The land surface and atmosphere interact through complex feedback loops that link energy and water cycles. Effectively characterizing these linkages is critical to modeling weather and climate extremes accurately. Seasonal variability in vegetation growth and human-driven land cover changes (LCC) can alter the biophysical properties of the land surface, which can in turn influence the water cycle. We quantified the impacts of seasonal variability in vegetation growth on land surface energy and water balances using ecosystem-scale eddy covariance and large aperture scintillometer observations. Our results indicated that the monthly precipitation and seasonal vegetation characteristics such as leaf area index, root length, and stomatal resistance are the main factors influencing ecosystem land surface energy and water balances when soil moisture and available energy are not limited. Using a regional-scale climate model, we examined the effect of LCC and irrigation on summer water cycle characteristics. Changes in biophysical properties due to LCC reducing the evapotranspiration, atmospheric moisture, and summer precipitation over the contiguous United States (CONUS). The combined effects of LCC and irrigation indicated a significant drying over the CONUS, with increased duration and decreased intensity of dry spells, and reduced duration, frequency, and intensity of wet spells. Irrigated cropland areas will become drier due to the added effect of low-precipitation wet spells and long periods (3-4% increase) of dry days, whereas rainfed croplands are characterized by intense (1-5% increase), short-duration wet spells and long periods of dry days. An analysis based on future climate change projections indicated that 3–4 °C of warming and an intensified water cycle will occur over the CONUS by the end of the 21st century. The results of this study highlighted the importance of the accurate representation of seasonal vegetation changes and LCC while forecasting present and future climate. / Doctor of Philosophy / The land surface and atmosphere interact through complex feedback loops that link energy and water cycles. Effectively characterizing these linkages is critical to accurately model weather and climate extremes. We quantified the influence of human-driven land cover change (LCC), in this case, LCC associated with irrigated agriculture, and seasonal vegetation growth on the water cycle using a regional climate model and ecosystem-level observations. Our results indicated that monthly precipitation and seasonal vegetation growth are the main factors influencing land surface energy and water balances when soil moisture and solar energy are not limited. Our results showed that irrigation-related LCC reduced summer precipitation over the contiguous United States (CONUS), with an increased number of dry days (days with less than 1 mm precipitation) and reduced hourly, daily, and summer precipitation totals. Irrigated cropland areas are becoming drier due to the combined effects of low precipitation and long dry days, whereas rainfed croplands are characterized by intense short-duration precipitation and long dry days. Climate change analyses indicate that 3–4 °C of warming and an intensified water cycle will occur over the CONUS by the end of the 21st century. The results of this study highlight the importance of the accurate representation of LCC while forecasting future climate.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/105061 |
| Date | 03 April 2019 |
| Creators | Valayamkunnath, Prasanth |
| Contributors | Biological Systems Engineering, Hession, W. Cully, Prisley, Stephen P., Benham, Brian L., Thompson, Theresa M. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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