Abstract

Abstract. Distributed and continuous catchment models are used to simulate water and energy balance and fluxes across varied topography and landscape. The landscape is discretized into computational plan elements at resolutions of 101–103 m, and soil moisture is the hydrologic state variable. At the local scale, the vertical soil moisture dynamics link hydrologic fluxes and provide continuity in time. In catchment models these local-scale processes are modeled using 1-D soil columns that are discretized into layers that are usually 10−3–10−1 m in thickness. This creates a mismatch between the horizontal and vertical scales. For applications across large domains and in ensemble mode, this treatment can be a limiting factor due to its high computational demand. This study compares continuous multi-year simulations of soil moisture at the local scale using (i) a 1-pixel version of a distributed catchment hydrologic model and (ii) a benchmark detailed soil water physics solver. The distributed model uses a single soil layer with a novel dual-pore structure and employs linear parameterization of infiltration and some other fluxes. The detailed solver uses multiple soil layers and employs nonlinear soil physics relations to model flow in unsaturated soils. Using two sites with different climates (semiarid and sub-humid), it is shown that the efficient parameterization in the distributed model captures the essential dynamics of the detailed solver.

Highlights

  • Soil moisture controls the partitioning of rainfall into infiltration and runoff, and it controls land surface temperature through its effect on the partitioning of available energy into sensible and latent heat fluxes

  • We focus on a novel dual-pore parameterized approach

  • The magnitude range and temporal dynamics of θ for all seven nodes are in close agreement especially near the surface

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Summary

Introduction

Soil moisture controls the partitioning of rainfall into infiltration and runoff, and it controls land surface temperature through its effect on the partitioning of available energy into sensible and latent heat fluxes. It is the hydrologic state variable, together with land temperature, in models of surface water and energy balance. In situ sensors can provide high accuracy and fine temporal resolution but at limited spatial footprint, sampling campaigns can provide better spatial resolution and coverage but at low sampling frequency and duration, while space-borne remote sensing platforms provide global spatial coverage for surface soil moisture sensing but at coarse spatial resolution and with infrequent revisits

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