In studies of erosion, runoff, and infiltration, high soil variability may demand many replicate measurements and rapid, inexpensive methodology. We developed a drop‐forming rainfall simulator in which flow through long, coiled capillary drip tubes is controlled by an adjustable Mariotte‐type bubbling tube. These rain simulators are inexpensive, rugged, simple to operate, easily transported, and require minimal maintenance. Responses to pressure head and water temperature changes were determined for two simulators using tap water. Flow response to pressure head changes corresponded closely to that predicted by Poiseuille's Law. Response to increasing water temperatures was somewhat less than predicted, due to formation of bubbles in the capillary tubes. Simulators incorporating long, coiled capillary tubes can provide combinations of low flow rates and large drop sizes, or a desired range of flow rates when appropriate drip tube diameters, lengths, and numbers of tubes per unit area are combined.
The concept of soil health has evolved over the past several decades, recognizing that dynamic soil property response to management and land use is highly dependent on sitespecific factors that must be considered when interpreting soil health measurements. Initially, the Soil Management Assessment Framework (SMAF) and Comprehensive Assessment of Soil Health (CASH) were developed and used globally for scoring soil health indicators. However, both SMAF and CASH frameworks were developed using a relatively small dataset and their interpretation curves were not validated at the nationwide scale. Expanding upon these concepts, we propose the Soil Health Assessment Protocol and Evaluation (SHAPE) tool. SHAPE was developed using 14,680 soil organic carbon (SOC) observations from across the United States and accounts for edaphic and climate factors at the continental scale. Data were compiled from the literature, the Cornell Soil Health Laboratory, and the Kellogg Soil Survey Laboratory. In this approach, scoring curves are Bayesian model-based estimates of the conditional cumulative distribution function (CDF) for defined soil peer groups reflecting five soil texture and five soil suborder classes adjusted for mean annual temperature and precipitation. Specifically, SHAPE produces scores between 0 and 1 (0 to 100%) for measured SOC values that reflect the quantile or position within the conditional This article is protected by copyright. All rights reserved. 4 CDF along with measures of uncertainty. Herein, we focus on development of the SHAPE scoring curve for SOC with four case studies. SHAPE is a flexible, quantitative tool that provides a regionally relevant interpretation of this key soil health indicator.
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