Abstract

Preferential flow can occur in practically all soils and landscapes and has significant impacts on water quantity and quality, stream discharge, groundwater recharge, contaminant transport, biogeochemical dynamics, and many other environmental and ecological processes. However, due to limited methods available to quantify and monitor preferential flow in the field, the frequency and controls of preferential flow occurrence remain poorly understood. This study examines various methods for identifying and quantifying preferential flow occurrence across space and time and its dominant controls under various field conditions. Based on data collected from a forest catchment and a farm land, we discuss soil moisture sensor networks that provide new opportunities to characterize preferential flow occurrence in real time. We summarize spatial factors that influence preferential flow occurrence, including landscape features (such as landform, hillslope type/shape, slope, and underlying bedrock), soil properties (such as soil type, texture, layering, and structure), and land use/land cover (such as vegetation type and management practices). Temporal factors influencing preferential flow occurrence include precipitation characteristics (such as amount, intensity, duration, and timing), initial soil moisture condition (such as dry, moist, and wet), and vegetation dynamics (such as canopy cover and root growth). We organize these six key categories of factors into an overarching framework for estimating the occurrence frequency and dominant controls of preferential flow across diverse soil-landscapes. Finally, we address optimal experimental design for preferential flow investigation in the field and provide a future outlook on new research opportunities.

Citation

Lin, H. and Guo, L. (2016): A framework for estimating the occurrence frequency and dominant controls of preferential flow across diverse soil landscape. 2016 Fall Meeting, American Geophysical Union, San Francisco, CA, 12-16 Dec..

This Paper/Book acknowledges NSF CZO grant support.