Simultaneous heat and water model SHAW validation

The SHAW model was modified using the 1999 dataset and validated using the 2000 dataset. The SHAW model is physically based and requires little calibration. Parameter adjustments during the development year were limited to measured and estimated soil properties (specifically, saturated hydraulic conductivity and the pore size distribution index) to more accurately simulate observed drainage trends. The model was validated against detailed measurements of snowcover, throughfall, and soil moisture, and estimates of transpiration and ET to verify that the model reasonably reproduced both the absolute magnitudes and general trends of the primary hydrological fluxes. A detailed discussion of the model validation is presented by Link etal. (2004a) and is summarized herein.

In 1999, the model simulated the development and ablation dates of the shallow snowcover in a canopy gap to within four 4 days. In 2000, the development date preceded the measured date by eight days, and the melt out date preceded the measured dates by four days beneath dense canopy and eight days in a large gap. Given the spatial variability of snowcover in this environment, we feel that the simulation of snowpack dynamics was reasonably represented by the model. Accurate simulation of snowcover ablation timing is important due to the strong control that the snowcover exerts on the timing of soil warming and onset of transpiration.

Simulated throughfall during the 1999 and 2000 rainfall seasons was 0.7 and 1.1% greater than the mean measured throughfall, indicating that the model can effectively simulate evaporation during the growing season. Throughfall estimates during the winter periods from November through March could not be validated with the existing instrumentation given the challenges of measuring throughfall in the transient snow zone.

Simulated transpiration and measured sap flux scaled to the plot are shown in Figure 11.5. The model reasonably simulates both the general seasonal decline in transpiration and the short-term variability that results from changing weather conditions. Isolated days where simulated sap fluxes are negligible are associated with infrequent midsummer wet days. The measured sap flux exhibits less variability than the simulated transpiration, possibly due to hydraulic capacitance in the tree stems, which may damp the response of sap flux to changing environmental conditions. For the period that sap flux measurements were available, the total transpiration simulated by the model was 184 mm, compared to 210 mm estimated from the scaled sap flux measurements. Given the uncertainties and potential errors associated with scaling individual sap flux measurements to the entire site, we consider these data to indicate acceptable performance of the model.

The daily simulated ET fluxes and measured fluxes from the 73-m EC system are shown in Figure 11.6. EC flux measurements are affected by the size of the areal flux source as determined by wind speed, direction, and atmospheric stability (Baldocchi 1997; Lee 1998) and are also influenced by the crane tower when wind direction is outside the optimal direction of fetch. The data presented in Figure 11.6 are not filtered for inappropriate fetch direction and do not include advected fluxes and

Simultaneous Heat And Water Shaw Model

Aug 1999

Figure 11.5 Simulated transpiration and measured sap flux scaled to the plot scale from six dominant Douglas-fir trees

Aug 1999

Figure 11.5 Simulated transpiration and measured sap flux scaled to the plot scale from six dominant Douglas-fir trees

1999

Figure 11.6 Simulated evaporation + transpiration and measured water flux from the eddy-covariance (EC) system at 73 m

1999

Figure 11.6 Simulated evaporation + transpiration and measured water flux from the eddy-covariance (EC) system at 73 m therefore are considered as estimates of total ecosystem water flux. Despite uncertainties in the EC flux data, the model reasonably matches the general magnitudes and trends of the EC data during the period for which data are available. Using more rigorous screening for wind direction, modeled ET fluxes were within 10% of EC fluxes during 10-17 day periods analyzed in detail by Unsworth et al. (2004), and closely matched diurnal EC flux trends (Link et al. 2004a).

Simulated and measured soil water content (9) in the top 0.30 m of the soil profile for the 1999 and 2000 water years are shown in Figure 11.7. The measured soil water content trend displayed in Figure 11.7 is from a sensor located in a canopy gap that was identified as a proxy for the site average (see Figure 11.4). The proxy sensor in the gap received slightly more precipitation than the site average, due to lower canopy interception, and therefore displayed a greater response to precipitation events than the modeled site average. Despite this discrepancy, the average model efficiency for the two years was 0.90, root mean square difference was 2.1 vol-1, and relative mean bias difference was +2.8%, indicating very good agreement between the measurements and simulated 9. Simulated 9 in the 0.30-0.60, 0.60-0.90, and 0.90-1.20 m soil layers also exhibited good agreement with the mean segmented TDR probe measurements taken every 3 -6 weeks, indicating that the model effectively simulated the seasonal evolution of the soil water profiles in this system (Link et al. 2004a). These data provide the best evidence of the model's ability to simulate ET, since virtually all fluxes from the soil reservoir after drainage ceases in the late spring are due to transpiration (soil evaporation being negligible).

Given the good quantitative agreement between the measured and simulated throughfall, estimated transpiration and soil moisture, the SHAW results can be used to provide reasonable estimates of the components and dynamics of the site water balance.

Renewable Energy 101

Renewable Energy 101

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable. The usage of renewable energy sources is very important when considering the sustainability of the existing energy usage of the world. While there is currently an abundance of non-renewable energy sources, such as nuclear fuels, these energy sources are depleting. In addition to being a non-renewable supply, the non-renewable energy sources release emissions into the air, which has an adverse effect on the environment.

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