The objective of this study was to evaluate biological water quality using fish assemblages in Nakdong River watershed. We selected 6 sites along the main axis of the river and evaluated the Index of Biological Integrity (IBI), Qualitative Habitat Evaluation Index (QHEI) and chemical water quality during July 2004${\sim}$March 2006. For the study, we applied the 10 metric IBI model, which was developed for national biological water quality criteria. Nakdong River's IBI value averaged 20.8 (n=14) during the study which means poor biological water quality. Physical habitat health at all sites, based on QHEI model, was measured as 110, indicating fair${\sim}$good condition. The habitat health varied depending on the locations sampled. Habitat health in sites 1 and 6 was judged as good, while the health in sites 3 and 4 was $poor{\sim}fair$. Especially, we found the metric values of $M1{\sim}M5$, M7, M10 were low in sites 3 and 4 compared to other sites. In these sites, thus, habitat restoration of substrate composition, riffles, and bank vegetation may be necessary. In the mean time, chemical water quality, based on BOD, COD, TSS, and nutrients, had no large spatial and temporal variations. Overall data analysis indicated that site 3 was largely impacted by the polluted-tributary, Keumho River and the downstreams showed better water quality due to the dilution of the polluted river water by Nam River and Hwang River.
Net radiation is the total amount of radiation energy used as a heat flux for the Earth's energy cycle, and net radiation from the surface is an important factor in areas such as hydrology, climate, meteorological studies and agriculture. It is very important to monitoring the net radiation through remote sensing to be able to understand the trend of heat island and urbanization phenomenon. However, net radiation estimation using only remote sensing data is generally causes difference in accuracy depending on cloud. Therefore, in this paper, we retrieved and monitored high resolution surface net radiation at 1 hour interval in Eunpyeong New Town where urbanization using Communication, Ocean and Meteorological Satellite (COMS), Landsat-8 satellite and Computational Fluid Dynamics (CFD) model data reflecting the difference in building height. We compared the observed and estimated net radiation at the flux tower. As a result, estimated net radiation was similar trend to the observed net radiation as a whole and it had the accuracy of RMSE $54.29Wm^{-2}$ and Bias $27.42Wm^{-2}$. In addition, the calculated net radiation showed well the meteorological conditions such as precipitation, and showed the characteristics of net radiation for the vegetation and artificial area in the spatial distribution.
This study aims to offer basic data to effectively preserve and manage pine forests using more precise pine forests' distribution status. In this regard, this study predicts the geographical distribution change of pine forests growing in South Korea, due to climate change, and evaluates the spatial distribution characteristics of pine forests by age. To this end, this study predicts the potential distribution change of pine forests by applying the MaxEnt model useful for species distribution change to the present and future climate change scenarios, and analyzes the effects of bioclimatic variables on the distribution area and change by age. Concerning the potential distribution regions of pine forests, the pine forests, aged 10 to 30 years in South Korea, relatively decreased more. As the area of the region suitable for pine forest by age was bigger, the decreased regions tend to become bigger, and the expanded regions tend to become smaller. Such phenomena is conjectured to be derived from changing of the interaction of pine forests by age from mutual promotional relations to competitive relations in the similar climate environment, while the regions suitable for pine forests' growth are mostly overlap regions. This study has found that precipitation affects more on the distribution of pine forests, compared to temperature change, and that pine trees' geographical distribution change is more affected by climate's extremities including precipitation of driest season and temperature of the coldest season than average climate characteristics. Especially, the effects of precipitation during the driest season on the distribution change of pine forests are irrelevant of pine forest's age class. Such results are expected to result in a reduction of the pine forest as the regions with the increase of moisture deficiency, where climate environment influencing growth and physiological responses related with drought is shaped, gradually increase according to future temperature rise. The findings in this study can be applied as a useful method for the prediction of geographical change according to climate change by using various biological resources information already accumulated. In addition, those findings are expected to be utilized as basic data for the establishment of climate change adaptation policies related to forest vegetation preservation in the natural ecosystem field.
Kim, Minyoung;Choi, Yonghun;O'Shaughnessy, Susan;Colaizzi, Paul;Kim, Youngjin;Jeon, Jonggil;Lee, Sangbong
Journal of The Korean Society of Agricultural Engineers
/
v.61
no.6
/
pp.111-121
/
2019
Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.
Ha, Kyoochul;Park, Changhui;Kim, Sunghyun;Shin, Esther;Lee, Eunhee
Economic and Environmental Geology
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v.54
no.2
/
pp.161-176
/
2021
In this study, one of the distributed hydrologic models, VELAS, was used to analyze the variation of hydrologic elements based on water balance analysis to evaluate the groundwater recharge in more detail than the annual time scale for the past and future. The study area is located in Yanggok-ri, Seobu-myeon, Hongseong-gun, Chungnam-do, which is very vulnerable to drought. To implement the VELAS model, spatial characteristic data such as digital elevation model (DEM), vegetation, and slope were established, and GIS data were constructed through spatial interpolation on the daily air temperature, precipitation, average wind speed, and relative humidity of the Korea Meteorological Stations. The results of the analysis showed that annual precipitation was 799.1-1750.8 mm, average 1210.7 mm, groundwater recharge of 28.8-492.9 mm, and average 196.9 mm over the past 18 years from 2001 to 2018 in the study area. Annual groundwater recharge rate compared to annual precipitation was from 3.6 to 28.2% with a very large variation and average 14.9%. By the climate change RCP 8.5 scenario, the annual precipitation from 2019 to 2100 was 572.8-1996.5 mm (average 1078.4 mm) and groundwater recharge of 26.7-432.5 mm (average precipitation 16.2%). The annual groundwater recharge rates in the future were projected from 2.8% to 45.1%, 18.2% on average. The components that make up the water balance were well correlated with precipitation, especially in the annual data rather than the daily data. However, the amount of evapotranspiration seems to be more affected by other climatic factors such as temperature. Groundwater recharge in more detailed time scale rather than annual scale is expected to provide basic data that can be used for groundwater development and management if precipitation are severely varied by time, such as droughts or floods.
Kim, Geunah;Youn, Youjeong;Kang, Jonggu;Choi, Soyeon;Park, Ganghyun;Chun, Junghwa;Jang, Keunchang;Won, Myoungsoo;Lee, Yangwon
Korean Journal of Remote Sensing
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v.38
no.5_1
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pp.627-646
/
2022
Recently, the seriousness of climate change-related problems caused by global warming is growing, and the average temperature is also rising. As a result, it is affecting the environment in which various temperature-sensitive creatures and creatures live, and changes in the ecosystem are also being detected. Seasons are one of the important factors influencing the types, distribution, and growth characteristics of creatures living in the area. Among the most popular and easily recognized plant seasonal phenomena among the indicators of the climate change impact evaluation, the blooming day of flower and the peak day of autumn leaves were modeled. The types of plants used in the modeling were forsythia and cherry trees, which can be seen as representative plants of spring, and maple and ginkgo, which can be seen as representative plants of autumn. Weather data used to perform modeling were temperature, precipitation, and solar radiation observed through the ASOS Observatory of the Korea Meteorological Administration. As satellite data, MODIS NDVI was used for modeling, and it has a correlation coefficient of about -0.2 for the flowering date and 0.3 for the autumn leaves peak date. As the model used, the model was established using multiple regression models, which are linear models, and Random Forest, which are nonlinear models. In addition, the predicted values estimated by each model were expressed as isopleth maps using spatial interpolation techniques to express the trend of plant seasonal changes from 2003 to 2020. It is believed that using NDVI with high spatio-temporal resolution in the future will increase the accuracy of plant phenology modeling.
Terrestrial ecosystem plays the important role as carbon sink in the global carbon cycle. Understanding of interactions of terrestrial carbon cycle with climate is important for better prediction of future climate change. In this paper, terrestrial carbon cycle is investigated by Hadley Centre Global Environmental Model, version 2, Carbon Cycle (HadGEM2-CC) that considers vegetation dynamics and an interactive carbon cycle with climate. The simulation for future projection is based on the three (8.5/4.5/2.6) representative concentration pathways (RCPs) from 2006 to 2100 and compared with historical land carbon uptake from 1979 to 2005. Projected changes in ecological features such as production, respiration, net ecosystem exchange and climate condition show similar pattern in three RCPs, while the response amplitude in each RCPs are different. For all RCP scenarios, temperature and precipitation increase with rising of the atmospheric $CO_2$. Such climate conditions are favorable for vegetation growth and extension, causing future increase of terrestrial carbon uptakes in all RCPs. At the end of 21st century, the global average of gross and net primary productions and respiration increase in all RCPs and terrestrial ecosystem remains as carbon sink. This enhancement of land $CO_2$ uptake is attributed by the vegetated area expansion, increasing LAI, and early onset of growing season. After mid-21st century, temperature rising leads to excessive increase of soil respiration than net primary production and thus the terrestrial carbon uptake begins to fall since that time. Regionally the NEE average value of East-Asia ($90^{\circ}E-140^{\circ}E$, $20^{\circ}N{\sim}60^{\circ}N$) area is bigger than that of the same latitude band. In the end-$21^{st}$ the NEE mean values in East-Asia area are $-2.09PgC\;yr^{-1}$, $-1.12PgC\;yr^{-1}$, $-0.47PgC\;yr^{-1}$ and zonal mean NEEs of the same latitude region are $-1.12PgC\;yr^{-1}$, $-0.55PgC\;yr^{-1}$, $-0.17PgC\;yr^{-1}$ for RCP 8.5, 4.5, 2.6.
Hwang River in South Korea, has experienced channel adjustments due to dam construction. Hapcheon main dam and re-regulation dam. The reach below the re-regulation dam (45 km long) changed in flow regime, channel width, bed material distribution, vegetation expansion, and island formation after dam construction. The re-regulation dam dramatically reduced annual peak flow from 654.7 $m^3$/s to 126.3 $m^3$/s and trapped the annual 591 thousand $m^3$ of sediment load formerly delivered from the upper watershed since the completion of the dam in 1989. An analysis of a time series of aerial photographs taken in 1982, 1993, and 2004 showed that non-vegetated active channel width narrowed an average of 152 m (47% of 1982) and non-vegetated active channel area decreased an average of 6.6 km2 (44% of 1982) between 1982 and 2004, with most narrowing and decreasing occurring after dam construction. The effects of daily pulses of water from peak hydropower generation and sudden sluice gate operations are investigated downstream of Hapcheon Dam in South Korea. The study reach is 45 km long from the Hapcheon re-regulation Dam to the confluence with the Nakdong River. An analysis of a time series of aerial photographs taken in 1982, 1993, and 2004 showed that the non-vegetated active channel width narrowed an average of 152 m (47% reduction since 1982). The non-vegetated active channel area also decreased an average of 6.6 $km^2$ (44% reduction since 1982) between 1982 and 2004, with most changes occurring after dam construction. The average median bed material size increased from 1.07 mm in 1983 to 5.72 mm in 2003, and the bed slope of the reach decreased from 0.000943 in 1983 to 0.000847 in 2003. The riverbed vertical degradation is approximately 2.6 m for a distance of 20 km below the re-regulation dam. It is expected from the result of the unsteady sediment transport numerical model (GSTAR-1D) steady simulations that the thalweg elevation will reach a stable condition around 2020. The model also confirms the theoretical prediction that sediment transport rates from daily pulses and flood peaks are 21 % and 15 % higher than their respective averages.
This study was aimed at looking into the distribution status and age structure of Abies holophylla population in Sudo-Am temple forest. It was found that a total of 302 individuals of Abies holophylla existed which were more than 2m in height within the study area. Furthermore the population size is one of the largest in the southern region of Korea. The CBH of Abies holophylla ranged from 1.5 cm to 500.8 cm. Age structure of Abies holophylla looks like a gourd-shaped bottle. This means that they have an unstable structure status and do not survive very long. This status results from a variety of factors including, vegetation succession, anthropogenic activities, and global warming. The environmental characteristics of Abies holophylla population was $931{\pm}64.5m$ in mean altitude, $19.2{\pm}8.7^{\circ}$ in mean slope in the northeastern and southeastern area of the slope direction, and $1,324,323{\pm}174,459wh\;m^{-2}$ in average of direct normal irradiation. Among the site environmental factors, the significant ones which influence the potential habitat for Abies holophylla distribution were chosen using the MaxEnt model. According to the results of this study, altitude and slope were found as the important factors. The average value of environmental conditions by ROC analysis were altitude 903.2 m, slope $20.04^{\circ}$, irradiation $1,352.248wh\;m^{-2}$, and the southeastern aspect.
This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.
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