• Title/Summary/Keyword: precipitation indicators

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A Study on the Differences in Body Condition, Size, and Climate Environment According to Sex of Kaloula borealis (맹꽁이(Kaloula borealis)의 성별에 따른 신체 상태와 크기 및 기후환경 차이에 관한 연구)

  • Il-Nam Kim;Min Seock Do;Sang-Cheol Lee;Yang-Seop Bae
    • Journal of Wetlands Research
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    • v.26 no.2
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    • pp.160-167
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    • 2024
  • The amphibians serve as environmental indicator species warning of threats from pollution and development, and information regarding their body condition and surrounding habitat can be utilized as crucial indicators for assessing ecosystem health. The objective of this study was to investigate the differences in body condition and the climate environments according to the season and sex of Class II endangered Kaloula borealis. A total of 53 surveys were conducted from June to October 2018, targeting frogs inhabiting the Godeok-dong area of Gangdong-gu, Seoul. Using the weight and length of each individual, the body condition index (SMI, Scaled mass index) was calculated. Results showed a total capture of 396 individuals, consisting of 235 males and 161 females. Females exhibited longer SVL and greater weight compared to males, with higher body condition indices. Monthly body condition indices were lower for males in June, while no differences were observed between males and females from July to September. Among the climate environments where females and males appeared, environmental variables related to precipitation and humidity showed differences. These research findings are deemed crucial for providing fundamental information to ascertain suitable habitats for Kaloula borealis and selecting alternative habitats due to developmental impacts in the future.

Effects of Impact of Climate Change on Livestock Productivity - For bullocks, dairy, pigs, laying hens, and broilers - (기후변화가 축산 생산성에 미치는 영향 -거세우, 낙농, 양돈, 산란계, 육계를 대상으로-)

  • Lee, H.K.;Park, H.M.;Shin, Y.K.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.20 no.1
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    • pp.107-123
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    • 2018
  • The global impact of climate change on agriculture is now increasing. The purpose of this study was to investigate the effect of climate change on livestock productivity. The variables that have the greatest influence on climate change factors were examined through previous studies and expert surveys. We also used the actual productivity data of livestock farmers to investigate the relationship with climate change. In order to evaluate the climate for changes in livestock productivity, national representative data (such as bullocks, dairy, pigs, laying hens, and broilers) were surveyed in Korea. Also, to select and classify evaluation indexes, we selected climate change factor variables as prior studies and studied the weighting factor of climate variable factors. In this study, the researchers of industry, academia, and farmers in the livestock sector conducted questionnaires on the indicators of vulnerability to climate change using experts, and then weighed the selected indicators using the hierarchical analysis process (AHP). In order to verify the validity of the evaluation index, was examined using domestic climate data (temperature, precipitation, humidity, etc.). Correlation and regression analysis were performed. The empirical relationship between climate change and livestock productivity was examined through this study. As a result, we used data with high reliability of statistical analysis and found that there are significant variables.

Review of Remote Sensing Studies on Groundwater Resources (원격탐사의 지하수 수자원 적용 사례 고찰)

  • Lee, Jeongho
    • Korean Journal of Remote Sensing
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    • v.33 no.5_3
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    • pp.855-866
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    • 2017
  • Several research cases using remote sensing methods to analyze changes of storage and dynamics of groundwater aquifer were reviewed in this paper. The status of groundwater storage, in an area with regional scale, could be qualitatively inferred from geological feature, surface water altimetry and topography, distribution of vegetation, and difference between precipitation and evapotranspiration. These qualitative indicators could be measured by geological lineament analysis, airborne magnetic survey, DEM analysis, LAI and NDVI calculation, and surface energy balance modeling. It is certain that GRACE and InSAR have received remarkable attentions as direct utilization from satellite data for quantification of groundwater storage and dynamics. GRACE, composed of twin satellites having acceleration sensors, could detect global or regional microgravity changes and transform them into mass changes of water on surface and inside of the Earth. Numerous studies in terms of groundwater storage using GRACE sensor data were performed with several merits such that (1) there is no requirement of sensor data, (2) auxiliary data for quantification of groundwater can be entirely obtained from another satellite sensors, and (3) algorithms for processing measured data have continuously progressed from designated data management center. The limitations of GRACE for groundwater storage measurement could be defined as follows: (1) In an area with small scale, mass change quantification of groundwater might be inaccurate due to detection limit of the acceleration sensor, and (2) the results would be overestimated in case of combination between sensor and field survey data. InSAR can quantify the dynamic characteristics of aquifer by measuring vertical micro displacement, using linear proportional relation between groundwater head and vertical surface movement. However, InSAR data might now constrain their application to arid or semi-arid area whose land cover appear to be simple, and are hard to apply to the area with the anticipation of loss of coherence with surface. Development of GRACE and InSAR sensor data preprocessing algorithms optimized to topography, geology, and natural conditions of Korea should be prioritized to regionally quantify the mass change and dynamics of the groundwater resources of Korea.

Habitat Climate Characteristics of Lauraceae Evergreen Broad-leaved Trees and Distribution Change according to Climate Change (녹나무과 상록활엽수 자생지 기후특성과 기후변화에 따른 분포 변화)

  • Yu, Seung-Bong;Kim, Byung-Do;Shin, Hyun-Tak;Kim, Sang-Jun
    • Korean Journal of Environment and Ecology
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    • v.34 no.6
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    • pp.503-514
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    • 2020
  • Climate change leads to changes in phenological response and movement of plant habitats. Korea's evergreen broad-leaved forest has widened its distribution area compared for the past 20 years, and the range of its native habitats is moving northward. We analyzed climate indices such as the warmth index, the cold index, the lowest temperature in the coldest month, and the annual average temperature, which are closely related to vegetation distribution, to predict the change in the native habitat of Lauraceae evergreen broad-leaved trees. We also analyzed the change and spatial distribution to identify the habitat climate characteristics of 8 species of Lauraceae evergreen broad-leaved trees distributed in the warm temperate zone in Korea. Moreover, we predicted the natural habitat change in the 21st century according to the climate change scenario (RCP 4.5/8.5), applying the MaxEnt species distribution model. The monthly average climate index of the 8 species of Lauraceae evergreen broad-leaved trees was 116.9±10.8℃ for the temperate index, the cold index 3.9±3.8℃, 1495.7±455.4mm for the annual precipitation, 11.7±3.5 for the humidity index, 14.4±1.1℃ for the annual average temperature, and 1.0±2.1℃ for the lowest temperature of winter. Based on the climate change scenario RCP 4.5, the distribution of the Lauraceae evergreen broad-leaved trees was analyzed to expand to islands of Jeollanam-do and Gyeongsangnam-do, adjacent areas of the west and south coasts, and Goseong, Gangwon-do on the east coast. In the case of the distribution based on the climate change scenario RCP 8.5, it was analyzed that the distribution would expand to all of Jeollanam-do and Gyeongsangnam-do, and most regions except for some parts of Jeollabuk-do, Chungcheongnam-do, Gyeongsangbuk-do, and the capital region. For the conservation of Lauraceae evergreen broad-leaved trees to prepare for climate change, it is necessary to establish standards for conservation plans such as in-situ and ex-situ conservation and analyze various physical and chemical characteristics of native habitats. Moreover, it is necessary to preemptively detect changes such as distribution, migration, and decline of Lauraceae evergreen broad-leaved trees following climate change based on phenological response data based on climate indicators and establish conservation management plans.

Modeling of Vegetation Phenology Using MODIS and ASOS Data (MODIS와 ASOS 자료를 이용한 식물계절 모델링)

  • 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
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    • 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.

A study on solar radiation prediction using medium-range weather forecasts (중기예보를 이용한 태양광 일사량 예측 연구)

  • Sujin Park;Hyojeoung Kim;Sahm Kim
    • The Korean Journal of Applied Statistics
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    • v.36 no.1
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    • pp.49-62
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    • 2023
  • Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

A Comparative Analysis of the Clinical and Pathological features of IgA Nephropathy and Thin Glomerular Basement Membrane Disease (IgA 신병증과 비박형 기저막 신증의 임상 및 병리학적 비교 분석 - 사구체 기저막의 비박화를 중심으로 -)

  • Chi, Geun-Ha;Ha, Chang-Woo;Kim, Young-Ju;Yoon, Hye-Kyung;Chung, Woo-Yeong
    • Childhood Kidney Diseases
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    • v.5 no.2
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    • pp.147-155
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    • 2001
  • Purpose : IgA nephropathy(IgAN) and thin glomerular basement membrane disease(TGBMD) are common glomerular diseases that cause hematuria in childhood. IgAN has characteristics of IgA deposit as the sole or predominantly localized to the mesangium Recently, it has been reported that thinning of glomerular basement membrane(GBM) is commonly accompanied with precipitation of electron dense deposits in IgAN. We performed this study to examine the frequency of thinning of GBM among children with IgAN and to analysis tile correlation between urinary abnormalities and GBM thickness and furthermore to conduct comparative analysis of the clinical and pathological features of IgAN and TGBMD. Methods : This study summarizes data collected from Department of Pediatrics, Busan Paik Hospital, Inje Medical College. Data include 51 cases who were diagnosed as IgAN from 1995 to 2000, and 26 cases who were diagnosed as TGBMD from 1990 to 2000 by percutaneous renal biopsy. Results : Males accounted for 29/51($56.9\%$) patients with IgAN and 8/26($30.8\%$) of those with TGBMD. The clinical and laboratory features between IgAN and TGBMD were significantly different regarding the incidence of proteinuria(IgAN vs TGBMD: $43.1\%\;vs\;3.8\%$, p=0.001), the incidence of co-appearance of proteinuria with hematuria ($41.2\%\;vs\;3.8\%$, p=0.001), total amount of protein in 24 hours collected urine ($808{\pm}\;mg\;vs\;251{\pm}200.7\;mg$, p=0.001) and the incidence of proteinuria more than 1 gm in 24 hours collected urine ($23.5\%\;vs\;3.8\%$, p=0.01). On the contrary, there were no significant differences in the levels of serum albumin, creatinine, BUN, and Ccr between two groups. The mean thickness of GBM in patients with IgAN was $293.0{\pm}79.2\;nm$(139.7-461.9 nm) and $180.9{\pm}35.8\;nm$(110.5-229.5 nm) in patients with TGBMD. The mean GBM thickness revealed significantly thinner in TGBMD compared than those with IgAN (P=0.0001). The frequency of thickness being less than 250 nm was $37.4{\pm}34.4\%$ in IgAN and $93.0{\pm}7.0\%$ in TGBMD (P=0.0001). But there were no correlations between urinary abnormalities and GBM thickness in patients with IgAN. Conclusion : The thinning of GBM would be one of the common pathological findings in IgAN Moreover, there is no significant correlations between urinary abnormalities and GBM thickness in patients with IgAN, However, patients with IgAN tend to have significantly higher possibilities of proteinuria, co-appearance of proteinuria with hematuria and higher total amount of protein in 24 hours collected urine compared those with TGBMD. These differences might be play all important role as progressive prognostic indicators in patients with IgAN. (J Korean Soc Pediatr Nephrol 2001;5 : 136-46)

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