A study of the humus content and the water content of San Saba clay and Denton clay. Studies show that the physical properties of soil are conducive to moisture retention and the availability of moisture to plants.

The permafrost region covers a vast area of land surface on the northern hemisphere,storing large amounts of carbon. Unfortunately, climate warming leads to permafrostthaw altering the hydrothermal state of permafrost soils. Due to the remoteness of thepermafrost region, access to field measurements is restricted. Therefore, remotesensing is an asset to study the permafrost region. Since permafrost is a sub-surfacephenomenon it cannot be directly observed from space. However, by using differenttypes of satellites the soil properties of the top soil layer, down to 10 cm depth, can beaccessed. To establish soil properties for the deeper soil layers modelling is required.The ERA5-Land (ERA5L) soil moisture is modelled based on climate reanalysis. Inthis study in-situ soil moisture data from the International Soil Moisture Network(ISMN) is used to evaluate the performance of the ERA5L soil moisture data withinthe permafrost region. The performance of the ERA5L soil moisture is found toperform best in soil layer 1 (0-7 cm depth) and worst in soil layer 3 (28-100 cm depth).For both soil layer 1 and 2 (0-7 and 7-28 cm depth) a moderate correlation(0.309 < R < 0.335) was found between ERA5L and in-situ soil moisture data, in Julyand August. The performance of the ERA5L soil moisture is best in Europe and worstin North-America. Compared to other evaluations of ERA5L soil moisture, within thepermafrost region, this study found a relatively low correlation. Therefore, this studyconcludes that on a global scale the ERA5L soil moisture is not ideal for directlyinforming permafrost research and decision making. However, integrating multisourcedatasets, resampled to a finer spatial resolution, could improve the performance ofERA5L soil moisture model on a global level. Moreover, on a local scale theapplication of a bias correction could also improve the performance of the ERA5L soilmoisture model.

The objectives of this study were to determine the influence of sublethal water stress on the physiology of loblolly and Aleppo pine. Gas exchange characteristics, uncoupled thylakoid electron transport capacity, and needle osmotic potentials were measured. Seedlings of both species were watered only when their needle water potential fell below -1.8 and -2.2 MPa respectively (water stress conditioning) or were kept well watered (controls). After 10 weeks of water stress conditioning, both regimes were allowed to dry down. During this period of increasing water stress, photosynthesis in both species was determined at 5 different cuvette CO₂ concentrations (approximately 200, 330, 500, 650, and 800 ppm). With Aleppo pine only, mesophyll resistances and stomatal limitations to gas exchange were estimated. Thylakoids were extracted from both species and their activity was measured in a liquid phase O₂ electrode (Hansatech L^td) as rate of O₂ consumption. Methyl Viologen (1,1’ -dimethyl -4, 4’- bipyridinium ion ) was included in the reaction medium. Photosynthesis decreased with increasing water stress but fell more slowly in the conditioned seedlings. As water stress increased, total resistance to CO₂ exchange increased for both regimes to a much higher level than explained by stomatal resistance alone. In the conditioned seedlings, resistances increased less precipitously than in controls. Osmotic adjustment as measured with thermocouple psychrometers occurred in both species. Decreases in photosynthesis (both species) and increases in mesophyll resistance (Aleppo pine) were not accompanied by a decrease in whole chain uncoupled electron transport capacity. / Master of Science

The National Aeronautics and Space Administration’s (NASA) Cyclone Global Navigation Satellite System (CYGNSS) mission has grown substantial attention within the land remote sensing community for estimating soil moisture (SM), wind speed, flood extent, and precipitation by using the Global Navigation Satellite System-Reflectometry (GNSS-R) technique. CYGNSS constellation generates important earth surface information called Delay-Doppler Maps (DDMs) from GNSS reflection measurements. Many previous findings considered only designed features from CYGNSS DDMs, such as the peak value of DDMs, whereas the whole DDMs are affected by SM, topography, inundation, and overlying vegetation. This dissertation explores a deep learning approach for estimating SM by leveraging spaceborne GNSS-RDDM observations provided by the CYGNSS constellation along with other remotely sensed geophysical data products. A data-driven approach utilizing convolutional neural networks (CNNs) that is trained jointly with three types of processed DDMs of Analog Power, Effective scattering area, and Bistatic Radar Cross-section (BRCS) with other auxiliary geophysical information such as normalized difference vegetation index (NDVI), elevation, soil properties, and vegetation water content (VWC). The model is trained and evaluated using the Soil Moisture Active Passive (SMAP) mission’s enhanced SM products at a 9km × 9km resolution. The model is also evaluated using in-situ measurements from International Soil Moisture Network (ISMN). The proposed approach is first explored in the Continental United States (CONUS) and then extended for global SM retrieval. The most challenging validation efforts show potential improvement for future spaceborne SM products with high spatial and temporal resolution. In addition, several SM fusion algorithms have been explored in order to combine several CYGNSS-based SM products. The fusion algorithm can help to achieve better estimation performance compared to individual products and keep the properties of individual products.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Call number: LD2668 .T4 1984 S22 / Master of Science

The effect of furrow spacing on infiltration should be determined in order to properly design an irrigation system. The blocked furrow infiltrometer (BFI) and the flowing furrow infiltrometer (FFI) methods were investigated for this purpose in two areas upon a precision field furrow. Three irrigations were performed in each method. The initial and final soil moisture contents (before and after irrigation), the furrow cross-section (before and after irrigation), the inflow volume and the furrow water surface elevations (during irrigation) were measured in each test furrow. Cumulative infiltration and infiltration rates were determined for each irrigation. The results indicate that the FFI test furrows infiltrated more water than did the BFI test furrows for the same infiltration time. The infiltration rates were higher in the FFI test furrows than in the BFI test furrows until they approach the basic intake rate. The infiltration rates were also higher during the 0.90 m spacing tests than during the 1.80 m spacing tests. The 0.90 m spacing test furrows infiltrated more water than did the 1.80 m spacing test furrows.

Production of bioethanol from crop residues such as wheat straw, has been considered as a viable approach to meet the ever increasing demands for energy without affecting our environment. However, lignin hinders the success of efficient production of bioethanol as it confers recalcitrance of lignocellulosic biomass to hydrolysis. Genetic modification of plant biomass lignin content or composition without affecting its agronomic functions, can reduce biomass recalcitrance, however, application of this strategy requires a detailed understanding of the molecular mechanisms underlying lignin synthesis. This thesis performed comprehensive analysis of the expression of wheat lignin biosynthesis candidate genes and identified genes that are predominant across different tissues. Using three commercial wheat cultivars that exhibit variation in stem resistance to lodging, it investigated the association of expression of these predominant genes with tissue lignin content. Furthermore, this identified transcriptional changes mediating the response of lignin biosynthesis in wheat to changes in soil moisture. / May 2015

This thesis is focused around improving soil moisture estimates of spatial variability and mean at the field scale, which are useful for many different applications. The objectives were: (1) examine soil moisture spatial patterns and variability within field scale, and (2) compare field-scale soil moisture determination methods. An observational study was conducted, in which soil moisture was monitored over a 500 m by 500 m area during two and a half growing seasons at a prairie pasture in central Saskatchewan. Analysis of the spatial patterns of root-zone soil moisture revealed two distinct spatial patterns representing wet (spring) and dry (fall) periods. The relationship between spatial variability and mean soil moisture was found to follow an unusual concave trend, where variability was smallest at mid-range moisture contents. These spatial variability characteristics are a result of differences in participation level. Some locations were non-participating having only small moisture changes over the growing season, while others were dynamic having large changes. At the pasture site, these participation differences are a result of high soil heterogeneity, which may be characteristic of Solonetzic soils. In the second part of this thesis, methods to determine mean field-scale root-zone soil moisture were evaluated. The cosmic-ray neutron probe has the most potential for providing field-scale measurements. However, these measurements are only representative of moisture in the top 20 cm of soil, and need to be scaled up in order to represent the entire root-zone (0–110 cm). The three scaling methods applied to obtain lower root-zone soil moisture were: (1) a single time stable location, (2) representative landscape unit, where a single monitoring profile for each vegetation type was used, and (3) modeling by exponential filter. The representative landscape unit approach estimated soil moisture changes well, but not volumetric water content. The time stability method performed the best, followed by the exponential filter. However, the exponential filter has more potential, as the time stability method is difficult to apply to other field sites; particularly those without existing soil moisture instrumentation, due to its calibration requirements. The findings of this thesis make a contribution to the large body of existing literature on soil moisture variability and scaling. Suggestions for future research are provided.

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