• Journal of Forest and Environmental Science
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• v.26 no.1
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• pp.17-23
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• 2010

The present study was conducted to quantify wood and leaf litter decomposition and nutrient release of a dominant tree species, Tectona grandis Linn. F. in a tropical dry deciduous forest of Rajasthan, Western India. The mean relative decomposition rate was maximum in the wet summer and minimum during dry summer. Rainfall and its associated variables exhibited greater control over litter decomposition than temperature. The concentrations of N and P increased in decomposing litter with increasing retrieval days. Mass loss was negatively correlated with N and P concentrations. The monthly weight loss was significantly correlated (P < 0.05) with soil moisture and rainfall in both wood and leaf litter. Tectona grandis was found to be most suitable tree species for plantation programmes in dry tropical regions as it has high litter deposition and decomposition rates and thus it has advantages in degraded soil restoration and sustainable land management.

• Economic and Environmental Geology
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• v.56 no.1
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• pp.65-73
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• 2023

As one of the most vulnerable countries to floods, there should be an increased necessity for accurate and reliable flood forecasting in Indonesia. Therefore, a new prediction model using a machine learning algorithm is proposed to provide daily flood prediction in Indonesia. Data crawling was conducted to obtain daily rainfall, streamflow, land cover, and flood data from 2008 to 2021. The model was built using a Random Forest (RF) algorithm for classification to predict future floods by inputting three days of rainfall rate, forest ratio, and stream flow. The accuracy, specificity, precision, recall, and F1-score on the test dataset using the RF algorithm are approximately 94.93%, 68.24%, 94.34%, 99.97%, and 97.08%, respectively. Moreover, the AUC (Area Under the Curve) of the ROC (Receiver Operating Characteristics) curve results in 71%. The objective of this research is providing a model that predicts flood events accurately in Indonesian regions 3 months prior the day of flood. As a trial, we used the month of June 2022 and the model predicted the flood events accurately. The result of prediction is then published to the website as a warning system as a form of flood mitigation.

• Journal of the Korean Society of Tobacco Science
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• v.4 no.1
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• pp.29-35
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• 1982

Potassium deficiency symptoms were studied with flue-cured tobacco which was applied with different levels of compound fertilizer (10-15-20) ; 75kg, 100hg, and 125kg/10a. Ratio of N/$K_2O$ in leaves was increased from bottom to top stalk position due to the increase of nitrogen content in leaves. Nitrogen content in leaves was increased from stalk to tip as wall as from midrib to laminae, but vice versa in potassium content. Consequently, resulting in potassium deficiency symptoms in tip of leaves. Rate of reabsorption by rainfall during the latter part of growth was highest at top stalk position in case of nitrogen, but lowest in potassium. This observation was more evident with higher application rate of fertilizer. Nitrogen content of about 4 % in leaves of top stalk position applied with 125kg/10a was maintained up to 85days after trans planting. No increase in potassium in upper leaves was observed over the level of 100kg/10a fertilizer application. As the result, N/$K_2O$ ratio in leaves of top stalk position applied with 125kg/10a was kept at more than 1.0 up to 85days after transplanting, but it was less than 0.9 at 65days after tracts planting with less than 100kg/10a fertilizer application.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.117-133
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• 2014

In this study, we analysed impacts of the recent increasing trend of exceedance rainfall thresholds for separation of data set and different research periods using Quantile Regression (QR) approach. And also we performed significant test for time series data using linear regression, Mann-Kendall test and Sen test over the Korean major 8-city. Spring and summer precipitation was tend to significant increase, fall and winter precipitation was tend to decrease, and heavy rainy days in last 30 years have increased from 3.1 to 15 percent average. In addition, according to the annual ranking of rainfall occurs Top $10^{th}$ percentile of precipitation for 3IQR (inter quartile range) of the increasing trend, most of the precipitation at the point of increasing trend was confirmed. Quantile 90% percentile of the average rainfall 43.5mm, the increasing trend 0.1412mm/yr, Quantile 99% percentile of the average rainfall 68.0mm, the increasing trend in the 0.1314mm/yr were analyzed. The results can be used to analyze the recent increasing trend for the annual maximum value series information and the threshold extreme hydrologic information. And also can be used as a basis data for hydraulic structures design on reflect recent changes in climate characteristics.

• Magazine of the Korean Society of Agricultural Engineers
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• v.11 no.2
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• pp.1644-1650
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• 1969

In the design of general hydrological structures, it is well know that the design flood is of importance in the design of those structures. As the design flood is estimated using the design storm, the design storm is defined by the rainfall intensity itself. Though I had studied and reported many times the reports about the rainfall-intensity in my country, poorly I did not study the long-period variation of the intensity through each section in my country before. But now, in the basin area of the Han river and the Keum river, the self-recorded rainfall charts of the single storms, which are mostly above rainfall amount of 30mm and data of about 4500 with the 150 stationyear, were analyzed, And then, the intensity formula of the hourly unit is estimated using the period from 10 minutes to 5 days. The method to analyze and estimate them, and the final results will be summarized as mentioned below: (i) At first I intended to select out the homogeneous watersheds of three, one in the Han river and two in the Keum river. But I would select the northern and the sourthern river basins, and westward from Koan station, in the basins of the Han river. Also I would select the upstream area, and the downstream area including the watershed of Chungioo, Kongjoo, Chupungryung, and the Mt. Sock, in the basins of the Keum river. Finally, I could find that there couldn't in the Keum river basin. So, I decided out and analyze only river basins of the Han river with limitation mentioned above. (ii) The statistical method to select out the homogenous watersheds is the test of homogeneous variance, and it is estimated from the following equation: $$X_{k1}^2=[{\Sigma}(n_i-1)log\bar{S^2}-\Sigma(n_i-1)log\bar{S^2}]{\times}loge$$ (iii) Actually, each homogeneous watershed has individually its own intensity formula, But I would express them as the actual amount, because the equation of intensity variance is experiential and theoretical equation of the variance. Therefore the caluating equation is actually more convenient in the actual uses. (iv) This report is one of the series for me to give the basis to the actual designs. The cost for this study is provided by the Ministry of Construction. And the designs of the hydrological structures in the watersheds with limitation mentioned above may be concerned with and based upon this report.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.587-596
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• 2014

Soil moisture is one of the most important interests in hydrological response and the interaction between the land surface and atmosphere. Estimation of Antecedent Wetness Conditions (AWC) which is soil moisture condition prior to a rainfall in the basin should be considered for rainfall-runoff prediction. In this study, Soil Wetness Index (SWI), Antecedent Precipitation Index ($API_5$), remotely sensed Soil Moisture ($SM_{rs}$), and 5 days ground Soil Moisture ($SM_{g5}$) were selected to estimate the AWC at four study area in the Korean Peninsula. The remotely sensed soil moisture data were taken from the AMSR-E soil moisture archive. The maximum potential retention ($S_{obs}$) was obtained from direct runoff and rainfall using Soil Conservation Service-Curve Number (SCS-CN) method by rainfall data of 2011 for each study area. Results showed the great correlations between the maximum potential retention and SWI with a mean correlation coefficient which is equal to -0.73. The results of time length representing the time scale of soil moisture showed a gap from region to region. It was due to the differences of soil types and the characteristics of study area. Since the remotely sensed soil moisture has been proved as reasonable hydrological variables to predict a wetness in the basin, it should be continuously monitored.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.302-310
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• 2023

In this study, the extent of the impact of rainfall on the outbreak of fire blight during the blossom infection risk period was explored. In the Chungnam province, the outbreak of fire blight disease began in 2015, and changes in the outbreak's scale were most pronounced between 2020 and 2022, significantly escalating from 63 orchards in 2020 to 170 orchards in 2021, before decreasing to 46 orchards in 2022. In 2022, the number of incidence has decreased and the number of canker symptom in branches has also decreased. It was evaluated that the significant decrease of fire blight disease in 2022 was due to the dry weather during the flowering season. In other words, this yearly fluctuation in fire blight outbreaks was correlated with the presence or absence of rainfall and accumulated precipitation during the blossom infection risk period. This trend was observed across all surveyed regions where apples and pears were cultivated. Among the weather conditions influencing the blossom infection risk period, rainfall notably affected the activation of pathogens from over-wintering cankers and flower infections. In particular, precipitation during the initial 3 days of the blossom infection risk warning was confirmed as a decisive factor in determining the outbreak's scale.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.6
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• pp.615-631
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• 2012

This study provides an evaluation for capability of Integrated Climate and Air quality Modeling System (ICAMS) on future regional scale climate projection. Temperature and precipitation are compared between ground-level observation data and results of regional models (MM5) for the past 30 years over the Korean peninsula. The ICAMS successfully simulates the local-scale spatial/seasonal variation of the temperature and precipitation. The probability distribution of simulated daily mean and minimum temperature agree well with the observed patterns and trends, although mean temperature shows a little cold bias about $1^{\circ}C$ compared to observations. It seems that a systematic cold bias is mostly due to an underestimation of maximum temperature. In the case of precipitation, the rainfall in winter and light rainfall are remarkably simulated well, but summer precipitation is underestimated in the heavy rainfall phenomena of exceeding 20 mm/day. The ICAMS shows a tendency to overestimate the number of washout days about 7%. Those results of this study indicate that the performance of ICAMS is reasonable regarding to air quality predication over the Korean peninsula.

• Journal of Korea Water Resources Association
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• v.34 no.2
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• pp.119-130
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• 2001

At-site and regional frequency analyses of annual maximum 1-, 2-, and 3-days rainfall in Han River basin was performed and compared based on the regional L-moments algorithm. To perform regional frequency analysis, Han River basin was subdivided into 3 sub-basins such as South Han River, North Han River, and downstream regions. For each sub-basin, the discordancy and homogeneity tests were performed. As the results of goodness of fit tests, lognormal model was selected as an appropriate probability distribution for both South Han River and downstream regions and gamma-3 model for North han River region. From Monte carlo simulation, RBIAS and RRMSE of the estimated quantiles from regional frequency analysis and at-site frequency analysis were calculated and compared each other. Regional frequency analysis shows less RRMSE of the estimated quantiles than at-sites frequency analysis in overall return periods. The differences of BRMSE between two approaches increase as the return period increases. As a result, it is shown that regional frequency analysis performs better than at-site analysis for annual maximum rainfall data in Han River basin.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.398-398
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• 2015

To estimate and forecast runoff by using Aritifitial Neaural Networks model (ANNs). it has been studied in Thailand for the past 10 years. The model was developed in order to be conformed with the conditions in which the collected dataset is short and the amount of dataset is inadequate. Every year, the Northerpart of Thailand faces river overflow and flood inundation. The most important basin in this area is Yom basin. The purpose of this study is to forecast runoff at Y.14 gauge station (Si-Satchanalai district, Sukhothai province) for 3 days in advance. This station located at the upstream area of Yom River basin. Daily rainfall and daily runoff from Royal Irrigation Department and Meteorological Department during flood period 2000-2012 were used as input data. In order to check an accuracy of forecasting, forecasted runoff were compared with observed data by pursuing Nash Sutcliffe Efficiency (NSE) and Coefficient of Determination ($R^2$). The result of the first day gets the highest accuracy and then decreased in day 2 and day 3, consequently. NSE and $R^2$ values for frist day of runoff forecasting is 0.76 and 0.776, respectively. On the second day, those values are 0.61 and 0.65, respectively. For the third day, the aforementioned valves are 0.51 and 0.52, respectively. The results confirmed that the ANNs model can be used when the range of collected dataset is short and insufficient. In conclusion, the ANNs model is suitable for applying during flood incident because it is easy to use and does not require numerous parameters for simulating.