• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.164-178
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• 2022

Uncertainties in weather forecasts would affect the reliability of yield prediction using crop models. The objective of this study was to compare uncertainty in crop yield prediction caused by the use of the weather forecast data. Daily weather data were produced at 10 km spatial resolution using W eather Research and Forecasting (W RF) model. The nearest neighbor method was used to downscale these data at the resolution of 5 km (W RF5K). Parameter-elevation Regressions on Independent Slopes Model (PRISM) was also applied to the WRF data to produce the weather data at the same resolution. W RF5K and PRISM data were used as inputs to the CROPGRO-SOYBEAN model to predict crop yield. The uncertainties of the gridded data were analyzed using cumulative growing degree days (CGDD) and cumulative solar radiation (CSRAD) during the soybean growing seasons for the crop of interest. The degree of agreement (DOA) statistics including structural similarity index were determined for the crop model outputs. Our results indicated that the DOA statistics for CGDD were correlated with that for the maturity dates predicted using WRF5K and PRISM data. Yield forecasts had small values of the DOA statistics when large spatial disagreement occured between maturity dates predicted using WRF5K and PRISM. These results suggest that the spatial uncertainties in temperature data would affect the reliability of the phenology and, as a result, yield predictions at a greater degree than those in solar radiation data. This merits further studies to assess the uncertainties of crop yield forecasts using a wide range of crop calendars.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.15 no.1
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• pp.35-44
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• 2017

A gamma-ray peak of $^{226}Ra$ (186.2 keV) overlaps with one of $^{235}U$ (185.7 keV) in a gamma-ray spectrometry system. Though reference peaks of $^{235}U$ can be used to correct the peak interference of $^{235}U$ in the analysis of $^{226}Ra$, this requires a complicated calculation process and a high limit of quantitation. On the other hand, evaluating $^{226}Ra$ using the correction constant in the overlapped peak can make a rapid measurement of $^{226}Ra$ without the complicated calculation process as well as overcome the disadvantage in the indirect measurement of $^{214}Bi$, which means the confinement of $^{222}Rn$ gas in a sample container and a time period to recover the secular equilibrium. About 93 samples with 6 species for raw-materials and by-products were prepared to evaluate the activity of $^{226}Ra$ using the correction constant. The results were compared with the activity of $^{214}Bi$, which means the indirect measurement of $^{226}Ra$, to validate the method of the direct measurement of $^{226}Ra$ using the correction constant. The difference between the direct and indirect measurement of $^{226}Ra$ was generally below about ${\pm}20%$. However, in the case of the phospho gypsum, a large error of about 50% was found in the comparison results, which indicates the disequilibrium between $^{238}U$ and $^{226}Ra$ in the materials. Application results of the contribution ratio of $^{226}Ra$ were below about ${\pm}10%$. The direct measurement of $^{226}Ra$ using the correction constant can be an effective method for its rapid measurement of raw materials and by-products because the activity of $^{226}Ra$ can be produced with a simple calculation without the consideration of the integrity of a sample container and the time period to recover the secular equilibrium.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.28-36
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• 2023

Solar radiation that is measured at relatively small number of weather stations is one of key inputs to crop models for estimation of crop productivity. Solar radiation products derived from GK-2A and Himawari 8 satellite data have become available, which would allow for preparation of input data to crop models, especially for assessment of crop productivity under an agrivoltaic system where crop and power can be produced at the same time. The objective of this study was to compare the degree of agreement between the solar radiation products obtained from those satellite data. The sub hourly products for solar radiation were collected to prepare their daily summary for the period from May to October in 2020 during which both satellite products for solar radiation were available. Root mean square error (RMSE) and its normalized error (NRMSE) were determined for daily sum of solar radiation. The cumulative values of solar radiation for the study period were also compared to represent the impact of the errors for those products on crop growth simulations. It was found that the data product from the Himawari 8 satellite tended to have smaller values of RMSE and NRMSE than that from the GK-2A satellite. The Himawari 8 satellite product had smaller errors at a large number of weather stations when the cumulative solar radiation was compared with the measurements. This suggests that the use of Himawari 8 satellite products would cause less uncertainty than that of GK2-A products for estimation of crop yield. This merits further studies to apply the Himawari 8 satellites to estimation of solar power generation as well as crop yield under an agrivoltaic system.