Spatial Scaling of Soil Moisture, ...

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XVI International Conference on Computational Methods in Water Resources (CMWR-XVI) Ingeniørhuset

Spatial Scaling of Soil Moisture, Evapotranspiration, and Leakage
Paper
Author:Michael Puma <mpuma@princeton.edu> (Princeton University)
Michael Celia <celia@princeton.edu> (Princeton University)
Ignacio Rodriguez-Iturbe <irodrigu@princeton.edu> (Princeton University)
Jan Nordbotten <jnordbot@princeton.edu> (Princeton University)
Andrew Guswa <aguswa@email.smith.edu> (Smith College)
Presenter:Michael Puma <mpuma@princeton.edu> (Princeton University)
Date: 2006-06-18     Track: Special Sessions     Session: Ecohydrology: From Detailed Descriptions To General Synthesis?
DOI:10.4122/1.1000000563
DOI:10.4122/1.1000000564

An outstanding issue in ecohydrological modeling is scaling nonlinear plant-level interactions among soil, vegetation, and water to larger spatial scales. Spatial heterogeneity in precipitation and vegetation exert significant control on scaling properties, especially in water-limited ecosystems. Computational results indicate that relationships between spatially averaged variables controlling soil-moisture dynamics are non-unique at larger averaging scales, even when unique, non-hysteretic relationships are defined at the plant level. The complexity of these relationships evolves with increasing averaging area based on the characteristics of the spatial heterogeneity. Through detail simulation studies, we can identify a threshold scale for soil moisture, evapotranspiration, and leakage beyond which the non-unique relationships will vary only slowly as averaging area becomes larger. The threshold scale, which is analogous to the concept of a representative elementary area, enables identification of a large-scale relationship that is meaningful with respect to the characteristics of the system. We use numerical simulations to assess the effects of storm spatial structure, rainfall intensity and frequency, and soil and vegetation characteristics on threshold-scale values of the relevant variables. Results are generalized by relating the threshold scales to a dimensionless group of parameters that includes length scales characteristic of the heterogeneity and the model's resolution. We then evaluate how the computationally derived non-unique relationships relate to analytical approaches to obtain spatially averaged functional relationships. Specific comparison of empirically obtained upscaled functions (based on the non- unique relationships) with the so-called statistical dynamic approach provides guidelines to account for spatial heterogeneity in soil, plant, and climate systems.