The effects of soil moisture, field-scale toposequential position, and slope on yields in irrigated upland rice fields in Flores, Comayagua, Honduras

Rice (Oryza sativa L.) is an important cash crop in Honduras because of the rice lobby’s size, willingness to protest, and ability to negotiate favorable price guarantees on a year-to-year basis. Despite the availability of inexpensive irrigation in the study area in Flores, La Villa de San Antonio, Comayagua, the rice farmers do not cultivate the crop using prescribed methods such as land leveling, puddling, and water conservation structures. Soil moisture (Volumetric Water Content) was measured using a soil moisture probe after the termination of the first irrigation within the tillering/vegetative, panicle emergence/flowering, post-flowering/pre-maturation and maturation stages. Yield data was obtained by harvesting on 1 m2 plots in each soil moisture testing site. Data was analyzed to find the influence of toposequential position along transects, slope, soil moisture, and farmers on yields. The results showed that toposequential position was more important than slope and soil moisture on yields. Soil moisture was not a significant predictor of rice yields. Irrigation politics, precipitation, and land tenure were proposed as the major explanatory variables for this result.

Evaluating the usefulness of soil moisture (forecasts) in streamflow prediction for central Texas

The past decade has brought significant advancements in seasonal climate forecasting. However, water resources decision support and management continues to be based almost entirely on historical observations and does not take advantage of climate forecasts. This study builds on previous work that conditioned streamflow ensemble forecasts on observable climate indicators, such as the El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) for use in a decision support model for the Highland Lakes multi-reservoir system in central Texas operated by the Lower Colorado River Authority (LCRA). In the current study, seasonal soil moisture is explored as a climate indicator and predictor of annual streamflow for the LCRA region. The main purpose of this study is to evaluate the correlation of fractional soil moisture with streamflow using the 1950-2000 Variable Infiltration Capacity (VIC) Retrospective Land Surface Data Set over the LCRA region. Correlations were determined by examining different annual and seasonal combinations of VIC modeled fractional soil moisture and observed streamflow. The applicability of the VIC Retrospective Land Surface Data Set as a data source for this study is tested along with establishing and analyzing patterns of climatology for the watershed study area using the selected data source (VIC model) and historical data. Correlation results showed potential for the use of soil moisture as a predictor of streamflow over the LCRA region. This was evident by the good correlations found between seasonal soil moisture and seasonal streamflow during coincident seasons as well as between seasonal and annual soil moisture with annual streamflow during coincident years. With the findings of good correlation between seasonal soil moisture from the VIC Retrospective Land Surface Data Set with observed annual streamflow presented in this study, future research would evaluate the application of NOAA Climate Prediction Center (CPC) forecasts of soil moisture in predicting annual streamflow for use in the decision support model for the LCRA.

Quantifying the ecological benefits of lakeshore restoration in northern Wisconsin

Housing development has increased dramatically in the Midwest with a high concentration around lakes. This development plays an important role in the economy of Northwoods communities. However, poorly planned development has the potential to alter a lake’s ecological processes and integrity. Studies have documented the impacts of housing developments and reported dramatic, negative changes to the flora and fauna in Vilas County, Wisconsin. One component of my research included examining the previously unstudied effects of residential development on the abundance and diversity of medium to large-bodied mammals using lakeshore ecosystems. The results suggest that a higher diversity of mammals were detected on low-development lakes. Coyotes were the most numerous species detected with the majority encountered on low-development lakes. White-tailed deer and red fox were more abundant on high-development lakes as compared to low-development lakes. I concluded that high-development lakes are having a negative affect on the mammal community in this area. Recently, lakeshore restoration has occurred on privately owned property in Vilas County and elsewhere in the Northwoods, but little is known about the benefit, if any, from these restoration efforts. A partnership between government agencies and academia has launched a long-term research project investigating the ecological benefits of lakeshore restoration. I investigated the impacts of using down woody material (DWM) to increase the success of restoration projects. Specifically, I tested the hypothesis that down woody material would reduce the variation in soil temperature, retain soil moisture, and improve plant survival and growth rates. I randomly assigned three DWM coverage treatments (0%, 25%, and 50%) on 3 m × 3 m experimental plots (n = 10 per treatment). The mean maximum soil temperature, temperature variation, and change in soil moisture content were significantly lower in the 25% and 50% DWM plots. I found no difference in survival, but snowberry (Symphoricarpos albus) and Barren strawberry (Waldstenia fragaroides) growth was significant greater in the 25% and 50% DWM plots. DWM addition can be considered a useful technique to physically manipulate soil properties and improve plant growth. Finally, I provided baseline data on vegetation structure, bird and small mammal community diversity and abundance for three lakes targeted for restoration efforts and their paired reference lakes. This study is one of the first of it kind in the area and continuing to document the degree of change in subsequent years will provide insight into the way the local ecosystem functions and how ecological communities are structured.

EVALUATION OF INTELLIGENT COMPACTION CONTROL IN THE M-189 RECONSTRUCTION PROJECT AT IRON RIVER, MICHIGAN

This research evaluated an Intelligent Compaction (IC) unit on the M-189 highway reconstruction project at Iron River, Michigan. The results from the IC unit were compared to several traditional compaction measurement devices including Nuclear Density Gauge (NDG), Geogauge, Light Weight Deflectometer (LWD), Dynamic Cone Penetrometer (DCP), and Modified Clegg Hammer (MCH). The research collected point measurements data on a test section in which 30 test locations on the final Class II sand base layer and the 22A gravel layer. These point measurements were compared with the IC measurements (ICMVs) on a point-to-point basis through a linear regression analysis. Poor correlations were obtained among different measurements points using simple regression analysis. When comparing the ICMV to the compaction measurements points. Factors attributing to the weak correlation include soil heterogeneity, variation in IC roller operation parameters, in-place moisture content, the narrow range of the compaction devices measurement ranges and support conditions of the support layers. After incorporating some of the affecting factors into a multiple regression analysis, the strength of correlation significantly improved, especially on the stiffer gravel layer. Measurements were also studied from an overall distribution perspective in terms of average, measurement range, standard deviation, and coefficient of variance. Based on data analysis, on-site project observation and literature review, conclusions were made on how IC performed in regards to compaction control on the M-189 reconstruction project.