• Title/Summary/Keyword: Long-term rainfall-runoff model

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Criteria for calculation of CSO volume and frequency using rainfall-runoff model (우수유출 모형을 이용한 합류식하수관로시스템의 월류량, 월류빈도 산정 기준 결정 연구)

  • Lee, Gunyoung;Na, Yongun;Ryu, Jaena;Oh, Jeill
    • Journal of Korean Society of Water and Wastewater
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    • v.27 no.3
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    • pp.313-324
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    • 2013
  • It is widely known that untreated Combined Sewer Overflows (CSOs) that directly discharged from receiving water have a negative impact. Recent concerns on the CSO problem have produced several large scale constructions of treatment facilities, but the facilities are normally designed under empirical design criteria. In this study, several criteria for defining CSOs (e.g. determination of effective rainfall, sampling time, minimum duration of data used for rainfall-runoff simulation and so on) were investigated. Then this study suggested a standard methodology for the CSO calculation and support formalized standard on the design criteria for CSO facilities. Criteria decided for an effective rainfall was over 0.5 mm of total rainfall depth and at least 4 hours should be exist between two different events. An Antecedent dry weather period prior to storm event to satisfy the effective rainfall criteria was over 3 days. Sampling time for the rainfall-runoff model simulation was suggested as 1 hour. A duration of long-term simulation CSO overflow and frequency calculation should be at least recent 10 year data. A Management plan for the CSOs should be established under a phase-in of the plan. That should reflect site-specific conditions of different catchments, and formalized criteria for defining CSOs should be used to examine the management plans.

Set up Reduction Goals of Combined Sewer Overflow Pollutant Load Using Long-Term Rainfall-Runoff Model Simulation (장기간 강우-유출 모의를 통한 합류식하수관로시스템의 월류부하량 저감목표 설정 연구)

  • Lee, Gunyoung;Na, Yongun;Ryu, Jaena;Oh, Jeill
    • Journal of Korean Society of Environmental Engineers
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    • v.35 no.11
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    • pp.785-794
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    • 2013
  • Combined sewer overflows during rainfall events contain sewer sediments and surface pollutants. This can cause significant chemical, physical and biological problems to receiving watershed. However, there are no method that can commonly apply to decide criteria for controlling the pollutant load. In this study, it sets up the reduction goals of combined sewer overflow through long-term simulation using the rainfall-runoff model. From a review of domestic and foreign management standard of combined sewer overflow for this, it makes decision that 60% (phase 1), 85% (phase 2) of total pollutant load and frequency per year for reduction goals is more proper. Also, the result of analyzing long-term simulation (minimum 10 years) applied to research basin indicates that reduction goals of BOD pollutant load are 1,123 kg (phase 1) and 2,374 kg (phase 2), and overflow volumes for research objective achievement are $11,685m^3$ (phase 1) and $24,701m^3$ (phase 2).

Development of Hydrologic Simulation Model to Predict Flood Runoff in a Small Mountaineous Watershed (산지 소유역의 홍수유출 예측을 위한 모의발생 수문모형의 개발)

  • 권순국;고덕구
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.30 no.3
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    • pp.58-68
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    • 1988
  • Most of the Korean watersheds are mountaineous and consist of various soil types and land uses And seldom watersheds are found to have long term hydrologic records. The SNUA, a hydrologic watershed model was developed to meet the unique characteristics of Korean watershed and simulate the storm hydrographs from a small mountaineous watershed. Also the applicability of the model was tested by comparing the simulated storm hydrographs and the observed from Dochuk watershed, Gwangjugun, Kyunggido The conclusions obtained in this study could be summarized as follows ; 1. The model includes the simulation of interception, evaporation and infiltration for land surface hydrologic cycle on the single storm basis and the flow routing features for both overland and channel systems. 2. Net rainfall is estimated from the continuous computation of water balance at the surface of interception storage accounting for the rainfall intensities and the evaporation losses at each time step. 3. Excess rainfall is calculated by the abstraction of infiltration loss estimated by the Green and Ainpt Model from the net rainfall. 4. A momentum equation in the form of kinematic wave representation is solved by the finite differential method to obtain the runoff rate at the exit of the watershed. 5. The developed SNUA Model is a type of distributed and event model that considers the spatial distribution of the watershed parameters and simulates the hydrograph on a single storm basis. 6. The results of verification test show that the simulated peak flows agree with the observed in the occurence time but have relative enors in the range of 5.4-40.6% in various flow rates and also show that the simulated total runoff have 6.9-32% of relative errors against the observed. 7. To improve the applicability of the model, it was thought that more studies like the application test to the other watersheds of various types or the addition of the other hydrologk components describing subsurface storages are needed.

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Improvement of Mid-and Low-flow Estimation Using Variable Nonlinear Catchment Wetness Index (비선형 유역습윤지수를 이용한 평갈수기 유출모의개선)

  • Hyun, Sukhoon;Kang, Boosik;Kim, Jin-Gyeom
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.36 no.5
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    • pp.779-789
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    • 2016
  • The effective rainfall is calculated considering the soil moisture. It utilizes observed data directly in order to incorporate the soil moisture into the rainfall-runoff model, or it calculates indirectly within the model. The rainfall-runoff model, IHACRES, used in this study computes the catchment wetness index (CWI) first varying with temperature and utilize it for estimating precipitation loss. The nonlinear relationship between the CWI and the effective rainfall in the Hapcheondam watershed was derived and utilized for the long-term runoff calculation. The effects of variable and constant CWI during calibration and validation were suggested by flow regime. The results show the variable CWI is generally more effective than the constant CWI. The $R^2$ during high flow period shows relatively higher than the ones during normal or low flow period, but the difference between cases of the variable and constant CWI was insignificant. The results indicates that the high flow is relatively less sensitive to the evaporation and soil moisture associated with temperature. On the other hand, the variable CWI gives more desirable results during normal and low flow periods which means that it is crucial to incorporate evaporation and soil moisture depending on temperature into long-term continuous runoff simulation. The NSE tends to decrease during high flow period with high variability which could be natural because NSE index is largely influenced by outliers of underlying variable. Nevertheless overall NSE shows satisfactory range higher than 0.9. The utilization of variable CWI during normal and low flow period would improve the computation of long-term rainfall-runoff simulation.

Prediction of SWAT Stream Flow Using Only Future Precipitation Data (미래 강수량 자료만을 이용한 SWAT모형의 유출 예측)

  • Lee, Ji Min;Kum, Donghyuk;Kim, Young Sug;Kim, Yun Jung;Kang, Hyunwoo;Jang, Chun Hwa;Lee, Gwan Jae;Lim, Kyoung Jae
    • Journal of Korean Society on Water Environment
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    • v.29 no.1
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    • pp.88-96
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    • 2013
  • Much attention has been needed in water resource management at the watershed due to drought and flooding issues caused by climate change in recent years. Increase in air temperature and changes in precipitation patterns due to climate change are affecting hydrologic cycles, such as evaporation and soil moisture. Thus, these phenomena result in increased runoff at the watershed. The Soil and Water Assessment Tool (SWAT) model has been used to evaluate rainfall-runoff at the watershed reflecting effects on hydrology of various weather data such as rainfall, temperature, humidity, solar radiation, wind speed. For bias-correction of RCP data, at least 30 year data are needed. However, for most gaging stations, only precipitation data have been recorded and very little stations have recorded other weather data. In addition, the RCP scenario does not provide all weather data for the SWAT model. In this study, two scenarios were made to evaluate whether it would be possible to estimate streamflow using measured precipitation and long-term average values of other weather data required for running the SWAT. With measured long-term weather data (scenario 1) and with long-term average values of weather data except precipitation (scenario 2), the estimate streamflow values were almost the same with NSE value of 0.99. Increase/decrease by ${\pm}2%$, ${\pm}4%$ in temperature and humidity data did not affect streamflow. Thus, the RCP precipitation data for Hongcheon watershed were bias-corrected with measured long-term precipitation data to evaluate effects of climate change on streamflow. The results revealed that estimated streamflow for 2055s was the greatest among data for 2025s, 2055s, and 2085s. However, estimated streamflow for 2085s decreased by 9%. In addition, streamflow for Spring would be expected to increase compared with current data and streamflow for Summer will be decreased with RCP data. The results obtained in this study indicate that the streamflow could be estimated with long-term precipitation data only and effects of climate change could be evaluated using precipitation data as shown in this study.

A Delta- and Attention-based Long Short-Term Memory (LSTM) Architecture model for Rainfall-runoff Modeling

  • Ahn, Kuk-Hyun;Yoon, Sunghyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.35-35
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    • 2022
  • 최근에 딥 러닝(Deep learning) 기반의 많은 방법들이 수문학적 모형 및 예측에서 의미있는 결과를 보여주고 있지만 더 많은 연구가 요구되고 있다. 본 연구에서는 수자원의 가장 대표적인 모델링 구조인 강우유출의 관계의 규명에 대한 모형을 Long Short-Term Memory (LSTM) 기반의 변형 된 방법으로 제시하고자 한다. 구체적으로 본 연구에서는 반응변수인 유출량에 대한 직접적인 고려가 아니라 그의 1차 도함수 (First derivative)로 정의되는 Delta기반으로 모형을 구축하였다. 또한, Attention 메카니즘 기반의 모형을 사용함으로써 강우유출의 관계의 규명에 있어 정확성을 향상시키고자 하였다. 마지막으로 확률 기반의 예측를 생성하고 이에 대한 불확실성의 고려를 위하여 Denisty 기반의 모형을 포함시켰고 이를 통하여 Epistemic uncertainty와 Aleatory uncertainty에 대한 상대적 정량화를 수행하였다. 본 연구에서 제시되는 모형의 효용성 및 적용성을 평가하기 위하여 미국 전역에 위치하는 총 507개의 유역의 일별 데이터를 기반으로 모형을 평가하였다. 결과적으로 본 연구에서 제시한 모형이 기존의 대표적인 딥 러닝 기반의 모형인 LSTM 모형과 비교하였을 때 높은 정확성뿐만 아니라 불확실성의 표현과 정량화에 대한 유용한 것으로 확인되었다.

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Estimation of Future Long-Term Riverbed Fluctuations and Aggregate Extraction Volume Using Climate Change Scenarios: A Case Study of the Nonsan River Basin (기후변화시나리오를 이용한 미래 장기하상변동 및 골재 채취량 산정: 논산천을 사례로)

  • Dae Eop Lee;Min Seok Kim;Hyun Ju Oh
    • Economic and Environmental Geology
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    • v.57 no.2
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    • pp.107-117
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    • 2024
  • The objective of this study is to estimate riverbed fluctuations and the volume of aggregate extraction attributable to climate change. Rainfall-runoff modeling, utilizing the SWAT model based on climate change scenarios, as well as long-term riverbed fluctuation modeling, employing the HEC-RAS model, were conducted for the Nonsan River basin. The analysis of rainfall-runoff and sediment transport under the SSP5-8.5 scenario for the early part of the future indicates that differences in annual precipitation may exceed 600 mm, resulting in a corresponding variation in the basin's sediment discharge by more than 30,000 tons per year. Additionally, long-term riverbed fluctuation modeling of the lower reaches of the Nonsan Stream has identified a potential aggregate extraction area. It is estimated that aggregate extraction could be feasible within a 2.455 km stretch upstream, approximately 4.6 to 6.9 km from the confluence with the Geum River. These findings suggest that the risk of climate crises, such as extreme rainfall or droughts, could increase due to abnormal weather conditions, and the increase in variability could affect long-term aggregate extraction. Therefore, it is considered important to take into account the impact of climate change in future long-term aggregate extraction planning and policy formulation.

The Development of Coupled SWAT-SWMM Model (II) Model Characteristics and Evaluation (SWAT-SWMM 결합모형의 개발 (II) 모형의 특징 및 평가)

  • Kim, Nam-Won;Won, Yoo-Seung
    • Journal of Korea Water Resources Association
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    • v.37 no.7
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    • pp.599-612
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    • 2004
  • The continuous long-term rainfall-runoff simulation model SWAT has the advantage of being able to account for various land use, however, SWAT lacks the capability of simulating the drainage characteristics of urban area. On the other hand, SWMM, which is the most popular model for runoff analysis of urban watershed, has the advantage of being capable of considering surface and drainage characteristics in urban area, but SWMM cannot easily account for land use other than urban area within a watershed. In this study, SWAT-SWMM model, which builds on the strengths of SWAT and SWMM, has been applied to the Osan River Watershed which is a tributary watershed to the Gyung-Ahn River. From the application, the results from coupled SWAT-SWMM model has been compared to the ones from SWAT for each hydrologic component such as evapotranspiration, surface runoff, groundwater flow, and watershed and channel discharge, and the runoff characteristics of two models for each hydrologic component has been discussed.

Storm-Water CSOs for Reservoir System Designs in Urban Area (도시유역 저류형 시스템 설계를 위한 CSOs 산정)

  • Jo, Deok-Jun;Kim, Myoung-Su;Lee, Jung-Ho;Park, Moo-Jong;Kim, Joong-Hoon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.1199-1203
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    • 2005
  • Combined sewer overflows(CSOs) are themselves a significant source of water pollution. Therefore, the control of urban drainage for CSOs reduction and receiving water quality protection is needed. Examples in combined sewer systems include downstream storage facilities that detain runoff during periods of high flow and allow the detained water to be conveyed by an interceptor sewer to a centralized treatment plant during periods of low flow. The design of such facilities as stormwater detention storage is highly dependant on the temporal variability of storage capacity available(which is influenced by the duration of interevent dry periods) as well as the infiltration capacity of soil and recovery of depression storage. As a result, a contiunous approach is required to adequately size such facilities. This study for the continuous long-term analysis of urban dranage system used analytical Probabilistic model based on derived probability distribution theory. As an alternative to the modeling of urban drainage system for planning or screening level analysis of runoff control alternatives, this model have evolved that offer much ease and flexibility in terms of computation while considering long-term meteorology. This study presented rainfall and runoff characteristics or the subject area using analytical Probabilistic model. Runoff characteristics manifasted the unique characteristics of the subject area with the infiltration capacity of soil and recovery of depression storage and was examined appropriately by sensitivity analysis. This study presented the average annual COSs and number of COSs when the interceptor capacity is in the range 3xDWF(dry weather flow). Also, calculated the average annual mass of pollutant lost in CSOs using Event Mean Concentration. Finally, this study presented a dicision of storage volume for CSOs reduction and water quality protection.

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Application of K-DRUM Model for Pakistan Kunhar River Basin Considering Long-term Snow Melt and Cover (장기 융·적설을 고려한 파키스탄 Kunhar강 유역 K-DRUM모형 구축 및 적용)

  • Park, Jin Hyeog;Hur, Young Teck;Noh, Joon Woo;Kim, Seo-Won
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.6
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    • pp.2237-2244
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    • 2013
  • In this study, physics based K-DRUM(K-water Distributed RUnoff Model) using GIS spatial hydrologic data as input data was developed to account for the temperature variation according to the altitude change considering snow melt and cover. The model was applied for Pakistan Kunhar River Basin($2,500km^2$) to calculate long-term discharge considering snow melt and cover. Time series analysis of the temperature and rainfall data reveals that temperature and rainfall of the river basin differs significantly according to altitude change compared to domestic basin. Thus, applying temperature and altitude lapse rate during generate input data generation. As a result, calculated discharge shows good agreement with observed ones considering snow melt and accumulation characteristic which has the difference of 4,000 meter elevation above sea level. In addition, the simulated discharge strongly showed snow melting effect associated with temperature rise during the summer season.