• Journal of the Korean Statistical Society
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• v.35 no.4
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• pp.355-376
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• 2006

To identify whether the sequence of observations follows a chain dependent process and whether the chain dependent or repeated observations follow stationary process or not, alternative procedures are suggested in this paper. These test procedures are formulated on the basis of logistic regression model under the likelihood ratio test criterion and applied to the daily rainfall occurrence data of Bangladesh for selected stations. These test procedures indicate that the daily rainfall occurrences follow a chain dependent process, and the different types of transition probabilities and overall transition probabilities of Markov chain for the occurrences of rainfall follow a stationary process in the Mymensingh and Rajshahi areas, and non-stationary process in the Chittagong, Faridpur and Satkhira areas.

• 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 Korea Water Resources Association
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• v.33 no.1
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• pp.99-110
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• 2000

In this study we proposed a simple method for generating multi-site daily rainfall based on the 1-order Markov chain and considering the spatial correlation. The occurrence of rainfall is simulated by a simple 1st-order Markov chain and its intensity to be chosen randomly from the observed data. The spatial correlation between sites could be conserved as the rainfall intensity at each site is to be chosen consistently with the target site in time through generation. It is found that the generated daily rainfall data reproduce genera] characteristics of the observed data such as average, standard deviation, average number of wet and dry days, but the clustering level in time is somewhat loosened. Thus, the lag-I correlation coefficient of the generated data gave smaller value than the observed, also the average lengths of wet run and dry run and the wet-to-wet and dry-to-dry probabilities were a bit less than the observed. This drawback seems to be overcome somewhat by choosing a proper site representing overall basin characteristics or by use of more detailed states of rainfall occurrence.

• Journal of Korea Water Resources Association
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• v.42 no.9
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• pp.747-758
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• 2009

In this study, long-term variabilities of rainfall-occurrence characteristics are analyzed using rainfall data at Seoul, which is the longest data record existing in world. first, the accuracy of Chukwooki data set (CWK) are evaluated in view of rainfall-occurrence probability by analyzing the transition probabilities and occurrence characteristics based on Markov chain. And long-term inter-monthly variabilities of transition probabilities are analyzed using two dimensional LOWESS regression. From the results of analyzed transition probabilities and occurrence characteristics, it is different that rainfall-occurrence characteristics between CWK and modern rain gage data set (MRG) for original rainfall data sets (M00). For characteristics of rainfall series, occurrences probabilities of rainfall are increased and durations of each rainfall are shorter than past. And from the results of analyzing the long-term inter-monthly variabilities of transition probabilities, in case of M20, lengths of dry spells between CWK and MRG are not different significantly and lengths of wet spells are decreased persistently after A.D. 1830. Especially, decreasing trend for lengths of wet spells at recent september are appeared significantly. These results are considered with increasing trend of recent rainfall, it is concluded that recent frequencies and intensities of rainfall are increasing.

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.933-951
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• 2009

Climate change of global warming may affect the water circulation in Korea. Rainfall is occurred with complex of multiple climatic indices. Therefore, the rainfall is one of the most significant index due to climate change in the process of water circulation. In this research, multiple time series data of rainfall events were extracted to represent the rainfall characteristics. In addition, the occurrence of rainfall time series analyzed by annual, seasonal and monthly data. Analysis method used change analysis of mean and standard deviation and trend analysis. Also, changes in rainfall characteristics and the relative error was calculated during the last 10 years for comparison with past data. At the results, significant statistical results weren't showed by randomness of rainfall data. However, amount of rainfall generally increased last 10 years, and number of raining days had trend of decrease. In addition, seasonal and monthly changes in the rainfall characteristics can be found to appear differently.

• Journal of Korea Water Resources Association
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• v.52 no.2
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• pp.141-148
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• 2019

When simulating the daily rainfall amount by existing Markov Chain model, it is general to simulate the rainfall occurrence and to estimate the rainfall amount randomly from the distribution which is similar to the daily rainfall distribution characteristic using Monte Carlo simulation. At this time, there is a limitation that the characteristics of rainfall intensity and distribution by time according to the rainfall duration are not reflected in the results. In this study, 1-day, 2-day, 3-day, 4-day rainfall event are classified, and the rainfall amount is estimated by rainfall duration. In other words, the distributions of the total amount of rainfall event by the duration are set using the Kernel Density Estimation (KDE), the daily rainfall in each day are estimated from the distribution of each duration. Total rainfall amount determined for each event are divided into each daily rainfall considering the type of daily distribution of the rainfall event which has most similar rainfall amount of the observed rainfall using the k-Nearest Neighbor algorithm (KNN). This study is to develop the limitation of the existing rainfall estimation method, and it is expected that this results can use for the future rainfall estimation and as the primary data in water resource design.

• The Plant Pathology Journal
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• v.28 no.2
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• pp.172-184
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• 2012

An infection risk model for Phytophthora blight on chili pepper was developed to estimate the first date of disease occurrence in the field. The model consisted of three parts including estimation of zoosporangium formation, soil water content, and amount of active inoculum in soil. Daily weather data on air temperature, relative humidity and rainfall, and the soil texture data of local areas were used to estimate infection risk level that was quantified as the accumulated amount of active inoculum during the prior three days. Based on the analysis on 190 sets of weather and disease data, it was found that the threshold infection risk of 224 could be an appropriate criterion for determining the primary infection date. The 95% confidence interval for the difference between the estimated date of primary infection and the observed date of first disease occurrence was $8{\pm}3$ days. In the model validation tests, the observed dates of first disease occurrence were within the 95% confidence intervals of the estimated dates in the five out of six cases. The sensitivity analyses suggested that the model was more responsive to temperature and soil texture than relative humidity, rainfall, and transplanting date. The infection risk model could be implemented in practice to control Phytophthora blight in chili pepper fields.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.617-625
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• 1999

Global warming has begun since the industrial revolution and it is getting worse recently. Even though the increase of greenhouse gases such as $CO_2$ is thought to be the main cause for global warming, its impact on global climate has not been revealed clearly in rather quantitative manners. However, researches using General Circulation Models(GCMs) has shown the accumulation of greenhouse gases increases the global mean temperature, which in turn impacts on the global water circulation pattern. This changes in global water circulation pattern result in abnormal and more frequent meteorological events such as severe floods and droughts, generally more severe than the normal ones, which are now common around the world and is referred as a indirect proof of global warming. Korean peninsula also cannot be an exception and have had several extremes recently. The main objective of this research is to analyze the impact of global warming on the change of flood and drought frequency. Based on the assumption that now is a point in a continuously changing climate due to global warming, we analyzed the observed daily rainfall data to find out how the increase of annual rainfall amount affects the distribution of daily rainfall. Obviously, the more the annual rainfall depth, the more frequency of much daily rainfall, and vice versa. However, the analysis of the 17 points data of Keum river basin in Korea shows that especially the number of days of under 10mm or over 50mm daily rainfall depth is highly correlated with the amount of annual rainfall depth, not the number of dry days with their correlation coefficients quite high around 0.8 to 0.9.

• Current Research on Agriculture and Life Sciences
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• v.5
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• pp.143-157
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• 1987

In order to determine the design precipitation, the most probable daily precipitation and annual precipitation at every spot are calculated and iso - precipitation line are drawn. Probability of precipitation and drought phenomena of each gage station are analyzied by the method of frequency analysis from the statistical conceptions. The results summarized in this study are as the follows. 1. Annual mean precipitation in kyungpook area are 1044 mm, about 115 mm less than annual mean precipitation of Korea amounts to l1S9mm, and found to regionally unequal. 2. Monthly mean rainfall of July is 242.2mm, 23.2%, August 174.2mm, 16.7%, June 115mm, 11% and September 114.2mm, 10.9% and Rainfall depth of July-August are more than 40% of annual precipition. This shows notable summer rainy weather by typoon and low pressure storm and seasonal unbalance of water supply. 3. The relation among the maximum precipi.tation per day, per two continuous days and per three contnous days are caculated and the latter is found 31.0% increased rate of the first and the last 48.2% increased rate of first. 4. Probability precipitation in Kyungpook area are shown as 9.0%(5 year), 13.3%(10 year), 17.7%(20 year), 23.1%(50 year), 27.0%(100 year) and 31.1%(200 year) increased rate of each recurrence year compared with observed average annual precipitation. 5. From annual precipitation and maximum daily rainfall data probability of precipitation and precipitation isohyetal line are derived which shown as Table 11 and Fig. 8. 6. Drought days are divided 6 class and analysed results are shown on table 12. Average occurrence time of 10-14 continuous drought days are 2.3 time per year, 15-19 days are 0.9 time per year, 20-24 days are one per six years, 30-34 days are once per nine years and over than 35days are once per 25 years.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.959-967
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• 2008

Disaggregation techniques are widely used to transform observed daily rainfall values into hourly ones, which serve as important inputs for flood forecasting purposes. However, an important limitation with most of the existing disaggregation techniques is that they treat the rainfall process as a realization of a stochastic process, thus raising questions on the lack of connection between the structure of the models on one hand and the underlying physics of the rainfall process on the other. The present study introduces a nonlinear deterministic (and specifically chaotic) framework to study the dynamic characteristics of rainfall distributions across different temporal scales (i.e. weights between scales), and thus the possibility of rainfall disaggregation. Rainfall data from the Seoul station (recorded by the Korea Meteorological Administration) are considered for the present investigation, and weights between only successively doubled resolutions (i.e., 24-hr to 12-hr, 12-hr to 6-hr, 6-hr to 3-hr) are analyzed. The correlation dimension method is employed to investigate the presence of chaotic behavior in the time series of weights, and a local approximation technique is employed for rainfall disaggregation. The results indicate the presence of chaotic behavior in the dynamics of weights between the successively doubled scales studied. The modeled (disaggregated) rainfall values are found to be in good agreement with the observed ones in their overall matching (e.g. correlation coefficient and low mean square error). While the general trend (rainfall amount and time of occurrence) is clearly captured, an underestimation of the maximum values are found.