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Spatial and Temporal Variation of Energy and Carbon Fluxes in Central Iowa

^a National Soil Tilth Lab,, 2150 Pammel Drive, Ames, IA 50011
^b Hyrdology and Remote Sensing Lab., Beltsville, MD 20705

^* Corresponding author (hatfield{at}nstl.gov)

Received for publication April 25, 2005.

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Energy balance and CO₂ exchange of agricultural crops has been investigated through limited field studies because of the expense of the monitoring equipment and availability of fields to place equipment. Quantifying the spatial and temporal variation in the energy balance and CO₂ dynamics over crop canopies will improve regional-scale estimates of water and C fluxes. A study was conducted in central Iowa during 2002 as part of the Soil Moisture Experiment to evaluate soil moisture energy exchange across an intensive corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] production area near Ames, IA (lat. 41.98380985, long. –93.75497316). Surface energy balance and CO₂ flux stations were placed in 12 corn and soybean fields across different soils and landscapes in and around the Walnut Creek watershed. Variability among fields was induced by three factors. Within a day, variations among fields were due to the presence of cumulus cloud formation in the afternoon. Short-term differences across days among the fields were due to variation in the spatial pattern of rainfall events causing differential drying. Throughout the season, differences among fields were due to soil water availability, which affected crop growth and ground cover. Differences in early season ground cover were correlated with energy balance (r = 0.80). During the growing season, latent heat and CO₂ uptake were closely related (r = 0.85). Characterization of the spatial distribution of energy balance and CO₂ uptake in an intensive cropping region provides guidance on the confidence that can be placed in interpreting single-site measurements.

Abbreviations: CO₂ flux, carbon dioxide uptake • DOY, day of the year • EC, eddy covariance • LAI, leaf area index • SMEX02, Soil Moisture Experiment 2002

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
EXCHANGES of energy and CO₂ from the soil and canopy surface in the Corn Belt are influenced by changes in land cover and cropping practices. Houghton (1999) estimated 124 Pg C (1 petagram = 10¹⁵ g) have been added to the atmosphere as a result of land use changes between 1850 and 1990, of which 13% has been from conversion of midlatitude grasslands to cultivated cropland. One of the most intense areas for this conversion is the Upper Midwest corn–soybean region of the USA, comprised of >60 million ha representing 60% of cultivated cropland in the USA. There are important implications for surface energy balance and CO₂ uptake associated with major land use conversions. In the Upper Midwest region, native prairie grasslands have been replaced with corn and soybean crops. This conversion is important because of the configuration of the rows planted on the soil surface and the reduction in the length of the year that the crop provides cover on the soil surface. Latent heat flux (LE) exchange processes between the surface and boundary layer of the atmosphere for a native prairie were altered when prairie was transformed from a continuously covered grass surface to a corn and soybean production system in which the soil surface annually transitions from bare soil to full canopy cover to crop residue and finally to bare soil again. The exposed soil surface during the non-growing portion of a year as well as during the emerging crop phase represents an important energy exchange period (Ham et al., 1991) that responds to varying soil surface conditions. Surface heterogeneity induced by early row crop development (exposed soil with changing crop canopy) contributes to the challenge of quantifying and understanding energy exchange processes from bare soil and emerging crops (Luxmoore et al., 1973; Hatfield, 1989; Ham et al., 1991). Byre et al. (2000) reported that hydrologic budgets were significantly altered for Wisconsin prairies after conversion to a corn–soybean agroecosystem. Although cumulative evapotranspiration (ET) was comparable between the two crops there was a different temporal distribution of ET between corn and prairie fields (Byre et al., 2000).

Climate and landscape were found to be two critical factors affecting the water balance in Australia (Farmer et al., 2003). These findings are similar to observations by Kustas and Albertson (2003), who used a large eddy simulation model to quantify spatial variations of sensible and latent heat fluxes. They found that spatial variation was present across landscapes and that the mechanisms for these differences needed to be understood to help improve regional-scale model predictions. Small and Kure (2003) suggested that coupling between soil moisture and the radiation budget would create significant differences across regions. Walker et al. (2001) observed that the spatial variation of soil moisture was critical to understanding the water balance of a watershed in eastern Australia. Lyons and Halldin (2004) observed that surface heterogeneity was a major factor in the spatial variation of sensible and latent heat exchanges in southern Sweden.

Estimating the surface energy balance components and understanding the complex processes of energy and mass exchange from land surfaces and the boundary layer of the atmosphere is critical to many applications in meteorology and hydrology. Measurement of mass, energy, and CO₂ fluxes between the terrestrial surface and the atmosphere was the major focus of this effort. Assuming advection is negligible, the surface energy fluxes are related by

[1]

where Q* is net radiation (W m^–2), G is soil heat flux (W m^–2), H is sensible heat flux (W m^–2), and LE is latent heat flux (W m^–2), where L is the latent heat of vaporization of water (J kg^–1, relatively constant) and E is the evapotranspiration rate (kg m^–2 s^–1). The variation of the energy balance with time and space has not been well characterized or quantified for particular ecoregions like the Corn Belt. In central Iowa, Hatfield and Prueger (2001) found large variations in water use within a production-scale cornfield (35 ha) that ranged between 300 and 600 mm during the growing season. Spatial analysis of these fluxes has not been examined in detail, although there is evidence that the degree of variation can be significant compared with the mean fluxes.

Spatial variation has also been observed in CO₂ fluxes. Soegaard et al. (2003) observed differences among crops and fields within a study area in western Denmark. They used a weighted field value of CO₂ to determine the regional estimate of CO₂ uptake. Arora (2003) observed that accurate predictions of CO₂ fluxes for winter wheat (Triticum aestivum L.) were only achieved when energy fluxes appropriate for the area were incorporated into the model. Meyers and Hollinger (2004) found that closure of the energy balance was possible when canopy storage terms were incorporated into the analysis of the energy balance, which decreased the scatter of the partitioning of Q* into the remaining energy components. Baker and Griffis (2005) observed that eddy covariance systems provided adequate tools for the assessment of the C balance of corn and soybean production systems. These recent studies have not addressed spatial variation but serve to show that further refinement in our understanding of the energy balance would improve our ability to quantify the impacts of changing management practices on energy and CO₂ fluxes.

Variation of energy balance and CO₂ fluxes within intensive agricultural areas has not been well documented. Many questions remain about the spatial and temporal dynamics of these fluxes across an agricultural watershed that, if better understood, could provide improved insights into regional-scale energy and CO₂ flux exchange. An intensive field study involving multiple towers and fields in central Iowa was conducted in the summer of 2002 as part of the Soil Moisture Experiment (SMEX02). The objective of this study was to quantify the spatial and temporal variations in the energy balance and CO₂ fluxes across a watershed under intensive corn and soybean production.

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Study Site
The study was conducted in the Walnut Creek watershed in central Iowa, located 5 km south of Ames (41°75'N, 93°41'W), as part of a long-term monitoring effort to assess interactions of crop water use, CO₂ uptake, and yield as a function of N management for corn and soybean. Walnut Creek watershed is a 5100-ha watershed of intensive corn and soybean production fields ranging in size from 40 to 160 ha. These two crops occupy approximately 85% of the land area in the watershed. The topography of the watershed and surrounding areas are characterized by flat to gently rolling terrain with elevations in the watershed ranging from 265 to 363 m, with the lowest elevations situated on the eastern end of the watershed where Walnut Creek drains. Details of production, tillage, and nutrient management systems within the watershed are described in Hatfield et al. (1999a).

In 2002, a remote sensing soil moisture experiment (SMEX02) was conducted in the Walnut Creek watershed. The energy balance study was conducted as part of a Soil Moisture and Energy Exchange (SMACEX) portion of SMEX02, as described by Kustas et al. (2005). This study provided the opportunity to place 12 eddy covariance (EC) stations across the watershed to measure and evaluate the spatial and temporal variation among fluxes across typical corn and soybean production fields in the Upper Midwest region. These stations were in operation during the intensive measurement period of the remote sensing campaign (Kustas et al., 2003) and continued to record measurements until late August 2002. Sites of the EC stations are shown in Fig. 1 . For each site in the field, the soil type was extracted from the soil map from Boone or Story county (Soil Conservation Service, 1981, 1984). Eddy covariance sites were located in a range of soil types typical of central Iowa and, in most fields, the location represented >0.20 of the total area in the field. The primary difference among the soils was the soil water-holding capacity in the upper 1 m of the soil profile (Table 1). This provided an excellent opportunity to measure and evaluate not only differences in turbulent fluxes between corn and soybean but also the spatial and temporal variability of turbulent flux exchange of CO₂ and H₂O across the agricultural landscape.

View larger version (48K): [in this window] [in a new window]   Fig. 1. Location of the monitoring towers within the Walnut Creek watershed and surrounding area and position within the corn and soybean fields.

Observations of ground cover and measurements of leaf area index (LAI) and plant biomass were conducted in each field. The sampling procedures were performed near the energy balance sites in each of the fields, and are reported in Anderson et al. (2004).

Data Screening and Processing
The 20-Hz time-series data were first conditioned by despiking for anomalies of the critical parameters of the three wind components (downwind u, crosswind v, and vertical w), the sonic temperature (T_s) and the signals for water vapor and CO₂. Data were then passed through a low-frequency filter and used to compute 30-min averages of H, LE, CO₂, and all pertinent micrometeorological parameters and statistics. Additionally, a two-dimensional coordinate rotation and corrections for air density fluctuation effects were applied to the scalar fluxes (Baldocchi, 1988; Webb et al., 1980). Half-hour data were screened for consistency and obvious data outliers for all of the parameters observed during the study. This was accomplished by plotting the data for each day and examining the calculated fluxes. This process was completed for each tower and any suspect data points resulted in the entire time period being deleted from the overall record. Data capture for this experiment was >95%.

	RESULTS AND DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Spatial variation in the energy balance components among fields are affected by changes in ground cover and plant growth differences. Variation in precipitation amounts within the growing season can affect the availability of water for evaporation either through water for surface evaporation or crop water use. Changes in the spatial patterns of energy exchanges and CO₂ fluxes throughout the growing season are important to quantifying regional-scale variation in crop production systems.

Variation in Ground Cover
Variation in ground cover among the corn fields during the intensive observation period was minimal (Fig. 2 ). All fields had >0.5 ground cover when the observations commenced and Site 6 had the most rapid rate of growth, achieving complete ground cover by DOY 180. Only Site 33 was not greater than 0.9 ground cover by the end of the intensive study period (Fig. 2).

View larger version (16K): [in this window] [in a new window]   Fig. 2. Ground cover for the corn fields with intensive energy balance in the SMACEX study for the period from Day of the Year (DOY) 172 to 189 in 2002.

View larger version (18K): [in this window] [in a new window]   Fig. 3. Ground cover for the soybean fields with intensive energy balance in the SMACEX study for the period from Day of the Year (DOY) 172 to 189 in 2002.

View larger version (34K): [in this window] [in a new window]   Fig. 4. Distribution of precipitation across the eddy covariance sites in Walnut Creek watershed on 4 July 2002 (Day of the Year [DOY] 185).

View larger version (34K): [in this window] [in a new window]   Fig. 5. Distribution of cumulative precipitation for the study period in 2002 for the eddy covariance sites in Walnut Creek watershed.

View larger version (38K): [in this window] [in a new window]   Fig. 6. Average daily fluxes of (a) net radiation, (b) soil heat flux, (c) latent heat, (d) sensible heat, (e) and CO2 fluxes for Days of the Year (DOY) 171 to 190 for corn fields in central Iowa.

View larger version (37K): [in this window] [in a new window]   Fig. 7. Average daily fluxes of (a) net radiation, (b) soil heat flux, (c) latent heat, (d) sensible heat, and (e) CO2 fluxes for Days of the Year (DOY) 171 to 190 for soybean fields in central Iowa.

Latent heat and H fluxes during this period changed in magnitude as the crop developed (Fig. 6c, 6d, 7c, and 7d). In the soybean fields, maximum values were 300 W m^–2 until the last 4 d of the intensive period, when the daytime maximums began to approach 500 W m^–2 (Fig. 7c). This large increase in LE fluxes and the concurrent decrease in H was related to the rainfall event on DOY 185. Sensible heat fluxes for the corn fields showed daytime maximums of 50 W m^–2 and did not vary by more than 20 W m^–2 during the intensive study period (Fig. 6d). Latent heat fluxes in the corn fields were larger than those in the soybean fields (Fig. 6c vs. 7c) with the sensible heat fluxes lower in the corn than the soybean (Fig. 6d vs. 7d). The larger amount of ground cover and LAI for the corn fields contributed to the larger LE and consequently lower H fluxes. In comparison, H fluxes for the soybean fields reached maximum values of 200 W m^–2 during the study period and did not begin to decline until the rainfall event on DOY 185, when the canopies began to cover more than 0.5 of the soil surface (Fig. 3 and 7d). After this time, the daytime maximums were similar to those of the corn canopies.

Fluxes of CO₂ showed the largest change during the study period over both canopies; CO₂ daytime fluxes steadily increased in response to photosynthetic uptake as the total biomass increased (Fig. 6e and 7e). For the corn canopies, there was a linear increase in the daytime maximum during the 20 d, with peak values increasing from 1.5 to 2.5 mg m^–2 s^–1 (Fig. 6e). Nighttime CO₂ fluxes for both crops remained relatively constant during the intensive study period (Fig. 6e and 7e). A similar trend was observed for the soybean canopies, with maximum CO₂ fluxes increasing from 0.5 mg m^–2 s ^–1 at the beginning of the study period to 1.2 mg m^–2 s^–1 at the end (Fig. 7e). Increases in CO₂ fluxes were closely coupled with LE fluxes during the intensive study period (corn, r = 0.87; soybean, r = 0.82), as expected with the increased canopy biomass and LAI.

Diurnal Variation in Energy Balance Parameters
Daytime fluxes (defined as Q* > 100 W m^–2, which avoids the transitional morning and nighttime periods characterized by calm neutral conditions) of mass and energy were evaluated for each site for each 30-min period. The averages and deviations from the average for each corn and soybean site were computed for the period from DOY 171 through 190. Variation among the sites throughout the daytime period for all of the energy balance parameters was greater than the estimated variance determined from the co-location study (Meek et al., 2005). Only selected days are shown for both corn and soybean because the fields showed a consistent deviation from the mean throughout the study period (Fig. 8 –11 ). Soil heat flux (G) and sensible heat (H) show the largest variation among the sites, in part due to the fact that the fraction of these two fluxes (G/Q* or H/Q*) were approximately 0.20 and differences among fields induced by either soil surface conditions or crop growth results in a large amount of variation from the average. For example, on DOY 172 there was a nearly clear sky throughout the day and adequate water for evaporation, with a midday H value of 60 W m^–2 and range in deviations ±20 W m^–2 (Fig. 8d). An examination of G for this same period shows a midday value of nearly 100 W m^–2 and a deviation of ±30 W m^–2. These deviations are similar to those for LE (Fig. 8c). Values for the soybean fields for this same day showed that the values for LE, H, and G were nearly equal and the amount of variation among the fields was the same for all these components. One factor that could be responsible for this is the difference in ground cover between the corn and soybean fields. The G/Q* ratio relative to the fraction of ground cover showed a significant negative correlation of –0.69 for the corn fields and –0.74 for the soybean fields. Sites with more ground cover showed less variation from average values throughout the day (Fig. 8b, 9b, 10b, and 11b). Later in the study period (DOY 189) under clear sky conditions, variation was minimal among sites because of adequate soil water for LE where LE/Q* was nearly 1.0 for the corn fields and 0.80 for the soybean fields (Fig. 9 and 11).

View larger version (35K): [in this window] [in a new window]   Fig. 8. Diurnal variation of average (a) net radiation, (b) soil heat flux, (c) latent heat, (d) sensible heat, and (e) CO2 fluxes and deviations of each field site from the mean across the corn fields in central Iowa monitored on Day of the Year (DOY) 172 in 2002.

View larger version (27K): [in this window] [in a new window]   Fig. 9. Diurnal variation of average (a) net radiation, (b) soil heat flux, (c) latent heat, (d) sensible heat, and (e) CO2 fluxes and deviations of each field site from the mean across the corn fields in central Iowa monitored on Day of the Year (DOY) 189 in 2002.

View larger version (36K): [in this window] [in a new window]   Fig. 10. Diurnal variation of average (a) net radiation, (b) soil heat flux, (c) latent heat, (d) sensible heat, and (e) CO2 fluxes and deviations of each field site from the mean across the soybean fields in central Iowa monitored on Day of the Year (DOY) 172 in 2002.

View larger version (29K): [in this window] [in a new window]   Fig. 11. Diurnal variation of average (a) net radiation, (b) soil heat flux, (c) latent heat, (d) sensible heat, and (e) CO2 fluxes and deviations of each field site from the mean across the soybean fields in central Iowa monitored on Day of the Year (DOY) 189 in 2002.

Latent heat and sensible heat fluxes for these 2 d were typical of the early portion of the growing season. The LE fluxes increased from less than half of Q* on DOY 172 to >0.9Q* on DOY 189 for the corn canopies (Fig. 8c and 10c). Variation among the fields for G, LE, H, and CO₂ fluxes for the period immediately following the rainfall event was lower than before the rainfall. In the corn fields following the rainfall event on DOY 185, the correlation between the variation among fields for LE and the precipitation was 0.89. In the soybean fields, this response was not as large because the leaf area and ground cover were not as large as the corn canopies (Table 3); however, the correlation of the variation in LE and precipitation was 0.78. Deviations among fields from the average values were due to the rainfall patterns across the watershed. We observed a large increase in LE in fields on the western portion of the watershed relative to the eastern portion following the precipitation event on DOY 185. Variation in rainfall patterns across a watershed can have a large effect on the energy balance observed among fields and, when these differences persist, can impact plant growth due to the availability of soil water.

Carbon dioxide fluxes during the initial growth period were small compared with later in the season when the crops achieved full ground cover and leaf area indices were >4. Leaf area differences among fields on DOY 189 are shown in Table 3. Growth progressions across the different fields showed a rapid increase during this period, from DOY 172 through 189, of almost 1.5 LAI units in corn and 0.6 LAI units in soybean (Anderson et al., 2004). The differences in CO₂ fluxes from the average in both corn and soybean were directly related to the LAI of the canopy (r = 0.85). Variations among fields within the day were related to the deviations in Q*, of which solar radiation is the largest component during the daylight hours (Fig. 8e, 9e, 10e, and 11e).

Cumulative Latent Heat and Carbon Dioxide Fluxes
Differences among fields early in the season were relatively minor; however, during the season (DOY 166–231), cumulative LE and CO₂ fluxes began to show larger differences (Fig. 12 and 13 ). In the corn canopies, the cumulative difference in LE ranged from 220 to 282 mm (Fig. 12a), while in the soybean the difference ranged from 200 to 230 mm (Fig. 13a). We have seen seasonal differences in soil water use within corn fields in this area of 300 mm (Hatfield and Prueger, 2001). Due to constraints for agronomic operations by the producers, the equipment was not able to be maintained in the fields for the entire growing season and the seasonal totals are reduced compared with a complete growing season. Differences in cumulative LE are related to the total biomass and LAI of the crop. The seasonal differences in crop water use are related to the rainfall patterns shown in Fig. 5 for the study area, where the western portion received more rainfall than the eastern sites. For example, Corn Site 25 was in the area of the watershed with drier soils, poor plant stands, and limited plant growth (Table 3; Fig. 5), while Site 6 was one of the wetter sites, with an more uniform plant population and better plant growth (Table 3). The biomass differences on DOY 189 were 900 vs. 600 g m^–2 for Sites 6 and 25, respectively (Tables 1 and 3). Differences among the cumulative LE values for soybean were quite small because these fields were very similar in their biomass and LAI (Table 3). Differences in LE were related to differences in total crop biomass produced during portion of the season.

View larger version (23K): [in this window] [in a new window]   Fig. 12. Cumulative (a) latent heat and (b) CO2 fluxes for the corn fields measured in central Iowa during 2002 from Days of the Year (DOY) 166 through 231.

View larger version (18K): [in this window] [in a new window]   Fig. 13. Cumulative (a) latent heat and (b) CO2 fluxes for the soybean fields measured in central Iowa during 2002 from Days of the Year (DOY) 166 through 231.

	CONCLUSIONS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Spatial variations among corn and soybean fields within an area of central Iowa that is considered to be relatively uniform in appearance were due to three factors. Within a given day, spatial variation among sites was due to variation in cloud cover because of the presence of cumulus clouds. The variation among sites in Q* increased when the diurnal values deviated from a clear sky condition. Cumulus clouds across the study site were sufficient to cause differences in Q* values and this is particularly evident when the morning was clear and clouds formed in the afternoon (typical of DOY 172, Fig. 6 and 8). On days that immediately followed a rainfall event, the differences among sites were minimal because of the wetting of the soil surface (DOY 189) and the clear skies. Within the intensive study, variation in canopy growth among sites was related to the rate of change in ground cover and leaf area. These growth differences significantly affected G, LE, and CO₂ uptake among the fields. During the growing season, differences in cumulative LE fluxes and C uptake across fields were related to the amount of rainfall received. The implications of these results would suggest that energy balance studies used to infer regional-scale fluxes should be interpreted with caution to ensure that the sites are represent of larger scale meteorological events, e.g., precipitation patterns. The differences we observed in this study are typical of what we have observed across similar soils within the same field (Hatfield and Prueger, 2001; Prueger et al., 2004). Understanding spatial variation in the energy balance and CO₂ fluxes can increase our ability to quantify the potential impacts of changing land management practices on regional-scale hydrology and C balance.

	ACKNOWLEDGMENTS

 
We express sincere appreciation for the efforts of Tim Hart and Forrest Goodman in establishing and operating the micrometeorological equipment. Without their diligence in this effort, this experiment would not be possible. The efforts by Lynn McKee to provide the overall coordination for the data collection from the field sites in SMEX02 and produce a quality data set from the many volunteers are invaluable. We thank the many different scientists that provided equipment to this study to make this all possible.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA.

	REFERENCES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 

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