• Title/Summary/Keyword: Geographical and topographical effects

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Spatial Distribution of Precipitation Trends According to Geographical and Topographical Conditions (지리지형적 조건에 따른 강수량 추세 분포)

  • Rim, Chang-Soo
    • Journal of Korea Water Resources Association
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    • v.42 no.5
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    • pp.385-396
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    • 2009
  • The spatial distribution of precipitation trends according to urbanization, geographical and topographical conditions have been studied. In this study, precipitation data from 1973 to 2006 were analyzed for 56 climatological stations including the Seoul metropolis in South Korea. In addition to annual average daily precipitation, monthly average daily precipitation in April, July, October and January were analyzed, considering seasonal effect. The geographical and topographical characteristics of these sites were examined using GIS analysis. Land use status of the study area was also examined to estimate the extent of urbanization. The study results indicate that annual average precipitation increased, and monthly average precipitation in April and October decreased, while those in January and July increased. Considering urbanization effect, annual average precipitation and monthly average precipitation in July increased; however, monthly average precipitation in January, April and October decreased. Furthermore, compared with urbanization rate and proximity to coast, average elevation of study area appeared to be the most close correlation with annual and monthly averages of precipitation trends.

Trends of Annual and Monthly FAO Penman-Monteith Reference Evapotranspiration (연별 및 월별 FAO Penman-Monteith 기준증발산 추세 분석)

  • Rim, Chang-Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.1B
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    • pp.65-77
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    • 2008
  • The effects of climatic changes owing to urbanization, geographical and topographical conditions on annual and monthly FAO Penman-Monteith (FAO P-M) reference evapotranspiration, and energy and aerodynamic terms of FAO P-M reference evapotranspiration were studied. In this study, 21 climatological stations were selected. The statistical methods applied for trend analysis are Spearman rank test, Sen's test, linear regression analysis and analysis of actual variation ratio. Furthermore, the cluster analysis was applied to cluster 21 study stations by considering the geographical and topographical characteristics of study area. The study results indicate that urbanization affects the trend and amount of FAO P-M reference evapotranspiration, energy term and aerodynamic term; however, the result of Sen's test indicates that urbanization does not significantly affect the magnitude of trend (Sen's slope). The energy term increased at study stations located in coastal area; however, decreased at study stations located in inland area. The topographical slope of study area did not significantly influence on the trend of energy term. The aerodynamic term increased in both coastal area and inland area, indicating much significantly increasing trend in inland area, and it was also affected by the topographical slope of the study area.

Urbanization Effects on Reference Evapotranspiration (도시화에 따른 수문기후변화 II (도시화가 기준 증발산량에 미치는 영향))

  • Rim, Chang-Soo
    • Journal of Korea Water Resources Association
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    • v.40 no.7
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    • pp.571-583
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    • 2007
  • The effects of climatic changes owing to urbanization, geographical and topographical conditions on Penman-Monteith reference evapotranspiration, and energy and aerodynamic terms of Penman-Monteith reference evapotranspiration have been studied. In this study, 56 climatological stations including the Seoul metropolis in South Korea have been selected, and the area of study site was set at $314\;km^2$. The climatological station is centrally located In the study area with a 10 km radius. The geographical and topographical characteristics of these sites were examined using GIS analysis. Land use status of the study area was also examined to estimate the extent of urbanization. The study results indicated that the variation of reference evapotranspiration rate is closely related to urbanization in most climatological stations. The level of change in reference evapotranspiration was higher in areas with higher urbanization rates. The change in reference evapotranspiration appears to be caused by temperature rises following heat island phenomena due to urbanization, and by the decrease in humidity, wind speed and sunshine duration due to the Increase in residential areas in urban districts. Especially, the humidity decrease causes a significant decrease in evapotranspiration rate. The study results showed that climatic change due to urbanization and proximity to the coast had the greatest effect on reference evapotranspiration.

Analysis of the Spatial Distribution of Pan Evaporation Trends (Pan 증발량 추세분포 분석)

  • Rim, Chang-Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3B
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    • pp.243-255
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    • 2010
  • The spatial distribution of pan evaporation and pan evaporation trends have been studied. In this study, pan evaporation data from 1973 to 1990 for 56 climatological stations were analyzed. In addition to annual average daily pan evaporation, monthly average daily pan evaporation in April, July, October and January were analyzed, considering seasonal effect. The study results indicate that in case of annual average daily pan evaporation, 38 stations out of 56 stations show decreasing trend. In case of average daily pan evaporation in January, 33 stations show decreasing trend. In April, 38 stations show increasing trend. In July, 47 stations show decreasing trend. In October, 35 stations show increasing trend. Therefore, on the whole, pan evaporation tended to decrease in January, July, and annual basis. On the other hand, pan evaporation tended to increase in April and October. Furthermore, pan evaporation trend in each individual region shows also different trend even though the region is located nearby, indicating that there are geographical and topographical effects on pan evaporation trend. Pan evaporation data and climatic data from 1973 to 2006 for 11 climatological stations were used for trend analysis. Climatic variables such as temperature, relative humidity and wind speed show same or opposite trend direction compared with pan evaporation in annual or monthly basis. Annual and monthly solar radiation trends show the same direction compared with pan evaporation; however, annual and monthly precipitation trends show the opposite direction compared with pan evaporation.

A Spatial Interpolation Model for Daily Minimum Temperature over Mountainous Regions (산악지대의 일 최저기온 공간내삽모형)

  • Yun Jin-Il;Choi Jae-Yeon;Yoon Young-Kwan;Chung Uran
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.2 no.4
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    • pp.175-182
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    • 2000
  • Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

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