• Water Engineering Research
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• v.5 no.1
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• pp.47-54
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• 2004

Several computer programs have been developed to make stochastically generated weather data from observed daily data. But they require fully dataset to run WGEN. Mostly, meterological data frequently have sporadic missing data as well as totally missing data. The modified WGEN has data filling algorithm for incomplete meterological datasets. Any other WGEN models have not the function of data filling. Modified WGEN with data filling algorithm is processing from the equation of Matalas for first order autoregressive process on a multi dimensional state with known cross and auto correlations among state variables. The parameters of the equation of Matalas are derived from existing dataset and derived parameters are adopted to fill data. In case of WGEN (Richardson and Wright, 1984), it is one of most widely used weather generators. But it has to be modified and added. It uses an exponential distribution to generate precipitation amounts. An exponential distribution is easier to describe the distribution of precipitation amounts. But precipitation data with using exponential distribution has not been expressed well. In this paper, generated precipitation data from WGEN and Modified WGEN were compared with corresponding measured data as statistic parameters. The modified WGEN adopted a formula of CLIGEN for WEPP (Water Erosion Prediction Project) in USDA in 1985. In this paper, the result of other parameters except precipitation is not introduced. It will be introduced through study of verification and review soon

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.155-164
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• 2016

Algal blooms not only destroy fish habitats but also diminish biological diversity of ecosystem which results into water quality deterioration of 4 major rivers in South Korea. The relationship between algal bloom and environmental factors had been analyzed through the cross-correlation function between concentration of chlorophyll a and other environmental factors. However, time series of cross-correlations can be affected by the stochastic structure such auto-correlated feature of other controllers. In order to remove external effect in the correlation analysis, the pre-whitening procedure was implemented into the cross correlation analysis. The modeling process is consisted of a series of procedure (e.g., model identification, parameter estimation, and diagnostic checking of selected models). This study provides the exclusive correlation relationship between algae concentration and other environmental factors. The difference between the conventional correlation using raw data and that of pre-whitened series was discussed. The process implemented in this paper is useful not only to identify exclusive environmental variables to model Chl-a concentration but also in further extensive application to configure causality in the environment.

• Journal of Soil and Groundwater Environment
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• v.20 no.5
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• pp.16-25
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• 2015

The City of Boulder is located at an average elevation of 1,655 m (5,430 feet), the foothills of the Rocky Mountains in Colorado. Its daily air temperature is much varying and snow is very frequent and heavy even in spring. This paper examines characteristics of shallow (surface and depth = 10 cm) soil temperatures measured from January to May 2015 in the high elevation city Boulder, Colorado. The surface soil temperature quickly responded to the air temperature with the strongest periodicity of 1 day while the subsurface soil temperatures showed a less correlation and delayed response with that. The short-time Fourier of the soil temperatures uncovered their very low frequencies characteristics in heavy snow days while it revealed high frequencies of their variations in warm spring season. The daily minimum air temperature exhibited high cross-correlations with the soil temperatures without lags unlike the maximum air temperature, which is derived from its higher and longer auto-correlation and stronger spectrums of low frequencies than the maximum air temperature. The snow depth showed an inverse relationship with the soil temperature variations due to snow's low thermal conductivity and high albedo. Multiple regression for the soil temperatures using the air temperature and snow depth presented its predicting possibility of them even though the multiple r² of the regression is not that much satisfactory (r² = 0.35-0.64).

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.6
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• pp.823-829
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• 1986

The Large-scale structure of the circular jet in the transition region, which influences the subsequent flow in the turbulent region, was studied experimentally. Measuring equipments are composed of the two channel hot-wire anemometer, the computer controlled two-directional traverse mechanism, the data acquisition system, and FFT-analyzer. The circular jet has 50mm diameter. The mean velocity distribution, the velocity fluctuation, the auto 'cross correlations and the power spectra were acquired at moderate Reynolds number of 10$^{4}$. And the VITA method was used to measure the convection velocity of Large-scale eddy. The phase of u'is in advance of that of v'in all regions. .over bar. $R_{u}$(.tau.=0) is approximately zero in the potential core region, but a small regular deviation is observed. At a position in the mixing layer region the convection velocity is different along the part of the eddy, and in this experiment the convection velocity of the inner region is larger than the outer region. The averge convection velocity of the eddy along y/D=0 was approximately constant in the transition region.D=0 was approximately constant in the transition region.