Irrigation return flow plays an important role in river flow forecasting, basin water supply planning, and determining irrigation water use. Therefore, accurate calculation of irrigation return flow rate is essential for the rational use and management of water resources. In this study, EPA-SWMM (Environmental Protection Agency-Storm Water Management Model) modeling was used to analyze the irrigation return flow and return flow rate of each intake work using irrigation canal network. As a result of the EPA-SWMM, we tried to estimate the quick return flow and delayed return flow using the water supply, paddy field, drainage, infiltration, precipitation, and evapotranspiration. We selected 9 districts, including pumping stations and weirs, to reflect various characteristics of irrigation water, focusing on the four major rivers (Hangang, Geumgang, Nakdonggang, Yeongsangang, and Seomjingang). We analyzed the irrigation period from May 1, 2021 to September 10, 2021. As a result of estimating the irrigation return flow rate, it varied from approximately 44 to 56%. In the case of the Gokseong Guseong area with the highest return flow rate, it was estimated that the quick return flow was 4,677 103 m3 and the delayed return flow was 1,473 103 m3, with a quick return flow rate of 42.6% and a delayed return flow rate of 13.4%.
A Study on the Attributes Classification of Agricultural Land Based on Deep Learning Comparison of Accuracy between TIF Image and ECW Image
In this study, We conduct a comparative study of deep learning-based classification of agricultural field attributes using Tagged Image File (TIF) and Enhanced Compression Wavelet (ECW) images. The goal is to interpret and classify the attributes of agricultural fields by analyzing the differences between these two image formats. “FarmMap,” initiated by the Ministry of Agriculture, Food and Rural Affairs in 2014, serves as the first digital map of agricultural land in South Korea. It comprises attributes such as paddy, field, orchard, agricultural facility and ginseng cultivation areas. For the purpose of comparing deep learning-based agricultural attribute classification, we consider the location and class information of objects, as well as the attribute information of FarmMap. We utilize the ResNet-50 instance segmentation model, which is suitable for this task, to conduct simulated experiments. The comparison of agricultural attribute classification between the two images is measured in terms of accuracy. The experimental results indicate that the accuracy of TIF images is 90.44%, while that of ECW images is 91.72%. The ECW image model demonstrates approximately 1.28% higher accuracy. However, statistical validation, specifically Wilcoxon rank-sum tests, did not reveal a significant difference in accuracy between the two images.
Determination of Flood-limited Water Levels of Agricultural Reservoirs Considering Irrigation and Flood Control
김지혜 Kim Jihye , 곽지혜 Kwak Jihye , 전상민 Jun Sang Min , 이성학 Lee Sunghack , 강문성 Kang Moon Seong
In this study, we developed a method to determine the flood-limited water levels of agricultural reservoirs, considering both their irrigation and flood control functions. Irrigation safety and flood safety indices were defined to be applied to various reservoirs, allowing for a comprehensive assessment of the irrigation and flood control properties. Seasonal flood-limited water level scenarios were established to represent the temporal characteristics of rainfall and agricultural water supply and the safety indices were analyzed according to these scenarios. The optimal scenarios were derived using a schematic solution based on Pareto front analysis. The method was applied to Obong, Yedang, and Myogok reservoirs, and the results showed that the characteristics of each reservoir were well represented in the safety indices. The irrigation safety of Obong reservoir was found to be significantly influenced by the late-stage flood-limited water level, while those of Yedang and Myogok reservoir were primarily affected by the early and mid-stage flood-limited water levels. The values of irrigation safety and flood safety indices for each scenario were plotted as points on the coordinate plane, and the optimal flood-limited water levels were selected from the Pareto front. The storage ratio of the optimal flood-limited water levels for the early, mid, and late stages were 65-70%, 70%, and 75% for Obong reservoir, 75%, 70-75%, and 65-70% for Yedang reservoir, and 75-80%, 70%, and 50% for Myogok reservoir. We expect that the method developed in this study will facilitate efficient reservoir operations.
A Sensitivity of Simulated Runoff Characteristics on the Different Spatial Resolutions of Precipitation Data
Rainfall data is one of the most important data in hydrologic modeling. In this study, the impacts of spatial resolution of precipitation data on hydrological responses were assessed using SWAT in the Santa Fe River Basin, Florida. High correlations were found between the FAWN and NLDAS rainfall data, which are observed weather data and simulated weather data based on observed data, respectively. FAWN-based scenarios had higher maximum rainfall and more rainfall days and events compared to NLDAS-based scenarios. Downstream areas showed lower correlations between rainfall and peak discharge than upstream areas due to the characteristics of study site. All scenarios did not show significant differences in base flow, and showed less than 5% of differences in high flows among NLDAS-based scenarios. The impact of resolution will appear differently depending on the characteristics of the watershed and topography and the applied model, and thus, is a process that must be considered in advance in runoff simulation research. The study suggests that applying the research method to watersheds in Korea may yield more pronounced results, and highlights the importance of considering data resolution in hydrologic modeling.
To improve the problem that the settlement curve of the consolidation theory of Terzaghi does not match well with the actual settlement curve, we included a secondary compression settlement and analyzed it by varying the beginning point and then obtained the following results. The current methods of calculating the compression index from the e-logσ curve and the coefficient of consolidation from the time-dependent settlement curve for each consolidation pressure proved that the final settlement amount will be consistent after a long time, but the actual settlement amount will always be smaller than the predicted settlement amount during the settlement progress stage. The consolidation factors estimated by the curve fitting with the condition that the secondary compression begins in the second half of the primary compression showed similar values to the consolidation factors estimated by the curve fitting for the primary compression only, and the settlement curves were in better agreement throughout the compression. It showed different values, showing low validity. It can be inferred that secondary compression acts from the point when a significant portion of the excess pore water pressure is dissipated, and the loading stress begins to have more influence on the skeletal structure of the soil. Analysis results show that secondary compression begins at the range of 91 % to 98 % on the average degree of primary consolidation.
Development of an Inventory-Based Flood Loss Estimation Method for Rural Areas
김시내 Kim Sinae , 이종혁 Lee Jonghyuk , 전상민 Jun Sang-min , 최원 Choi Won , 강문성 Kang Moon-seong
In recent times, the frequency and intensity of natural disasters, such as heavy rains and typhoons, have been increasing due to the impacts of climate change. This has led to a rise in social and economic damages. Rural areas, in particular, possess limited disaster response capabilities due to their underdeveloped infrastructure and are highly vulnerable to flooding. Therefore, it is crucial to establish preventative and responsive measures. In this study, an Inventory-Based Flood Loss Estimation (IB-FLE) method utilizing high-resolution spatial information was developed for estimating flood-related losses in rural areas. Additionally, the developed approach was applied to a study area and compared with the Multidimensional Flood Damage Analysis (MD-FDA) method. Compared to the MD-FDA, the IB-FLE enables faster and more accurate estimation of flood damages and allows for the assessment of individual building and agricultural land losses using up-to-date information. The findings of this study are expected to contribute to the rational allocation of budgets for rural flood damage prevention and recovery, as well as enhancing disaster response capabilities.
A Satellite Imagery-Based Survey of Reclaimed Land in South Pyongan Province, North Korea
조정호 Cho Jung-ho , 김혁 Kim Hyuk , 남원호 Nam Won-ho , 김관호 Kim Kwan-ho
This study surveyed the actual status of reclamation areas in South Pyongan Province, North Korea, using satellite images and literature to survey the creation date, area, and length of the embankment of the reclamation areas. The reclamation areas in South Pyongan Province were created in three stages, with the first stage completed in the late 1970s or early 1980s, the second stage in the late 1980s or early 1990s, and the third stage in the 2000s. The total area of the reclamation areas is 105,570 hectares. The land cover of the reclamation areas is as follows: agriculture (50.5%), saltern (29.5%), water bodies (13.6%), foreshore (12.4%), grasslands (3.0%), bare land (0.4%), facility (0.1%), and forests (0.1%). The study also found that the NDVI values of the reclamation areas vary depending on the location. The NDVI values of the Gwiseong and Namyang reclamation areas are low, while the NDVI values of the Samcheonpo and Jigdongbaedali reclamation areas are high. The study found that the NDVI values of the reclamation areas are correlated with the land cover of the reclamation areas. The study’s findings can be used to understand the development direction and regional characteristics of the reclamation areas in South Pyongan Province. The study’s findings can also be used to develop policies and plans for the sustainable development and utilization of the reclamation areas in South Pyongan Province.
Analysis of Groundwater Conductivity and Water Temperature Changes in Greenhouse Complex by Water Curtain Cultivation
This study aimed to analyze the impact of water curtain cultivation in the greenhouse complexes on groundwater’s electric conductivity and water temperature. The greenhouse complexes are mainly situated along rivers to secure water resources for water curtain cultivation. We classified the groundwater monitoring well into the greenhouse (riverside) and field cultivation areas (plain) to compare the groundwater impact of water curtain cultivation in the greenhouse complex. The groundwater observation network in Miryang, Gyeongsangnam-do, located downstream of the Nakdong River, was selected for the study area. As a result of analyzing the electric conductivity and water temperature, the following differences were found in the observed characteristics by region. 1) The electric conductivity and water temperature of the riverside area, where the permeability is high and close to rivers, showed a constant pattern of annual changes due to the influence of river flow and precipitation. 2) The flat land in general agricultural areas showed general characteristics of bedrock observation in the case of water temperature. Still, it seemed more affected by the surrounding well's water use and water quality. The electric conductivity did not show any particular trend and was influenced by the surrounding environment according to the location of each point.
