Estimation Of Energy Balance Components Research Articles

Theoretical Estimation of Energy Balance Components in Water Networks for Top-Down Approach

The energy balance calculation for pressurized water networks is an important step in assessing the energy efficiency of water distribution systems. However, the calculation generally requires mathematical modelling of the water networks to estimate three important energy components: outgoing energy through water loss (El), friction energy loss (Ef) and energy associated with water loss (EWL). Based on a theoretical energy balance analysis of simplified pipe networks, a simple method is proposed to estimate El, Ef and EWL with minimum data requirements: input energy, water loss (WL) and head loss between the source and the minimum energy point (ΔH). By inclusion of the head loss in water networks into the estimation, the percentages of El and EWL are lower and higher, respectively, than using only the percentage of WL. The percentage of Ef can be a function of the percentage of ΔH. By demonstrating our analysis with the simulation results from the mathematical models of 20 real water networks, the proposed method can be used to effectively estimate El, Ef and EWL as a top-down energy balance approach.

Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV)

A field experiment was carried out to implement a remote sensing energy balance (RSEB) algorithm for estimating the incoming solar radiation (Rsi), net radiation (Rn), sensible heat flux (H), soil heat flux (G) and latent heat flux (LE) over a drip-irrigated olive (cv. Arbequina) orchard located in the Pencahue Valley, Maule Region, Chile (35°25′S; 71°44′W; 90 m above sea level). For this study, a helicopter-based unmanned aerial vehicle (UAV) was equipped with multispectral and infrared thermal cameras to obtain simultaneously the normalized difference vegetation index (NDVI) and surface temperature (Tsurface) at very high resolution (6 cm × 6 cm). Meteorological variables and surface energy balance components were measured at the time of the UAV overpass (near solar noon). The performance of the RSEB algorithm was evaluated using measurements of H and LE obtained from an eddy correlation system. In addition, estimated values of Rsi and Rn were compared with ground-truth measurements from a four-way net radiometer while those of G were compared with soil heat flux based on flux plates. Results indicated that RSEB algorithm estimated LE and H with errors of 7% and 5%, respectively. Values of the root mean squared error (RMSE) and mean absolute error (MAE) for LE were 50 and 43 W m−2 while those for H were 56 and 46 W m−2, respectively. Finally, the RSEB algorithm computed Rsi, Rn and G with error less than 5% and with values of RMSE and MAE less than 38 W m−2. Results demonstrated that multispectral and thermal cameras placed on an UAV could provide an excellent tool to evaluate the intra-orchard spatial variability of Rn, G, H, LE, NDVI and Tsurface over the tree canopy and soil surface between rows.

Impacts of the broadband albedo on actual evapotranspiration estimated by S-SEBI model over an agricultural area

Surface albedo and emissivity are essential variables in surface energy balance. In recent decades, several land surface energy models have used both surface broadband albedo and emissivity in order to achieve reliable evapotranspiration retrievals on a daily basis. Despite these improvements in surface energy models, we noticed an assumption that most studies make when using this framework. It assumes that the surface broadband albedo and emissivity can be estimated directly as a weighted average of spectral surface bi-directional reflectances, and as a weighted average of spectral surface emissivities retrieved at a given view angle, respectively. However, this approach does not take into account surface anisotropy, which is described by the Bi-directional Reflectance Distribution Function (BRDF) in the case of the surface albedo. In this paper, we analyze the influence that estimating land surface albedo directly from the surface reflectance (αREF) or through the BRDF integration (αBRDF) has on the estimation of energy balance components (net radiation, latent and sensible heat fluxes and evapotranspiration) by using the Simplified Surface Energy Balance Index (S-SEBI). To this end, in-situ data and remote sensing images acquisitioned at different view zenith angles (VZA) such as 0°, ±40° and ±57° by the Airborne Hyperspectral Scanner (AHS) over an agricultural area were used. Results show high variation in αREF depending on the VZA when compared to αBRDF, with the highest difference observed in the backward scattering direction along the hot spot region (RMSE of 0.11 and relative error of 65%). Net radiation gives relative errors from 6 to 17%, with the maximum error obtained in the images that include the hot spot effect, whereas significant changes are not observed in case of the ground heat flux and the evaporative fraction. However, sensible heat flux, latent heat flux and daily evapotranspiration show relative errors ranging between 23–39%, 6–18% and 5–15% respectively. In a future study, the influence of estimating surface emissivity directly from the average of spectral emissivities under a given view angle or using a hemispherical value will be analyzed.

Snowmelt modeling in a balsam fir forest: comparison between an energy balance model and other simplified models

This study compares snowmelt models and determines the relative importance of the meteorological parameters affecting snowmelt during the 1985, 1986, and 1987 melt seasons in a dense balsam fir stand in Laurentide forest, 80 km north of the city of Québec. Net all-wave radiation, air temperature, wind speed, relative humidity, and rainfall were correlated with meltwater that reached the base of the snow cover as measured with a 20-m2 snow lysimeter. The estimation of energy balance components of the snow cover during the snowmelt period showed that while solar radiation absorption dominated, turbulent transfers as well as heat exchanges with ground and rain were negligible. The temperature index model SNOW-17 yielded predictions of snow cover outflow as accurately as the energy balance model, both explaining 64% of hourly outflow variation and more than 85% of daily outflow variation. Single meteorological parameters usually explained less than 25% of the hourly melt because of the meltwater transmission lag through the snowpack. On a daily basis, the relationships using air temperature or net all-wave radiation as sole index both explained nearly 70% of snowmelt outflow for the same period. Combining these two parameters with rainfall in the same equation increased the explained variance to 85%.