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Notes: : Several crop water stress indices were examined to determine their potential for use from a space-based system. These indices were compared using data collected over a wheat crop grown under arid environmental conditions. Indices that required concurrent ground-based measurements were less adaptable than the simple difference between canopy temperatures of a field with unknown stress conditions and a similar crop known to be unstressed. The results indicate that it would be feasible to develop space-based crop water stress techniques that would be useful for scheduling irrigations.

Notes: : The Linacre (1988) model for calculating evaporation from open water or well-watered surfaces only requires inputs of air temperature, latitude and elevation, and windspeed if it is available. The model was developed using data collected at a large number of sites in different climatic regions of the world, while independent tests of the model have shown it to be suitable for estimating evaporation in a variety of locations. This study was intended to contribute to the broad goal of evaluating temperature-based evaporation models for use in California by testing the Linacre model in the agriculturally intensive Central Valley. Observed monthly mean reference evaporation (Eo) and meteorological data for periods ranging up to 72 months were obtained from 25 California Irrigation and Management Information System (CIMIS) stations distributed throughout the Central Valley. Uncalibrated and calibrated Linacre models were used to estimate monthly mean reference evaporation, and the performance of each model was evaluated using indices that quantified the random and systematic errors and overall model performance. The accuracy of the radiation and ventilation components of the model were evaluated separately. The uncalibrated model was found to systematically overestimate Eo with most of the model error being attributed to the ventilation component. Calibration of the radiation and ventilation components removed most of the systematic model errors, and the root mean square error for monthly mean Eo was 0.676 mm day−1 (16.8 percent of the mean observed value). (KEY TERMS: reference evaporation; Linacre model; irrigation scheduling.)

Notes: : A canopy reflectance model is incorporated into a routine for simulating water and energy flows in the soil-plant-atmosphere system. The reflectance model is structured tocalculate canopy albedo throughout each simulation period and to determine spectral reflectances at a specified time during the day. Spectral vegetation indices are then calculated from the reflectances and related to the evapotranspiration and thermal response of the canopy. The canopy reflectance model is also used to establish the photo-sytheticaily active radiation load at various depths in the canopy. Stomatal resistances are calculated using these radiation values and integrated to give the minimum canopy resistance. Actual canopy resistance is obtained by adjusting minimum canopy resistance for environmental stresses such as leaf water potential and leaf temperature. Using data for a soybean canopy, canopy evapotranspiration and temperatures are simulated for a range of leaf area index values and compared with the corresponding spectral vegetation indices. The resuits indicate that the normalized difference spectral index has an inverse linear relationship with canopy temperature, concurring with results obtained from satellite observations. The possibility of using a spectral vegetation index and thermal observations together to parameterize surface moisture availability for evapotranspiration is considered.

Notes: : Distributed hydrologic models which link seasonal streamflow and soil moisture patterns with spatial patterns of vegetation are important tools for understanding the sensitivity of Mediterranean type ecosystems to future climate and land use change. RHESSys (Regional Hydro-Ecologic Simulation System) is a coupled spatially distributed hydroecological model that is designed to be able to represent these feedbacks between hydrologic and vegetation carbon and nutrient cycling processes. However, RHESSys has not previously been applied to semiarid shrubland watersheds. In this study, the hydrologic submodel of RHESSys is evaluated by comparing model predictions of monthly and annual streamflow to stream gage data and by comparing RHESSys behavior to that of another hydrologic model of similar complexity, MIKESHE, for a 34 km2 watershed near Santa Barbara, California. In model intercomparison, the differences in predictions of temporal patterns in streamflow, sensitivity of model predictions to calibration parameters and landscape representation, and differences in model estimates of soil moisture patterns are explored. Results from this study show that both models adequately predict seasonal patterns of streamflow response relative to observed data, but differ significantly in terms of estimates of soil moisture patterns and sensitivity of those patterns to the scale of landscape tessellation used to derive spatially distributed elements. This sensitivity has implications for implementing RHESSys as a tool to investigate interactions between hydrology and ecosystem processes.

Notes: Net CO2 flux measurements conducted during the summer and winter of 1994–96 were scaled in space and time to provide estimates of net CO2 exchange during the 1995–96 (9 May 1995–8 May 1996) annual cycle for the Kuparuk River Basin, a 9200 km2 watershed located in NE Alaska. Net CO2 flux was measured using dynamic chambers and eddy covariance in moist-acidic, nonacidic, wet-sedge, and shrub tundra, which comprise 95% of the terrestrial landscape of the Kuparuk Basin. CO2 flux data were used as input to multivariate models that calculated instantaneous and daily rates of gross primary production (GPP) and whole-ecosystem respiration (R) as a function of meteorology and ecosystem development. Net CO2 flux was scaled up to the Kuparuk Basin using a geographical information system (GIS) consisting of a vegetation map, digital terrain map, dynamic temperature and radiation fields, and the models of GPP and R.Basin-wide estimates of net CO2 exchange for the summer growing season (9 May−5 September 1995) indicate that nonacidic tundra was a net sink of −31.7 ± 21.3 GgC (1 Gg = 109 g), while shrub tundra lost 32.5 ± 6.3 GgC to the atmosphere (negative values denote net ecosystem CO2 uptake). Acidic and wet sedge tundra were in balance, and when integrated for the entire Kuparuk River Basin (including aquatic surfaces), whole basin summer net CO2 exchange was estimated to be in balance (−0.9 ± 50.3 GgC). Autumn to winter (6 September 1995–8 May 1996) estimates of net CO2 flux indicate that acidic, nonacidic, and shrub tundra landforms were all large sources of CO2 to the atmosphere (75.5 ± 8.3, 96.4 ± 11.4, and 43.3 ± 4.7 GgC for acidic, nonacidic, and shrub tundra, respectively). CO2 loss from wet sedge surfaces was not substantially different from zero, but the large losses from the other terrestrial landforms resulted in a whole basin net CO2 loss of 217.2 ± 24.1 GgC during the 1995–96 cold season. When integrated for the 1995–96 annual cycle, acidic (66.4 + 25.25 GgC), nonacidic (64.7 ± 29.2 GgC), and shrub tundra (75.8 ± 8.4 GgC) were substantial net sources of CO2 to the atmosphere, while wet sedge tundra was in balance (0.4 + 0.8 GgC). The Kuparuk River Basin as a whole was estimated to be a net CO2 source of 218.1 ± 60.6 GgC over the 1995–96 annual cycle. Compared to direct measurements of regional net CO2 flux obtained from aircraft-based eddy covariance, the scaling procedure provided realistic estimates of CO2 exchange during the summer growing season. Although winter estimates could not be assessed directly using aircraft measurements of net CO2 exchange, the estimates reported here are comparable to measured values reported in the literature. Thus, we have high confidence in the summer estimates of net CO2 exchange and reasonable confidence in the winter net CO2 flux estimates for terrestrial landforms of the Kuparuk river basin. Although there is larger uncertainty in the aquatic estimates, the small surface area of aquatic surfaces in the Kuparuk river basin (≈ 5%) presumably reduces the potential for this uncertainty to result in large errors in basin-wide CO2 flux estimates.

Notes: The spatial and temporal patterns in CO2 flux for the Kuparuk River Basin, a 9200-km2 watershed located in NE Alaska were estimated using the Regional Arctic CO2 Exchange Simulator (RACES) for the 1994–1995 growing seasons. RACES uses non-linear models and a Geographical Information System database (GIS) consisting of the normalized difference vegetation index (NDVI) and dynamic temperature and radiation maps. The spatial and temporal patterns in the NDVI during both growing seasons suggest that ecosystem development occurred 2–4 weeks earlier and was relatively more rapid in the southern portion of the Kuparuk River Basin. Rates of gross primary production (GPP) and whole-ecosystem respiration (R) were 2–4 fold higher in the southern basin than along the arctic coastal plain depending on time of year. The higher rate of GPP estimated for the southern basin was primarily due to higher NDVI values, while the higher R estimated for the southern basin was due in part to higher temperature and the NDVI. While GPP and R showed strong latitudinal trends, spatial and temporal trends in net ecosystem CO2 exchange (NEE) were much more variable. Thus, while spatial trends in carbon gain (GPP) and loss (R) were highly correlated, small spatial and temporal differences in these large fluxes (GPP and/or R) lead to corresponding large spatial variations in the NEE.

Notes: : Average daily values of the Priestley-Taylor coefficient (a) were calculated for two eddy covariance (flux) tower sites with contrasting vegetation, soil moisture, and temperature characteristics on the North Slope of Alaska over the 1994 and 1995 growing seasons. Because variations in a have been shown to be associated with changes in vegetation, soil moisture, and meteorological conditions in Arctic ecosystems, we hypothesized that a values would be significantly different between sites. Since variations in the normalized difference vegetation index (NDVI) follow patterns of vegetation community composition and state that are largely controlled by moisture and temperature gradients on the North Slope of Alaska, we hypothesized that temporal variations in a respond to these same conditions and thus co-vary with NDVI. Significant differences in a values were found between the two sites in 1994 under average precipitation conditions. However, in 1995, when precipitation conditions were above average, no significant difference was found. Overall, the variations in a over the two growing seasons showed little relationship to the seasonal progression of the regional NDVI. The only significant relationship was found at the drier, upland study site.