Call number: LD2668 .T4 1986 S237 / Master of Science / Agronomy

No description available.

Graduation date: 1994

Soil solution samplers have certain inadequacies that limit their range of possible applications. Passive Capillary Samplers (PCAPS), which apply suction to the soil pore-water via a fiber glass wick, have shown promising results in preliminary experiments in regard to collection efficiency of water and of bromide tracers. The objectives of this study were to evaluate PCAPS under non-steady state field conditions with respect to (1) effect of installation procedure and operational characteristics, (2) ability to estimate the soil-water flux, and (3) ability to estimate the mean concentration of agrochemicals. At the same time, samplers were used to (4) evaluate the effect of a cereal rye (Secale cereale (L.)) cover crop on NO₃⁻ leaching. Thirty-two PCAPS and 32 suction cup samplers were installed below the root zone at a depth of 120 cm in a Willamette Variant loam wet soil (fine loamy mixed mesic Pachic Ultic Argixeroll). Samplers were installed in an ongoing cover crop/crop rotation study. Regarding overall performance, flux measurements were within 20 % of the native values as determined by a water balance. The air release from the sample bottles was a point of concern and might have slowed down the sampling rate. The installation procedure introduced bias into volume and concentration measurements of the part of the PCAPS closest to the refilled trench. The leachate concentration as calculated using the arithmetic mean of suction cup sampler measurements holds a significant bias, deviating by up to 97 % for bromide concentrations. Phosphate was not detected by the suction cup samplers indicating that ceramic cups should not be used for phosphate sampling. Matrix and preferential flow could clearly be distinguished using the PCAPS, showing that PCAPS are a valuable tool to assess the hydrology and solute transport mechanisms of a field site. The cover crop reduced NO₃⁻-N leaching significantly at the recommended N rate as evaluated by PCAPS. The cover crop reduced the seasonal mean NO₃⁻-N concentration at the recommended N rate from 13.5 mg LI to 8.1 mg L⁻¹, which is under the E.P.A. drinking water quality standard of 10 mg L⁻¹. The total NO₃⁻-N mass lost under the fallow treatment at the recommended N rate was 48 kg N ha⁻' which compares to 32 kg N ha⁻' under the cover crop treatment. Given the increasing problems with nitrate contamination of ground water, programs to support the cultivation of catch crops in conjunction with nitrogen soil testing should be considered as a relatively easy, effective, and biologically sound means to reduce nitrate concentrations in the recharge to the ground water in agricultural settings. / Graduation date: 1994

Increasing irrigation efficiency on turfgrass could help reduce water consumption on large turf facilities. Two experiments were conducted using perennial ryegrass (Lolium perenne (L.) Derby) to evaluate the potential of using remote sensing to estimate turf water status, predict daily evapotranspiration (ET), and estimate turf biomass. In the first experiment a crop water stress index, utilizing remotely sensed canopy temperature, were used to schedule irrigations on 6 of 10 drainage lysimeters. Three of the remaining lysimeters were irrigated used on meteorological estimates of ET calculated using a modified Penman equation. The results of this experiment were inconclusive due to inconsistent lysimeter drainage characteristics. The second experiment was conducted on a turf green with multiple heights to evaluate the potential for using canopy radiance to estimate turf biomass. These results showed that turf biomass could be estimated from a vegetative index (Red Ratio = Near Infrared/Red radiance) obtained through measurements of canopy radiance (r2 = 0.91).

No description available.

No description available.

Effective management of saline soils requires rapid, reliable methods of monitoring both soil water content (theta) and salt concentration, the latter measured in terms of electrical conductivity (sigma). This thesis examines estimation of theta, and bulk soil sigma (sigmaa) and soil water sigma (sigmaw), using time domain reflectometry (TDR). Calibration experiments were conducted in soil columns and in a vineyard that were irrigated with saline water. Within a theta range of 0.025--0.490 m3/m3, the correlation between TDR theta (thetaTDR) and gravimetrically determined theta (theta g) was high (r2 = 0.979 in soil columns, r2 = 0.836 in the field). The error of estimate of thetaTDR was 0.020 m3/m3 or less. Field thetaTDR estimates were sensitive to high salinity (sigmaw > 10 dS/m). Using a dual pathway parallel conductance (DPPC) model, sigma a was derived from sigmaw of saturated paste extracts and theta g. The correlation of TDR sigmaa to DPPC sigmaa was good in the laboratory (r2 = 0.915), and moderate in the field (r2 = 0.791), indicating a functional relationship between sigmaw and theta and TDR sigmaa. Models, to estimate sigmaw, were built by regression between paste extract sigma w and TDR sigmaa and thetaTDR. In a sigma w range of 3.0--23.4 dS/m in the columns, error of estimate of sigma w was small at 1.50 dS/m (+/-12.4% relative error range). In a sigma w range of 2.2--25.2 dS/m in the field, error of estimate of sigma w was 3.37 dS/m (+/-37% relative error range), which was significantly higher than the acceptable error range of +/-10%. ANOVA tests indicated that both TDR sigmaa and sigmaw·theta changed significantly with respect to the same sources of variance. Error in field estimates of sigmaw was associated with effects of salinity on thetaTDR and variability of soil conditions, particularly with respect to depth and time of sampling.

Typescript. / Thesis (Ph. D.)--University of Hawaii at Manoa, 1987. / Bibliography: leaves [179]-185. / Photocopy. / Microfiche. / xiv, 185 leaves, bound ill. 29 cm

Drought is the most costly hazard among all natural disasters. Despite the significant improvements in drought modeling over the last decade, accurate provisions of drought conditions in a timely manner is still one of the major research challenges. In order to improve the current drought monitoring and forecasting skills, this study presents a hybrid system with a combination of remotely sensed data assimilation based on particle filtering and a probabilistic drought forecasting model. Besides the proposed drought monitoring system through land data assimilation, another novel aspect of this dissertation is to seek the use of data assimilation to quantify land initial condition uncertainty rather than relying entirely on the hydrologic model or the land surface model to generate a single deterministic initial condition. Monthly to seasonal drought forecasting products are generated using the updated initial conditions. The computational complexity of the distributed data assimilation system required a modular parallel particle filtering framework which was developed and allowed for a large ensemble size in particle filtering implementation. The application of the proposed system is demonstrated with two case studies at the regional (Columbia River Basin) and the Conterminous United States. Results from both synthetic and real case studies suggest that the land data assimilation system significantly improves drought monitoring and forecasting skills. These results also show how sensitive the seasonal drought forecasting skill is to the initial conditions, which can lead to better facilitation of the state/federal drought preparation and response actions.