• 제목/요약/키워드: Water depth estimation

검색결과 258건 처리시간 0.028초

Characteristics of Pit Corrosion and Estimation Models of Corrosion Depth in Buried Water Pipes (상수도관의 부식특성과 부식깊이 추정 모델)

  • Kim, Jea-Hag;Ryu, Tae-Sang;Kim, Ju-Hawn;Ha, Sung-ryung
    • Journal of Korean Society of Water and Wastewater
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    • 제21권6호
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    • pp.689-699
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    • 2007
  • The accurate estimation of water pipe deterioration is indispensable to prevent pipe breakage and manage in advance. In this study, corrosion of water pipe is adopted, which is relatively underestimated although it takes most part of deteriorating pipeline. Predicting corrosion rate and corrosion depth of a pipe can make an increase the life span of the pipeline, which is laid under the ground according to characteristics of soil and water corrosion. For the purpose, mathematical models that can presume nominal depth through estimation of pit corrosion and corrosion rate is introduced. As comparison of results with conventional methods in other foreign countries, it is evaluated that the external corrosion depth is estimated less than the models, proposed by other researchers and the internal corrosion rate was processed faster than the external corrosion rate.

Estimation of Water Depth in Coastal Area Using Hyperspectral Satellite Imagery (하이퍼스펙트럴 위성영상을 이8한 연안지역의 수심산정)

  • Lee Jong-Chool;Kim Dae-Hyun;Lee Young-Do;Yu Young-Hwa
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 한국측량학회 2006년도 춘계학술발표회 논문집
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    • pp.165-169
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    • 2006
  • Purpose of this research is estimation of water depth by hyperspectral remote sensing in area that access of ship is difficult This research used EO-1 Hyperion satellite imagery. Atmospheric and geometric correction is executed. Compress of band used MNF transforms. Diffuse Attenuation Coefficient of target area is decided in imagery for water depth estimation. Determination of Emdmember in pixel is using Linear Spectral Unmixing techniques. Water depth estimated using this result.

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A Study on Estimation of Water Depth Using Hyperspectral Satellite Imagery (초분광 위성영상을 이용한 수심산정에 관한 연구)

  • Yu, Yeong-Hwa;Kim, Youn-Soo;Lee, Sun-Gu
    • Aerospace Engineering and Technology
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    • 제7권1호
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    • pp.216-222
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    • 2008
  • Purpose of this research is estimation of water depth by hyperspectral remote sensing in area that access of ship is difficult. This research used EO-l Hyperion satellite imagery. Atmospheric and geometric correction is executed. Compress of band used MNF transforms. Diffuse Attenuation Coefficient of target area is decided in imagery for water depth estimation. Determination of Emdmember in pixel is using Linear Spectral Unmixing techniques. Water depth estimated using this result.

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Analysis of Variance of Paddy Water Demand Depending on Rice Transplanting Period and Ponding Depth (이앙시기 및 담수심 변화에 따른 논벼 수요량 변화 분석)

  • Cho, Gun-Ho;Choi, Kyung-Sook
    • Journal of The Korean Society of Agricultural Engineers
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    • 제63권3호
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    • pp.75-85
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    • 2021
  • This study evaluated variations in the paddy rice water demand based on the continuous changing in rice transplanting period and ponding depth at the four study paddy fields, which represent typical rice producing regions in Korea. Total 7 scenarios on rice transplanting periods were applied while minimum ponding depth of 0 and 20 mm were applied in accordance with maximum ponding depth ranging from 40 mm to 100 mm with 20 mm interval. The weather data from 2013 to 2019 was also considered. The results indicated that the highest rice water demand occurred at high temperature and low rainfall region. Increased rice transplanting periods showed higher rice water demand. The rice water demand for 51 transplanting days closely matched with the actual irrigation water supply. In case of ponding depth, the results showed that the minimum ponding depth had a proportional relationship with rice water demand, while maximum ponding depth showed the contrary results. Minimum ponding depth had a greater impact on rice water demand than the maximum ponding depth. Therefore, these results suggest that increasing the rice transplanting period, which reflects the current practice is desirable for a reliable estimation of rice water demand.

Estimation of river water depth using UAV-assisted RGB imagery and multiple linear regression analysis (무인기 지원 RGB 영상과 다중선형회귀분석을 이용한 하천 수심 추정)

  • Moon, Hyeon-Tae;Lee, Jung-Hwan;Yuk, Ji-Moon;Moon, Young-Il
    • Journal of Korea Water Resources Association
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    • 제53권12호
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    • pp.1059-1070
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    • 2020
  • River cross-section measurement data is one of the most important input data in research related to hydraulic and hydrological modeling, such as flow calculation and flood forecasting warning methods for river management. However, the acquisition of accurate and continuous cross-section data of rivers leading to irregular geometric structure has significant limitations in terms of time and cost. In this regard, a primary objective of this study is to develop a methodology that is able to measure the spatial distribution of continuous river characteristics by minimizing the input of time, cost, and manpower. Therefore, in this study, we tried to examine the possibility and accuracy of continuous cross-section estimation by estimating the water depth for each cross-section through multiple linear regression analysis using RGB-based aerial images and actual data. As a result of comparing with the actual data, it was confirmed that the depth can be accurately estimated within about 2 m of water depth, which can capture spatially heterogeneous relationships, and this is expected to contribute to accurate and continuous river cross-section acquisition.

Development of the Estimation System for Agricultural Water Demand (농업용수 수요량 산정 시스템 개발)

  • 이광야;김선주
    • Magazine of the Korean Society of Agricultural Engineers
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    • 제43권1호
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    • pp.53-65
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    • 2001
  • To estimate agricultural water demand, many factors such as weather, crops, soil, cultivation method, crop coefficient and cultivation area, etc. must be considered. But it is not easy to estimate water demand in consideration of these factors, which are variable according to growth stage and regional environment. This study provides estimation system for agricultural water demand(ESAD) in order to estimate water demand easily and accurately, and arranges all factors needed for water demand estimation. This study identifies the application of estimation system for agricultural water demand with the data observed in the other studies, and analyzes nationwide agricultural water demand. The results are as follows. 1) The practice of different rice cultivation in the paddy field resulted in different water demands. Water depth and infiltration ratio in paddy are the most important factors to estimate water demand. The water depths in paddy simulated by ESAD is very similar to the observed ones. 2) Water demand of upland crops varies with the crops, soil, etc.. Effective rainfall estimated by daily routing of soil moisture varies according to the crops, soil, and effective soil zone(root depth). As crop root become grown, effective rainfall and an amount of irrigation water has been increased. 3) The current unit water demand of upland crops applied as 500mm or 550mm to estimate water demand does not reflect the differences caused by the crops, regional surrounding, weather condition, etc. Results from ESAD for the estimation of water demand of upland crops show that ESAD can simulate the actual field conditions reasonably because it simulates the actual irrigation practices with the daily routing of soil moisture.

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Development of Nonpoint Sources Runoff Load Estimation Model Equations for the Vineyard Area (포도밭에 대한 비점오염물질 유출량 추정 모델식 개발)

  • Yoon, Young-Sam;Kwon, Hun-Gak;Yi, Youn-Jung;Yu, Jay-Jung;Lee, Jae-Kwan
    • Journal of Environmental Science International
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    • 제19권7호
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    • pp.907-915
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    • 2010
  • Agriculture nonpoint pollution source is a significant contributor to water quality degradation. To establish effective water quality control policy, environpolitics establishment person must be able to estimate nonpoint source loads to lakes and streams. To meet this need for orchard area, we investigated a real rainfall runoff phenomena about it. We developed nonpoint source runoff estimation models for vineyard area that has lots of fertilizer, compost specially between agricultural areas. Data used in nonpoint source estimation model gained from real measuring runoff loads and it surveyed for two years(2008-2009 year) about vineyard. Nonpoint source runoff loads estimation models were composed of using independent variables(rainfall, storm duration time(SDT), antecedent dry weather period(ADWP), total runoff depth(TRD), average storm intensity(ASI), average runoff intensity(ARI)). Rainfall, total runoff depth and average runoff intensity among six independent variables were specially high related to nonpoint source runoff loads such as BOD, COD, TN, TP, TOC and SS. The best regression model to predict nonpoint source runoff load was Model 6 and regression factor of all water quality items except for was $R^2=0.85$.

A Derivation of Aerosol Optical Depth Estimates from Direct Normal Irradiance Measurements

  • Yun Gon Lee;Chang Ki Kim
    • New & Renewable Energy
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    • 제20권1호
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    • pp.79-87
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    • 2024
  • This study introduces a method for estimating Aerosol Optical Depth (AOD) using Broadband Aerosol Optical Depth (BAOD) derived from direct normal irradiance and meteorological factors observed between 2016 and 2017. Through correlation analyses between BAOD and atmospheric components such as Rayleigh scattering, water vapor, and tropospheric nitrogen dioxide, significant relationships were identified, enabling accurate AOD estimation. The methodology demonstrated high correlation coefficients and low Root Mean Square Errors (RMSE) compared to actual AOD500 measurements, indicating that the attenuation effects of water vapor and the direct impact of tropospheric nitrogen dioxide concentration are crucial for precise aerosol optical depth estimation. The application of BAOD for estimating AOD500 across various time scales-hourly, daily, and monthly-showed the approach's robustness in understanding aerosol distributions and their optical properties, with a high coefficient of determination (0.96) for monthly average AOD500 estimates. This study simplifies the aerosol monitoring process and enhances the accuracy and reliability of AOD estimations, offering valuable insights into aerosol research and its implications for climate modeling and air quality assessment. The findings underscore the viability of using BAOD as a surrogate for direct AOD500 measurements, presenting a promising avenue for more accessible and accurate aerosol monitoring practices, crucial for improving our understanding of aerosol dynamics and their environmental impacts.

SPATIAL AND TEMPORAL INFLUENCES ON SOIL MOISTURE ESTIMATION

  • Kim, Gwang-seob
    • Water Engineering Research
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    • 제3권1호
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    • pp.31-44
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    • 2002
  • The effect of diurnal cycle, intermittent visit of observation satellite, sensor installation, partial coverage of remote sensing, heterogeneity of soil properties and precipitation to the soil moisture estimation error were analyzed to present the global sampling strategy of soil moisture. Three models, the theoretical soil moisture model, WGR model proposed Waymire of at. (1984) to generate rainfall, and Turning Band Method to generate two dimensional soil porosity, active soil depth and loss coefficient field were used to construct sufficient two-dimensional soil moisture data based on different scenarios. The sampling error is dominated by sampling interval and design scheme. The effect of heterogeneity of soil properties and rainfall to sampling error is smaller than that of temporal gap and spatial gap. Selecting a small sampling interval can dramatically reduce the sampling error generated by other factors such as heterogeneity of rainfall, soil properties, topography, and climatic conditions. If the annual mean of coverage portion is about 90%, the effect of partial coverage to sampling error can be disregarded. The water retention capacity of fields is very important in the sampling error. The smaller the water retention capacity of the field (small soil porosity and thin active soil depth), the greater the sampling error. These results indicate that the sampling error is very sensitive to water retention capacity. Block random installation gets more accurate data than random installation of soil moisture gages. The Walnut Gulch soil moisture data show that the diurnal variation of soil moisture causes sampling error between 1 and 4 % in daily estimation.

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