H31G-0734
Interaction between Hydrosphere and Biosphere: Challenges and Opportunities
Vegetated terrestrial ecosystems and the overlying atmosphere are dynamically linked though the continuous transfer of mass, energy and momentum. The hydrologic variability interacts with the vegetation at time scales ranging from hours to days to inter-annual and decadal. The existing distribution of ecosystems is a result of evolutionary selections in response to environmental constraints which are themselves modified as terrestrial systems evolve until reaching a dynamic equilibrium. However this balance is changing, often rapidly, in response to anthropogenic influences such as climate change, land use/land cover change, and urban and agricultural expansions. Evidence suggests that vegetation response is adaptive in that they alter their survival strategies in response to environmental change, for example, through development of deep rooting and using hydraulic redistribution to better utilize the available moisture in the deeper soil layers. Yet little is known on how this impacts the hydrologic cycle and its variability. Active and adaptive control of vegetation and atmospheric flow moves soil-moisture that is no longer constrained by watershed boundaries. How do the atmospheric and terrestrial moisture, and vegetation interact to produce the observed variability in the water cycle and how does/will this variability change in response to the anthropogenic influences? What are the ecological consequences of this change? These broad questions lie at the heart of understanding the interaction between the hydrosphere and biosphere. Some specific questions to address are: · How does biosphere mediate the interaction between long time scale sub-surface hydrology and short time scale atmospheric hydrologic cycle? · How has this interaction given rise to the observed self-organized patterns of ecosystems and how do these ecosystems sustain the hydrologic regime needed for their own sustenance? · How are the dynamic regimes of ecohydrologic interactions affected by the anthropogenic impacts of land use/land cover change, elevated CO2 and temperature, water use, etc? · How do these linkages and changes there in alter the biogeochemical cycling in a region? Addressing these challenges is a sub-theme of the synthesis project supported by NSF. In this talk we will describe the progress made in regard to these issues.
H31G-0735
Evolution, structure and function of hydrologic subsystems in hillslopes
Hillslopes offer a useful elementary scale to construct catchment hydrologic models, and to understand the role of water in the landscape. However, hillslopes exhibit enormous complexity and heterogeneity, much of which is not easily observable. The complexity is driven by the interactions between water, biogeochemistry, ecology and soils, within the constraints set by the climate and the geologic history of the system. These interactions create complex, non-random patterns and structures in space-time. Current models have difficulty accounting for these interactions and unobserved structural complexity. A new approach may ask: why do the complex structures exist at all? Taking the view that the hydrology of a landscape has evolved along with its soils, ecology and geomorphology, we may ask if the hydrologic subsystem of a hillslope has a functional role in the maintenance of the overall system. This functional role may be expressed as an organizing principle - a constraint on possible ways that the hydrologic flowpaths may be organized such that the functional role is met. If a relationship can be established between an organizing principle and the structure of hydrologic flow-paths and storages, it can form the basis for developing closure relations at the hillslope scale that have meaningful relationships to the underlying dynamics. In this way, heterogeneity and complexity of hillslopes are no longer problems to be overcome, but rather are keys to making meaningful predictions. Formulating and testing organizing principles will necessarily require the synthesis of knowledge from many disciplines. One approach is to construct artificial hillslopes in a controlled environment, and use them to ask, given a set of observable constraints (climate, soil, ecologic and biogeochemical parameters) which structures and responses are "behavioral" - in the sense that they fulfill the function set by the organizing principle. Such artificial hillslopes will be constructed at the newly established B2 Earthscience facility run by the University of Arizona. This effort is also part of one of the synthesis activities organized by an NSF funded hydrologic synthesis project, coordinated by the University of Illinois at Urbana- Champaign. Decisions about critical design parameters will be based on a series of consultations (in the form of workshops) engaging scientists from different Earth science disciplines.
H31G-0736
Optimality and soil water-vegetation dynamics
Soil moisture is an important factor for nearly all hydrological and biogeochemical processes. Antecedent soil moisture impacts on infiltration and runoff generation, the soil moisture distribution within the soil together with other factors determines the soil carbon and nutrient cycling and the amount of soil moisture within the rooting zone often constitutes a major constraint for plant growth and evapo-transpiration. The main processes determining soil moisture dynamics are infiltration, percolation, evaporation and root water uptake. Therefore, modelling soil moisture dynamics requires an interdisciplinary approach that links hydrological and biological processes. Previous approaches treat either root water uptake rates or root distributions and transpiration rates as a given, and calculate the soil moisture dynamics based on the theory of flow in unsaturated media. The present study introduces a different approach to linking soil water and vegetation dynamics, based on optimality. Assuming that plants aim at minimising the costs related to the maintenance of the root system while meeting their demand for water, a model was formulated that dynamically adjusts the vertical root distribution in the soil profile to meet this objective. The model was used to compute the soil moisture dynamics in a tropical savanna over 12 months, which showed a better resemblance with the observed time series of surface soil moisture than models based on fixed root distributions. The optimality-based approach to modelling soil-vegetation interactions requires a new level of interdisciplinary synthesis, as biological and hydrological knowledge needs to be combined to derive the very basis of the model, namely the costs and benefits of different root properties. On the other hand, this approach has the potential to reduce the number of unknowns in a model (e.g. the vertical root distribution), which makes it a valuable alternative to more empirically-based approaches.
H31G-0737
Synergistic use of ENVISAT ASAR Global Mode Soil Moisture Products in the Okavango Delta: Runoff & Wetland Monitoring
The Okavango Delta of northern Botswana is a fast-changing system of canals and floodplains which serves as an important wetland habitat. The area of the wetland is highly dependent on local source of precipitation as well as on external inflow from the upper Okavango River. The Advanced Synthetic Aperture Radar (ASAR) is an active remote sensing instrument onboard ENVISAT platform operating at C-band. The data from the ASAR Global ScanSAR Mode (GM) have amply demonstrated the ability for inland wetland monitoring as well as for near surface soil moisture derivation. The processing chain for ENVISAT derived soil moisture was setup within the ESA Tiger DUE Innovator project SHARE for hydrometeorological applications in the Southern African Development Community (SADC). The ASAR GM provides up to weekly samples of the Okavango delta with 1 km spatial resolution. The extent of the Okavango Delta wetlands is derived from the ENVISAT ASAR GM data applying threshold of absolute backscatter values. The relations of the wetland size, river discharge, and the relative mean soil moisture in the upper Okavango catchment are studied. Correlation above 0.9 can be observed between the relative mean soil moisture and river discharge. High dependence of the wetland extent on the relative mean soil moisture in the upper Okavango is also clearly evident. With this work we demonstrate that the relative soil moisture derived from the ENVISAT ASAR GM data can be clearly related to the river discharge measurements in subtropic environments. Additionally, we show the ability of ENVISAT ASAR Global Mode to monitor dynamics of wetland areas as a response to the relative soil moisture in the upper Okavango catchment. This allows for prediction of the wetland extent up to six months in advance. An incorporation of spatially improved soil moisture and wetland products may improve prediction models for the wetland region. http://www.ipf.tuwien.ac.at/radar/share/
H31G-0738
Evaluation of Alternative Conceptual Models Using Interdisciplinary Information: An Application in Shallow Groundwater Recharge and Discharge
Natural systems are complex, thus extensive data are needed for their characterization. However, data acquisition is expensive; consequently we develop models using sparse, uncertain information. When all uncertainties in the system are considered, the number of alternative conceptual models is large. Traditionally, the development of a conceptual model has relied on subjective professional judgment. Good judgment is based on experience in coordinating and understanding auxiliary information which is correlated to the model but difficult to be quantified into the mathematical model. For example, groundwater recharge and discharge (R&D) processes are known to relate to multiple information sources such as soil type, river and lake location, irrigation patterns and land use. Although hydrologists have been trying to understand and model the interaction between each of these information sources and R&D processes, it is extremely difficult to quantify their correlations using a universal approach due to the complexity of the processes, the spatiotemporal distribution and uncertainty. There is currently no single method capable of estimating R&D rates and patterns for all practical applications. Chamberlin (1890) recommended use of "multiple working hypotheses" (alternative conceptual models) for rapid advancement in understanding of applied and theoretical problems. Therefore, cross analyzing R&D rates and patterns from various estimation methods and related field information will likely be superior to using only a single estimation method. We have developed the Pattern Recognition Utility (PRU), to help GIS users recognize spatial patterns from noisy 2D image. This GIS plug-in utility has been applied to help hydrogeologists establish alternative R&D conceptual models in a more efficient way than conventional methods. The PRU uses numerical methods and image processing algorithms to estimate and visualize shallow R&D patterns and rates. It can provide a fast initial estimate prior to planning labor intensive and time consuming field R&D measurements. Furthermore, the Spatial Pattern 2 Learn (SP2L) was developed to cross analyze results from the PRU with ancillary field information, such as land coverage, soil type, topographic maps and previous estimates. The learning process of SP2L cross examines each initially recognized R&D pattern with the ancillary spatial dataset, and then calculates a quantifiable reliability index for each R&D map using a supervised machine learning technique called decision tree. This JAVA based software package is capable of generating alternative R&D maps if the user decides to apply certain conditions recognized by the learning process. The reliability indices from SP2L will improve the traditionally subjective approach to initiating conceptual models by providing objectively quantifiable conceptual bases for further probabilistic and uncertainty analyses. Both the PRU and SP2L have been designed to be user-friendly and universal utilities for pattern recognition and learning to improve model predictions from sparse measurements by computer-assisted integration of spatially dense geospatial image data and machine learning of model dependencies. http://isda.ncsa.uiuc.edu/download/
H31G-0739
Highly Improved Predictability in the Forecasting of the East Asian Summer Monsoon
The East Asian summer monsoon greatly influences the lives and property of about a quarter of all the people in the world. However, the predictability of the monsoon is very low in comparison with that of Indian summer monsoon because of the complexity of the system which involves both tropical and sub-tropical climates. Previous monsoon prediction models emphasized ocean factors as the primary monsoon forcing. Here we show that pre-season land surface cover is at least as important as ocean indices. A new statistical forecast model of the East Asian summer monsoon using land cover conditions in addition to ocean heat sources doubles the predictability relative to a model using ocean factors alone. This work highlights the, as yet, undocumented importance of seasonal land cover in monsoon prediction and the role of the biosphere in the climate system as a whole. We also detail the physical mechanisms involved in these land surface forcings.
H31G-0740
Influence of Morphology and Permafrost Dynamics on Surface Water - Groundwater Exchange in Arctic Headwater Streams under Present and Enhanced Thaw Conditions
We investigated surface water - groundwater (hyporheic) exchange in two morphologically distinct arctic headwater streams with expanding (thawing) sub-channel permafrost active-layers using solute injection experiments (SIEs) coupled with groundwater flow and particle tracking model simulations. Results of SIEs were used to characterize surface-subsurface water exchange under varying active-layer conditions throughout the 2005 thaw season (May - September). Ground penetrating radar, stream water surface and channel topographic surveys characterized sub-stream active-layer, vertical head, and morphologic conditions. These data were used to parameterize and calibrate the models. Within the context of predicted arctic warming, the models were used to assess the current and potential future ranges of sub-channel permafrost and the influence of those ranges on hyporheic flow paths, residence time distributions, and exchange area of the thawed active-layer (i.e., potential hyporheic zone). Average active-layer thicknesses were consistently at least two-fold greater in the higher-energy, alluvial stream than in the low-energy, peat-lined stream. Alluvial hyporheic exchange was characterized by shorter residence times and longer flow paths that occurred across greater portions of the active-layer. For both reaches, results indicate that morphologic (longitudinal bed topography) and hydraulic conditions (surface and groundwater flow properties) set the potential for hyporheic flow. Forward simulations of deepening sub-channel active-layers, as predicted under a warming arctic climate, only influence hyporheic exchange until a threshold depth is achieved. This depth is primarily determined by the hydraulic head gradients imposed by the dominant morphology of the stream. Therefore, hyporheic exchange extent in arctic streams is likely to be independent of greater active-layer depths.
H31G-0741
Long term adjustment of canopy root depth and strength: Implications catchment hydrology and slope stability
The species composition of southern Appalachian forests is changing rapidly due to fire suppression, residential expansion and introduced parasites, such as the woody adelgid. Changes in the distribution and age of tree and understory species cause changes in rooting characteristics and therefore the stability of slopes. Roots increase soil cohesive strength and fail in tension during debris flows. The amount of root reinforcement to the soil mass is dependent on the number, size and tensile strength of the roots. We have characterized how changes in the composition of southern Appalachian forests, particularly the expansion of Rhododenron maximum due to fire suppression, may affect the potential for slope failure. We measured the vertical distribution and tensile strength of roots for fifteen individual trees and two mixed species locations in the Coweeta Hydrological Laboratory, North Carolina. The individual pits were chosen to capture variations in species (10 species total), topographic position (nose, side slope, hollow), and age (a range of DBH between 5 cm and 60 cm). Root tensile strengths from different hardwood species were very similar, while rhododendron, a woody shrub, has considerably weaker roots. Roots are concentrated close to the soil surface (at least 70% of biomass occurs within 50 cm of the surface) and variations in this pattern occur primarily as a function of age. R. maximum roots are shallower and weaker than tree roots, which when coupled with low transpiration rates, lowers the total cohesive strength and makes them susceptible to high pore pressure events. We have investigated the potential for mapping R. maximum based on the ratio of near-infrared to red within leaf-off color infrared images. When we combine the remotely-sensed distribution of R. maximum with the root cohesion data from individual pits, we can produce a realistic spatial distribution of root cohesion for southern Appalachian forests. The spatial distribution of root cohesion can be coupled with an eco-hydrological model (we use the Regional Hydro-Ecologic Simulation System (RHESSys)) to understand how coupled changes between hydrology and ecology affect the slope stability of southern Appalachian forests.
H31G-0742
Simulation of Nutrient Transport in Streams During High Flows
The occurrence of high flows in watersheds requires models that link solute transport processes with hydraulics of flooded stream cross sections. For instance, nutrient export occurs predominantly during high flows. Important mechanisms include the retention caused by exchange with flood plains, stagnant water in the stream channel and retention in the hyporheic zone. The investigation uses a 1-dimensional network model and parameterizes the result in a form appropriate for nutrient in a compartment model that has been developed for Swedish conditions during decades. The compartment model is a (kinetic) mass-balance model that accounts for a large set of processes, while the stream network model uses the 1-dimensional advection-dispersion equation with transient storage and lateral inflow. The distribution of stream segment within the network is described through the width function, which reflects the frequency distribution of flow distances within the network. The ability to describe these processes in a physically based manner has provided a tool to improve predictability of the nutrient status of watershed and the possibility to trace and explain the problems behind e.g. eutrophication.
H31G-0743
Responses of Emergent Behaviour in Headwater Catchments to Long-term and Short-term Environmental Change
Emergent behaviour of hydrological processes at the catchment scale often results in relatively simple and predictable functional characteristics which are underpinned by heterogeneous, complex processes at the small scale. It is unclear how such small-scale processes are affected by long- and short-term perturbations in forcing factors affected by various environmental changes. This leads to uncertainty in how emergent behaviour will change and how hydrology and hydrochemistry will respond at the catchment scale. A powerful resource in improving predictions of such responses is applying advanced statistical analysis to long-term data sets of conservative tracers, particularly in gauged catchments that are subject to marked environmental change. Changes in tracer behaviour can provide an integrated insight into the emergent response of system functioning and its non-linear characteristics. In this paper, we present the analysis of long-term tracer data collected since 1982 in 2 small (ca. 1km2) experimental catchments in the Scottish highlands. These have been affected by marked change and variability in driving variables of climate, land cover and rainfall chemistry: Annual rainfall ranged between 1490 and 2500mm and an average 1°C increase in air temperatures was observed over the monitoring period. In addition, forestry operations resulted in 70% of each catchment being clear felled. Finally, air pollution legislation targeting acid emissions has improved the quality of precipitation, resulting in a marked reduction in acid deposition. Long-term (20 year, weekly) time-series analyses of two tracers are used to assess changes in emergent catchment behaviour. Chloride input-output time series are analysed using a range of residence time models which highlighted non-stationarity in the catchment mean residence times (which ranged between 2-11 months for individual years) and corresponding residence time distributions. At the catchments scale these were driven mainly by climatic variability and little altered by forestry. The acid neutralising capacity (ANC) of stream waters was also used to examine how the composition and contribution of different hydrological sources changed over the study period in response to reduced climatic variability, forestry and acid deposition. Non-linear curve fitting methods allowed the temporal changes in concentration-discharge relationships to be sufficiently well described to facilitate chemically-based hydrograph separation. This allowed temporal differences in catchment-scale hydrological source contributions (specifically groundwater) to be related, mainly to climatic variability. Impacts of forestry operations were stochastic and depended on the prevailing climatic conditions.
H31G-0744
Precipitation Relationships between the Great Plains, U.S. Southwest, and Mexican Monsoons
While considerable research has documented the Mexican monsoons and their influence on the U.S. Southwest, not much has been done to date to investigate possible connections between these two monsoons and the U.S. Great Plains. Previous research has suggested an out-of-phase relationship between the decay of significant moisture in the Great Plains and the onset of the Mexican monsoons. However, the focus is mainly on the Low Level Jet patterns and is limited to 1979-91. Using data from 1979-2005, our focus is on determining (a) if there is a predictable relationship between the amount of precipitation each spring in the Great Plains and the amount in the Southwest the following summer, (b) if one Mexican monsoon is more important in determining the relationship, and (c) if cold season snow cover patterns will aid in predicting warm season precipitation in the Great Plains and Southwest. Previous research was used to determine the specific regions of interest for the Great Plains and U.S. Southwest, based on correlation values made using the 1979-91 results. We then constructed time series for both regions for precipitation. The seasonal cycle and variability on time scales less than one year are removed from these time series to examine year-to-year anomalies. Contour plots of correlation values between snow cover and each region are made to determine highly correlated areas. The data hint that the amount of precipitation for May in the Great Plains and for July in the Southwest from 1979-91 is positively correlated. This amount is then negatively correlated and shifted to June in the Great Plains and August in the Southwest for 1992-2005. A strong negative correlation, within the 95% CI, is found between snow cover and the Southwest for 1979-91; however, for 1992-2005, there is a strong positive correlation between the two regions. The highly correlated regions of snow cover to each region shifts from 1979-91 to 1992-2005, with intriguing suggestions of a relationship between March snow cover in the central and southern Great Plains and summertime precipitation in the Southwest during the latter period. These results could be indicative of changes taking place in the global circulation between these two time periods.
H31G-0745
Ecohydrological Fingerprinting of Land-Falling Hurricanes in the Southeastern United States - Eloise as a Prototype
Hurricanes and tropical storms (collectively known as tropical cyclones, hereafter referred to as TCs) are regular events of varying magnitude (category dependent) and moderate frequency (years-1) that provide a significant influx of freshwater resources to surface and subsurface reservoirs in the warm season. Beyond the popular association with disasters, hurricanes and tropical storms with varying degrees of intensity, structural organization, and terrestrial tracks are an essential element of the hydroclimatic regime of vast regions of the planet, including the Asian Monsoon Region, the Caribbean, and, of particular interest to our project, the eastern and southern United States. Whereas a historical data base of hurricane and tropical cyclone tracks already exists [http://maps.csc.noaa.gov/hurricanes/index.htm], systematic forensic studies to inventory and quantify landform and land-use (LU) and land-cover (LC) changes along the path of land-falling storms have yet to be conducted but for isolated place-based assessments. The objective of our research is to develop a framework to systematize a comprehensive analysis of satellite data both historical and more recent, including Landsat (TM and ETM+), AVHRR, SSMI, ASTER, SPOT and MODIS leading to the characterization of continental-scale changes of terrestrial land-use and land-cover along the tracks of land-falling hurricanes and tropical cyclones. We are interested in detecting changes caused by individual storms, and in characterizing the time-rates and strategies of landscape recovery toward ecohydrological fingerprinting of LULC change. To this end, we present first results for the historical analysis of Hurricane Eloise (13-24 September, 1975), which caused 76 deaths and $2.1 billion in damage. We build on these results to develop a framework for assessing the integrated impact of extreme events on the regional water cycle.
H31G-0746
A distributed hydrological model for drought and flood forecast in the upper Yangtze River basin
The Yangzte River (also called Changjiang in Chinese) is the largest river basin in China, which has frequent flood and drought. Building on the physically-based description of hydrological processes, a distributed model has been established in the upper Yangtze River for drought and flood forecast have been addressed in this study. For assessing water resources and drought, a large scale distributed hydrological model has been chosen for the upper Yangtze River which has about 1 million km2 area. In this model, the whole area is divided into a discrete grid system of 10km size, and each grid is represented by a number of geometrically-symmetrical hillslopes. Hydrological simulation has been carried out during 1961~2000, the simulated river discharges, soil moisture and evapotranspiration provided an inside investigation into water resources in the study basin. Results showed that the ratio of seasonal runoff to annual one has a significant increasing trend in summer in the eastern Sichuan basin and the Three Gorges region in the 1990s, but a decreasing trend in autumn. This implies an increasing flood risk in summer and water shortage in autumn. Based on the results of hydrological simulation, a new monthly drought index, GBHM-PDSI, was proposed based on the Palmer Drought Severity Index. It was found that the new drought index has advantages for describing the temporal change of drought severity and the spatial variation. In order to reduce the uncertainties of real time flood forecast in the Three Gorges region, the radar rainfall data has been used together with the smaller scale (1km grid size) distributed hydrological model. Results showed, by means of distributed model combining with radar rainfall data, it could capture adequately the spatial variation of rainstorm, and provide better flood forecast at real time.
H31G-0747
Synergies Between Changes in Climate, Land Cover/Use, and Streamflow Regulation, in the Mekong River Basin
How a changing climate will interact synergetically with land cover and use change and streamflow regulation to impact the hydrologic regime of a particular river basin is an open research question with important implications for society's adaptation and planning. We take the case of the Mekong, the largest river basin in Southeast Asia (circa 800,000 km2) and evaluate its combined response to these three pressures. We use the Variable Infiltration Capacity macro-scale hydrologic model, which explicitly accounts for differences in land cover, coupled with a model of reservoir operation, to simulate streamflows under scenarios of land cover/use and climate change. The changed climate is represented by perturbing the historical climatology according to the results of an ensemble of global climate models. Our results reveal important synergetic relationships between all three pressures, and major differences in response between seasons. For example, where both the precipitation and temperature are expected to rise, the simulated streamflow response of a subbasin may be an increase or a decrease, depending on the subbasin's average seasonal temperature (colder subbasins being generally more sensitive to temperature rises), and depending on the degree of conversion of forest to agriculture. While reservoir operation is a dominant pressure during the dry season, it is dependent to considerable degree on the changes in incoming streamflow determined by land cover/use and climate changes.
H31G-0748
A Scalable Water Balance Model Within the Russian River, California, Basin
The availability of long term hydrologic data sets provides opportunities for quantifying hydrologic variability and examining evidence for changing conditions following land surface alterations and climate change. The Russian River basin in California is typical of many watersheds on the fringe of expanding metropolitan regions with competing demands for water from municipal, agricultural, recreational, and environmental constituencies. The Russian River basin is convenient for analysis because there is limited water imported and exported. One of the major challenges faced by water resources engineers within this basin is to understand the conditions necessary for the restoration of salmon and steelhead trout that have life cycles dependent upon migrations between the upper reaches of the watershed and the Pacific Ocean. The amount, timing and duration of surface water flows are frequently cited as some of the key factors controlling fishery health and recovery. The Russian River basin has numerous long-term data sets on flow, precipitation and water quality measures that have been gathered into a data cube for analysis and synthesis. Results to date have focused on comparing annual water balances for sub-watersheds that span over an order of magnitude in area. The data reveal a simple scalable relationship that annual runoff depth equals annual precipitation minus approximately 450 mm of water. This 450 mm of annual water demand represents a basin-wide integration of soil and groundwater dynamics and transpiration by vegetation. There is little evidence of human alteration of this relationship over a 60 year record. This scalable relationship is used to investigate how runoff from the basin would respond to changes in annual precipitation.
H31G-0749
Ecohydrologic Response of Vegetation Patterns to Climate Variability in Arid and Semi-arid Ecosystems.
In arid and semi-arid regions, the interaction and feedbacks between climate, soils, vegetation and topography gives rise to the emergence of distinct patterns of vegetation and surface water re-distribution. These patterns are associated with a spatially variable infiltration field characterized by low infiltration rates in the bare soil areas and high infiltration rates in the vegetated areas (that have improved soil aggregation and macroporosity). Here we use a modeling framework that couples evolving landforms, dynamic vegetation and hydrology to explore the dynamics of these patterns at the hillslope-scale. We analyze the spatial and temporal dynamics of soil moisture, runoff and erosion that is driven by the spatially variable infiltration rates associated with those patterns. We also analyze the effect of interannual rainfall fluctuations on the soil water balance, on the dynamics and temporal variability of the vegetation patterns, and on the hydrologic response of the hillslope. We run the model with different parameter choices to simulate the dynamics of grasses, shrubs, and coexisting grasses and shrubs for long term climate fluctuations. Our results show that the coexistence of grasses and shrubs in these patterns increases long term biomass production as compared to the results for the individual plant types, suggesting that the observed self-organized patterns maximize water use and biomass production. We further discuss the consequences for long term erosion and equilibrium profiles.
H31G-0750
The Influence of Woodland Encroachment on Runoff and Erosion in Sagebrush Steppe Systems, Great Basin, USA.
Pinyon and juniper woodlands have expanded 10 to 30% in the past 30 years and now occupy nearly 20 million hectares of sagebrush shrub steppe in the Great Basin Region and Colorado Plateau, USA. The conversion of sagebrush steppe to pinyon and juniper woodlands has been linked to changes in plant community structure and composition and respective increases in overland flow and erosion from these landscapes. The Sagebrush Steppe Treatment Evaluation Project (SageSTEP, www.sagestep.org) was implemented in 2005 as a 5 year interdisciplinary research study to evaluate restoration methodologies for sagebrush rangelands degraded by woodland and grassland encroachment over a six state area within the Great Basin. The hydrology component of SageSTEP focuses on the relationships between changes in vegetation and groundcover and runoff/erosion processes. In 2006, 140 small scale (0.5 m2) rainfall simulations were conducted at 2 locations within the Great Basin to determine whether critical thresholds exist in vegetation and ground cover that significantly influence infiltration, runoff, and erosion in pinyon and juniper woodlands. Simulation plots were distributed on interspaces (areas between shrub/tree canopies) and juniper, pinyon, and shrub coppices (areas underneath canopy). Water drop penetration times and litter depths were also collected for each plot to explore controls on soil hydrophobicity. Preliminary results suggest a positive correlation between litter depth and hydrophobicity, as soils under thick pinyon and juniper coppices are strongly water repellant and soils in interspaces and under shrub coppices are easily wettable. Interspace plots with varying amounts of grasses and forbs have the highest erosion and runoff rates due to higher percentages of bare ground and relatively low soil stability. Pinyon coppices have the least runoff and erosion due to very high litter depths and low bare ground cover, even though surface soils are hydrophobic. Juniper and shrub coppice plots produce a similar amount of sediment, but juniper coppices produce significantly more runoff. Lower sediment concentrations from juniper coppice plots are attributed to higher litter depths, higher surface soil stability, and a lower percent of bare ground, while high runoff rates are attributed to higher soil surface water repellency. Results suggest that runoff and erosion from woodland encroachment sites are highly influenced by the amount of ground cover and strength of water repellency. http://www.sagestep.org
H31G-0751
Impact of Land-use Change on Soil Erosion and Hydrologic Response at Regional Scale: Application of a Coupled Erosion and Hydrologic Modeling Scheme
Large-scale land-use change will impact regional hydrologic responses, and seasonal soil frost adds its effect to the complexity. Increases in soil erosion potential related to cold season processes at scales larger than a hillslope or field is a concern for scientific decision support and resources management. Numerous watershed models capable of predicting soil erosion have been developed in the past, but they are often limited by their inappropriate representations of the hydrologic processes involved. The process-based Water Erosion Prediction Project (WEPP) model has the ability to predict spatial and temporal distribution of soil loss at the field scale, but its winter hydrology routines still need improvement. The recent development of a stand-alone version of the WEPP hillslope erosion code is coupled with the Variable Infiltration Capacity (VIC) large-scale hydrology model, which is capable of representing cold season processes for long-term, large-scale watersheds simulations. The coupled model system uses VIC model simulations of hydrologic variables as an input to the erosion model to develop predictions of soil erosion potential. Coupled model system point simulations produce very similar results to those from the full WEPP model for a series of sampled hillslopes. The coupled model system is then applied to watersheds in Minnesota, Wisconsin and Michigan to simulate the impact of land-use change from pre-settlement to modern conditions on hydrologic responses and soil erosion potential. The study thus demonstrates an improved ability to predict and analyze regional hydrologic responses and erosion potentials due to land-use change for large-scale applications.
H31G-0752
Investigation of the Impacts of Spatial Variability of Soil Moisture on Convective Precipitation in the Central Plains
Altering the spatial and temporal variability of soil moisture and vegetative cover can potentially lead to significant impacts on local weather and climate through feedbacks in surface energy balance partitioning, water dynamics, and precipitation. In order to examine the impacts of spatial heterogeneity of soil moisture on convective precipitation, a suite of 15 simulations were conducted using the Advanced Regional Prediction System (ARPS) mesoscale model with resolutions ranging from 1 km to 16 km. Model spin-up induces spatial variance in soil moisture via topographic redistribution. Following spin-up, we are able to examine how initial soil moisture and the associated spatial variance impact the surface energy balance and resulting feedbacks on convective precipitation as a function of spatial scale and downwind distance. To investigate these responses as a function of mean soil moisture, initial soil moisture conditions were varied from wilting point to field capacity for each resolution. Implications for the impact on local land-atmosphere interactions resulting from anthropogenic changes to land-surface cover and moisture availability via agricultural practices and irrigation will be discussed.
H31G-0753
Extreme Rainfall Frequency Analysis in a Changing Climate Pattern in South Korea
It is now widely acknowledged that climate variability modulates the frequency of extreme hydrologic events. Traditional methodologies for hydrologic frequency analysis are not devised to account for variation in the exogenous teleconnections. We use Hierarchical Bayesian Analysis to consider the exogenous factors that can influence on the frequency of hydrologic extreme events. The sea surface temperatures (SST), the ensemble of rainfall predictions by GCM, in addition to the typhoon attributes were found to have direct correlation with extreme rainfall events and were used as inputs to nonstationary frequency model. The parameters of the model are estimated using a Markov Chain Monte Carlo (MCMC) algorithm. The predictors are compared in terms of the resulting posterior distributions of the parameters associated with estimated frequency distributions. Major Rainfall stations throughout Korea are considered in this analysis