168 research outputs found
RHESSys: Regional Hydro-Ecologic Simulation SystemâAn Object-Oriented Approach to Spatially Distributed Modeling of Carbon, Water, and Nutrient Cycling
Process-based models that can represent multiple and interacting processes provide a framework for combining field-based measurements with evolving science-based models of specific hydroecological processes. Use of these models, however, requires that the representation of processes and key assumptions involved be understood by the user community. This paper provides a full description of process implementation in the most recent version of the Regional Hydro-Ecological Simulation System (RHESSys), a model that has been applied in a wide variety of research settings. An overview of the underlying (Geographic Information System) GISbased model framework is given followed by a description of the mathematical models used to represent various biogeochemical cycling and hydrologic processes including vertical and lateral hydrologic fluxes, microclimate variability, canopy radiation transfer, vegetation and soil microbial carbon and nitrogen cycling. An example application of RHESSys for a small forested watershed as part of the Baltimore Long-Term Ecological Research site is included to illustrate use of the model in exploring spatial-temporal dynamics and the coupling between hydrology and biogeochemical cycling
Simulations of snow distribution and hydrology in a mountain basin
We applied a version of the Regional HydroâEcologic Simulation System (RHESSys) that implements snow redistribution, elevation partitioning, and windâdriven sublimation to Loch Vale Watershed (LVWS), an alpineâsubalpine Rocky Mountain catchment where snow accumulation and ablation dominate the hydrologic cycle. We compared simulated discharge to measured discharge and the simulated snow distribution to photogrammetrically rectified aerial (remotely sensed) images. Snow redistribution was governed by a topographic similarity index. We subdivided each hillslope into elevation bands that had homogeneous climate extrapolated from observed climate. We created a distributed wind speed field that was used in conjunction with daily measured wind speeds to estimate sublimation. Modeling snow redistribution was critical to estimating the timing and magnitude of discharge. Incorporating elevation partitioning improved estimated timing of discharge but did not improve patterns of snow cover since wind was the dominant controller of areal snow patterns. Simulating windâdriven sublimation was necessary to predict moisture losses
Subsurface storage capacity influences climateâevapotranspiration interactions in three western United States catchments
Winter wheat, 2000
"July 2000.""Publication costs paid by Missouri Seed Improvement Association."The objective of the Missouri Winter Wheat Performance Tests is to provide wheat growers in Missouri with a reliable, unbiased, up-to-date source of information that will permit valid comparisons among improved wheat varieties. This information should help Missouri wheat growers select varieties best suited to their particular area and growing conditions. This report summarizes soft red winter wheat variety trials conducted throughout Missouri during the 1999-00 cropping season. No hard red winter wheat test was grown in 2000
Winter wheat, 1994
"July 1994.""Publication costs paid by Missouri Seed Improvement Association."The objective of the Missouri Winter Wheat Performance Tests is to provide wheat growers in Missouri with a reliable, unbiased, up-to-date source of information that will permit valid comparisons among improved wheat varieties. This information should help Missouri wheat growers select varieties best suited to their particular area and growing conditions. This report summarizes soft and hard winter wheat variety trials conducted throughout Missouri during the 1993-94 cropping season
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Coupling snowpack and groundwater dynamics to interpret historical streamflow trends in the western United States
A key challenge for resource and land managers is predicting the consequences of climate warming on streamflow and water
resources. During the last century in the western United States, significant reductions in snowpack and earlier snowmelt have led
to an increase in the fraction of annual streamflow during winter and a decline in the summer. Previous work has identified
elevation as it relates to snowpack dynamics as the primary control on streamflow sensitivity to warming. But along with changes
in the timing of snowpack accumulation and melt, summer streamflows are also sensitive to intrinsic, geologically mediated
differences in the efficiency of landscapes in transforming recharge (either as rain or snow) into discharge; we term this latter
factor drainage efficiency. Here we explore the conjunction of drainage efficiency and snowpack dynamics in interpreting
retrospective trends in summer streamflow during 1950â2010 using daily streamflow from 81 watersheds across the western
United States. The recession constant (k) and fraction of precipitation falling as snow (S[subscript f]) were used as metrics of deep
groundwater and overall precipitation regime (rain and/or snow), respectively. This conjunctive analysis indicates that summer
streamflows in watersheds that drain slowly from deep groundwater and receive precipitation as snow are most sensitive to
climate warming. During the spring, however, watersheds that drain rapidly and receive precipitation as snow are most sensitive
to climate warming. Our results indicate that not all trends in western United States are associated with changes in snowpack
dynamics; we observe declining streamflow in late fall and winter in rain-dominated watersheds as well. These empirical findings
support both theory and hydrologic modelling and have implications for how streamflow sensitivity to warming is interpreted
across broad regions. Copyright © 2012 John Wiley & Sons, Ltd.Keywords: Groundwater processes, Climate, Warming, Hydrologic processes, Streamflow tren
Winter wheat, 1990
"August, 1990.""Publication costs paid by Missouri Seed Improvement Association."Authors: Kenneth D. Kephart, Assistant Professor and State Extension Agronomist-Small Grains; Anne L. McKendry, Assistant Professor and Small Grains Breeder; David N. Tague, Senior Research Laboratory Technician; and James E. Berg, Research Specialist, Department of Agronomy, University of Missouri, Columbia. Calvin L. Hoenshell, Research Specialist, Southwest Missouri Research Center, Mt. Vernon. Roger C. Wilkins, Farm Worker II, Greenley Memorial Center, Novelty.Special Report No. 416 is a contribution of the Department of Agronomy, University of Missouri Agricultural Experiment Station. The Missouri Winter Wheat Performance Testing program is partially funded by Missouri wheat farmers and businessmen through a grant from the Missouri Seed Improvement Association and by fees from companies submitting varieties for evaluation
Energy, water, and carbon fluxes in a loblolly pine stand: Results from uniform and gappy canopy models with comparisons to eddy flux data
1] This study investigates the impacts of canopy structure specification on modeling net radiation (R n), latent heat flux (LE) and net photosynthesis (A n) by coupling two contrasting radiation transfer models with a two-leaf photosynthesis model for a maturing loblolly pine stand near Durham, North Carolina, USA. The first radiation transfer model is based on a uniform canopy representation (UCR) that assumes leaves are randomly distributed within the canopy, and the second radiation transfer model is based on a gappy canopy representation (GCR) in which leaves are clumped into individual crowns, thereby forming gaps between the crowns. To isolate the effects of canopy structure on model results, we used identical model parameters taken from the literature for both models. Canopy structure has great impact on energy distribution between the canopy and the forest floor. Comparing the model results, UCR produced lower R n , higher LE and higher A n than GCR. UCR intercepted more shortwave radiation inside the canopy, thus producing less radiation absorption on the forest floor and in turn lower R n . There is a higher degree of nonlinearity between A n estimated by UCR and by GCR than for LE. Most of the difference for LE and A n between UCR and GCR occurred around noon, when gaps between crowns can be seen from the direction of the incident sunbeam. Comparing with eddy-covariance measurements in the same loblolly pine stand from May to September 2001, based on several measures GCR provided more accurate estimates for R n , LE and A n than UCR. The improvements when using GCR were much clearer when comparing the daytime trend of LE and A n for the growing season. Sensitivity analysis showed that UCR produces higher LE and A n estimates than GCR for canopy cover ranging from 0.2 to 0.8. There is a high degree of nonlinearity in the relationship between UCR estimates for A n and those of GCR, particularly when canopy cover is low, and suggests that simple scaling of UCR parameters cannot compensate for differences between the two models. LE from UCR and GCR is also nonlinearly related when canopy cover is low, but the nonlinearity quickly disappears as canopy cover increases, such that LE from UCR and GCR are linearly related and the relationship becomes stronger as canopy cover increases. These results suggest the uniform canopy assumption can lead to underestimation of R n , and overestimation of LE and A n . Given the potential in mapping regional scale forest canopy structure with high spatial resolution optical and Lidar remote sensing plotforms, it is possible to use GCR for up-scaling ecosystem processes from flux tower measurements to heterogeneous landscapes, provided the heterogeneity is not too extreme to modify the flow dynamics., Energy, water, and carbon fluxes in a loblolly pine stand: Results from uniform and gappy canopy models with comparisons to eddy flux data, J. Geophys. Res., 114, G04021, doi:10.1029/2009JG000951
Hillslope Hydrology in Global Change Research and Earth System Modeling
Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope-scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid-level water, energy, and biogeochemical fluxes. In contrast to the one-dimensional (1-D), 2- to 3-m deep, and free-draining soil hydrology in most ESM land models, we hypothesize that 3-D, lateral ridge-to-valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions. Plain Language Summary Hillslopes are key landscape features that organize water availability on land. Valley bottoms are wetter than hilltops, and sun-facing slopes are warmer and drier than shaded ones. This hydrologic organization leads to systematic differences in soil and vegetation between valleys and hilltops, and between sunny and shady slopes. Although these patterns are fundamental to understanding the structures and functions of water and terrestrial ecosystems, they are too fine grained to be represented in global-scale Earth System Models. Here we bring together Critical Zone scientists who study the interplay of vegetation, the porous upper layer of the continental crust from vegetation to bedrock, and moisture dynamics deep into the weathered bedrock underlying hillslopes and Earth System Model scientists who develop global models, to ask: Do hillslope-scale processes matter to predicting global change? The answers will help scientists understand where and why hillslopes matter, and to better predict how terrestrial ecosystems, including societies, may affect and be affected by our rapidly changing planet.National Science Foundation [NSF-EAR-1528298, NSF-EAR-0753521]6 month embargo; published online: 27 February 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
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