• Journal of Biosystems Engineering
• /
• v.43 no.4
• /
• pp.426-439
• /
• 2018

Purpose: To continuously monitor soil and climatic properties, a data acquisition system (DAQ) was developed and tested in plum farms (Gyewol-ri and Haechang-ri, Suncheon, Korea). Methods: The DAQ consisted of a Raspberry-Pi processor, a modem, and an ADC board with multiple sensors (soil moisture content (SEN0193), soil temperature (DS18B20), climatic temperature and humidity (DHT22), and rainfall gauge (TR-525M)). In the laboratory, various tests were conducted to calibrate SEN0193 at different soil moistures, soil temperatures, depths, and bulk densities. For performance comparison of the SEN0193 sensor, two commercial moisture sensors (SMS-BTA and WT-1000B) were tested in the field. The collected field data in Raspberry-Pi were transmitted and stored on a web server database through a commercial communications wireless network. Results: In laboratory tests, it was found that the SEN0193 sensor voltage reading increased significantly with an increase in soil bulk density. A linear calibration equation was developed between voltage and soil moisture content depending on the farm soil bulk density. In field tests, the SEN0193 sensor showed linearity (R = 0.76 and 0.73) between output voltage and moisture content; however, the other two sensors showed no linearity, indicating that site-specific calibration is important for accurate sensing. In the long-term monitoring results, it was observed that the measured climate temperature was almost the same as website information. Soil temperature information was higher than the values measured by DS18B20 during spring and summer. However, the local rainfall measured using TR 525M was significantly different from the values on the website. Conclusion: Based on the test results obtained using the developed monitoring system, it is thought that the measurement of various parameters using one device would be helpful in monitoring plum growth. Field data from the local farm monitoring system can be coupled with website information from the weather station and used more efficiently.

• Atmosphere
• /
• v.25 no.4
• /
• pp.611-622
• /
• 2015

Heavy rainfall ($>30mm\;hr^{-1}$) over the Korean Peninsula is examined in order to understand thermo-dynamic characteristics of the atmosphere, using radiosonde observational data from seven upper-air observation stations during the last 17 years (1997~2013). A total of 82 heavy rainfall cases during the summer season (June-August) were selected for this study. The average values of thermo-dynamic indices of heavy rainfall events are Total Precipitable Water (TPW) = 60 mm, Convective Available Potential Energy (CAPE) = $850J\;kg^{-1}$, Convective Inhibition (CIN) = $15J\;kg^{-1}$, Storm Relative Helicity (SRH) = $160m^2s^{-2}$, and 0~3 km bulk wind shear = $5s^{-1}$. About 34% of the cases were associated with a Changma front; this pattern is more significant than other synoptic pressure patterns such as troughs (22%), migratory cyclones (15%), edges of high-pressure (12%), typhoons (11%), and low-pressure originating from Changma fronts (6%). The spatial distribution of thermo-dynamic conditions (CAPE and SRH) is similar to the range of thunderstorms over the United States, but extreme conditions (supercell thunderstorms and tornadoes) did not appear in the Korean Peninsula. Synoptic conditions, vertical buoyancy (CAPE, CIN), and wind parameters (SRH, shear) are shown to discriminate among the environments of the three types. The first type occurred with high CAPE and low wind shear by the edge of the high pressure pattern, but Second type is related to Changma front and typhoon, exhibiting low CAPE and high wind shear. The last type exhibited characteristics intermediate between the first and second types, such as moderate CAPE and wind shear near the migratory cyclone and trough.

• Water for future
• /
• v.14 no.4
• /
• pp.53-72
• /
• 1981

In this study, South Korea is divided into 5 zones and is studied about the analysis of time-regional distribution of previpitation frequency and rainfall intensity in Korea. In the previpitation frequency analysis, the basic data groups of 39 stations were selected. The diagram of previpitation frequency was drawn, and the time-regional distribution of precipitation frequency was analized. In the rainfall intensity analysis, the basic data groups of 36 stations were selected. The probable rainfall, I-D-F curve, and regression equation between 24hr. and 10min.-18hr. areal depth were obtained. The results of this study are following; 1) The precipitation class of max. recurrence probability in every season except summer was commonly (1) 1-5mm, (2) 0.1-1mm, (3) 5-10mm in order. 2) The zone of max. recurrence frequency owing to the precipitation class was zone II in precipitation frequency of below 20mm, zone IV in precipitation frequency of 30-40mm, zone I in precipitation frequency of above 70mm for a year. 3) The recurrence probability of precipitation in Korea can be represented to the equation of exponential function; $$W(x)=e^{\alpha+\beta}$$ 4) The first and third zones were expected heavy rain for the short and long duration. 5) The I.D.F. curves were drawn, and established that the time interval for the least deviation of I.D.F curve is 10~40min., 40min. -4hr., 4~24hr. 6) The regression equations of areal mean depth between 24hr. and 10min.-18hr. for each zone were obtained. 7)The probable rainfall of 36 points were calculated.

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

• Journal of Korea Water Resources Association
• /
• v.54 no.12
• /
• pp.1285-1294
• /
• 2021

In recent years, as rainfall is concentrated and rainfall intensity increases worldwide due to climate change, the scale of flood damage is increasing. Rainfall of a previously unobserved magnitude falls, and the rainy season lasts for a long time on record. In particular, these damages are concentrated in ASEAN countries, and at least 20 million people among ASEAN countries are affected by frequent flooding due to recent sea level rise, typhoons and torrential rain. Korea supports the domestic flood warning system to ASEAN countries through various ODA projects, but the communication network is unstable, so there is a limit to the central control method alone. Therefore, in this study, an artificial intelligence-based flood prediction model was developed to develop an observation station that can observe water level and rainfall, and even predict and warn floods at once at one observation station. Training, validation and testing were carried out for 0.5, 1, 2, 3, and 6 hours of lead time using the rainfall and water level observation data in 10-minute units from 2009 to 2020 at Junjukbi-bridge station of Seolma stream. LSTM was applied to artificial intelligence algorithm. As a result of the study, it showed excellent results in model fit and error for all lead time. In the case of a short arrival time due to a small watershed and a large watershed slope such as Seolma stream, a lead time of 1 hour will show very good prediction results. In addition, it is expected that a longer lead time is possible depending on the size and slope of the watershed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.12
• /
• pp.603-611
• /
• 2020

Potholes on the road directly affect drivers' safety, satisfaction, and vehicle damage. Thus, real-time detection and response are required. Increasing frequency of patrols allows for potholes to be detected and responded to quickly, but this takes much manpower, money, and time. In addition, potholes have different occurrence characteristics depending on the rain conditions, so it is necessary to consider the optimal frequency from an economic and road-service perspective. Therefore, a quantitative analysis was done on the effects of rainfall on the occurrence characteristics of potholes. Information on the persistence, impact of rainfall intensity, and weather information was collected over a long period. Based on the results, a risk-based, optimized, and changeable road-patrol strategy is presented. The analysis results show that the probability of pothole occurrence increases by 2.4 times in rainy weather. Furthermore, the impact continues for 3 days even after the rain stops. The probability of pothole occurrence increases by 0.46% per 1 mm of rainfall, and the occurrence characteristics react sensitively to even a small amount of rain of around 1 mm. It was concluded that road patrol is required at least once every three days for an effect-free period, while twice a day is needed for the "sphere of influence" period to achieve a 95% reliability level.ys for effect-free period, while twice a day for sphere of influence period to satisfy 95% reliability level.

• Journal of Korea Water Resources Association
• /
• v.54 no.11
• /
• pp.955-968
• /
• 2021

A water resource plan is routinely based on a natural flow and can be estimated using observed streamflow data or a long-term continuous rainfall-runoff model. However, the watershed with the natural flow is very limited to the upstream area of the dam. In particular, for the ungauged watershed, a rainfall-runoff model is established for the gauged watershed, and the model is then applied to the ungauged watershed by transferring the associated parameters. In this study, the GR4J rainfall-runoff model is mainly used to regionalize the parameters that are estimated from the 14 dam watershed via an optimization process. In terms of optimizing the parameters, the Bayesian approach was applied to consider the uncertainty of parameters quantitatively, and a number of parameter samples obtained from the posterior distribution were used for the regionalization. Here, the relationship between the estimated parameters and the topographical factors was first identified, and the dependencies between them are effectively modeled by a Copula function approach to obtain the regionalized parameters. The predicted streamflow with the use of regionalized parameters showed a good agreement with that of the observed with a correlation of about 0.8. It was found that the proposed regionalized framework is able to effectively simulate streamflow for the ungauged watersheds by the use of the regionalized parameters, along with the associated uncertainty, informed by the basin characteristics.

• Journal of Korea Water Resources Association
• /
• v.55 no.7
• /
• pp.545-556
• /
• 2022

It is recommended to use long-term hydrometeorological data for more than the service life of the hydraulic structures and water resource planning. For the purpose of expanding rainfall data, stochastic simulation models, such as Modified Bartlett-Lewis Rectangular Pulse (BLRP) and Neyman-Scott Rectangular Pulse (NSRP) models, have been widely used. The optimal parameters of the model can be estimated by repeatedly comparing the statistical moments defined through a combination of parameters of the probability distribution in the optimization context. However, parameter estimation using relatively small observed rainfall statistics corresponds to an ill-posed problem, leading to an increase in uncertainty in the parameter estimation process. In addition, as shown in previous studies, extreme values are underestimated because objective functions are typically defined by the first and second statistical moments (i.e., mean and variance). In this regard, this study estimated the parameters of the NSRP model using the objective function with the third moment and compared it with the existing approach based on the first and second moments in terms of estimation of extreme rainfall. It was found that the first and second moments did not show a significant difference depending on whether or not the skewness was considered in the objective function. However, the proposed model showed significantly improved performance in terms of estimation of design rainfalls.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.6B
• /
• pp.597-603
• /
• 2006

The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.

• Journal of Korean Society on Water Environment
• /
• v.24 no.2
• /
• pp.230-238
• /
• 2008

This study evaluated the economic aspect of the rainwater harvesting facilities by hydrologically analyzing the inflow, rainwater consumption, rainfall loss, tank storage, and overflow time series to derive the net rainwater consumption and the number of days of rainwater available. This study considers several rainwater harvesting facilities in Seoul National University, Korea Institute of Construction Technology and Daejon World Cup Stadium and the results derived are as follows. (1) Increasing the water consumption decreases the number of days of rainwater available. (2) Due to the climate in Korea, a larger tank storage does not increase the amount and the number of days of water consumption during wet season (June to September), but a little in October. (3) Economic evaluation of the rainwater harvesting facilities considered in this study shows no net benefit (private benefit). (5) Flood reduction effect of rainwater harvesting facilities was estimated very small to be about 1% even in the case that 10% of all the basin is used as the rainwater collecting area.