• Journal of the Korean earth science society
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• v.34 no.6
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• pp.515-523
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• 2013

The eastern coast of South Korea is expected to be damaged by volcanic ash when Mt. Baekdusan volcano erupts. Even if the amount of volcanic ash is small, it can be fatal on the agricultural sector withering many plants and causing soil acidification. Thus, in this paper, we aim to estimate agricultural losses caused by the volcanic ash and to visualize them with Google map. To estimate the volcanic ash losses, a damage assessment model is needed. As the volcanic ash hazard depends on the kind of a crops and the ash thickness, the fragility function of damage assessment model should represent the relation between ash thickness and damage rate of crops. Thus, we model the fragility function using the damage rate for each crop of RiskScape. The volcanic ash losses can be calculated with the agricultural output and the price of each crop using the fragility function. This paper also represents the estimated result of the losses in Gangwon province, which is most likely to get damaged by volcanic ashes in Korea. According to the result with gross agricultural output of Gangwon province in 2010, the amount of volcanic ash losses runs nearly 635,124 million wons in Korean currency if volcanic ash is accumulated over four millimeters. This amount represents about 50% of the gross agricultural output of Gangwon province. We consider the damage only for the crops in this paper. However, a volcanic ash fall has the potential to damage the assets for a farm, including the soil fertility and installations. Thus, to estimate the total amount of volcanic ash damage for the whole agricultural sectors, these collateral damages should also be considered.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.1
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• pp.55-63
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• 2001

N fertilizer recommendations to optimize with consideration to maximum crop yields, maximum profits, and minimum N losses to ground or runoff water, an advisory system. Nitrogen Expert System (NES), was developed. The system was to estimate the optimal rate of N fertilizer application cornfields in Illinois. NES was constructed using Smart Elements, a knowledge-based system that manages the expertise of human experts. NES was reinforced by addition of the effect of a productivity index (PI), soil organic matter content (SOM), and pre-sidedressing of nitrate concentration (PSNT) to the optimal N fertilizer recommendation. NES contains 49 rules, 1 class, 14 objects, and 2 properties. NES was successfully operated, showing N recommendations with inputs of three soil properties including PI, SOM, and PSNT. NES can reduce N loss to the environment, but adherence to the recommendations may also reduce farmers income. Therefore, NES will be more effective by evaluating both environmental damage assessment and other economic agricultural management parameters and other soil physico-chemical parameters.