• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.1
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• pp.1-10
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• 2023

This study aimed to confirm the importance ratio of climate and management variables on production of orchardgrass in Korea (1982-2014). For the climate, the mean temperature in January (MTJ, ℃), lowest temperature in January (LTJ, ℃), growing days 0 to 5 (GD 1, day), growing days 5 to 25 (GD 2, day), Summer depression days (SSD, day), rainfall days (RD, day), accumulated rainfall (AR, mm), and sunshine duration (SD, hr) were considered. For the management, the establishment period (EP, 0-6 years) and number of cutting (NC, 2nd-5th) were measured. The importance ratio on production of orchardgrass was estimated using the neural network model with the perceptron method. It was performed by SPSS 26.0 (IBM Corp., Chicago). As a result, EP was the most important variable (100%), followed by RD (82.0%), AR (79.1%), NC (69.2%), LTJ (66.2%), GD 2 (63.3%), GD 1 (61.6%), SD (58.1%), SSD (50.8%) and MTJ (41.8%). It implies that EP, RD, AR, and NC were more important than others. Since the annual rainfall in Korea is exceed the required amount for the growth and development of orchardgrass, the damage caused by heavy rainfall exceeding the appropriate level could be reduced through drainage management. It means that, when cultivating orchardgrass, factors that can be controlled were relatively important. Although it is difficult to interpret the specific effect of climates on production due to neural networking modeling, in the future, this study is expected to be useful in production prediction and damage estimation by climate change by selecting major factors.

• 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.18 no.3
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• pp.4195-4205
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• 1976

The purpose of this study is to evaluate the existing methods for calculating or estimating the consumptive use (Evaportranspiration) of any agricutural development project area. In determing the consumptive use water in the project area, there will require the best way for estimating irrigation requirement. Many methods for computing the evaportranspiration have been used, each of them with its merits and demerits at home and abroad. Some of these methods are listed as follows: 1.The Penman's formula 2.The B1aney-Criddle method 3.The Munson P.E. Index method 4.The Atmometer method 5.The Texas Water Rights Commission (TWRC) method 6.The Jensen-Haise method 7.The Christiasen method Therefore, the authors will introduce the more widely used method for calculating Consumptive Use by G.H. Hargreaves. The formula is expressed in the form Ep= K·d·T (1.0-0.01·Hn) Hn=1.0+0.4H+0.005H2. This method was adopted for the first time to determine the Irrigation requirements of Ogseo Comprehensive Agricultual Development project (Benefited area:100,500ha) in Korea. This method is presented in somewhat greater detail than the others. Formula is given for the computation of evaportranspiration (with various levels of data availability) Sampel computation of irrigation requirements for Ogseo irrigation project is included. The results and applied materials are summarized as follows. 1. In calculating the Hargreaves formula, the mean temperature relative, humidity, length of day, and percentage of sunshine from three stations of Iri, Jeonju, and Gunsan were used. 2. Monthly evaporation values were calculated by using the formula. 3. Meteological data from the three stations records for the ten years (1963∼1972) were used. 4. The annual irrigation requirements is 1,186mm per hectare, but the case to consider effective rainfall amount takes the annual irrigation demand being 700mm per hectare.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.407-407
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• 2019

According to Asian Development Bank report Pakistan is among water scarce countries. Climate scenario on the basis IPCC fifth assessment report (AR5) revealed that annual mean temperature of Pakistan from year 2010-2019 was $17C^o$ which will rise up to $21C^o$ at the end of this century, similarly almost 10% decrease of annual rainfall is expected at the end of the century. It is a changing task in underdeveloped countries like Pakistan to meet the water demands of rapidly increasing population in a changing climate. While many studies have tackled scarcity and stream flow forecasting of the Upper Indus Basin (UIB) Pakistan, very few of them are related to socio-economic and climate change impact on sustainable water management of UIB. This study investigates the pattern of current and future surface water availability for various demand sites (e.g. domestic, agriculture and industrial) under different socio-economic and climate change scenarios in Upper Indus Basin (UIB) Pakistan for a period of 2010 to 2050. A state-of-the-art planning tool Water Evaluation and Planning (WEAP) is used to analyze the dynamics of current and future water demand. The stream flow data of five sub catchment (Astore, Gilgit, Hunza, Shigar and Shoyke) and entire UIB were calibrated and validated for the year of 2006 to 2011 using WEAP. The Nash Sutcliffe coefficient and coefficient of determination is achieved ranging from 0.63 to 0.92. The results indicate that unmet water demand is likely to increase severe threshold and the external driving forces e.g. socio-economic and climate change will create a gap between supply and demand of water.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.490-499
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• 2000

Several studies on development of water quality treatment systems by wetlands are on going because of their benefits of low construction cost and high efficiency of waste water treatment. The objectives of this study were to review the necessary contents of survey and design factors for constructing constructed wetlands and to examine the required wetland area to treat non-point source pollution through case studies. The measurement of water quality and quantity in precipitation period is needed to analyse the inflow characteristics of the non-point pollution and to determine the amount of design flow. The design inflow for constructing constructed wetland was determined to the total runoff from 30mm of daily rainfall in the AMC(III) condition of the SCS method and is similar 70% of the annual mean runoff. The natural type wetland system with 0.1m of water depth and 5 hours of detention time was applied. From the results of the case studies, 70% of inflow could be treated and 1∼3% of wetland area of the total basin is needed.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.170-170
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• 2020

Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in the hydrologic field such as regression-based regional frequency analysis (RFA). The main purpose of this study is to compare two frameworks of RFA based on the artificial neural network (ANN) models: quantile regression technique (QRT-ANN) and parameter regression technique (PRT-ANN). As an output layer of the ANN model, the QRT-ANN predicts quantiles for various return periods whereas the PRT-ANN provides prediction of three parameters for the generalized extreme value distribution. Rainfall gauging sites where record length is more than 20 years were selected and their annual maximum rainfalls and various hydro-meteorological variables were used as an input layer of the ANN model. While employing the ANN model, 70% and 30% of gauging sites were used as training set and testing set, respectively. For each technique, ANN model structure such as number of hidden layers and nodes was determined by a leave-one-out validation with calculating root mean square error (RMSE). To assess the performances of two frameworks, RMSEs of quantile predicted by the QRT-ANN are compared to those of the PRT-ANN.

• Journal of Korean Society on Water Environment
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• v.22 no.4
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• pp.695-705
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• 2006

This study was carried out to make a basic information for establishment of countermeasures against water pollution of Hoengseong watershed, accordingly we investigated the characteristics of pollutants discharge and estimated the unit loads from Hoengseong watershed. Seven sites (S1~S7) were selected for sampling and samples were taken 4 times during the dry and rainy seasons, respectively. During rainfall events, measured site mean concentration (SMC) ranges of $BOD_5$, $COD_{Mn}$, TOC, SS, Turbidity, T-N and T-P were 0.8~1.3 mg/L, 2.3~6.3 mg/L, 1.284~2.110 mg/L, 3.4~69.3 mg/L, 2.36~52.68 NTU, 1.243~1.669 mg/L and 0.025~0.070 mg/L, respectively. And the calculated annual unit loads of $BOD_{5}$, $COD_{Mn}$, SS, T-N and T-P in Hoengseong watershed were 1.327 kg/ha/yr, 7.349 kg/ha/yr, 87.075 kg/ha/yr, 1.848 kg/ha/yr and 0.103 kg/ha/yr, respectively. It was difficult to directly compare the unit loads proposed in this study with the estimated existing those. Because the unit loads in this paper were estimated not by land use types, but by complex land use of non-urban area. From the survey results, they showed that the unit loads in Hoengseong watershed were similar to those exisiting in the forest area, and showed lower than those existing in the paddy/dry field.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.815-826
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• 2012

The underestimating trend using existing ordinary regression (OR) based trend analysis has been a well-known problem. The existing OR method based on least squares approximate the conditional mean of the response variable given certain values of the time t, and the usual assumption of the OR method is normality, that is the distribution of data are not dissimilar form a normal distribution. In this regard, this study proposed a quantile regression that aims at estimating either the conditional median or other quantiles of the response variable. This study assess trend in annual daily maximum rainfall series over 64 weather stations through both in OR and QR approach. The QR method indicates that 47 stations out of 67 weather stations are a strong upward trend at 5% significance level while OR method identifies a significant trend only at 13 stations. This is mainly because the OR method is estimating the condition mean of the response variable. Unlike the OR method, the QR method allows us flexibly to detect the trends since the OR is designed to estimate conditional quantiles of the response variable. The proposed QR method can be effectively applied to estimate hydrologic trend for either non-normal data or skewed data.

• Korean Journal of Ecology and Environment
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• v.33 no.4 s.92
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• pp.342-349
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• 2000

This paper demonstrates the influence of intensity of the monsoon on morpho-hydrological fluctuations in Taechung Reservoir during 1993${\sim}$1994. During the study, hydrological variables including rainfall, inflow, and discharge volume showed distinct contrast between 1993 and 1994. Interannaul differences in rainfall occurred during the monsoon in July${\sim}$August monsoon and influenced inflow, discharge, and water residence time (WRT). Total inflow in 1993 was four times greater than that of 1994, and summer inflow in 1993 was 8 times greater than summer 1994. Annual Mean WRT was 93.2 d in 1993 vs. 158.6 d in 1994 and the largest differences occurred between monsoons of 1993 and 1994. Morphometric variables reflected the interannual contrasts of hydrology, so that in 1993 surface area, total volume, shoreline development, and mean depth increased consistently from premonsoon to postmonsoon and over this same period in 1994 they decreased. This outcome indicates that the area of shallow littoral zones in 1993 was greater than in 1994. Also, the drainage area to surface area (D/L) at 80 m MSL was 60.7 which was much greater than values in Soyang and Andong reservoirs and natural lakes world-wide. The morpho-hydrodynamic conditions seemed to influence in-reservoir nutrient concentration which is one of the most important factors regulating the eutrophication processes. I believe, under the maximum hydrodynamic fluctuations in Korean waterbodies during the monsoon, applications of mass balance models to man-made lakes for assessments of external loading should be considered because the models can be used under the seasonally stable inflow and water residence time.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.1
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• pp.58-66
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• 2014

Water pollution problems of urban rivers due to the urbanization and industrialization have been the subject of public attention. In particular, considering the fact that the characteristics of water cycle of each basin change dramatically through the development of new towns, a large number of concerns about future water quality have been raised. However, reasonable measures to predict future water quality quantitatively have not been presented by this moment. In this study, by the linkage of annual unit load generation based on long-term monitoring results of the ministry of environment (MOE) to a semi-distributed rainfall runoff model, SWMM (Storm Water Management Model), we proposed a new methodology to estimate future water quality macroscopically and testified it to verify its applicability for the estimation of future water quality of a small watershed at G new town. As a result of the estimation using Y-EMC (Yearly based Event Mean Concentration), future water quality were simulated as BOD 18.7, T-N 16.1 and T-P 0.85 mg/L respectively which could not achieve the grade III of domestic river life guidance and these criteria could be satisfied by the reduction of domestic wastewater discharge load by over 80%. The results of this study are shown to be utilized for one of basic tools to estimate and manage water quality of urban rivers in the course of new town developments.