Assessment of Irrigation Physics in a Land Surface Modeling Framework using Non-Traditional and Human-Practice Datasets.

Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASA's Land Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily time scales. In addition, this study uses point and gridded soil moisture observations from fixed and roving Cosmic Ray Neutron Probes and co-located human practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation for accurate simulation of water and energy states and fluxes over cropland.

Tuition reduction is the key factor determining tax burden of graduate students under the Tax Cuts and Job Act.

BACKGROUND: The proposed Tax Cuts and Jobs Act (H.R.1) has stirred significant public debate on the future of American economics.  While supporters of the plan have championed it as a necessity for economic revitalization, detractors have pointed out areas of serious concern, particularly for low- and middle-income Americans.  One particularly alarming facet of the plan is the radical change to education finance programs and taxation of students in higher education.  Methods:  By analyzing actual income and tuition of a public and a private university student, as well as the 'average' graduate student, we investigated the effect of both the House and Senate versions of H.R. 1 on taxation of students of various family structures.  Results:  Our findings indicate that taxable tuition would be the greatest contributor to graduate student tax burden across all four categories of filing status.  However, when tuition reduction is upheld or a student is on sustaining fees rather than full tuition, graduate students would realize decreases in taxation. CONCLUSIONS:   Overall, we conclude that removal of tuition reduction would result in enormous tax burdens for graduate students and their families and that these effects are dependent not only on the status of the student in their degree program but also on their tuition and stipend, and therefore the institution they attend.