Date Available

12-6-2013

Year of Publication

2013

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Agriculture, Food and Environment

Department/School/Program

Plant and Soil Sciences

First Advisor

Dr. Junfeng Zhu

Second Advisor

Dr. Mark Coyne

Abstract

There is a shared desire among public and private sectors to make more reliable predictions, accurate mapping, and appropriate scaling of soil moisture and associated parameters across landscapes. A discrepancy often exists between the scale at which soil hydrologic properties are measured and the scale at which they are modeled for management purposes. Moreover, little is known about the relative importance of hydrologic modeling parameters as soil moisture fluctuates with time. More research is needed to establish which observation scales in space and time are optimal for managing soil moisture variation over large spatial extents and how these scales are affected by fluctuations in soil moisture content with time. This research fuses high resolution geoelectric and light detection and ranging (LiDAR) as auxiliary measures to support sparse direct soil sampling over a 40 hectare inner BluegrassKentucky (USA) landscape. A Veris 3100 was used to measure shallow and deep apparent electrical conductivity (aEC) in tandem with soil moisture sampling on three separate dates with ascending soil moisture contents ranging from plant wilting point to near field capacity. Terrain attributes were produced from 2010 LiDAR ground returns collected at ≤1 m nominal pulse spacing. Exploratory statistics revealed several variables best associate with soil moisture, including terrain features (slope, profile curvature, and elevation), soil physical and chemical properties (calcium, cation exchange capacity, organic matter, clay and sand) and aEC for each date. Multivariate geostatistics, time stability analyses, and spatial regression were performed to characterize scale-dependent soil moisture patterns in space with time to determine which soil-terrain parameters influence soil moisture distribution. Results showed that soil moisture variation was time stable across the landscape and primarily associated with long-range (~250 m) soil physicochemical properties. When the soils approached field capacity, however, there was a shift in relative importance from long-range soil physicochemical properties to short-range (~70 m) terrain attributes, albeit this shift did not cause time instability. Results obtained suggest soil moisture’s interaction with soil-terrain parameters is time dependent and this dependence influences which observation scale is optimal to sample and manage soil moisture variation.

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