scholarly journals Estimating hourly reference evapotranspiration from limited weather data by sequentially adaptive RBF network

2011 ◽  
Vol 9 (3) ◽  
pp. 473-480 ◽  
Author(s):  
Slavisa Trajkovic
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
Reference Evapotranspiration ◽  
Soil Heat Flux ◽  
Weather Data ◽  
Canopy Resistance ◽  
Net Radiation ◽  
Rbf Networks ◽  
Rbf Network ◽  
Two Parameters

This study investigates the utility of adaptive Radial Basis Function (RBF) networks for estimating hourly grass reference evapotranspiration (ET0) from limited weather data. Nineteen days of micrometeorological and lysimeter data collected at half-hour intervals during 1962-63 and 1966-67 in the Campbell Tract research site in Davis, California were used in this study. Ten randomly chosen days (234 patterns) were selected for the RBF networks training. Two sequentially adaptive RBF networks with different number of inputs (ANNTR and ANNTHR) and two Penman-Monteith equations with different canopy resistance values (PM42 and PM70) were tested against hourly lysimeter data from remaining nine days (200 patterns). The ANNTR requires only two parameters (air temperature and net radiation) as inputs. Air temperature, humidity, net radiation and soil heat flux were used as inputs in the ANNTHR. PM equations use air temperature, humidity, wind speed, net radiation and soil heat flux density as inputs. The results reveal that ANNTR and PM42 were generally the best in estimating hourly ET0. The ANNTHR performed less well, but the results were acceptable for estimating ET0. These results are of significant practical use because the RBF network with air temperature and net radiation as inputs could be used to estimate hourly ET0 at Davis, California.

scholarly journals Testing hourly reference evapotranspiration approaches using lysimeter measurements in a semiarid climate

2009 ◽  
Vol 41 (1) ◽  
pp. 38-49 ◽  
Author(s):  
Slavisa Trajkovic
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Irrigation Management ◽  
Weather Data ◽  
Canopy Resistance ◽  
Rbf Network ◽  
Artificial Neural ◽  
Two Parameters

Numerous approaches have been developed for estimating hourly reference evapotranspiration ET0, most of which require numerous meteorological data. In many areas, the necessary data are lacking and new techniques are required. The objectives of this study are: (1) to develop artificial neural networks for estimating hourly reference evapotranspiration from limited weather data; (2) to evaluate the reliability of obtained artificial neural networks (ANNs) and Food and Agricultural Organization—56 Penman Monteith (FAO-56 PM) equation compared to the lysimeter measurements; (3) to test the performance of the FAO-56 PM equation for hourly daytime periods using rc=70 s m−1 (PM70) and using a lower rc=50 s m−1 (PM50); and (4) to evaluate the reliability of obtained ANNs compared to the FAO-56 PM equation using an hourly dataset from a variety of locations. The accuracy of two reduced-set artificial neural networks (ANNTR and ANNTHR) and two FAO-56 Penman-Monteith equations with different canopy resistance values (PM50 and PM70) was assessed using hourly lysimeter data from Davis, California. The ANNTR required only two parameters (temperature and radiation) as inputs. Temperature, humidity and (Rn−G) term were used as inputs in the ANNTHR. The ANNTR and PM50 were best at estimating hourly grass ET0. The ANNTR approach was additionally tested using hourly FAO-56 PM ET0 data from California Irrigation Management Information System (CIMIS) dataset. The overall results recommended Radial Basis Function (RBF) network for estimating hourly ET0 from limited weather data. Also, the results support the introduction of new value for canopy resistance (rc=50 s m−1) in the hourly FAO-56 PM equation.

scholarly journals Hydrometeorological dataset of West Siberian boreal peatland: a 10-year record from the Mukhrino field station

2021 ◽  
Vol 13 (6) ◽  
pp. 2595-2605
Author(s):  
Egor Dyukarev ◽  
Nina Filippova ◽  
Dmitriy Karpov ◽  
Nikolay Shnyrev ◽  
Evgeny Zarov ◽  
...  
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
Gaussian Process Regression ◽  
Soil Heat Flux ◽  
Net Radiation ◽  
Field Station ◽  
Local Climate ◽  
Ombrotrophic Peatland ◽  
Meteorological Observations ◽  
Northern Peatlands

Abstract. Northern peatlands represent one of the largest carbon pools in the biosphere, but the carbon they store is increasingly vulnerable to perturbations from climate and land-use change. Meteorological observations taken directly at peatland areas in Siberia are unique and rare, while peatlands are characterized by a specific local climate. This paper presents a hydrological and meteorological dataset collected at the Mukhrino peatland, Khanty-Mansi Autonomous Okrug – Yugra, Russia, over the period of 8 May 2010 to 31 December 2019. Hydrometeorological data were collected from stations located at a small pine–shrub–Sphagnum ridge and Scheuchzeria–Sphagnum hollow at ridge–hollow complexes of ombrotrophic peatland. The monitored meteorological variables include air temperature, air humidity, atmospheric pressure, wind speed and direction, incoming and reflected photosynthetically active radiation, net radiation, soil heat flux, precipitation (rain), and snow depth. A gap-filling procedure based on the Gaussian process regression model with an exponential kernel was developed to obtain continuous time series. For the record from 2010 to 2019, the average mean annual air temperature at the site was −1.0 ∘C, with the mean monthly temperature of the warmest month (July) recorded as 17.4 ∘C and for the coldest month (January) −21.5 ∘C. The average net radiation was about 35.0 W m−2, and the soil heat flux was 2.4 and 1.2 W m−2 for the hollow and the ridge sites, respectively. The presented data are freely available through Zenodo (https://doi.org/10.5281/zenodo.4323024, Dyukarev et al., 2020), last access: 15 December 2020) and can be used in coordination with other hydrological and meteorological datasets to examine the spatiotemporal effects of meteorological conditions on local hydrological responses across cold regions.

Analysis of Variations in Soil Heat Flux and Air Temperature by Net Radiation at a Mud Flat in Hampyeong Bay

2017 ◽  
Vol 26 (9) ◽  
pp. 1101-1110
Author(s):  
Ho-seon Park ◽  
Byung Hyuk Kwon ◽  
Il-Kyu Kim ◽  
Yoon Hwan So ◽  
Se Bong Oh ◽  
...  
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
Soil Heat Flux ◽  
Net Radiation ◽  
Mud Flat

scholarly journals Hydrometeorological dataset of West Siberian boreal peatland: a 10-year record from the Mukhrino field station

2021 ◽  
Author(s):  
Egor Dyukarev ◽  
Nina Filippova ◽  
Dmitriy Karpov ◽  
Nikolay Shnyrev ◽  
Evgeny Zarov ◽  
...  
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
Gaussian Process Regression ◽  
Soil Heat Flux ◽  
Net Radiation ◽  
Field Station ◽  
Local Climate ◽  
Spatio Temporal ◽  
Meteorological Observations ◽  
Northern Peatlands

Abstract. Northern peatlands represent one of the largest carbon pools in the biosphere but the carbon they store is increasingly vulnerable to perturbations from climate and land-use change. Meteorological observations taken directly at peatland areas in Siberia are unique and rare, while peatlands are characterized by a specific local climate. This paper presents a hydrological and meteorological dataset collected at the Mukhrino peatland, Khanty-Mansi Autonomous Okrug – Yugra, Russia, over the period of 8 May 2010 to 31 December 2019. Hydrometeorological data were collected from stations located at a small pine-shrub-Sphagnum ridge and Scheuchzeria-Sphagnum hollow at ridge–hollow complexes of ombrotrophic peatland. The monitored meteorological variables include air temperature, air humidity, atmospheric pressure, wind speed and direction, incoming and reflected photosynthetically active radiation, net radiation, soil heat flux, precipitation (rain) and snow depth. A gap-filling procedure based on the Gaussian process regression model with an exponential kernel was developed to obtain continuous time series. For the record from 2010 to 2019, the average mean annual air temperature at the site was −1.0 °C, with the mean monthly temperature of the warmest month (July) recorded as 17.4 °C and for the coldest month (January) −21.5 °C. The average net radiation was about 35.0 W m−2, and the soil heat flux was 2.4 and 1.2 W m−2 for the hollow and the ridge sites, respectively. The presented data are freely available through Zenodo (https://zenodo.org/record/4323024, last access: 15 December 2020) and can be used in coordination with other hydrological and meteorological datasets to examine the spatio‐temporal effects of meteorological conditions on local hydrological responses across cold regions.

scholarly journals Characteristic Variation of Ground Heat Flux and Net Radiation at Tropical Station in Ile-Ife, Osun State, Nigeria

2020 ◽  
pp. 35-42
Author(s):  
A. Usman ◽  
B. B. Ibrahim ◽  
L. A. Sunmonu
Keyword(s):  
Heat Flux ◽  
Research Work ◽  
Soil Heat Flux ◽  
Entire Period ◽  
Net Radiation ◽  
Sampled Data ◽  
Minimum Value ◽  
Maximum Value ◽  
Characteristic Variation ◽  
Ground Heat Flux

Characteristic variation of ground heat flux and net radiation enhances the understanding of the significance of indicated trends of variability to everyday life and factors that might be responsible for such variations. This research work critically analyses some specific days with field data over grass-covered surface at Ile-Ife, Nigeria between ground heat flux and net radiation. For the field observations, an instrumented meteorological mast was set up at an experimental site (7°33’N, 4°35’E) located at Obafemi Awolowo University campus, Ile-Ife, Nigeria for a period of two weeks (31st May-14th June, 2013). The soil heat flux, net radiation and soil temperature from the soil heat flux plate; an all-wave net radiometer, and soil thermometer were recorded every 10 seconds and averaged over 2 minutes interval. The sampled data was stored in the data logger (Campbell Scientific, Model CR10X) storage module. After the removal of spurious measurement values (Quality Assurance and Quality Control), the data stored was further reduced to 30 minutes averages using the Microcal Origin (version 7.0) data analysis software. The results showed that the measured ground heat flux, HGM during the daytime increases until 1400 hrs with maximum value of about 136.86 Wm-2 and minimum value of about -72.87 Wm-2 at 0830 hrs (DOY 156). The measured net radiation, Rn value of 649.65 Wm-2 observed at 1400 hrs (DOY 156), represented the maximum value for the entire period of the study. -10.75 Wm-2 value observed at1800 hrs (DOY 154), represented the minimum value for the entire period of the study due to the cloudy condition of the sky which reduces the amount of incoming solar radiation reaching the earth surface.

ENERGY BALANCE OVER PRAIRIE GRASS

1972 ◽  
Vol 52 (2) ◽  
pp. 215-225 ◽  
Author(s):  
LAWRENCE C. NKEMDIRIM ◽  
SHUJI YAMASHITA
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Bowen Ratio ◽  
Soil Heat Flux ◽  
Daily Basis ◽  
Net Radiation ◽  
Large Variability ◽  
Prairie Grass ◽  
Latent Flux ◽  
Evaporative Flux

The energy balance over prairie grass was computed for four cloudless days using the Bowen ratio and the Fourier heat conduction equation. For the 3 advection-free days evaporation accounted for an average of 55% of daytime net radiation. Turbulent flux of heat and soil heat flux shared the remaining portion almost equally. Hourly evaporation can be related to net radiation by the empirical equation: E = 1.2 + 0.75 R cal cm−2 hr−1, where E is the evaporative flux and R the net radiation. The patterns of the soil heat flux was fairly steady from day to day. The relation between hourly flux of sensible heat and soil heat flux was linear on a daily basis. The linearity of the two fluxes when the hourly value for the whole period of investigation was pooled was poor. The proportion of net radiation used as latent flux and sensible flux showed large variability under advection conditions.

scholarly journals Modeling the Interaction of Plastic Film Mulch and Potato Canopy Growth with Soil Heat Transport in a Semiarid Area

Agronomy ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 190 ◽  
Author(s):  
You-Liang Zhang ◽  
Feng-Xin Wang ◽  
Clinton C. Shock ◽  
Shao-Yuan Feng
Keyword(s):  
Heat Flux ◽  
Heat Transport ◽  
Solanum Tuberosum L ◽  
Thermal Conditions ◽  
Soil Heat Flux ◽  
Gansu Province ◽  
Water Evaporation ◽  
Plastic Film ◽  
Net Radiation ◽  
Plastic Mulch

Plastic film mulch is an important agricultural technology to reduce water evaporation and modify the soil thermal conditions for crop production. The optical properties of plastic film mulch and the crop canopy growth are both key factors impacting soil heat transport in the soil-film-canopy-atmosphere ecosystem. In this study, a process-oriented model was developed to better understand the interaction among the plastic film mulch, potato (Solanum tuberosum L.) canopy growth, and soil thermal conditions. Canopy growth, photosynthetically active radiation transmittance, net radiation, soil heat flux, and temperature were monitored in a two-year plastic mulch field experiment in Wuwei (Gansu Province, China). Results showed that the simulation of daily soil surface temperature had a good performance with 2.8 and 1.5 °C of root mean square error (RMSE) for the transparent film mulch (TM) and black film mulch (BM), respectively. Moreover, the simulation of the daily net radiation and soil heat flux model indicated reasonable fluctuations with potato phenological development with the daily R2 ranging from 0.89 to 0.98 in 2014 and 2015 for the TM and BM treatments. It was shown that the canopy temperature under BM was greater than that in TM treatment, and the maximum value difference could be up to 7 °C during the early potato growing period, which implied that the BM may perform better in modifying the canopy thermal condition. The model could provide heat distribution information for plastic film choosing in potato field to avoid heat stress.

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