1] We present here a simple and robust framework for quantifying the effective sensor depth of cosmic ray soil moisture neutron probes such that reliable water fluxes may be computed from a time series of cosmic ray soil moisture. In particular, we describe how the neutron signal depends on three near-surface hydrogen sources: surface water, soil moisture, and lattice water (water in minerals present in soil solids) and also their vertical variations. Through a combined modeling study of one-dimensional water flow in soil and neutron transport in the atmosphere and subsurface, we compare average water content between the simulated soil moisture profiles and the universal calibration equation which is used to estimate water content from neutron counts. By using a linear sensitivity weighting function, we find that during evaporation and drainage periods the RMSE of the two average water contents is 0.0070 m 3 m À3 with a maximum deviation of 0.010 m 3 m À3 for a range of soil types. During infiltration, the RMSE is 0.011 m 3 m À3 with a maximum deviation of 0.020 m 3 m À3 , where piston like flow conditions exists for the homogeneous isotropic media. Because piston flow is unlikely during natural conditions at the horizontal scale of hundreds of meters that is measured by the cosmic ray probe, this modeled deviation of 0.020 m 3 m À3 represents the worst case scenario for cosmic ray sensing of soil moisture. Comparison of cosmic ray soil moisture data and a distributed sensor soil moisture network in Southern Arizona indicates an RMSE of 0.011 m 3 m À3 over a 6 month study period. Citation: Franz, T. E., M. Zreda, T. P. A. Ferre, R. Rosolem, C. Zweck, S. Stillman, X. Zeng, and W. J. Shuttleworth (2012), Measurement depth of the cosmic ray soil moisture probe affected by hydrogen from various sources, Water Resour. Res., 48, W08515,
Patients with breast cancer who undergo autologous bone marrow/peripheral blood stem cell transplantation (ABMT) cope not only with a life-threatening medical treatment, but also with multiple, interrelated symptoms including pain, fatigue, psychological distress, and nausea. The purpose of this study was to determine, in a randomized controlled clinical trial, whether a comprehensive coping strategy program (CCSP) was effective in significantly reducing pain, fatigue, psychological distress, and nausea in patients with breast cancer who underwent ABMT. The CCSP was composed of preparatory information, cognitive restructuring, and relaxation with guided imagery. Randomization placed 52 patients in the CCSP treatment group and 58 patients in the control group. The CCSP was found to be effective in significantly reducing nausea as well as nausea combined with fatigue 7 days after the ABMT when the side effects of treatment were most severe. These results are important given the high incidence of nausea and fatigue in the ABMT population. The CCSP-treated group experienced mild anxiety as compared with the control group who reported moderate anxiety. The greatest effectiveness of CCSP may correspond to the time of the greatest morbidity for patients with breast cancer who have undergone ABM.
Precipitation and soil moisture are rigorously measured or estimated from a variety of sources. Here, 22 precipitation and 23 soil moisture products are evaluated against long-term daily observed precipitation (Pobs) and July–September daily observationally constrained soil moisture (SM) datasets over a densely monitored 150 km2 watershed in southeastern Arizona, United States. Gauge–radar precipitation products perform best, followed by reanalysis and satellite products, and the median correlations of annual precipitation from these three categories with Pobs are 0.83, 0.68, and 0.46, respectively. Precipitation results from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are the worst, including an overestimate of cold season precipitation and a lack of significant correlation of annual precipitation with Pobs from all (except one) models. Satellite soil moisture products perform best, followed by land data assimilation systems and reanalyses, and the CMIP5 results are the worst. For instance, the median unbiased root-mean-square difference (RMSD) values of July–September soil moisture compared with SM are 0.0070, 0.011, 0.014, and 0.029 m3 m−3 for these four product categories, respectively. All 17 (except 3) precipitation [17 (except 2) soil moisture] products with at least 20 years of data agree with Pobs (SM) without significant trends. The uncertainties associated with the scale mismatch between Pobs and coarser-resolution products are addressed using two 4-km gauge–radar precipitation products, and their impact on the results presented in this study is overall small. These results identify strengths and weaknesses of each product for future improvement; they also emphasize the importance of using multiple gauge–radar and satellite products along with their uncertainties in evaluating reanalyses and models.
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