Global root zone storage capacity from satellite-based evaporation

Abstract

Abstract. This study presents an "Earth observation-based" method for estimating root zone storage capacity – a critical, yet uncertain parameter in hydrological and land surface modelling. By assuming that vegetation optimises its root zone storage capacity to bridge critical dry periods, we were able to use state-of-the-art satellite-based evaporation data computed with independent energy balance equations to derive gridded root zone storage capacity at global scale. This approach does not require soil or vegetation information, is model independent, and is in principle scale independent. In contrast to a traditional look-up table approach, our method captures the variability in root zone storage capacity within land cover types, including in rainforests where direct measurements of root depths otherwise are scarce. Implementing the estimated root zone storage capacity in the global hydrological model STEAM (Simple Terrestrial Evaporation to Atmosphere Model) improved evaporation simulation overall, and in particular during the least evaporating months in sub-humid to humid regions with moderate to high seasonality. Our results suggest that several forest types are able to create a large storage to buffer for severe droughts (with a very long return period), in contrast to, for example, savannahs and woody savannahs (medium length return period), as well as grasslands, shrublands, and croplands (very short return period). The presented method to estimate root zone storage capacity eliminates the need for poor resolution soil and rooting depth data that form a limitation for achieving progress in the global land surface modelling community.

Calibration of Spatially Distributed Hydrological Processes and Model Parameters in SWAT Using Remote Sensing Data and an Auto-Calibration Procedure: A Case Study in a Vietnamese River Basin

“…Soil evaporation is limited by a complementary relationship hypothesis which defines land-atmospheric interactions from vapor pressure deficit and relative humidity [69]. Various ET comparison studies using MOD16 data have been undertaken, see for instance [32,39,70]. MOD16 ET was validated [71] using flux towers in South Africa, and found that ET was systematically underestimated by 7.5 to 26.3 mm per month, something confirmed by [72,73].…”

Derivation of Flow Duration Curves to Estimate Hydropower Generation Potential in Data-Scarce Regions

“…Those measurements enable the estimation of root zone storage capacity [24], landscape heterogeneity, dominant runoff generating mechanisms [25,26], sub-surface storage fluctuation, and groundwater recession [27].…”

Remote Sensing for Crop Water Management: from Experiments to User-Driven Services

“…Within the six approaches classified by Wang-Erlandsson et al [115], for the estimation of root zone water storage capacity, RS-based studies are generally based on field observations and look up tables [116][117][118][119]. Nevertheless, some recent studies propose the optimization-calibration and inverse modelling approaches with diverse purposes.…”

“…Some approaches assimilate into the soil water balance models either water stress estimates based on canopy temperature [120,121] or ET estimates based on SEB models [93,113,116,122] in order to calibrate the fraction of water depleted derived from the water balance model. In slightly different approach, some authors propose the integration of actual ET values in order to calibrate the soil water balance model in terms of the root zone storage capacity [115,[123][124][125]. The rationale of these approaches is that any empirical approach to the plant water stress, or alternative formulations as those based on the canopy temperature, must be equivalent to the soil water stress, a stress index based on the parametrization of the soil properties [122].…”