Two‐dimensional (2‐D) satellite imagery has been increasingly employed to improve prediction of floodplain inundation models. However, most focus has been on validation of inundation extent, with little attention on the spatial variations of water elevation and slope. The availability of high resolution Interferometric Synthetic Aperture Radar (InSAR) imagery offers unprecedented opportunity for quantitative validation of surface water heights and slopes derived from 2D hydrodynamic models. In this study, the LISFLOOD‐ACC hydrodynamic model is applied to the central Atchafalaya Basin Floodway System, Louisiana, during high flows typical of spring floods in the Mississippi Delta region, for the purpose of demonstrating the utility of InSAR in 2‐D floodplain model calibration. Two schemes calibrating Manning's roughness in channels and floodplains are compared. First, the model is calibrated in terms of water elevations at a single in situ gage during a 62‐d simulation period from 1 April 2008 to 1 June 2008. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR 2D imagery acquired on 16 April 2008 and 1 June 2009, an interval of 46 d. The best‐fit model shows that the mean absolute error is 5.7 cm/46 d for InSAR water level calibration. Daily storage changes within the ∼230‐km² model area are also calculated to be on the order of 107 m³ d⁻¹ during high water of the modeled period. The favorable comparison between both approaches demonstrates the feasibility of SAR interferometry for 2‐D hydrodynamic model calibration and for improved understanding of complex floodplain hydrodynamics.

An evapotranspiration (ET) ensemble composed of 36 land surface model (LSM) experiments and four diagnostic datasets (GLEAM, ALEXI, MOD16, and FLUXNET) is used to investigate uncertainties in ET estimate over five climate regions in West Africa. Diagnostic ET datasets show lower uncertainty estimates and smaller seasonal variations than the LSM-based ET values, particularly in the humid climate regions. Overall, the impact of the choice of LSMs and meteorological forcing datasets on the modeled ET rates increases from north to south. The LSM formulations and parameters have the largest impact on ET in humid regions, contributing to 90% of the ET uncertainty estimates. Precipitation contributes to the ET uncertainty primarily in arid regions. The LSM-based ET estimates are sensitive to the uncertainty of net radiation in arid region and precipitation in humid region. This study serves as support for better determining water availability for agriculture and livelihoods in Africa with earth observations and land surface models.