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Currently accepted pedotransfer functions show negligible effect of managementinduced changes to soil organic carbon (SOC) on plant available water holding capacity (θ AWHC ), while some studies show the ability to substantially increase θ AWHC through management. The Soil Health Institute's North America Project to Evaluate Soil Health Measurements measured water content at field capacity using intact soil cores across 124 long-term research sites that contained increases in SOC as a result of management treatments such as reduced tillage and cover cropping. Pedotransfer functions were created for volumetric water content at field capacity (θ FC ) and permanent wilting point (θ PWP ). New pedotransfer functions had predictions of θ AWHC that were similarly accurate compared with Saxton and Rawls when tested on samples from the National Soil Characterization database. Further, the new pedotransfer functions showed substantial effects of soil calcareousness and SOC on θ AWHC . For an increase in SOC of 10 g kg -1 (1%) in noncalcareous soils, an average increase in θ AWHC of 3.0 mm 100 mm -1 soil (0.03 m 3 m -3 ) on average across all soil texture classes was found. This SOC related increase in θ AWHC is about double previous estimates. Calcareous soils had an increase in θ AWHC of 1.2 mm 100 mm -1 soil associated with a 10 g kg -1 increase in SOC, across all soil texture classes. New equations can aid in quantifying benefits of soil management practices that increase SOC and can be used to model the effect of changes in management on drought resilience.

The Walnut Gulch Experimental Watershed is a semi-arid experimental watershed and long-term agro-ecosystem research (LTAR) site managed by the USDA-Agricultural Research Services (ARS) Southwest Watershed Research Center for which highresolution, long-term hydroclimatic data are available across its 149-km 2 drainage area. Quality control and quality assurance of the massive data set are a major challenge. We present the analysis of 50 years of data sets to develop a strategy to identify errors and inconsistencies in historical rainfall and runoff databases. A multiple regression model was developed to relate rainfall, watershed properties, and the antecedent conditions to runoff characteristics in 12 subwatersheds ranging in area from 0.002-94 km 2. A regression model was developed based on 18 predictor variables, which produced predicted runoff with correlation coefficients ranging from 0.4-0.94 and Nash efficiency coefficients up to 0.76. The model predicted 92% of runoff events and 86% of no-runoff events. The modeling approach is a complement to existing quality assurance and quality control (QAQC) procedures and provides a specific method for ensuring that rainfall and runoff data in the USDA-ARS Walnut Gulch Experimental Watershed database are consistent and contain minimal error. The model has the potential for making runoff predictions in similar hydroclimatic environments with available high-resolution observations.