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Shervan Gharari, Martyn P. Clark, Naoki Mizukami, Jefferson S. Wong, Alain Pietroniro, and Howard S. Wheater

Abstract

Land models are increasingly used and preferred in terrestrial hydrological prediction applications. One reason for selecting land models over simpler models is that their physically based backbone enables wider application under different conditions. This study evaluates the temporal variability in streamflow simulations in land models. Specifically, we evaluate how the subsurface structure and model parameters control the partitioning of water into different flow paths and the temporal variability in streamflow. Moreover, we use a suite of model diagnostics, typically not used in the land modeling community to clarify model weaknesses and identify a path toward model improvement. Our analyses show that the typical land model structure, and their functions for moisture movement between soil layers (an approximation of Richards equation), has a distinctive signature where flashy runoff is superimposed on slow recessions. This hampers the application of land models in simulating flashier basins and headwater catchments where floods are generated. We demonstrate the added value of the preferential flow in the model simulation by including macropores in both a toy model and the Variable Infiltration Capacity model. We argue that including preferential flow in land models is essential to enable their use for multiple applications across a myriad of temporal and spatial scales.

Open access
Jefferson S. Wong, Xuebin Zhang, Shervan Gharari, Rajesh R. Shrestha, Howard S. Wheater, and James S. Famiglietti

Abstract

Obtaining reliable water balance estimates remains a major challenge in Canada for large regions with scarce in situ measurements. Various remote sensing products can be used to complement observation-based datasets and provide an estimate of the water balance at river basin or regional scales. This study provides an assessment of the water balance using combinations of various remote sensing– and data assimilation–based products and quantifies the nonclosure errors for river basins across Canada, ranging from 90 900 to 1 679 100 km2, for the period from 2002 to 2015. A water balance equation combines the following to estimate the monthly water balance closure: multiple sources of data for each water budget component, including two precipitation products—the global product WATCH Forcing Data ERA-Interim (WFDEI), and the Canadian Precipitation Analysis (CaPA); two evapotranspiration products—MODIS, and Global Land surface Evaporation: The Amsterdam Methodology (GLEAM); one source of water storage data—GRACE from three different centers; and observed discharge data from hydrometric stations (HYDAT). The nonclosure error is attributed to the different data products using a constrained Kalman filter. Results show that the combination of CaPA, GLEAM, and the JPL mascon GRACE product tended to outperform other combinations across Canadian river basins. Overall, the error attributions of precipitation, evapotranspiration, water storage change, and runoff were 36.7%, 33.2%, 17.8%, and 12.2%, which corresponded to 8.1, 7.9, 4.2, and 1.4 mm month−1, respectively. In particular, the nonclosure error from precipitation dominated in Western Canada, whereas that from evapotranspiration contributed most in the Mackenzie River basin.

Open access