• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.271-271
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• 2015

The Ecuadorian coast has two different climate regions. One is humid region where the annual rainfall is above 2000 mm and rain falls in almost all months of the year, and the other is dry region where the annual rainfall can fall below 50 mm and rainfall can be very seasonal. The agriculture is frequently limited by the seasons during the year and the availability of rainfall amounts. The corn fields in Ecuador are cultivated during the rainy season, due to this reason. The weather conditions for optimum development of corn growth require a monthly average rainfall of 120 mm to 140 mm and a temperature range of $22^{\circ}C{\sim}32^{\circ}C$ for the dry region, and a monthly average rainfall of 200 mm to 400 mm and a temperature range of $25^{\circ}C{\sim}30^{\circ}C$ for the humid area. The objective of this study is to predict how the weather conditions are going to change in corn fields of the coastal region of Ecuador in the future decades. For this purpose, this study selected six General Circulation Models (GCM) including BCC-CSM1-1, IPSL-CM5A-MR, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, MRIC-CGC3 with different climate scenarios of the RCP 4.5, RCP 6.0, and RCP 8.5, and applied for the period from 2011 to 2100. The climate variables information was obtained from the INAMHI (National Institute of Meteorology and Hydrology) in Ecuador for the a base line period from 1986 to 2012. The results indicates that two regions would experience significant changes in rainfall and temperature compared to the historical data. In the case of temperature, an increment of $1^{\circ}C{\sim}1.2^{\circ}C$ in 2025s, $1.6^{\circ}C{\sim}2.2^{\circ}C$ in 2055s, $2.1^{\circ}C{\sim}3.5^{\circ}C$ in 2085s were obtained from the dry region while less increment were shown from the humid region with having an increment of $1^{\circ}C$ in 2025s, $1.4^{\circ}C{\sim}1.8^{\circ}C$ in 2055s, $1.9^{\circ}C{\sim}3.2^{\circ}C$ in 2085s. Significant changes in rainfall are also projected. The rainfall projections showed an increment of 8%~11% in 2025s, 21%~33% in 2055s, and 34%~70% in 2085s for the dry region, and an increment of 2%~10%, 14%~30% and 23%~57% in 2025s, 2055s and 2085s decade respectively for humid region.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.5
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• pp.116-126
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• 2002

Discharge pattern and water quality were investigated in the drainage water from about 10 ha of groundwater-irrigated paddy field in the growing season of 2001. Total discharge quantity was about 1,117.2 mm in which about 75% was caused by management drainage due to cultural practice of paddy rice farming and the rest by rainfall runoff where total rainfall was about 515 mm. Dry-day sampling data showed wide variations in constituent concentrations with average of 26.14 mg/L, 0.37 mg/L, 3.54 mg/L at the inlet, and 43.60 mg/L, 0.34 mg/L, 3.58 mg/L at the outlet for CO $D_{cr}$ , T-P, and T-N, respectively. Wet-day sampling data demonstrated that generally CO $D_{cr}$ followed the discharge pattern and T-P was in opposite to the discharge pattern, but T-N did not show apparent pattern to the discharge. Discharge and load are in strong relationship. And based on regression equation, pollutant loads from groundwater irrigation area are estimated to be 288.34, 1.17, and 5.45 kg/ha for CO $D_{cr}$ , T-P, and T-N, respectively, which was relatively lower than the literature value from surface water irrigation area which implies that groundwater irrigation area might use less irrigation water and result in less drainage water, Therefore, total pollutant load from paddies irrigation with groundwater could be significantly lower than that with surface water. This study shows that agricultural drainage water management needs a good care of drainage outlet as well as rainfall runoff. This study was based on limited monitoring data of one year, and further monitoring and successive analysis are recommended for more generalized conclusion.

• Magazine of the Korean Society of Agricultural Engineers
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• v.7 no.1
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• pp.861-876
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• 1965

During my stay in the Netherlands, I have studied the following, primarily in relation to the Mokpo Yong-san project which had been studied by the NEDECO for a feasibility report. 1. Unit hydrograph at Naju There are many ways to make unit hydrograph, but I want explain here to make unit hydrograph from the- actual run of curve at Naju. A discharge curve made from one rain storm depends on rainfall intensity per houre After finriing hydrograph every two hours, we will get two-hour unit hydrograph to devide each ordinate of the two-hour hydrograph by the rainfall intensity. I have used one storm from June 24 to June 26, 1963, recording a rainfall intensity of average 9. 4 mm per hour for 12 hours. If several rain gage stations had already been established in the catchment area. above Naju prior to this storm, I could have gathered accurate data on rainfall intensity throughout the catchment area. As it was, I used I the automatic rain gage record of the Mokpo I moteorological station to determine the rainfall lntensity. In order. to develop the unit ~Ydrograph at Naju, I subtracted the basic flow from the total runoff flow. I also tried to keed the difference between the calculated discharge amount and the measured discharge less than 1O~ The discharge period. of an unit graph depends on the length of the catchment area. 2. Determination of sluice dimension Acoording to principles of design presently used in our country, a one-day storm with a frequency of 20 years must be discharged in 8 hours. These design criteria are not adequate, and several dams have washed out in the past years. The design of the spillway and sluice dimensions must be based on the maximun peak discharge flowing into the reservoir to avoid crop and structure damages. The total flow into the reservoir is the summation of flow described by the Mokpo hydrograph, the basic flow from all the catchment areas and the rainfall on the reservoir area. To calculate the amount of water discharged through the sluiceCper half hour), the average head during that interval must be known. This can be calculated from the known water level outside the sluiceCdetermined by the tide) and from an estimated water level inside the reservoir at the end of each time interval. The total amount of water discharged through the sluice can be calculated from this average head, the time interval and the cross-sectional area of' the sluice. From the inflow into the .reservoir and the outflow through the sluice gates I calculated the change in the volume of water stored in the reservoir at half-hour intervals. From the stored volume of water and the known storage capacity of the reservoir, I was able to calculate the water level in the reservoir. The Calculated water level in the reservoir must be the same as the estimated water level. Mean stand tide will be adequate to use for determining the sluice dimension because spring tide is worse case and neap tide is best condition for the I result of the calculatio 3. Tidal computation for determination of the closure curve. During the construction of a dam, whether by building up of a succession of horizontael layers or by building in from both sides, the velocity of the water flowinii through the closing gapwill increase, because of the gradual decrease in the cross sectional area of the gap. 1 calculated the . velocities in the closing gap during flood and ebb for the first mentioned method of construction until the cross-sectional area has been reduced to about 25% of the original area, the change in tidal movement within the reservoir being negligible. Up to that point, the increase of the velocity is more or less hyperbolic. During the closing of the last 25 % of the gap, less water can flow out of the reservoir. This causes a rise of the mean water level of the reservoir. The difference in hydraulic head is then no longer negligible and must be taken into account. When, during the course of construction. the submerged weir become a free weir the critical flow occurs. The critical flow is that point, during either ebb or flood, at which the velocity reaches a maximum. When the dam is raised further. the velocity decreases because of the decrease\ulcorner in the height of the water above the weir. The calculation of the currents and velocities for a stage in the closure of the final gap is done in the following manner; Using an average tide with a neglible daily quantity, I estimated the water level on the pustream side of. the dam (inner water level). I determined the current through the gap for each hour by multiplying the storage area by the increment of the rise in water level. The velocity at a given moment can be determined from the calcalated current in m3/sec, and the cross-sectional area at that moment. At the same time from the difference between inner water level and tidal level (outer water level) the velocity can be calculated with the formula $h= \frac{V^2}{2g}$ and must be equal to the velocity detertnined from the current. If there is a difference in velocity, a new estimate of the inner water level must be made and entire procedure should be repeated. When the higher water level is equal to or more than 2/3 times the difference between the lower water level and the crest of the dam, we speak of a "free weir." The flow over the weir is then dependent upon the higher water level and not on the difference between high and low water levels. When the weir is "submerged", that is, the higher water level is less than 2/3 times the difference between the lower water and the crest of the dam, the difference between the high and low levels being decisive. The free weir normally occurs first during ebb, and is due to. the fact that mean level in the estuary is higher than the mean level of . the tide in building dams with barges the maximum velocity in the closing gap may not be more than 3m/sec. As the maximum velocities are higher than this limit we must use other construction methods in closing the gap. This can be done by dump-cars from each side or by using a cable way.e or by using a cable way.

• Water for future
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• v.9 no.2
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• pp.67-75
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• 1976

With 9 existng reservoirs selected in the Sab-Gyo River Basin, the sedimentation of the reservoirs has been calculated by comparing the present capacity with the original value, which revealed its reduced reservoirs capacity. The reservoirs has a total drainage area of 6,792 ha, with a total capacity of 1,204.09 ha-m, and are short of water supply due to reduction of reservoirs capacity. Annual sedimention in the reservcire is relation to the drainage area, the mean of annual rain fall, and the slop of drainage area. The results of obtained from the investigation are summarized as follow; (1) A sediment deposition rate is very high, being about $9.19{m}^3/ha$ of drainage area, and resulting in the average decrease of reservoir capacity by 19.1%. This high rate of deposition could be mainly attributed to the serve denvdation of forests due to disor derly cuttings of tree. (2) An average unit storage of 415.8mm as the time of initial construation is decreesed to 315.59mm at present, as resultting, we could'nt supply water at 566.24ha. (3) A sediment deposition rate as a relation to the capacity of unit drainage area is as follow; $Qs=1.43 (c/a)^{0.531}$ (4) A sediment deposition rate as a relation to the mean of annval rainfall is as follow; $Qs=672.61 p^{0.024}$ (5) A sediment deposition rate as a relation to the mean slop of drainage area is follow; $Qs=267.21 S^{0.597}$

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.102-114
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• 2017

The purpose of this study was the assessment of the accuracy of Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG), a rainfall data source derived from satellite images, for evaluation of its applicability to use in ungauged or inaccessible areas. The study area was the overall area of the Korean peninsula divided into six regions. Automated Surface Observing System (ASOS) rainfall data from the Korean Meteorological Administration and IMERG satellite rainfall were used. Their average correlation coefficient was 0.46 for a 1-h temporal resolution, and it increased to 0.69 for a 24-h temporal resolution. The IMERG data quantitatively estimated less than the rainfall totals from ground gauges, and the bias decreased as the temporal resolution was decreased. The correlation coefficients of the two rainfall events, which had relatively greater rainfall amounts, were 0.68 and 0.69 for a 1-h temporal resolution. Additionally, the spatial distributions of the ASOS and IMERG data were similar to each other. The study results showed that the IMERG data were very useful in the assessment of the hydro-meteorological characteristics of ungauged or inaccessible areas. In a future study, verification of the accuracy of satellite-derived rainfall data will be performed by expanding the analysis periods and applying various statistical techniques.

• Journal of Environmental Science International
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• v.7 no.1
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• pp.1-7
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• 1998

This paper alms to estimate the change point of the precipitation in Pusan area using the several statistical approaches. The data concerning rainfall are extracted from the annual climatological report and monthly weather report issued by the Korean Meteorological Administration. The average annual precipitation at Pusan is 1471.6 mm, with a standard deviation of 406.0 mm, less than the normal(1486.0 mm). The trend of the annual precipitation is continuously decreasing after 1991 as a change point. And the statistical tests such as t-test and Wilcoxon rank sum test reveals that the average annual precipitation of after 1991 is less than that of before 1991 at 10% significance level. And the mean gnu성 precipitation In Kyongnam districts is also continuously decreasing after 1991 same as Pusan.

• Korean Journal of Ecology and Environment
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• v.56 no.3
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• pp.259-267
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• 2023

This study analyzed the relationship between distribution of Bolboschoenus planiculmis which is main food source of swans (national monument species) with environmental factors, discharge, rainfall, and salinity in Eulsuk-do from 2020 to 2023. The distribution area of B. planiculmis in Eulsuk tidal flat was 103,672m² in 2020, 95,240 m² in 2021, 88,163 m² in 2022, and 110,879 m² in 2023, and represents a sharp decrease compared to the 400,925 m² area recorded in 2004. From 2020 to 2023, the growth densities of B. planiculmis were 243.6±12.5 m^-2, 135.45±7.38 m^-2, 51.10±2.54 m^-2, and 238.20±16.36 m^-2, respectively, and the biomass was 199.89±28.01 gDW m^-2, 18.57±5.12 gDW m^-2, 6.55±1.12 gDW m^-2, and 153.53±25.43 gDW m^-2 in 2020, 2023, 2021, and 2022, respectively. Based on discharge during May~July, which affects plant growth, the left gate discharge of the estuary barrage from 2020 to 2023 was 62,322 m³ sec^-1, 33,329 m³ sec^-1, 6,810 m³ sec^-1, and 93,641 m³ sec^-1, respectively; rainfall was 1,136 mm, 799 mm, 297 mm, and 993 mm, respectively; and average salinity was 14.7±9.4 psu, 21.1±4.7 psu, 26.1±2.7 psu, and 14.5±11.1 psu, respectively. In 2022, cumulative rainfall (978 mm, about 70% of the 30-year average) and discharge (43,226 m³ sec^-1) decreased sharply, resulting in the highest mean salinity (25.46 psu), and the distribution area, density, and biomass of the B. planiculmis decreased sharply. In 2023, there was a rise in discharge with an increase in rainfall, leading to a decrease in salinity. Consequently, this environmental change facilitated the recovery of B. planiculmis growth.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.78-88
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• 2006

This paper is to apply Geographical Information System (GIS) supported Geomorphoclimatic Instantaneous Unit Hydrograph (GCIUH) approach for the calculated flash flood trigger rainfall of the mountainous area. GIS techniques was applied in geography data construction such as average slope, drainage area, channel characteristics. Especially, decided stream order using GIS at stream order decision that is important for input variable of GCIUH. We compared the GCIUH peak discharge with the existing report using the design storm at Chundong basin($14.58km^2$). The results showed that derived the GCIUH was a very proper method in the calculation of mountaunous discharge. At the Chundong basin, flash flood trigger rainfall was 12.57mm in the first 20 minutes when the threshold discharge was $11.42m^3/sec$.

• Spatial Information Research
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• v.17 no.3
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• pp.261-268
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• 2009

This study accomplished to draw a soil erosion map and a grade map of soil loss hazard in Korea. RUSLE and Rainfall-runoff (R) factor, which was estimated by using the rainfall data observed in 59 meteorological stations from 1977 to 2006 (for 30 years). FARD was used to analyze the frequency, and the whole country R factor was estimated according to the frequency. In the analysis of estimating the whole country R factor, Nakdong river has the smallest vaule, but Han river has the biggest value. According to the result of analyzing soil loss, soil loss occurred in a grass land, a bare land and a field in size order, and also approximately 17.2 ton/ha soil loss happened on the whole area. The average soil loss amount by the unit area takes place in a bare land and a grass land a lot. The total amount of soil loss in 5-year-frequency rainfall yields 15,000 ton and, what is more, a lot of soil loss happens in a paddy field, a forest and a crop field. The grade map of soil loss hazard is drawn up by classifying soil loss hazard grade by 5. As a result of analyzing soil loss, the moderate area which is the soil loss hazard grade 2 takes up the largest part, 72.8% of the total soil loss hazard area, on the contrary, the severe soil loss hazard area takes up only $1,038km^2$ (1.1%) of the whole area. The severe soil loss hazard area by land cover shows $93.5km^2$ in a bare land, $168.1km^2$ in a grass land and $327.4km^2$ in a crop field respectively.

• Journal of Korea Water Resources Association
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• v.36 no.4
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• pp.521-531
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• 2003

Pollutant load to Yongdam Reservoir considering rainfall effect is estimated using data collected during dry and wet days between Dec 1998 and Oct. 1999. Limit of significant rainfall was assumed to be as 10 mm/day and numbers of days of significant rainfall for each month were counted using 10 years of meteorological data of the study area. Water quality input concentrations were estimated by taking weighted averages of concentrations in dry and wet days in each month. The resulting concentrations were used as inputs for water quality modeling of Yongdam Reservoir. When rainfall effect was included average reservoir concentrations of BOD, TN and TP were increased by 70％, 5％ and 27％, respectively Considering the fact that Korea is under the significant influence of monsoon effect during the summer, it should be important to include rainfall effect in estimating pollutant input to receiving waters. This method is expected to increase reliability of annual water quality modeling results by providing realistic input data.