The objective of this study was to compare the rainfall-runoff characteristics in streams of classified urban and rural watershed using land use and population density. EMC (event mean concentration) of BOD, COD, TP and SS increased significantly in urban and rural watershed, but that of TN remained unchanged. Although there were no significant differences in EMC of BOD, COD, TN, TP depending on the watershed characteristics, EMC of BOD and COD significantly increased in the urban watershed, while EMC of TP increased in the rural watershed. In the urban watershed, the first flush time was faster and the first flush effect was stronger in BOD, COD, and TP. However, the difference between cumulative mass and cumulative volume was found to be less than 0.2 in the rural watershed, indicating a weak first flush effect. The discharged masses of BOD (70 %), COD (64 %), and TP (66 %) in the first flush of runoff were higher in urban watershed, while TN (67 %) was higher in rural watershed. The reproducibility of first flush time and the strength of first flush using CV (coefficient of variation) was found to be more reproducible for first flush time in both watersheds. In rural watershed, the CV value of first flush time for TP out of water quality parameters was lower. Whereas the CV values of first flush time for BOD, COD and TP in urban watersheds were similar.
The interest in hydrological modeling has increased significantly recently due to the necessity of watershed management, specifically in regards to lumped models, which are being prosperously utilized because of their relatively uncomplicated algorithms which require less simulation time. However, lumped models require empirical coefficients for hydrological analyses, which do not take into consideration the heterogeneity of site-specific characteristics. To overcome such obstacles, a distributed model was offered as an alternative and the number of researches related to watershed management and distributed models has been steadily increasing in the recent years. Thus, in this study, the feasibility of a grid-based rainfall-runoff model was reviewed using the flood runoff process in the Han River basin, including the ChungjuDam, HoengseongDam and SoyangDam watersheds. Hydrological parameters based on GIS/RS were extracted from basic GIS data such as DEM, land cover, soil map and rainfall depth. The accuracy of the runoff analysis for the model application was evaluated using EFF, NRMSE and QER. The calculation results showed that there was a good agreement with the observed data. Besides the ungauged spatial characteristics in the SoyangDam watershed, EFF showed a good result of 0.859.
Communications for Statistical Applications and Methods
/
v.31
no.3
/
pp.309-322
/
2024
Identifying algae in water is important for managing algal blooms which have great impact on drinking water supply systems. There have been various microscopic approaches developed for algae classification. Many of them are based on the morphological features of algae. However, there have seldom been mathematical frameworks for comparing the shape of algae, represented as a planar continuous curve obtained from an image. In this work, we describe a recent framework for computing shape distance between two different algae based on the elastic metric and a novel functional representation called the square root velocity function (SRVF). We further introduce statistical procedures for multiple shapes of algae including computing the sample mean, the sample covariance, and performing the principal component analysis (PCA). Based on the shape distance, we classify six algal species in watersheds experiencing algal blooms, including three cyanobacteria (Microcystis, Oscillatoria, and Anabaena), two diatoms (Fragilaria and Synedra), and one green algae (Pediastrum). We provide and compare the classification performance of various distance-based and model-based methods. We additionally compare elastic shape distance to non-elastic distance using the nearest neighbor classifiers.
Journal of the Korean Institute of Landscape Architecture
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v.48
no.1
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pp.25-34
/
2020
Land use in watersheds has been shown to be a major driving factor in determining the status of the water quality of streams. In this light, scientists have been investigating the roles of riparian vegetation on the relationships between land use in watersheds and the associated stream water quality. Numerous studies reported that riparian vegetation could alleviate the adverse effects caused by land use in watersheds and on stream water quality through various hydrological, biochemical and ecological mechanisms. However, this concept has been criticized as the true effects of riparian vegetation must be assessed by comprehensive models that mimic real environmental settings. This study aimed to estimate a comprehensive structural equation model integrating topography, land use, and characteristics of riparian vegetation. We used water quality data from the Nakdong River system monitored under the National Aquatic Ecosystem Monitoring Program (NAEMP) of the Korean Ministry of Environment (MOE). Also, riparian vegetation data and land use data were extracted from the Land Use/Land Cover map (LULC) produced by the MOE. The number of structural equation models (SEMs) were estimated in Amos of IBM SPSS. Study results revealed that land use was determined by elevation, and developed areas within a watershed significantly increased the concentration of Total Nitrogen (TN) in streams and LDI in riparian vegetation. On the contrary, developed areas significantly reduced LPI and PLAND. At the same time, PLAND and LDI significantly reduced the concentration of TN in streams. Thus, it was clear that developed areas in watersheds had both a direct and an indirect impact on the concentration of TN in streams, and spatial pattern and the amount of vegetation of riparian vegetation could significantly alleviate the negative impacts of developed areas on TN concentration in streams. To enhance stream water quality, reducing developed areas in a watershed is critical for long-term watershed management plans, restoration patterns for riparian vegetation could be immediately implemented since riparian areas were less developed than most other watersheds.
Kim, Jin-Ho;Choi, Chul-Mann;Kim, Won-Il;Lee, Jong-Sik;Jung, Goo-Bok;Han, Kuk-Heon;Ryu, Jong-Soo;Lee, Jung-Taek;Kwun, Soon-Kuk
Korean Journal of Environmental Agriculture
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v.26
no.1
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pp.17-24
/
2007
This study was carried out to classify the streams at rural watersheds by characteristics of water quality. The water quality data of 319 steams at rural watersheds in Korea were selected. Multivariate analysis was used for this purpose. The cases were divided into 5 types, and then factor analysis and cluster analysis were done. The characteristics of water quality of rural watersheds can be showed more than 40% of total water quality by first factor(organic matters and nutrients). The cluster analysis of extracted factors using factor analysis was carried out. The results showed that the Case 1 and Case 2 were classified 4 communities, Case 3 was classified 5 communities and Case 4 and 5 were classified 3 communities. Among 5 types cases, to classified the steams of rural watersheds, Case 4 - 7 water quality items - was selected as a desirable case. Many kinds of statistical analysis can be used to classify the streams of rural watersheds. Our results showed a good example to evaluate the water quality properties in Korean rural watershed.
Song, Chul Min;Kim, Jung Soo;Lee, Min Sung;Kim, Seo Jun;Shin, Hyung Seob
Ecology and Resilient Infrastructure
/
v.9
no.1
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pp.1-14
/
2022
The total maximum daily load (TMDL) implemented in Korea mainly manages the mainstream considering a single common pollutant and river discharge, and the river system is divided into unit watersheds. Changes in the water quality of managed rivers owing to the water quality management in tributaries and unit watersheds are not considered when implementing the TMDL. In addition, it is difficult to consider the difference in the load of pollutants generated in the tributary depending on the conditions of the water quality change in each unit watershed, even if the target water quality was maintained in the managed water system. Therefore, it is necessary to introduce the total maximum load management at tributaries to manage the pollution load of tributaries with a high degree of pollution. In this study, the HSPF model, a watershed runoff model, was applied to the target areas consisting of 53 sub-watersheds to analyze the effect of water quality changes the in tributaries on the mainstream. Sub-watersheds were selected from the three major areas of the Paldang water system, including the drainage basins of the downstream of the South Han-River, Gyeongan stream, and North Han-River. As a result, BOD ranged from 0.17 mg/L to 4.30 mg/L, and was generally high in tributaries and decreased in the downstream watershed. TP ranged from 0.02 mg/L - 0.22 mg/L, and the watersheds that had a large impact on urbanization and livestock industry were high, and the North Han-River basin was generally low. In addition, a pollution source reduction scenario was selected to analyze the change in water quality by the amount of pollution load discharged at each unit watershed. The reduction rate of BOD and TP according to the scenario changes was simulated higher in the watershed of the downstream of the North Han-River and downstream and midstream of the Gyeongan stream. It was found that the benefits of water quality reduction from each sub-watershed efforts to improve water quality are greatest in the middle and downstream of each main stream, and it is judged that it can be served as basic data for the management of total tributaries.
Rainfall-runoff prediction studies using deep learning while considering catchment attributes have been gaining attention. In this study, we selected two models: the Transformer model, which is suitable for large-scale data training through the self-attention mechanism, and the LSTM-based multi-state-vector sequence-to-sequence (LSTM-MSV-S2S) model with an encoder-decoder structure. These models were constructed to incorporate catchment attributes and predict the inflow of 10 multi-purpose dam watersheds in South Korea. The experimental design consisted of three training methods: Single-basin Training (ST), Pretraining (PT), and Pretraining-Finetuning (PT-FT). The input data for the models included 10 selected watershed attributes along with meteorological data. The inflow prediction performance was compared based on the training methods. The results showed that the Transformer model outperformed the LSTM-MSV-S2S model when using the PT and PT-FT methods, with the PT-FT method yielding the highest performance. The LSTM-MSV-S2S model showed better performance than the Transformer when using the ST method; however, it showed lower performance when using the PT and PT-FT methods. Additionally, the embedding layer activation vectors and raw catchment attributes were used to cluster watersheds and analyze whether the models learned the similarities between them. The Transformer model demonstrated improved performance among watersheds with similar activation vectors, proving that utilizing information from other pre-trained watersheds enhances the prediction performance. This study compared the suitable models and training methods for each multi-purpose dam and highlighted the necessity of constructing deep learning models using PT and PT-FT methods for domestic watersheds. Furthermore, the results confirmed that the Transformer model outperforms the LSTM-MSV-S2S model when applying PT and PT-FT methods.
Journal of the Korean Association of Geographic Information Studies
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v.20
no.3
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pp.141-152
/
2017
This paper presents a technical method for flood estimation based on satellite rainfall and satellite rainfall correction method for watersheds lacking measurement data. The study area was the Sebou Watershed, Morocco. The Integrated Flood Analysis System(IFAS) and Grid-based Rainfall-Runoff Model(GRM) were applied to estimate watershed runoff. Daily rainfall from ground gauges and satellite-derived hourly data were used. In the runoff simulation using satellite rainfall data, the composites of the daily gauge rainfall and the hourly satellite data were applied. The Shuttle Radar Topographic Mission Digital Elevation Model(SRTM DEM) with a 90m spatial resolution and 1km resolution data from Global map land cover and United States Food and Agriculture Organization(US FAO) Harmonized World Soil Database(HWSD) were used. Underestimated satellite rainfall data were calibrated using ground gauge data. The simulation results using the revised satellite rainfall data were $5,878{\sim}7,434m^3/s$ and $6,140{\sim}7,437m^3/s$ based on the IFAS and GRM, respectively. The peak discharge during flooding of Sebou River Watershed in 2009~2010 was estimated to range from $5,800m^3/s$ to $7,500m^3/s$. The flood estimations from the two hydrologic models using satellite-derived rainfall data were similar. Therefore, the calibration method using satellite rainfall suggested in this study can be applied to estimate the flood discharge of watersheds lacking observational data.
Fine sediment loadings from agricultural watersheds have led to habitat degradation in Lake Takkobu, northern Japan. Fifteen lake sediment core samples were obtained and analyzed to develop a chronology using physical sediment characters, $^{137}Cs$, and tephra. The reconstructed sedimentation rates over the past ca 300 years suggested that sedimentation rates increased drastically after land use development. With a natural sedimentation rate of 0.1-1.1 mm $year^{-1}$ until 1898, lake sedimentation accelerated to 0.6-12.8 mm $year^{-1}$ after 1898. The sedimentation rates after land use change, such as forestry, river engineering works, and agricultural development, were about 6-12 times higher than that under natural conditions, leading to accelerated lake shallowing over the last ca 100 years. Sedimentation rates between 1898 and 1963 differed with location in the lake because of spatial variation in the sediment flux from the contributing rivers and their watersheds. The sedimentation rate in the southern zone between 1898 and 1963 was significantly higher than that in the middle and northern zones, reflecting active sediment production associated with forestry for charcoal production and canal construction for transportation in the southern watersheds and wetlands. The sedimentation rate after 1963 did not vary among the three zones, because decreasing sedimentation was found in most of the southern sites whereas an increasing trend was observed in the middle and northern sites. This result can be explained by shallowing of lake-bottom morphology with sedimentation and the resultant reduction of sediment retention capacity in the southern zone. Moreover, the sedimentation rate at sampling sites close to river mouths increased by 5-32 times compared with natural rates before 1898. The Kushiro River, into which Lake Takkobu drains under regular flow conditions, further contributed to an increased sedimentation rate, because water from the Kushiro River flows back into Lake Takkobu during floods.
In order to estimate the non-point pollution loads from each watersheds among 209 watersheds, the calibration and validation of HSPF model were carried out based on 2012 in 2013 years. In the case of flow rate, R2 of calibration and validation were 0.71~0.93 and 0.71~0.79, which were relatively good values. With the respect to calibration of water quality, % differences between measured and simulated values were 0.4 ~ 9.7 of DO, BOD 0.5 ~ 30.2% and TN 1.9~28.6% except for Hwhangkang B site. In case of validation, DO was 0.2 ~ 13.7%, BOD 1.3~23% and TN 0.5~24.3% excluding Hwhangkang B. However, since the concentration of TP was very small compared with other items, the range of difference was large as 0.8~55.3%. level. As the result of calculating annual accumulative BOD loads for each watershed, it was found that RCH 123 (Uryeong, Gyeongsangnamdo), RCH 121 (Jinju, Gyeongsangnamdo) and RCH 92 (Daegu) were the high ranked. The unit watersheds including various landuse type susch as forest and agricultural sites in mainstream areas have a higher BOD nonpoint pollution load than those in dam regions. However, the results of the annual cumulative loading of the basins for nutrients did not appear to be consistent with the BOD annual cumulative loading ranks. Other factors that represent watershed characteristics such as landslope and soiltypes, including landuse pattern, have been found to be closely related to nonpoint pollutant loads.
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