Estimation of Runoff Curve Number for Chungju Dam Watershed Using SWAT

김남원,; 이진원,; 이정우,; 이정은,

doi:10.3741/jkwra.2008.41.12.1231

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…Particularly for rainfall events of less than 10 mm, the estimated CN values were greater than 90 in most land cover types except those for uplands and orchards. This result might be caused by the value for S (potential maximum retention after runoff begins), which is largely affected by high runoff occurring from high rainfall events (Kim et al , ; Kwak et al , ).…”

Section: Resultsmentioning

confidence: 99%

“…These application studies showed that there is an asymptotic relationship between CN and rainfall amounts. Also, Kim et al () and Kwak et al () illustrated that direct runoff estimated using the ACN‐RB method matched observed runoff better than estimates using the original NRCS‐CN method did.…”

Section: Introductionmentioning

confidence: 99%

“…The CN values included in the NEH-4 have been widely used in various spreadsheet-based runoff models (e.g., L-THIA (Harbor, 1994) and STEPL (Tetra Tech, 2011;Park et al, 2014)) as well as in Geographic Information System (GIS)-based direct runoff and NPS pollution estimation models (Lim, et al, 2005a;Tyagi et al, 2008;Kim et al, 2008;Soulis and Valiantzas, 2012;Park et al, 2014;Tejram et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Approach of Land Cover Based Asymptotic Curve Number Regression Equation to Estimate Runoff

Ryu

Jung

Kong

et al. 2016

Irrigation and Drainage

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The Natural Resources Conservation Service‐Curve Number (NRCS‐CN) method has been used widely for estimation of direct runoff. However, the determination methods of CN values for land covers from the National Engineering Handbook Chapter 4 (NEH‐4) are inadequate due to uncertainty raised in determining the of the hydrologic soil group, which could change from reported soil survey data due to soil compaction and other human activities. To overcome these drawbacks, an asymptotic CN (ACN) regression equation for the relationship between measured streamflow and rainfall for gauged river basins (ACN‐RB) was developed and used in various studies. The ACN‐RB determines various CN values depending on the amount of rainfall in an event. The ACN‐RB has limitations in application to ungauged river basin because the ACN‐based CN values do not consider various land covers. Accordingly, 13 land cover‐based asymptotic CN regression equations (LC‐ACN‐REs) were developed and evaluated in this study by comparing estimated direct runoff with measured data. The estimated direct runoff using the LC‐ACN‐REs, which were classified as “standard types”, matched observed direct runoff well, as evidenced by a Nash‐Sutcliff efficiency (NSE) value of 0.78 for Jungrang A basin and a NSE value of 0.73 for Tancheon A basin. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Approach of Land Cover Based Asymptotic Curve Number Regression Equation to Estimate Runoff

Ryu

Jung

Kong

et al. 2016

Irrigation and Drainage

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“…연구지역의 주요 지질은 하부 로부터 계명산층, 향산리돌로마이트층, 대향산규암층, 문 주리층, 운교리층, 황강리층 등과 이를 관입한 중생대 화 성암류로 구성된다. 화성암류는 주로 조립질반상화강암, 흑운모화강암, 각섬석화강암, 화강반암, 규장암, 염기성암 맥, 산성암류 등으로 이루어져 있다 (Kim and Lee, 1965;Lee and Kim, 1972). 또한 연구지역의 지질을 구성하는 변성암류는 변성이질암, 화강암질편마암, 함철규암, 변성 심성산성암, 변성반심성산성암, 변성화산산성암, 변성염 기성암, 변성역질암, 변성사질암, 규암, 결정질 돌로마이 트질석회암 등으로 구성되어 있다 (Kang et al, 2017).…”

Section: 연구지역 및 지질개요unclassified

Physical Properties of Major Bedrocks in Chungju-Goesan Area as Aggregates

You

2022

Econ. Environ. Geol.

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This study examined the granite, quartzite, phyllite, schist, and gneiss as aggregate resources among the original rock distributed in the Chungju-Goesan area. The granite distributed in the study area is mainly composed of Jurassic biotite granite, and the quartzite layer is from the Daehyangsan quartzite Formation distributed on the upper part of the Gyemyeongsan Formation and the Hyangsan-ri dolomitic limestone Formation. In addition, phyllite is pophyrytic phyllite-schist from the Hwanggangri Formation of the Okcheon group, schist is chlorite schist, from the Munjuri Formation of the Okcheon group, and gneiss is porphyroblastic gneiss which is the upper part of the Seochangri Formation. Aggregate quality evaluation factors of these rocks included fineness modulus, absorption, unit weight, absolute dry density, solid content, porosity, resistance to abrasion, and soundness. In the case of granite, it was found to be partially unsatisfactory in terms of unit weight, solid content, porosity, and resistance to abrasion. Gneiss was found to be out of the standard values in resistance to abrasion and schist in porosity and solid content. As for the overall quality of aggregate resources, it was analyzed that quartzite, gneiss, and phyllite showed excellent quality. Aggregate quality tests are performed simply for each rock, but the rock may vary depending on the morphology of the mineral. Therefore, when analyzing and utilizing the quality evaluation of aggregate resources, it will be possible to use them more efficiently if the rock-mineralological research is performed together.

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“…, 특히 Cho et al (2004) and Kim et al (2007) (Park et al, 2005;Lee et al, 2005 (Mogeln, 2000;Paudel et al, 2009;Ebrahimian et al, 2012;Moon et al, 2014 6 2006, 2007, 2008, 2009, 2010 6 2006, 2007, 2008, 2009, 2010 3 2005, 2006, 2007, 2008, 2009, 2010 7 2006, 2007, 2008, 2009, 2010, 2011Cheongju Geum River 161.44 32.84 20.1 2006, 2007, 2008, 2009, 2010, 2011 Chunyang Youngsan River 143.1 16.74 34.3 2006, 2007, 2008, 2009Toigyewon Han River 200.45 27.92 26.7 2005, 2006, 2007, 2008, 2009, 2010, 2011Pyeongchang Han River 695.67 72.84 40.3 2005, 2006, 2007, 2008, 2009, 2010, 2011...…”

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confidence: 98%

Comparing Calculation Techniques for Effective Rainfalls Using NRCS-CN Method: Focused on Introducing Weighted Average and Slope-based CN

Moon¹,

Yoo²,

Kim³

2014

Journal of the Korean Society of Civil Engineers

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The NRCS-CN method is generally used to estimate effective rainfalls in a basin. However, since the curve number which plays a critical role in the NRCS-CN method was originally developed for US watersheds, it is limited to be directly applied to other basins outside the United States. Therefore various modifications have been suggested to revise the NRCS-CN for specific watershed condition. This study introduced the weighted average method and the slope-based CN to estimate effective rainfalls available for Korean watersheds and compared with the observed direct runoff. The overall results achieved from this study indicated that the adjusted slope-based CN considerably increases effective rainfalls in general and makes the duration of effective storm longer. Based on the statistical error analysis performed for various modifications of NRCS-CN, the weighted average method with the adjusted slope-based CN has highest precision with the observed direct runoff. In addition, after analyzing the relation between the initial loss estimated from rainfall-runoff observations and the potential maximum retention from GIS-based data, it turns out that the assumption of linear relationship between the initial loss and the potential maximum retention is not available for Korean watersheds.

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Estimation of Runoff Curve Number for Chungju Dam Watershed Using SWAT

Cited by 7 publications

References 8 publications

Approach of Land Cover Based Asymptotic Curve Number Regression Equation to Estimate Runoff

Approach of Land Cover Based Asymptotic Curve Number Regression Equation to Estimate Runoff

Physical Properties of Major Bedrocks in Chungju-Goesan Area as Aggregates

Comparing Calculation Techniques for Effective Rainfalls Using NRCS-CN Method: Focused on Introducing Weighted Average and Slope-based CN

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