• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.389-395
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• 2014

This technical note describes about the base stages of technology implementation for establishing "Early Warning System for Weather Hazard Management in Climate-smart Agriculture" to national onsite service. First of all, a special weather report service at catchment was represented sequential risk of 810 units of catchment by spatial statistical methods to existing 150 counties units special weather report released in KMA. The second, chronic hazard alarm service based on daily data of 76 Synoptic stations was monitor about 810 Catchment of mid-long term lapse weather and represented as a relative risk index chronic hazard risk of this time in preparation for the climatological normal conditions in the same period. Finally, we establish the foundation for delivering individually calculated field specific in hazard risk about volunteer farmer of early warning service demonstration area in seomjin downstream watershed. These three types of information were built a near real-time map service on the VWORLD background map of Ministry of Land as superposed layers nationwide catchment and demonstration areas within the farm unit weather hazard.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.37-49
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• 2023

Rainfall data is one of the most important data in hydrologic modeling. In this study, the impacts of spatial resolution of precipitation data on hydrological responses were assessed using SWAT in the Santa Fe River Basin, Florida. High correlations were found between the FAWN and NLDAS rainfall data, which are observed weather data and simulated weather data based on observed data, respectively. FAWN-based scenarios had higher maximum rainfall and more rainfall days and events compared to NLDAS-based scenarios. Downstream areas showed lower correlations between rainfall and peak discharge than upstream areas due to the characteristics of study site. All scenarios did not show significant differences in base flow, and showed less than 5% of differences in high flows among NLDAS-based scenarios. The impact of resolution will appear differently depending on the characteristics of the watershed and topography and the applied model, and thus, is a process that must be considered in advance in runoff simulation research. The study suggests that applying the research method to watersheds in Korea may yield more pronounced results, and highlights the importance of considering data resolution in hydrologic modeling.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.45-52
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• 2012

Along with global warming, ever intensifying weather events have increased damages to agricultural farms and facilities. The objective of this study was to investigate the spatial distribution and regional characteristics of agricultural damages by extreme weather events. Agricultural disaster statistics provided by the National Emergency Management Agency were summed over for a 13-year period from 1998 to 2010 and used for the spatial analysis. Two indices of damage area ration and property damage per unit area were introduced to quantify regional agricultural damages. As the results, farm inundation accounted for the largest area primarily damaged by typhoons with heavy rainfalls. Most property damages to farm lands originated from farm erosion in the alpine regions by localized guerrilla rains. The two major causes of damages to greenhouse and livestock facilities were typhoon with strong wind and winter blizzards. Gangwon was the province of the largest property loss mostly from farm land erosion losses, followed by Gyeongnam, Jeonnam, and Chungnam where losses to greenhouse and livestock facilities were relatively greater. Property loss per unit area was also the greatest for the Gangwon province (4.91 M\/ha), followed by Gyongnam and Chungnam of 2.20 and 1.50 M\/ha, respectively. Unit loss for greenhouse and livestock facilities was 13.3 M\/ha, approximately 13 times greater than that for farm land (1.06 M\/ha). The study findings indicated the importance of reducing highland farm erosion and reinforcing farming facilities structures for agricultural disaster management.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.6
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• pp.173-183
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• 2015

The aim of this study was to develop a soil moisture simulation model equipped with meteorological data enhanced by WRF (Weather Research and Forecast) model, and this soil moisture model was applied for quantifying soil moisture content and irrigation requirement. The WRF model can provide grid based meteorological data at various resolutions. For applicability assessment, comparative analyses were conducted using WRF data and weather data obtained from weather station located close to test bed. Water balance of each upland grid was assessed for soils represented with four layers. The soil moisture contents simulated using the soil moisture model were compared with observed data to evaluate the capacity of the model qualitatively and quantitatively with performance statistics such as correlation coefficient (R), coefficient of determination (R2) and root mean squared error (RMSE). As a result, R is 0.76, $R^2$ is 0.58 and RMSE 5.45 mm in soil layer 1 and R 0.61, $R^2$ 0.37 and RMSE 6.73 mm in soil layer 2 and R 0.52, $R^2$ 0.27 and RMSE 8.64 mm in soil layer 3 and R 0.68, $R^2$ 0.45 and RMSE 5.29 mm in soil layer 4. The estimated soil moisture contents and irrigation requirements of each soil layer showed spatiotemporally varied distributions depending on weather and soil texture data incorporated. The estimated soil moisture contents using weather station data showed uniform distribution about all grids. However the estimated soil moisture contents from WRF data showed spatially varied distribution. Also, the estimated irrigation requirements applied WRF data showed spatial variabilities reflecting regional differences of weather conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.337-347
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• 2018

Weather causes much of the risk of agricultural activity. For efficient farming, we need to use weather information. Modern agriculture has been developed to create high added value through convergence with state-of-the-art Information and Communication Technology (ICT). This study deals with the quality control algorithms of weather monitoring equipment through Ubiquitous Sensor Network (USN) observational equipment for efficient cultivation of cabbage. Accurate weather observations are important. To achieve this goal, the Korea Meteorological Administration, for example, developed various quality control algorithms to determine regularity of the observation. The research data of this study were obtained from five USN stations, which were installed in Anbandegi and Gwinemi from 2015 to 2017. Quality control algorithms were developed for flat line check, temporal outliers check, time series consistency check and spatial outliers check. Finally, the quality control algorithms proposed in this study can also identify potential abnormal observations taking into account the temporal and spatial characteristics of weather data. It is expected to be useful for efficient management of highland cabbage production by providing quality-controlled weather data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.34-45
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• 2021

Weather is one of the important factors in the agricultural industry as it affects the price, production, and quality of crops. Upland crops are directly exposed to the natural environment because they are mainly grown in mountainous areas. Therefore, it is necessary to provide accurate weather for upland crops. This study examined the effectiveness of 12 forest soil factors to interpolate the weather in mountainous areas. The daily temperature and precipitation were collected by the Korea Meteorological Administration between January 2009 and December 2018. The Generalized Additive Model (GAM), Kriging, and Random Forest (RF) were considered to interpolate. For evaluating the interpolation performance, automatic weather stations were used as training data and automated synoptic observing systems were used as test data for cross-validation. Unfortunately, the forest soil factors were not significant to interpolate the weather in the mountainous areas. GAM with only geography aspects showed that it can interpolate well in terms of root mean squared error and mean absolute error. The significance of the factors was tested at the 5% significance level in GAM, and the climate zone code (CLZN_CD) and soil water code B (SIBFLR_LAR) were identified as relatively important factors. It has shown that CLZN_CD could help to interpolate the daily average and minimum daily temperature for upland crops.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.1
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• pp.63-72
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• 1994

The objective of the study is to develop weather generators for daily rainfall and small pan evaporation and to test the applicability with recorded data. Daily rainfall forecasting model(DRFM) was developed that uses a first order Markov chain to describe rainfall seque- nces and applies an incomplete Gamma function to predict the amount of precipitation. Daily evaporation forecasting model(DEFM) that adopts a normal distribution function to generate the evaporation for dry and wet days was also formulated. DRFM and DEFM were tested with twenty year weather data from eleven stations using Chi-square and Kolmogorov and Smirnov goodness of fit tests. The test results showed that the generated sequences of rainfall occurrence, amount of rainfall, and pan evaporation were statistically fit to recorded data from eleven, seven, and seven stations at the 5% level of significance. Generated rainfall data from DRFM were very close in frequency distri- bution patterns to records for stations all over the country. Pan evaporation for rainy days generated were less accurate than that for dry days. And the proposed models may be used as tools to provide many mathematical models with long-term daily rainfall and small pan evaporation data. An example is an irrigation scheduling model, which will be further detailed in the paper.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.71-79
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• 2017

Climate change phenomenon is posing a serious threat to sustainable corn production in Ghana. This study investigated the impacts of climate change on the rain-fed corn yield in the Dangme East district, Ghana by using Aquacrop model with a daily weather data set of 22-year from 1992 to 2013. Analysis of the weather data showed that the area is facing a warming trend as the numbers of years hotter and drier than the normal seemed to be increasing. Aquacrop model was assessed using the limited observed data to verify model's sufficiency, and showed credible results of $R^2$ and Nash-Sutcliffe efficiency (NSE). In order to simulate the corn yield response to climate variability four climate change scenarios were designed by varying long-term average temperature in the range of ${\pm}1^{\circ}C{\sim}{\pm}3^{\circ}C$ and average annual rainfall to ${\pm}5%{\sim}{\pm}30%$, respectively. Generally, the corn yield was negatively correlated to temperature rise and rainfall reduction. Rainfall variations showed more prominent impacts on the corn yield than that of temperature variations. The reduction in average rainfall would instantly limit the crop growth rate and the corn yield irrespective of the temperature variations.

• Korean Journal of Agricultural Science
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• v.29 no.2
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• pp.122-134
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• 2002

DPRK have been encountered serious food problems in recent years, because of lack of availabilility of supplies, unfavorable weather conditions and above all lack of production incentives for farmers. Self-management is one of the method of increasing production incentives for farmers. For the well established self-management program, DPRK have to distribute farmland to farmers, not property rights but utilization rights. However farming situations are different, the distribution methods will be different according to the farming situations.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 1999.04a
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• pp.42.2-42
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• 1999