B14A-01 INVITED 16:00h
Impact of Recent Land Use Changes in the Great Plains
During the last fifty years there has been substantial changes in agricultural land use practices and loss of agricultural land due to urbanization in the Great Plains. The major changes in land use include expansion of irrigated agriculture during the 1960's and 1970's, changes in dryland tillage practices, use of improved crop varieties, and increases in the amount of fertilizer applied to both dryland and irrigated crops. Selected regions like the Front Range of Colorado have experienced large population growth and a resulting decrease in agricultural land area and increased irrigated lawn area. The Daycent ecosystem model was used to simulate the impact of these land use changes on total system carbon and trace gas fluxes. We will highlight recent model results for the urban and rural regions in Eastern Colorado. Model results suggest that adding 4 million ha of irrigated land since the 1960's has resulted in a net carbon storage of 0.43 Tg C and a dramatic increase( 3 to 4 times higher compared to dryland agriculture ) in N2O soil emissions. Conversion agricultural land to urban lawns ( > 40000. Ha ) since the 1950's has resulted in a significant storage of carbon in the soil and a dramatic increase in NO3 leaching and N2O soil emissions ( 3 to 10 times higher compared to natural grasslands and dryland agriculture ). Results for the simulated historical changes in the net green house budgets for selected counties in Colorado will also be presented.
B14A-02 INVITED 16:18h
Land use/cover changes at local to regional scales that affect dynamics of hydrology and climate across the Upper Great Lakes States
The pace and pervasiveness of anthropogenic modification of ecosystems has been dramatic since industrialization. During this period, essentially all of the earth's ecosystems have been influenced at some level by human activity. One of the most significant changes to ecosystems has resulted from changes in the use of the land. Deforestation, urbanization, and agricultural extensification are global phenomena which effect hydrological dynamics, net primary production, fiber and food production and by many accounts, regional and global climate change. Unfortunately, little is known about the spatial and temporal nature of these land use changes and what continued alterations of land use may look like. Our presentation will review an analysis of a variety of spatially explicit land use databases collected across the Upper Great Lake States of the US representing change over the last 150 years. We will examine spatial (e.g., patch sizes, fragmentation) and temporal characteristics (e.g., percent change, total change per decade) of change for major categories of land use. This information, combined with MODIS and other remote sensing products, will then be related to land surface properties for the Upper Great Lake States region. We conclude with a brief summary of implications of land use model forecasts to 2050 for hydrologic and climate dynamics in this region.
B14A-03 INVITED 16:36h
Ecosystem Water Use Varies With Disturbance And Stand Age
Many functions of an ecosystem are strongly controlled by water. Compared to ecosystem carbon exchange, the dynamics and controls of ecosystem water balance have received relatively less attention. Yet, these two fluxes are tightly interdependent, with water availability having a direct effect on the carbon budget. Using direct measurements (eddy flux towers) of net ecosystem exchange (NEE) of water and carbon from over 12 different ecosystem types in the Pacific Northwest and the Upper Great Lakes Region, we examined the magnitude and rate of change in ecosystem water use (WUe, defined as the mass ratio of NEE of carbon to NEE of water). We constructed empirical relationships for estimating WUe that incorporate disturbance and stand age, as well as the biophysical regulations such as vapor pressure deficit (VPD), solar radiation, and soil moisture conditions. WUe varied little throughout the growing season (June through September) in both regions, but there were notable differences in WUe with stand age. In northern Wisconsin, WUe was higher in mature stands (4.5 $\mu$g C.g$^-1$ H$_{2}$O) than in the younger, recently disturbed stands (2.1 $\mu$g C.g$^-1$ H$_{2}$O); yet WUe was much higher in 20 and 40 year-old stands (0.34-5.57) than in a 450-year-old stand (0.38-1.59) in the Pacific Northwest. The lowest WUe was found in a recent clearcut, where leaf area index was also the lowest. VPD is found to be a significant predictor of WUe in many ecosystems. Given the broad network of eddy flux towers currently collecting NEE data across the United States (e.g., Fluxnet), we expect that in the future we will be able to make further generalizations about WUe in ecosystems of different ages and under various disturbance regimes.
B14A-04 INVITED 16:54h
Retrieval of Crop Biophysical Characteristics from Remotely Sensed Data
In this paper we discuss some techniques to remotely assess the fraction of photosynthetically active radiation absorbed by green vegetation [fAPAR-GREEN=fAPAR*(green LAI/total LAI)], fractional green vegetation cover (FGVC), green leaf area index (GLAI) and green leaf biomass (GLB) in crops. fAPAR-GREEN is one of the main players used in the formulation of production efficiency models. FGVC is used in radiative transfer models to compute fAPAR, and is also required for calculating sensible heat fluxes. GLAI pertains to the ratio of green leaf surface area to ground surface area. Both GLAI and GLB are directly related to the photosynthetic apparatus of the vegetation. While all these biophysical characteristics are interrelated, different techniques are required to estimate them remotely. We suggest to use the green NDVI (with near infra-red, NIR, and green, around 550 nm) and the red-edge NDVI (with NIR and a band around 700 nm) to estimate fAPAR-GREEN in soybean and maize. For estimating FGVC, we suggest the Visible Atmospherically Resistant Index (VARI). VARI uses only visible (the blue, red and either the green or the red edge) spectral bands. The index showed linear relationship with FGVC in wheat, maize and soybean providing the estimation of FGVC with an error of less than 10%. To estimate GLAI and green leaf biomass, we developed a technique that uses reflectances in two spectral channels: NIR and either the green around 550 nm, or in the red-edge near 700 nm. The technique was tested in agricultural fields under irrigated and rainfed maize and soybean, and proved suitable for an accurate estimation of GLAI and GLB in both crops.
B14A-05 17:12h
Satellite-based mapping of paddy rice agriculture in Asia
Paddy rice fields are distributed throughout the Asia and serve as a main food source for billions of people in Asia. One unique feature of paddy rice fields is that they have a layer of surface water to cover soils, and consequently it acts as a major source of methane emissions and plays an important role in global atmospheric methane budget. Flooding (irrigation) of paddy rice fields consumes large amounts of water. Intermittent drainage of paddy rice fields is widely practiced by farmers as a way for enhancing plant growth and increasing rice crop yield. Changes in spatial distribution of paddy rice fields and temporal management of water (flooding/drainage) in paddy rice fields are likely to have significant impacts on food production and trace gases emissions. Here we present an effort to develop novel approaches for identifying and mapping paddy rice fields in Asia. The 8-day composites of MODIS in 2002 and ancillary data are used in geospatial data analysis. Our objective is to generate geospatial database of paddy rice fields at 500-m spatial resolution for Asia, including the spatial distribution of paddy rice fields, timing of transplanting and harvesting, and water management (flooding and drainage). The resultant geospatial database is likely to serve many applications, including the carbon cycle, trace gases emissions, and water management.
B14A-06 17:27h
Land Cover Change Effects on Hydrological and Biogeochemical Functions in the Mekong River Basin: Insights From Macro-Scale Hydrologic and Biogeochemical Models.
Concerns with the high rates of deforestation in the tropics include the possible impacts on species diversity, hydrologic response, biogeochemical cycles and water quality, topsoil erosion, atmosphere chemistry, and land surface-atmosphere interactions affecting climate. Our work is concerned with hydrologic response and stream biogeochemistry under the monsoonal climate of Southeast Asia. How are the different components of the terrestrial hydrological cycle affected by changes in land cover, such as conversion of forest to agricultural land? Field observations have confirmed local hydrologic effects; but how do localized changes in land cover affect the streamflow at a distance downstream? How does land cover affect the flow response to rainstorms? How does it affect dry season flows? What are the main implications for stream biogeochemistry? Finally, how might each of these effects turn out under altered climate conditions, such as higher average temperature and modified precipitation patterns? We apply the macro-scale Variable Infiltration Capacity (VIC) model to the Mekong basin (795,000 sq.km) in Southeast Asia at a resolution of 5 arc-minutes (roughly, 9 km), using climate forcing from 1979-2004, long-term stream-flow records, historical land cover, and hypothetical land cover and climate scenarios. We consider not only the replacement of forest cover with permanent agriculture, but also the often prevalent but little studied deforestation for swidden cultivation, succeeded by secondary regrowth. Field studies and a simple model attempt to capture effects on stream biogeochemistry. While soil-vegetation-atmosphere transfer schemes (SVATS) have recently been incorporated into GCMs, use of such models to study the impacts on the hydrologic response of river basins has been limited, particularly in the humid tropics.
B14A-07 17:42h
Challenges in Estimating Global Tropical Deforestation in the 1980s and 1990s
Estimates of carbon emissions from tropical deforestation over the last two decades are highly uncertain due to disagreement in the amount of deforestation and ambiguity in the fate of cleared land. Recent estimates of deforestation vary by more than 50% due in part to differences in domain, forest baselines, methods, and definitions. Further, these satellite and census-based estimates often capture only net changes, and therefore underestimate both deforestation and forest regrowth. Decadal snapshots and coarse spatial resolution likely mask the dynamic patterns of forest regrowth and clearing that typically follow deforestation. Changes in tropical forest area may need to be assessed every 2-3 years to reduce uncertainty in the rate of deforestation and associated carbon fluxes. We are reconciling estimates of global tropical deforestation and producing an improved estimate by triangulating coarse-resolution satellite and census data. In particular, we are comparing estimates based on the 8km AVHRR Percent Tree Cover record, TREES project, Landsat Pathfinder data, and FAO country statistics and Landsat analysis. We are also synthesizing locally available information to infer the dynamics of land cover transitions following deforestation. Specifically, regional Markov models describing annual transition probabilities are being constructed from a synthesis of case-studies and high-resolution remote sensing data. These transition probabilities can be used to infer the dynamics and rates of deforestation and regrowth and to model the full-suite of land transformations following deforestation. Ultimately, we will superimpose the Markov transition rates on the satellite-based snapshots to create a globally consistent, spatially explicit product of annual changes in tropical forest cover over the last two decades.