Korean Journal of Agricultural and Forest Meteorology
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v.13
no.2
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pp.69-78
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2011
Rice is one of the world's staple foods. Paddy rice fields have unique biophysical characteristics that the rice is grown on flooded soils unlike other crops. Information on the spatial distribution of paddy fields and the timing of irrigation are of importance to determine hydrological balance and efficiency of water resource management. In this paper, we detected the timing of irrigation and spatial distribution of paddy fields using the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the NASA EOS Aqua satellite. The timing of irrigation was detected by the combined use of MODIS-based vegetation index and Land Surface Water Index (LSWI). The detected timing of irrigation showed good agreement with field observations from two flux sites in Korea and Japan. Based on the irrigation detection, a land cover map of paddy fields was generated with subsidiary information on seasonal patterns of MODIS enhanced vegetation index (EVI). When the MODISbased paddy field map was compared with a land cover map from the Ministry of Environment, Korea, it overestimated the regions with large paddies but underestimated those with small and fragmented paddies. Potential reasons for such spatial discrepancies may be attributed to coarse pixel resolution (500 m) of MODIS images, uncertainty in parameterization of threshold values for discarding forest and water pixels, and the application of LSWI threshold value developed for paddy fields in China. Nevertheless, this study showed that an improved utilization of seasonal patterns of MODIS vegetation and water-related indices could be applied in water resource management and enhanced estimation of evapotranspiration from paddy fields.
Over the last twenty years, farmers in Western Australia have begun to change land management practices to minimise the effects of salinity to agricultural land. A farm plan is often used as a guide to implement changes. Most plans are based on minimal data and an understanding of only surface water flow. Thus farm plans do not effectively address the processes that lead to land salinisation. A project at Broomehill in the south-west of Western Australia applied an approach using a large suite of geospatial data that measured surface and subsurface characteristics of the regolith. In addition, other data were acquired, such as information about the climate and the agricultural history. Fundamental to the approach was the collection of airborne geophysical data over the study area. This included radiometric data reflecting soils, magnetic data reflecting bedrock geology, and SALTMAP electromagnetic data reflecting regolith thickness and conductivity. When interpreted, these datasets added paddock-scale information of geology and hydrogeology to the other datasets, in order to make on-farm and in-paddock decisions relating directly to the mechanisms driving the salinising process. The location and design of surface-water management structures such as grade banks and seepage interceptor banks was significantly influenced by the information derived from the airborne geophysical data. To evaluate the effectiveness ofthis planning., one whole-farm plan has been monitored by the Department of Agriculture and the farmer since 1996. The implemented plan shows a positive cost-benefit ratio, and the farm is now in the top 5% of farms in its regional productivity benchmarking group. The main influence of the airborne geophysical data on the farm plan was on the location of earthworks and revegetation proposals. There had to be a hydrological or hydrogeological justification, based on the site-specific data, for any infrastructure proposal. This approach reduced the spatial density of proposed works compared to other farm plans not guided by site-specific hydrogeological information.
Song, Tae Yoon;Yoo, Man Ho;Lee, In Ho;Kang, Eue-Tae;Kim, Mi Ok;Choi, Joong Ki
Korean Journal of Ecology and Environment
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v.47
no.2
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pp.71-81
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2014
A survey was carried out to understand the influence of hydrology on the composition, abundance and adaptive strategies of phytoplankton in artificial Lake Hwaseong, an estuarine reservoir with seawater exchange through a sluice. Samples were collected seven times from May to October 2012. Hydrological events (seawater exchange, rainfall) resulted in a wide variation in salinity along with nutrients and turbidity. Shifts in the dominant phytoplankton composition occurred on every survey. Chlorophyll-a ranged from 9.7 to $104.1{\mu}g\;L^{-1}$. Multivariate analysis allowed us to identify the four phases on phytoplankton community change. Phase I (May~June) was characterized by small-sized Gymnodinium sp. and Heterosigma akashiwo dominated in warm temperature and high salinity derived from seawater exchange, and followed by Cylindrotheca closterium blooms due to rainfall and winds during phase II (July and September). During phase III (August), the dominance of Oscillatoria spp. was correlated with high temperature and low salinity. Abundant cryptomonads were associated with lower temperature during phase IV (October). Adaptive strategies were identified in the phytoplankton as morphological and physiological characteristics. These strategies identified small-sized flagellates as CR-strategists, fast-growing opportunistic species, which might favor the weak stratification of lake due to the seawater exchange during phase I and IV. Dominant species during phase II and III were characterized with R-strategists, medium-sized stress-tolerant species, which might favor turbulence by river flow. The results indicate that stronger stratification following the termination of seawater exchange for the freshening might intensify the predominance of smaller flagellates. In conclusion, this study suggests that hydrology may drive phytoplankton community change and blooms through the controls of salinity, turbulence and nutrients.
This study was carried out to determine the variation of the water level and crosssection area for investigating changes of stream foreland, and to determine the correlation between the average flow velocity and cross-section area so as to understand the hydrological characteristics of the stream. The slope of the cross-sectional area was changed in water levels of 0.6~1.0 m and 1.8~2.0 m. The first change occurred in the low-water level season, and the second change occurred in the high-water level seasons. It is assumed that the changes occurred due to the geological transfigure. The correlation between the cross-sectional area and the average flow velocity was 0.22~0.86 in the exponential equation and 0.20~0.87 in the linear equation. The low water level had a higher correlation than the high water level, and free weirs in the upper stream showed a very low correlation. Therefore, this study provides novel information for the management of water quality in the riverside, using correlation equations of the water level and flow velocity with the cross section area.
A mathematical modeling program called Hydrological Simulation Program-FORTRAN (HSPF) developed by the United States Environmental Protection Agency(EPA) was applied to the Yongdam Watershed to examine its applicability for loading estimates in watershed scale. It was run under BASINS (Better Assessment Science for Integrating point and Nonpoint Sources) program, and the model was validated using monitoring data of 2002 ${\sim}$ 2003. The model efficiency of runoff was high in comparison between simulated and observed data, while it was relatively low in the water quality parameters. But its reliability and performance were within the expectation considering complexity of the watershed and pollutant sources and land uses intermixed in the watershed. The estimated pollutant load from Yongdam watershed for BOD, T-N and T-P was 1,290,804 kg $yr{-1}$, 3,753,750 kg $yr{-1}$ and 77,404 kg $yr{-1}$,respectively. Non-point source (NPS) contribution was high showing BOD 57.2%, T-N 92.0% and T-P 60.2% of the total annual loading in the study area. The NPS loading during the monsoon rainy season (June to September) was about 55 ${\sim}$ 72% of total NPS loading, and runoff volume was also in a similar rate (69%). However, water quality was not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. Overall, the BASINS/HSPF was applied to the Yongdam watershed successfully without difficulty, and it was found that the model could be used conveniently to assess watershed characteristics and to estimate pollutant loading in watershed scale.
In 2020, South Korea initiated research and development of a longitudinal connectivity evaluation between upstream and downstream based on stream ecosystem health. This study analyzed the migration of upstream and downstream migratory fish species, fish distribution characteristics, trophic guilds, tolerance guilds, and species composition changes from 2015 to 2020 at Songrim weir in Yeongok stream, where the cross-structure of an ice harbor-type fishway for fish movement was recently improved. A total of 5,136 fish, including 36 species, were collected and three major migratory fishes were identified, namely, Tribolodon hakonensis, Plecoglossus altivelis altivelis, and Oncorhynchus keta. According to the comparative analysis before (Pre-I) and after (Post-I) improvement of the fishway, the relative abundance of primary freshwater fish increased in the upstream section, while the number of migratory fishes decreased. The fish species that used the fishway in the Songrim weir were Tribolodon hakonensis (58.4%) and Plecoglossus altivelis altivelis(11.8%). According to the Wilcoxon Signed-Rank Test migratory fish showed a statistically significant difference (p<0.05) in the upstream and downstream, showing a biological improvement effect of the crossstructure. On the other hand, the annual change of migratory fish based on the MannKendall trend test did not significantly increase or decrease (p>0.05). Therefore, in the fish passage improvement project, it is necessary not only for physical, hydrological, and structural tests, but also for pre- and post-biological tests on the use and improvement effect of fishway.
Kim, Seoyeon;Jeong, Yemin;Cho, Subin;Youn, Youjeong;Kim, Nari;Lee, Yangwon
Korean Journal of Remote Sensing
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v.36
no.6_1
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pp.1465-1483
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2020
Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.
In this study, a two-dimensional numerical model (Nays2DH) was applied to analyze the process of morphological changes in the river channel bed depending on the changes in the amount of flooding after fully opening the Sejong weir, which was constructed upstream of the Geum River. For this, numerical simulations were performed by assuming the flow conditions, such as a non-uniform flow (NF), unsteady flows (single flood event, SF), and a continuous flood event (CF). Here, in the cases of the SF and CF, the normalized hydrograph was calculated from real flood events, and then the hydrograph was reconfigured by the peak flow discharge according to the scenario, and then it was employed as the flow discharge at the upstream boundary condition. In this study, to quantitatively evaluate the morphological changes, we analyzed the time changes in the bed deformation the bed relief index (BRI), and we compared the aerial photographs of the study area and the numerical simulation results. As simulation results of the NF, when the steady flow discharge increases, the ratio of lower width to depth decreases and the speed of bar migration increases. The BRI initially increases, but the amount of change decreased with time. In addition, when the steady flow discharge increases, the BRI increased. In the case of SF, the speed of bar migration decreased with the change of the flow discharge. In terms of the morphological response to the peak flood discharge, the time lag also indicated. In other words, in the SF, the change of channel bed indicates a phase lag with respect to the hydraulic condition. In the result of numerical simulation of CF, the speed of bar migration depending on the peak flood discharges decreased exponentially despite the repeated flood occurrences. In addition, as in the result of SF, the phase lag indicated, and the speed of bar migration decreased exponentially. The BRI increased with time changes, but the rate of increase in the BRI was modest despite the continuous peak flooding. Through this study, the morphological changes based on the hydrological characteristics of the river were analyzed numerically, and the methodology suggested that a quantitative prediction for the river bed change according to the flow characteristic can be applied to the field.
Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.
Jung, Sungho;Le, Xuan Hien;Kim, Yeonsu;Choi, Hyungu;Lee, Giha
Journal of Korea Water Resources Association
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v.54
no.spc1
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pp.1095-1105
/
2021
The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.
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