Jennifer M. Jacobs

EVAPOTRANSPIRATION FROM A WET PRAIRIE WETLAND UNDER DROUGHT CONDITIONS: PAYNES PRAIRIE PRESERVE, FLORIDA, USA

Evapotranspiration and other surface-energy balance components of a wet prairie community dominated by Panicum hemitomon (maiden cane), Ptilimnium capillaceum (mock bishop’s weed), and Eupatorium capillifolium (dog fennel) in Central Florida, USA were investigated. Drought conditions resulted in water-table levels from 0.58 to 1.20 m below ground level and variable soil wetness conditions during the observation period. Energy-balance measurements were made using the eddy correlation approach. The overall evapotranspiration rate was 4.16 mm d−1, and the average Bowen ratio was 0.42. Energy partitioning had an enhanced sensible heat-flux component and a dampened latent heat-flux component when the volumetric soil water content was less than or equal to 0.09 for the sandy soil. Evapotranspiration was classified into a two stages, first stage (wet) and second stage (dry) based on the soil water availability. The Penman-Monteith model gave good results for the first stage evapotranspiration. The Priestly-Taylor and the Penman models overstimated first stage evapotranspiration. A simple second stage evapotranspiration model, developed by applying a reduction factor based on soil moisture to the Penman-Monteith model, provided improved estimates of evapotranspiration for second stage observations.

GOES surface insolation to estimate wetlands evapotranspiration

Incoming solar radiation derived from GOES-8 satellite observations, in combination with local meteorological measurements, were used to model evapotranspiration from a wetland. The wetland experiment was conducted in the Paynes Prairie Preserve, North Central Florida during a growing season characterized by significant convective activity. The satellite solar radiation measurements generally agreed with pyranometer data gathered at the site. The satellite net radiation estimates were in good agreement with the 30-min averages of measured net radiometer data. Satellite derived net radiation estimates were used in the Penman‐ Monteith and Priestley ‐ Taylor models to calculate evapotranspiration. The calculated instantaneous evaporative fluxes were in good agreement with 30-min average ground-based eddy correlation system measurements. The daily averages of modeled evapotranspiration were in very good agreement ðr 2 ¼ 0:90Þ with reference eddy flux

Bahiagrass crop coefficients from eddy correlation measurements in central Florida

Bahiagrass (Paspalum notatum) is a warm-season grass used primarily in pastures and along highways and other low maintenance public areas in Florida. It is also used in landscapes to some extent because of its drought tolerance. Bahiagrass can survive under a range of moisture conditions from no irrigation to very wet conditions. Its well-watered consumptive use has not been reported previously. In this study, bahiagrass crop coefficients (Kc) for an irrigated pasture were determined for July 2003 through December 2006 in central Florida. The eddy correlation method was used to estimate crop evapotranspiration (ETc) rates. The standardized reference evapotranspiration (ETo) equation (ASCE-EWRI standardization of reference evapotranspiration task committee report, 2005) was applied to calculate ETo values using on site weather data. Daily Kc values were estimated from the ratio of the measured ETc and the calculated ETo. The recommended Kc values for bahiagrass are 0.35 for January–February, 0.55 for March, 0.80 for April, 0.90 for May, 0.75 for June, 0.70 for July–August, 0.75 for September, 0.70 for October, 0.60 for November, and 0.45 for December in central Florida. The highest Kc value of 0.9 in May corresponded with maximum vapor pressure deficit conditions as well as cloud free conditions and the highest incoming solar radiation as compared to the rest of the year. During the summer (June to August), frequent precipitation events increased the cloud cover and reduced grass water use. The Kc annual trend was similar to estimated Kc values from another well-watered warm-season grass study in Florida.

Impacts of Unsaturated Zone Soil Moisture and Groundwater Table on Slope Instability

The combined effect of soil moisture in unsaturated soil layers and pore-water pressure in saturated soil layers is critical to predict landslides. An improved infinite slope stability model, that directly includes unsaturated zone soil moisture and groundwater, is derived and used to analyze the factor of safety’s sensitivity to unsaturated zone soil moisture. This sensitivity, the change in the factor of safety with respect to variable unsaturated zone soil moisture, was studied at local and regional scales using an active landslide region as a case study. Factors of safety have the greatest sensitivity to unsaturated zone soil moisture dynamics for shallow soil layers ( <2 m ) and comparatively deep groundwater tables (1 m). For an identical groundwater table, the factor of safety for a 1 m thick soil mantle was four times more sensitive to soil moisture changes than a 3-m thick soil. At a regional scale, the number of unstable areas increases nonlinearly with increasing unsaturated zone soil moisture ...

Comparison of passive microwave and modeled estimates of total watershed SWE in the continental United States

In the U.S., a dedicated system of snow measurement stations and snowpack modeling products is available to estimate the snow water equivalent (SWE) throughout the winter season. In other regions of the world that depend on snowmelt for water resources, snow data can be scarce, and these regions are vulnerable to drought or flood conditions. Even in the U.S., water resource management is hampered by limited snow data in certain regions, as evident by the 2011 Missouri Basin flooding due in large part to the significant Plains snowpack. Satellite data could potentially provide important information in under-sampled areas. This study compared the daily AMSR-E and SSM/I SWE products over nine winter seasons to spatially distributed, modeled output SNODAS summed over 2100 watersheds in the conterminous U.S. Results show large areas where the passive microwave retrievals are highly correlated to the SNODAS data, particularly in the northern Great Plains and southern Rocky Mountain regions. However, the passive microwave SWE is significantly lower than SNODAS in heavily forested areas, and regions that typically receive a deep snowpack. The best correlations are associated with basins in which maximum annual SWE is less than 200 mm, and forest fraction is less than 20%. Even in many watersheds with poor correlations between the passive microwave data and SNODAS maximum annual SWE values, the overall pattern of accumulation and ablation did show good agreement and therefore may provide useful hydrologic information on melt timing and season length.

Intercomparison Study of the Land Surface Process Model and the Common Land Model for a Prairie Wetland in Florida

Abstract Common Land Model (CLM) and Land Surface Process (LSP) model simulations are compared to measured values for a 13-day dry-down period with a rapidly decreasing near-surface water table for a marsh wetland community in Florida. LSP was able to provide reasonable estimates without any modifications to the model physics. To obtain reasonable simulations using CLM, the baseline TOPMODEL baseflow generation and the bottom drainage mechanisms were not employed and the lower layers were allowed to remain saturated. In addition, several of CLM’s default wetland vegetation parameters were replaced with grassland parameters. Even after these modifications, CLM underestimated soil water storage. However, both model-simulated soil temperatures showed very good agreement as compared to measured temperatures, capturing both the soil warming during the study period and the diurnal fluctuations. Modeled surface energy fluxes also agreed well with measured values. LSP’s inability to consistently capture latent he...

WEIGHING LYSIMETERS FOR EVAPOTRANSPIRATION RESEARCH IN A HUMID ENVIRONMENT

Three weighing lysimeters were developed for evapotranspiration research at the University of Florida, Institute of Food and Agricultural Sciences, Plant Science Research and Education Unit near Citra, Florida. The lysimeter design followed accepted procedures as well as aspects unique to the study site, including a foundation designed for a perched water table outside the lysimeters, fetch distance, deep drainage, and lightning protection. Each lysimeter has a planted surface area of 2.32 m2 and a soil depth of 1.37 m. The soil in each lysimeter is reconstructed sandy soil originally from the experimental site. The lysimeter facility includes monitoring wells, an automatic pumping system, and additional lightning protection system for load cells and soil moisture sensors. The construction materials and installation cost (excluding labor) were

Solar radiation, longwave radiation and emergent wetland evapotranspiration estimates from satellite data in Florida, USA / Estimations à partir de données satellitales du rayonnement solaire, du rayonnement de grande longueur d’onde et de l’évapotranspiration d’une zone humide de Floride (EUA)

63,443 for the three lysimeters. Lysimeter on-site maintenance, operation, and performance are discussed. Four load cells with an accuracy of 0.02% (0.12 mm) are used to weigh the average 5.8 Mg lysimeter mass, including the steel lysimeter tank and soil. Initial data show that the three lysimeters provided a consistent hourly evapotranspiration (ETc) measurement over a five-day period in the summer season, although many field activities and precipitation events occurred. An additional 30 days of daily bahiagrass ETc resulted in a 0.82 ratio between the ETc and Penman-Monteith reference evapotranspiration in November 2003.

Method for Evaluating Implications of Climate Change for Design and Performance of Flexible Pavements

Abstract Abstract Routine estimates of daily incoming solar radiation from the GOES-8 satellite were compared to locally measured values in Florida. Longwave radiation estimates corrected using GOES-derived cloud amount and cloud top temperature products improved net radiation estimates as compared to a clear sky longwave approach. The Penman-Monteith, Turc, Hargreaves and Makkink models were applied using GOES-derived estimates of solar radiation and net radiation to predict daily evapotranspiration and were compared to evapotranspiration measured with an eddy-correlation system in an emergent wetland experimental site in north-central Florida under unstressed conditions. While the Penman-Monteith model provided the best estimates of evapotranspiration (R 2 = 0.92), the empirical Makkink method demonstrated nearly comparable agreement (R 2 = 0.90) using only the GOES solar radiation and measured temperature. The results show that it is possible to generate spatially distributed daily potential evapotranspiration estimates using GOES-derived solar radiation and net radiation with limited additional surface measurements.

Enhancing Water Cycle Measurements for Future Hydrologic Research

A method to assess the impacts of forecasted climate change on pavement deterioration is presented. Traditional methods of pavement design use historic climate data and assume that climate is stationary with time. Climate change challenges this assumption of stationarity (i.e., natural driving forces of engineering have a variability described by a time-invariant probability density function). Therefore, the use of historic climate data is insufficient for the prediction of climate conditions. The focus is on the preparation and the use of climate model data sets as inputs to the Mechanistic–Empirical Pavement Design Guide (MEPDG) model to simulate flexible pavement performance and deterioration over time. The method is illustrated with a case study that uses future climate model temperature data from three North American Regional Climate Change Assessment Program scenarios at four sites across New England. Pavement distress predicted with future temperature scenarios is compared with that from MEPDG temperature data. Application of the method demonstrates the importance of matching the overlapping periods before using climate forecast output in the MEPDG. Although the simulated impact of future temperature changes on pavement performance was negligible for alligator cracking at the four study sites, asphalt concrete rutting differences were great enough to warrant additional consideration and to suggest that climate change and variability in future climate scenarios could affect pavement design and evaluation. The proposed method can be used to evaluate the impact of other climate variables alone or in combination. The method also can readily use new climate model output and be adapted for new downscaling methods.