

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Section: Discussionmentioning

confidence: 99%

Adjoint-based spatially distributed calibration of a grid GR-based parsimonious hydrological model over 312 French catchments with SMASH platform

Colleoni

Garambois

Javelle

et al. 2022

Preprint

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“…Discharge retrieval. The calibrated model can be used to convert ATL13 WSE observations into estimates of river discharge using WSE-discharge relations (Malou et al, 2021). At any time of ICESat-2 acquisitions, or any other type of altimetry data, we can ingest an observation of WSE to produce discharge estimates for any point of the river stretch using the estimated rating curves from the 1D hydraulic model.…”

Section: Wse Densification and Discharge Retrievalmentioning

confidence: 99%

“…To create WSE and discharge time series, the interpolation of WSE is needed. We use the calibrated hydraulic model to create WSE-discharge relationships in the form of rating curves along the river stretch, an approach that has been previously used in other studies successfully (Malou et al, 2021). Rating curves make possible the interpolation of WSE and estimation of discharge at any point in the river for a given ATL13 WSE observation.…”

Section: Wse Densification and Discharge Estimationmentioning

confidence: 99%

River hydraulic modeling with ICESat-2 land and water surface elevation

Frías

Liu

et al. 2023

Hydrol. Earth Syst. Sci.

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Abstract. Advances in geodetic altimetry instruments are providing more accurate measurements, thus enabling satellite missions to produce useful data for narrow rivers and streams. Altimetry missions produce spatially dense land and water surface elevation (WSE) measurements in remote areas where in situ data are scarce that can be combined with hydraulic and/or hydrodynamic models to simulate WSE and estimate discharge. In this study, we combine ICESat-2 (Ice, Cloud and land Elevation Satellite) land and water surface elevation measurements with a low-parameterized hydraulic calibration to simulate WSE and discharge without the need for surveyed cross-sectional geometry and a rainfall–runoff model. ICESat-2 provides an opportunity to map river cross-sectional geometry very accurately, with an along-track resolution of 0.7 m, using the ATL03 product. These measurements are combined with the inland water product ATL13 to calibrate a steady-state hydraulic model to retrieve unobserved hydraulic parameters such as river depth or the roughness coefficient. The low-parameterized model, together with the assumption of steady-state hydraulics, enables the application of a global search algorithm for a spatially uniform parameter calibration at a manageable computational cost. The model performance is similar to that reported for highly parameterized models, with a root mean square error (RMSE) of around 0.41 m. With the calibrated model, we can calculate the WSE time series at any chainage point at any time for an available satellite pass within the river reach and estimate discharge from WSE. The discharge estimates are validated with in situ measurements at two available gauging stations. In addition, we use the calibrated parameters in a full hydrodynamic model simulation, resulting in a RMSE of 0.59 m for the entire observation period.

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“…An automated selection of raw data based on physical criteria is employed in Hydroweb (Crétaux et al 2011;Santos da Silva et al 2010) together with bias estimates to provide coherent multi-mission estimates of WL (mainly for Jason-2, Jason-3 and Sentinel3-A and B missions). Thanks to these methodologies, a number of studies have employed the satellite multi-mission databases to estimate river discharge (since the pioneering study in an African basin from Coe and Birkett 2004 on Lake Tchad basin, to recent ones such as Papa et al 2010;Paris et al 2016;Tourian et al 2016;Bogning et al 2018;Scherer et al 2020;Pujol et al 2020;Malou et al 2021). Despite the huge contribution provided by multi-mission approaches, the combination of different altimetry measurements represents still a challenge because of the inter-satellite biases (Normandin et al 2018) which impede a straightforward combination of water level measurements (Tourian et al 2022).…”

Section: Radar Altimetry For Understanding the River Flow: Past Curre...mentioning

confidence: 99%

“…Yet, the solution can be improved when not performing well enough (see possible reasons in Paris et al 2016), in particular with the ancillary datasets from EO as exposed above. In case of particular local problematics, the framework can be completed as shown hereafter: 1) use of other EO datasets to derive discharge from space or/and 2) implement an assimilation system that will propagate the discrete daily estimates of discharge from space all over the basin or/and 3) use the estimated discharge as an informer for a locally relevant hydraulic model (see an application of such framework in Malou et al 2021) that will convert level and discharges into flood risk and areas or in refined depths. Also, the density of VSs now makes it possible to infer a priori RCs at newly monitored locations, such as VSs of future missions.…”

Section: On the Use Of Eo Datasets For Building Large Scale Hydrologi...mentioning

confidence: 99%

Water Resources in Africa: The Role of Earth Observation Data and Hydrodynamic Modeling to Derive River Discharge

Tarpanelli

Paris²,

Sichangi

et al. 2022

Surv Geophys

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For more than a century, river discharge has been measured indirectly through observations of water level and flow velocity, but recently the number of gauging stations worldwide has decreased and the situation is particularly serious in African countries that suffer more than others from discontinuous and incomplete monitoring. As one of the most vulnerable regions in the world to extreme weather events and global warming, African countries need adequate and reliable monitoring. Decades of available Earth Observations data represent a tool complementary to the hydro-monitoring network and, in recent decades, they have demonstrated their potential, especially for data-poor regions. In this paper, a review of methods for hydrological and hydraulic modeling and for estimating river discharge by the use of satellite data, specifically radar altimetry and optical sensors, is provided, with particular focus on their role in the climate changes monitoring. More emphasis is placed on their relevance on African basins highlighting limits and advantages.

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Generation and analysis of stage-fall-discharge laws from coupled hydrological-hydraulic river network model integrating sparse multi-satellite data

Cited by 14 publications

References 59 publications

Adjoint-based spatially distributed calibration of a grid GR-based parsimonious hydrological model over 312 French catchments with SMASH platform

Adjoint-based spatially distributed calibration of a grid GR-based parsimonious hydrological model over 312 French catchments with SMASH platform

River hydraulic modeling with ICESat-2 land and water surface elevation

Water Resources in Africa: The Role of Earth Observation Data and Hydrodynamic Modeling to Derive River Discharge

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