• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.627-637
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• 2022

To know the magnitudes of extreme floods for various sizes of watersheds, massive streamflow data is fundamentally required. However, small/medium-size watersheds missed streamflow data because of the lack of gauge stations. In this study, the Streamflow Propagation Method (SPM) was applied to generate streamflow data for small/medium size watersheds with no measurements. Based on the generated streamflow data for ungauged watersheds at three different locations (i.e., Chungju Dam (CJD), Seomjin Dam (SJD), and Andong Dam (ADD) watersheds), the scale ranges of extreme floods were evaluated for different sizes of ungauged watersheds by using the specific flood distribution analysis. As a general result, a range of specific floods decreases with increasing watershed size. The distribution of the specific flood in the same size of a watershed possibly depends on the size and topography of the watershed area. The delivered equations were compared to show the relations between the specific flood and sizes of watersheds. In the comparisons of equations, the Creager envelope curve has the higher potential to represent the maximum flood distribution for each watershed. For the generalization of the maximum flood distribution for three watersheds, optimized envelop curves are obtained with lower RMSE than that of Creager envelope curve.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.735-743
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• 2017

With growing concerns about ever-increasing anthropogenic greenhouse gas emissions, it is crucial to enhance preparedness for unprecedented extreme weathers that can bring catastrophic consequences. In this study, we proposed a stochastic framework that considers uncertainty in weather forecasts for flood analyses. First, we calibrated a simple rainfall-runoff model against observed hourly hydrographs. Then, using probability density functions of rainfall depths conditioned by 6-hourly weather forecasts, we generated many stochastic rainfall depths for upcoming 48 hours. We disaggregated the stochastic 6-hour rainfalls into an hourly scale, and input them into the runoff model to quantify a probabilistic range of runoff during upcoming 48 hours. Under this framework, we assessed two rainfall events occurred in Bocheong River Basin, South Korea in 2017. It is indicated actual flood events could be greater than expectations from weather forecasts in some cases; however, the probabilistic runoff range could be intuitive information for managing flood risks before events. This study suggests combining deterministic and stochastic methods for forecast-based flood analyses to consider uncertainty in weather forecasts.

• Journal of Korean Society of Disaster and Security
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• v.13 no.2
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• pp.53-63
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• 2020

In this study, the two-dimensional flow analysis model Hydro_AS-2D model was used to simulate the situation of flooding in Seongsangu and Uichang-gu in Changwon in the event of rising sea levels and extreme flooding, and the results were expressed on three-dimensional topography and the optimal evacuation path was derived using BIM technology. Climate change significantly affects two factors in terms of flood damage: rising sea levels and increasing extreme rainfall ideas. The rise in sea level itself can not only have the effect of flooding coastal areas and causing flooding, but it also raises the base flood level of the stream, causing the rise of the flood level throughout the stream. In this study, the rise of sea level by climate change, the rise of sea level by storm tidal wave by typhoon, and the extreme rainfall by typhoon were set as simulated conditions. The three-dimensional spatial information of the entire basin was constructed using the information of topographical space in Changwon and the information of the river crossing in the basic plan for river refurbishment. Using BIM technology, the target area was constructed as a three-dimensional urban information model that had information such as the building's height and location of the shelter on top of the three-dimensional topographical information, and the results of the numerical model were expressed on this model and used for analysis for evacuation planning. In the event of flooding, the escape route is determined by an algorithm that sets the path to the shelter according to changes in the inundation range over time, and the set path is expressed on intuitive three-dimensional spatial information and provided to the user.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.20-25
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• 2012

New Zealand suffers from regular floods, these being the most common source of insurance claims for damage from natural hazard events in the country. This paper describes the origin and distribution of the largest floods in New Zealand, and describes the systems used to monitor and predict floods. In New Zealand, broad-scale heavy rainfall (and flooding), is the result of warm moist air flowing out from the tropics into the mid-latitudes. There is no monsoon in New Zealand. The terrain has a substantial influence on the distribution of rainfall, with the largest annual totals occurring near the South Island's Southern Alps, the highest mountains in the country. The orographic effect here is extreme, with 3km of elevation gained over a 20km distance from the coast. Across New Zealand, short duration high intensity rainfall from thunderstorms also causes flooding in urban areas and small catchments. Forecasts of severe weather are provided by the New Zealand MetService, a Government owned company. MetService uses global weather models and a number of limited-area weather models to provide warnings and data streams of predicted rainfall to local Councils. Flood monitoring, prediction and warning are carried out by 16 local Councils. All Councils collect their own rainfall and river flow data, and a variety of prediction methods are utilized. These range from experienced staff making intuitive decisions based on previous effects of heavy rain, to hydrological models linked to outputs from MetService weather prediction models. No operational hydrological models are linked to weather radar in New Zealand. Councils provide warnings to Civil Defence Emergency Management, and also directly to farmers and other occupiers of flood prone areas. Warnings are distributed by email, text message and automated voice systems. A nation-wide hydrological model is also operated by NIWA, a Government-owned research institute. It is linked to a single high resolution weather model which runs on a super computer. The NIWA model does not provide public forecasts. The rivers with the greatest flood flows are shown, and these are ranked in terms of peak specific discharge. It can be seen that of the largest floods occur on the West Coast of the South Island, and the greatest flows per unit area are also found in this location.

• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.104-110
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• 2014

The Han River is the only waterway in Korea where estuary is not blocked by dykes so that tidal water is flowing in and out through the tidal reach. The extreme tidal range in the Yellow Sea causes an intense flood current, stretching over horizontal extents of tens of kilometers into the rivers. To elucidate the flow reversal by discharge conditions and transient tidal level in the Han river, numerical simulations were conducted under 7 boundary conditions for two days with 10 minute time step. As the flow conditions changed from low discharge and high tidal difference to high discharge and low tidal difference, the flow reversals became weaker and the velocity of forward flow direction became higher due to the increased flow momentums and decreased tidal differences. In the case of normal flow, the maximum reverse velocity was 0.4 m/s, which was equivalent to the maximum forward velocity. In addition, the pattern of the development and decay of forward and reverse flow was presented.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.661-671
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• 2017

The objective of this study was to analyze the flood stage considering the uncertainty caused by the river roughness coefficients and discharge. The methodology of this study involved the GLUE (Generalized Likelihood Uncertainty Estimation) to quantify the uncertainty bounds applying three different storm events. The uncertainty range of the roughness was 0.025~0.040. In case of discharge, the uncertainty stemmed from parameters in stage-discharge rating curve, if h represents stage for discharge Q, which can be written as $Q=A(h-B)^C$. Parameters in rating curve (A, B and C) were estimated by non-linear regression model and assumed by t distribution. The range of parameters in rating curve was 5.138~18.442 for A, -0.524~0.104 for B and 2.427~2.924 for C. By sampling 10,000 parameter sets, Monte Carlo simulations were performed. The simulated stage value was represented by 95% confidence interval. In storm event 1~3, the average bound was 0.39 m, 0.83 m and 0.96 m, respectively. The peak bound was 0.52 m, 1.36 m and 1.75 m, respectively. The recurrence year of each storm event applying the frequency analysis was 1-year, 10-year and 25-year, respectively.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.733-745
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• 2010

Seasonality of hydrologic extreme variable is a significant element from a water resources managemental point of view. It is closely related with various fields such as dam operation, flood control, irrigation water management, and so on. Hydrological frequency analysis conjunction with partial duration series rather than block maxima, offers benefits that include data expansion, analysis of seasonality and occurrence. In this study, nonstationary frequency analysis based on the Bayesian model has been suggested which effectively linked with advantage of POT (peaks over threshold) analysis that contains seasonality information. A selected threshold that the value of upper 98% among the 24 hours duration rainfall was applied to extract POT series at Seoul station, and goodness-fit-test of selected GEV distribution has been examined through graphical representation. Seasonal variation of location and scale parameter ($\mu$ and $\sigma$) of GEV distribution were represented by Fourier series, and the posterior distributions were estimated by Bayesian Markov Chain Monte Carlo simulation. The design rainfall estimated by GEV quantile function and derived posterior distribution for the Fourier coefficients, were illustrated with a wide range of return periods. The nonstationary frequency analysis considering seasonality can reasonably reproduce underlying extreme distribution and simultaneously provide a full annual cycle of the design rainfall as well.

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.711-723
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• 2008

In this study, Hydrologic regime alterations(magnitude, magnitude and duration of annual extreme, frequency and duration of high and low pulse, rate and frequency of water condition changes, Range of Variability Approach) were analyzed by using Indicators of Hydrologic Alterations at the 11 major multi-purpose dam. The analysis result of the magnitude of monthly water conditions during drought season, inflow was $6.38m^3/sec{\sim}39.84m^3/sec$ and outflow was $20.36m^3/sec{\sim}49.43m^3/sec$, was increased $1.84%{\sim}200.98%$. The analysis result of the magnitude of monthly water conditions during flood season, inflow was from $79.06m^3/sec{\sim}137.12m^3/sec$ and outflow was from $65.32m^3/sec{\sim}80.16m^3/sec$, was decreased from $18.19%{\sim}40.39%$. The analysis result of the magnitude and duration of annual extreme, 1-day minimum was increased $82.86%{\sim}2,950%$, but 1-day maximum was decreased $34.78%{\sim}83.96%$. The analysis result of the frequency and duration of high and low pulse, low pulse count was decreased $29.67%{\sim}99.07%$ and high pulse count was also decreased $4.6%{\sim}92.35%$ after dam operation. Hydrograph rise rate was decreased $15.84%{\sim}79.31%$ and fall rate was $1.97%{\sim}107.10%$. RVA of 1-day minimum was increased $0.60{\sim}2.67$, also RVA of 1-day maximum was decreased $0.50{\sim}1.00$.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.32-32
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• 2023

Incidences of urban flood and extreme heat waves (due to the urban heat island effect) are expected to increase in New Zealand under future climate change (IPCC 2022; MfE 2020). Increasingly, the mitigation of such events will depend on the resilience of a range Nature-Based Solutions (NBS) used in Sustainable Urban Drainage Schemes (SUDS), or Water Sensitive Urban Design (WSUD) (Jamei and Tapper 2019; Johnson et al 2021). Understanding the impact of changing precipitation and temperature regimes due climate change is therefore critical to the long-term resilience of such urban infrastructure and design. Cuthbert et al (2022) have assessed the trade-offs between the water retention and cooling benefits of different urban greening methods (such as WSUD) relative to global location and climate. Using the Budyko water-energy balance framework (Budyko 1974), they demonstrated that the potential for water infiltration and storage (thus flood mitigation) was greater where potential evaporation is high relative to precipitation. Similarly, they found that the potential for mitigation of drought conditions was greater in cooler environments. Subsequently, Jaramillo et al. (2022) have illustrated the locations worldwide that will deviate from their current Budyko curve characteristic under climate change scenarios, as the relationship between actual evapotranspiration (AET) and potential evapotranspiration (PET) changes relative to precipitation. Using the above approach we assess the impact of future climate change on the urban water-energy balance in three contrasting New Zealand cities (Auckland, Wellington, Christchurch and Invercargill). The variation in Budyko curve characteristics is then used to describe expected changes in water storage and cooling potential in each urban area as a result of climate change. The implications of the results are then considered with respect to existing WSUD guidelines according to both the current and future climate in each location. It was concluded that calculation of Budyko curve deviation due to climate change could be calculated for any location and land-use type combination in New Zealand and could therefore be used to advance the general understanding of climate change impacts. Moreover, the approach could be used to better define the concept of urban infrastructure resilience and contribute to a better understanding of Budyko curve dynamics under climate change (questions raised by Berghuijs et al 2020)). Whilst this knowledge will assist in implementation of national climate change adaptation (MfE, 2022; UNEP, 2022) and improve climate resilience in urban areas in New Zealand, the approach could be repeated for any global location for which present and future mean precipitation and temperature conditions are known.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.3
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• pp.549-559
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• 2017

The complementary relationship hypothesis for areal evapotranspirations was validated in the regional-scale area of multipurpose dam basins in Korea and the long-term water balances were indirectly identified. Annual actual evapotranspiration ($ET_A$) was assumed the difference between total annual precipitation and total annual inflow and the available moisture was assumed the total precipitation. The seasonally varying pan coefficient (kp) is estimated as the ratio of the $ET_{pan}$ and the evapotranspiration calculated by FAO Penman-Monteith equation ($ET_{PM}$). The complementary relationships using ground observation data of $ET_P$ and $ET_A$ in the multipurpose dam basins follow generally the typical pattern that $ET_P$ and $ET_A$ is complementary and converges to equivalent evapotranspiration ($ET_W$) under the extreme wet environment. However, $ET_A$ of Juam dam was estimated relatively greater than other basins and exceeds even $ET_P$ at certain range with high moisture availability, which can be understood as the results of possible over-estimation of precipitation or under-estimation of dam inflow. It is expected that the use of evapotranspiration complementary relationship for validating hydrological water balances will contribute to controlling uncertainties in estimating dam inflows during flood season in particular.