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The relationships between a variety of hydro-meteorological variables and irrigation water use rates (WUR) were investigated in this study. Standardized Precipitation Index (SPI), Potential Evapotranspiration (PET), and Normalized Difference Vegetation Index (NDVI) were explored to identify the relationship with the WUR. The Yeongsan river basin, the agricultural land of which is mostly occupied by well-irrigated paddy, was used for the pilot study. Four different temporal scales of SPI-3, 6, 9, and 12 were tested, and PET was calculated using the Thornthwaite method. To calculate NDVI, the surface spectral reflectance data, which was acquired by Moderate Resolution Imaging Spectroradiometer (MODIS) equipped on the Terra satellite, were used. As a result, there was a statistically significant relationship between SPI9 and the WUR during drought periods in which negative values of SPI9 were obtained. The WUR was strongly correlated with both PET and NDVI. Compared with SPI, the variability of WUR in this study area was more sensitively affected by PET and NDVI, which can cause a potential lack of agricultural water supply. The finding of this study implies that SPI9, PET, and NDVI are the critical factors for predicting water withdrawal during drought conditions so that they can be used for irrigational water use management. Although a part of the findings of this study has been discussed by a few previous studies, this study is novel in that it quantifies the relationship between these factors using actual field observations of streamflow withdrawal for irrigation.
Jang Sung; Donghae Baek; Young Ryu; Seung Seo; Kee-Won Seong. Effects of Hydro-Meteorological Factors on Streamflow Withdrawal for Irrigation in Yeongsan River Basin. Sustainability 2021, 13, 4969 .
AMA StyleJang Sung, Donghae Baek, Young Ryu, Seung Seo, Kee-Won Seong. Effects of Hydro-Meteorological Factors on Streamflow Withdrawal for Irrigation in Yeongsan River Basin. Sustainability. 2021; 13 (9):4969.
Chicago/Turabian StyleJang Sung; Donghae Baek; Young Ryu; Seung Seo; Kee-Won Seong. 2021. "Effects of Hydro-Meteorological Factors on Streamflow Withdrawal for Irrigation in Yeongsan River Basin." Sustainability 13, no. 9: 4969.
The relationships between a variety of hydro-meteorological variables and irrigation water use rates (WUR) were investigated in this study. Standardized Precipitation Index (SPI), Potential Evapotranspiration (PET), and Normalized difference vegetation index (NDVI) are explored in order to identify the relationship with the WUR. The Yeongsan river basin which agricultural land is mostly occupied by well-irrigated paddy was used for the pilot study. 4 different temporal scale of SPI-3, 6, 9, and 12-were tested, and PET was calculated using Thornthwaite method. To calculate NDVI, the surface spectral reflectance data, which was acquired by Moderate Resolution Imaging Spectroradiometer (MODIS) equipped on Terra satellite, were used. As a result, there was a statistically significant relationship between SPI9 and the WUR during drought period in which negative values of SPI9 occurred. Besides, the WUR was strongly correlated with both PET and NDVI. Comparing to SPI, the variability of WUR in this study area was more sensitively affected by PET and NDVI which can cause potential lack of agricultural water supply. Based on the finding of this study, it implies that SPI9, PET, and NDVI are the critical factors for predicting water withdrawal during drought conditions so that they can be used for the irrigational water use management. Although the findings of this study have been suggested by a few previous studies, this study has its novelty in quantifying those discussions using actual field observations of streamflow withdrawal for irrigation.
Jang Hyun Sung; Donghae Baek; Young Ryu; Seung Beom Seo. Effects of Hydro-Meteorological Factors on Streamflow Withdrawal for Irrigation. 2021, 1 .
AMA StyleJang Hyun Sung, Donghae Baek, Young Ryu, Seung Beom Seo. Effects of Hydro-Meteorological Factors on Streamflow Withdrawal for Irrigation. . 2021; ():1.
Chicago/Turabian StyleJang Hyun Sung; Donghae Baek; Young Ryu; Seung Beom Seo. 2021. "Effects of Hydro-Meteorological Factors on Streamflow Withdrawal for Irrigation." , no. : 1.
This study projected future changes in potential evapotranspiration (PET) over North Korea, which has been exposed to climate change risks. For this purpose, climate change scenarios downscaled at station scale were produced under RCP8.5, which downscale method preserves the long-term trend driven by climate models. Based on the ability to replicate observation, representative climate change scenarios (RCCS) were selected using performance indicators and TOPSIS method. The GCMs having higher spatial resolution were selected as RCCS, and projected that PET would increase in the future. It is found that the inter-model variability of PET in the summer was gradually increased over North Korea and annual mean evapotranspiration would be expected to increase by 1.4 times (F1, 2011–2040), 2.0 times (F2, 2041–2070) and 2.6 times (F3, 2071–2100). In preparation for the deficit of available water due to the increase in evapotranspiration, securing alternative water resources and construction of multi-purpose dams are required.
Young Ryu; Eun-Sung Chung; Seung Beom Seo; Jang Hyun Sung. Projection of Potential Evapotranspiration for North Korea Based on Selected GCMs by TOPSIS. KSCE Journal of Civil Engineering 2020, 24, 2849 -2859.
AMA StyleYoung Ryu, Eun-Sung Chung, Seung Beom Seo, Jang Hyun Sung. Projection of Potential Evapotranspiration for North Korea Based on Selected GCMs by TOPSIS. KSCE Journal of Civil Engineering. 2020; 24 (9):2849-2859.
Chicago/Turabian StyleYoung Ryu; Eun-Sung Chung; Seung Beom Seo; Jang Hyun Sung. 2020. "Projection of Potential Evapotranspiration for North Korea Based on Selected GCMs by TOPSIS." KSCE Journal of Civil Engineering 24, no. 9: 2849-2859.
Although many studies have sought to characterize future meteorological droughts, a few efforts have been done for quantifying the uncertainty, inter-model variability, arises from global circulation models (GCM) ensemble. A clear understanding of the uncertainty in multiple GCMs should be preceded before future meteorological droughts are projected. Therefore, this study evaluates the uncertainty in future meteorological drought characteristics that are induced by GCM ensemble using the custom measure “the degree of GCM spreading”. Future meteorological drought indices, the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), were computed to five different time scales: 3, 6, 9, 12 and 24 months using statistically downscaled 28 GCMs under Representative Concentration Pathway (RCP) 4.5 and 8.5 at 60 weather stations in South Korea. The frequency, duration, and severity of drought events were estimated for three different future periods; F1 (2010–2039), F2 (2040–2069), and F3 (2070–2099). It was found that the uncertainty increases as the time scale lengthens regardless of a choice of drought indices or RCP scenarios. It also turned out that the SPI exhibits larger uncertainty rather than the SPEI, because temperature data exhibit a relatively much smaller variability comparing to precipitation data. Moreover, there was a shift of regions having larger values of the increasing rate between F1 and F2, which is shift from the north-western to southern region of South Korea.
Jang Hyun Sung; Junehyeong Park; Jong-June Jeon; Seung Beom Seo. Assessment of Inter-Model Variability in Meteorological Drought Characteristics Using CMIP5 GCMs over South Korea. KSCE Journal of Civil Engineering 2020, 24, 2824 -2834.
AMA StyleJang Hyun Sung, Junehyeong Park, Jong-June Jeon, Seung Beom Seo. Assessment of Inter-Model Variability in Meteorological Drought Characteristics Using CMIP5 GCMs over South Korea. KSCE Journal of Civil Engineering. 2020; 24 (9):2824-2834.
Chicago/Turabian StyleJang Hyun Sung; Junehyeong Park; Jong-June Jeon; Seung Beom Seo. 2020. "Assessment of Inter-Model Variability in Meteorological Drought Characteristics Using CMIP5 GCMs over South Korea." KSCE Journal of Civil Engineering 24, no. 9: 2824-2834.
The role of large-scale drivers—climate, population, and adaption of efficient irrigation practices—in controlling irrigation water use efficiency has rarely been addressed. The primary objectives of our study are to (1) investigate the long-term changes in irrigation water use over the contiguous United States using a nationwide, multidecadal database created by USGS; and (2) understand the role of large-scale drivers in the water application rate, an indicator of irrigation efficiency. The authors find that the eastern states are currently withdrawing more surface water than in the past, while groundwater withdrawal has increased across all states. An increase in efficient irrigation schemes is leading to a decrease in traditional flood irrigation schemes. Spatiotemporal analyses confirm that the eastern states are presently withdrawing more irrigation water per acreage than in the past. While the choice of efficient irrigation practices (sprinkler and drip) is the major driver influencing the application rate, other factors such as cost and type of crops predominantly determine the type of irrigation system chosen for improving the application rate.
Rajarshi Das Bhowmik; Seung Beom Seo; Priyam Das; A. Sankarasubramanian. Synthesis of Irrigation Water Use in the United States: Spatiotemporal Patterns. Journal of Water Resources Planning and Management 2020, 146, 04020050 .
AMA StyleRajarshi Das Bhowmik, Seung Beom Seo, Priyam Das, A. Sankarasubramanian. Synthesis of Irrigation Water Use in the United States: Spatiotemporal Patterns. Journal of Water Resources Planning and Management. 2020; 146 (7):04020050.
Chicago/Turabian StyleRajarshi Das Bhowmik; Seung Beom Seo; Priyam Das; A. Sankarasubramanian. 2020. "Synthesis of Irrigation Water Use in the United States: Spatiotemporal Patterns." Journal of Water Resources Planning and Management 146, no. 7: 04020050.
Accurate streamflow forecasts enable the appropriate management of water resources. Although there is a general consensus that climate information can enhance hydrological predictability, this might not be the case if the accuracy of the given climate information is unreliable. Hence, this study has developed a modeling framework to estimate the role of climate information in forecasting accurate streamflow. Ensemble streamflow prediction (ESP) technology was adopted as a dynamic hydrologic forecast method to 35 watersheds in South Korea. The probabilistic precipitation forecast (PPF), issued by the Korea Meteorological Administration, was used as climate information for updating the probabilities of climate scenarios. First, we found that the current PPF is not accurate enough for significantly enhancing the streamflow forecasting accuracy. Subsequently, multiple sets of PPF were synthetically generated to evaluate the role of climate information. Given the perfect categorical climate forecasts, we found that there is much potential for the enhancement of streamflow forecast skill especially in the seasons that exhibit greater streamflow variability. However, there is less potential for increasing the streamflow forecasting skill under below-normal conditions. The proposed modeling framework is capable of quantifying the magnitude of potential improvement in hydrological predictability under the assumption that better climate information will be available in the future. We expect that this modeling framework can be effectively applied to other regions across a wide range of climate regimes.
Seung Beom Seo; Jang Hyun Sung. The role of probabilistic precipitation forecasts in hydrologic predictability. Theoretical and Applied Climatology 2020, 141, 1203 -1218.
AMA StyleSeung Beom Seo, Jang Hyun Sung. The role of probabilistic precipitation forecasts in hydrologic predictability. Theoretical and Applied Climatology. 2020; 141 (3-4):1203-1218.
Chicago/Turabian StyleSeung Beom Seo; Jang Hyun Sung. 2020. "The role of probabilistic precipitation forecasts in hydrologic predictability." Theoretical and Applied Climatology 141, no. 3-4: 1203-1218.
In order to enhance the streamflow forecast skill, seasonal/sub-seasonal streamflow forecasts can be post-processed by incorporating new information, such as climate signals. This study proposed a simple yet efficient approach, the “Bivar_update” model that utilizes bivariate climate forecast to update individual probabilities of the ensemble streamflow prediction. The Bayesian updating scheme is used to update the joint probability mass function derived from historic precipitation and temperature data sets. Thirty-five dam basins were used for the case study, and the modified Tank model was embedded into the ensemble streamflow prediction framework. The performance of the proposed approach was evaluated through a comparison with a reference streamflow forecast model, the “Univar_update” model, that reflects only precipitation forecast, in terms of deterministic and categorical streamflow forecast accuracy. For this purpose, multiple cases of probabilistic precipitation and temperature forecasts were synthetically generated. As a result, the Bivar_update model was able to decrease the errors in forecast under below-normal conditions. The improvements in forecasting skills were found for both measures; deterministic and categorical streamflow forecasts. Since the proposed Bivar_update model reflects both precipitation and temperature information, it can compensate low predictability especially under dry conditions in which the streamflow’s dependency on temperature increases.
Jang Hyun Sung; Young Ryu; Seung Beom Seo. Utilizing Bivariate Climate Forecasts to Update the Probabilities of Ensemble Streamflow Prediction. Sustainability 2020, 12, 2905 .
AMA StyleJang Hyun Sung, Young Ryu, Seung Beom Seo. Utilizing Bivariate Climate Forecasts to Update the Probabilities of Ensemble Streamflow Prediction. Sustainability. 2020; 12 (7):2905.
Chicago/Turabian StyleJang Hyun Sung; Young Ryu; Seung Beom Seo. 2020. "Utilizing Bivariate Climate Forecasts to Update the Probabilities of Ensemble Streamflow Prediction." Sustainability 12, no. 7: 2905.
This study aims to provide a practically efficient approach for determining the most efficient joint operation rule for two reservoirs connected by a waterway tunnel. For this purpose, the connecting tunnel's effect was assessed and three heuristic joint operation rules accounting for the connecting tunnel were evaluated. A standard operation policy with the connecting tunnel led to positive effects on the water resource system of the target basin with regard to a reliable water supply. The connecting tunnel provides an additional water supply of 12.4 million m3/year to the basin, and the reliability of the two reservoirs increased. Among the three rules, the equivalent reservoir (ER) rule led to the most positive effect on water supply. We found that the ER rule could maximize the positive effects of the connecting tunnel by maintaining the effective water storage rates of the two reservoirs. Moreover, the effects of hydrologic uncertainty on the joint operation rules were discussed using the synthetically generated multiple streamflow traces.
Ji Woo Jeong; Young-Oh Kim; Seung Beom Seo. Evaluating joint operation rules for connecting tunnels between two multipurpose dams. Water Policy 2020, 51, 392 -405.
AMA StyleJi Woo Jeong, Young-Oh Kim, Seung Beom Seo. Evaluating joint operation rules for connecting tunnels between two multipurpose dams. Water Policy. 2020; 51 (3):392-405.
Chicago/Turabian StyleJi Woo Jeong; Young-Oh Kim; Seung Beom Seo. 2020. "Evaluating joint operation rules for connecting tunnels between two multipurpose dams." Water Policy 51, no. 3: 392-405.
This study proposed a simple and efficient method for developing time-varying discrete hedging rules. The novelty of the proposed methodology is that long-range streamflow traces are inserted into the sequent peak processes in order to reflect long-lasting drought events, which is rarely considered, during the development of the hedging rules. The developed rules were evaluated with three performance indices (risk, resiliency, and vulnerability) across a wide range of synthetic streamflow scenarios that represent changes in the annual mean streamflow and the long-range streamflow dependency. Boryung Dam, located in South Korea, was used as a case study. As a result, the developed hedging rules reflecting long-range streamflow traces led to enhanced reservoir operation performance results in terms of resiliency and vulnerability indices. The developed hedging rules outperformed the reference hedging rules, especially under dry conditions. When there was a strong long-range dependency in streamflow, the superiority of the developed hedging rules was found to be remarkable. Since the proposed methodology is relatively simple, it will be easy for dam operators to understand and implement discrete hedging rules at different sites.
Seung Beom Seo; Young-Oh Kim; Shin-Uk Kang. Time-Varying Discrete Hedging Rules for Drought Contingency Plan Considering Long-Range Dependency in Streamflow. Water Resources Management 2019, 33, 2791 -2807.
AMA StyleSeung Beom Seo, Young-Oh Kim, Shin-Uk Kang. Time-Varying Discrete Hedging Rules for Drought Contingency Plan Considering Long-Range Dependency in Streamflow. Water Resources Management. 2019; 33 (8):2791-2807.
Chicago/Turabian StyleSeung Beom Seo; Young-Oh Kim; Shin-Uk Kang. 2019. "Time-Varying Discrete Hedging Rules for Drought Contingency Plan Considering Long-Range Dependency in Streamflow." Water Resources Management 33, no. 8: 2791-2807.
The numerous choices between climate change scenarios makes decision-making difficult for the assessment of climate change impacts. Previous studies have used climate models to compare performance in terms of simulating observed climates or preserving model variability among scenarios. In this study, the Katsavounidis-Kuo-Zhang algorithm was applied to select representative climate change scenarios (RCCS) that preserve the variability among all climate change scenarios (CCS). The performance of multi-model ensemble of RCCS was evaluated for reference and future climates. It was found that RCCS was well suited for observations and multi model ensemble of all CCS. Using the RCCS under RCP (Representative Concentration Pathway) 8.5, the future extreme precipitation was projected. As a result, the magnitude and frequency of extreme precipitation increased towards the farther future. Especially, extreme precipitation (daily maximum precipitation of 20-year return-period) during 2070-2099, was projected to occur once every 8.3-year. The RCCS employed in this study is able to successfully represent the performance of all CCS, therefore, this approach can give opportunities managing water resources efficiently for assessment of climate change impacts.
Jang Hyun Sung; Minsung Kwon; Jong-June Jeon; Seung Beom Seo. A Projection of Extreme Precipitation Based on a Selection of CMIP5 GCMs over North Korea. Sustainability 2019, 11, 1976 .
AMA StyleJang Hyun Sung, Minsung Kwon, Jong-June Jeon, Seung Beom Seo. A Projection of Extreme Precipitation Based on a Selection of CMIP5 GCMs over North Korea. Sustainability. 2019; 11 (7):1976.
Chicago/Turabian StyleJang Hyun Sung; Minsung Kwon; Jong-June Jeon; Seung Beom Seo. 2019. "A Projection of Extreme Precipitation Based on a Selection of CMIP5 GCMs over North Korea." Sustainability 11, no. 7: 1976.
For adaptation to the changing climate, planning of new water infrastructures should be carefully evaluated by either “robust” or “adaptive” decision making methods. For this purpose, a new economic feasibility analysis framework has been developed using real option analysis that can reflect “robust” and “adaptive” perspectives in decision making. To reflect uncertainty in climate (“robust”), the probabilities of drought occurrences are estimated by the results of dam storage simulation. To provide flexibility in decision making (“adaptive”), three different types of real options are used as a form of a decision tree. By re-evaluating economic feasibility of the Boryeong Dam conduit project, it is found that the “abort” option can be the best choice for minimal economic loss on the project. Further, more conditions for maximizing economic feasibility on the project are addressed from the sensitivity analysis. It is found that the “invest” option would be more economically feasible than “abort” option, when the probability of severe drought increases by approximately 20%. Thus, though the Boryeong Dam conduit project is not economically feasible for now, it might be an appropriate infrastructure if it is constructed in the future, when the probability of drought occurrence increases.
Sun Hoo Ihm; Seung Beom Seo; Young-Oh Kim. Valuation of Water Resources Infrastructure Planning from Climate Change Adaptation Perspective using Real Option Analysis. KSCE Journal of Civil Engineering 2019, 23, 2794 -2802.
AMA StyleSun Hoo Ihm, Seung Beom Seo, Young-Oh Kim. Valuation of Water Resources Infrastructure Planning from Climate Change Adaptation Perspective using Real Option Analysis. KSCE Journal of Civil Engineering. 2019; 23 (6):2794-2802.
Chicago/Turabian StyleSun Hoo Ihm; Seung Beom Seo; Young-Oh Kim. 2019. "Valuation of Water Resources Infrastructure Planning from Climate Change Adaptation Perspective using Real Option Analysis." KSCE Journal of Civil Engineering 23, no. 6: 2794-2802.
This study has developed a hydrologic forecasting system for correcting the systematic bias inherent in hydrologic simulations based on the Bayes' theorem. The observed climatology was used as prior information, and results of a linear regression model that describes the relationship between ‘the observed streamflow’ and ‘the mean of the Ensemble Streamflow Prediction (ESP) forecasts’ was used to form a likelihood function. The Bayes' theorem was then applied to produce posterior information for the streamflow forecast. Thirty-five watersheds, in which a dam is operated, were tested in this study, and the forecast accuracy was evaluated. It was found that the developed Bayesian ESP (B-ESP) model is capable of improving the forecast accuracy of the ESP. It was found that the forecasting accuracy was improved for all the different lengths of lead-times with the B-ESP model. Nonetheless, the B-ESP model obtained lower RPSS values than the ESP, while its deterministic forecasting accuracy was better than the ESP. This is due to the intrinsic attribute of the Bayesian inference.
Seung Beom Seo; Young-Oh Kim; Shin-Uk Kang; Gun Il Chun. Improvement in long-range streamflow forecasting accuracy using the Bayes' theorem. Water Policy 2019, 50, 616 -632.
AMA StyleSeung Beom Seo, Young-Oh Kim, Shin-Uk Kang, Gun Il Chun. Improvement in long-range streamflow forecasting accuracy using the Bayes' theorem. Water Policy. 2019; 50 (2):616-632.
Chicago/Turabian StyleSeung Beom Seo; Young-Oh Kim; Shin-Uk Kang; Gun Il Chun. 2019. "Improvement in long-range streamflow forecasting accuracy using the Bayes' theorem." Water Policy 50, no. 2: 616-632.
South Korea endured extreme drought through 2015 and 2016. This hydrological drought led to a socio-economic drought which is a restriction on stream water use. Previous studies have explored streamflow drought using a threshold level based on flow duration curves, but streamflow drought does not necessarily lead to stream water deficit, which is related to water demand. Therefore, this study introduced a threshold for stream water deficit in South Korea, which is termed as river management flow, and was applied to Geum River Basin where a severe drought recently occurred. The stream water coordination council has restricted the use of stream water to cope with the stream water deficit. The deficit characteristics for the upstream and downstream river management flow should be similar in order to ensure the feasibility of stream water restrictions. Thus, upstream and downstream river management flows, which reproduced similar deficit characteristics to those of the reference site, were estimated. The deficit characteristics of Bugang and Gyuam were estimated from their river management flows for the 2015 drought and were comparable to those of Gongju. We expect this study to minimize the conflict between upstream and downstream water users in future.
Jang Hyun Sung; Seung Beom Seo. Estimation of River Management Flow Considering Stream Water Deficit Characteristics. Water 2018, 10, 1521 .
AMA StyleJang Hyun Sung, Seung Beom Seo. Estimation of River Management Flow Considering Stream Water Deficit Characteristics. Water. 2018; 10 (11):1521.
Chicago/Turabian StyleJang Hyun Sung; Seung Beom Seo. 2018. "Estimation of River Management Flow Considering Stream Water Deficit Characteristics." Water 10, no. 11: 1521.
A conjunctive management model has been developed to obtain optimal allocation of surface water and groundwater under different constraints during a drought. Two simulation models—a fully distributed hydrologic model and a reservoir simulation model—were incorporated in an optimization formulation using a simulation-optimization approach with response functions. The model was tested for the Haw River Basin located in North Carolina. A fully distributed hydrologic model, penn state integrated hydrologic model (PIHM), was used to compute simultaneous depletions in streamflow and groundwater level under pumping. A reservoir simulation model was then incorporated within the optimization framework to determine the optimal allocation of surface water and groundwater resources by minimizing reservoir deficit. A new groundwater sustainability constraint, recovery time for groundwater levels, was introduced in the conjunctive management model. Incorporating the reservoir simulation model within the optimization model resulted in reduced reservoir deficits. Moreover, the recovery time constraint will allow decision makers to evaluate the trade-off between maximizing water availability and preserving groundwater sustainability during a drought. It is envisioned that the management model proposed in this study is a step toward sustainable groundwater withdrawal during a drought.
S. B. Seo; G. Mahinthakumar; A. Sankarasubramanian; M. Kumar. Conjunctive Management of Surface Water and Groundwater Resources under Drought Conditions Using a Fully Coupled Hydrological Model. Journal of Water Resources Planning and Management 2018, 144, 04018060 .
AMA StyleS. B. Seo, G. Mahinthakumar, A. Sankarasubramanian, M. Kumar. Conjunctive Management of Surface Water and Groundwater Resources under Drought Conditions Using a Fully Coupled Hydrological Model. Journal of Water Resources Planning and Management. 2018; 144 (9):04018060.
Chicago/Turabian StyleS. B. Seo; G. Mahinthakumar; A. Sankarasubramanian; M. Kumar. 2018. "Conjunctive Management of Surface Water and Groundwater Resources under Drought Conditions Using a Fully Coupled Hydrological Model." Journal of Water Resources Planning and Management 144, no. 9: 04018060.
For sustainable management of water resources, adaptive decisions should be determined considering future climate change. Since decision makers have difficulty in formulating a decision when they should consider a large number of climate change scenarios, selecting a subset of Global Circulation Models (GCM) outputs for climate change impact studies is required. In this study, the Katsavounidis-Kuo-Zhang (KKZ) algorithm was used for representative climate change scenarios selection and a comprehensive analysis has been done through a national-level case study of South Korea. The KKZ algorithm was applied to select a subset of GCMs for each subbasin in South Korea. To evaluate impacts of spatial aggregation level of climate data sets on preserving inter-model variability of hydrologic variables, three different scales (national level, river region level, subbasin level) were tested. It was found that only five GCMs selected by KKZ algorithm can explain almost of whole inter-model variability driven by all the 27 GCMs under Representative Concentration Pathways (RCP) 4.5 and 8.5. Furthermore, a single set of representative GCMs selected for national level was able to explain inter-model variability on almost the whole subbasins. In case of low flow variable, however, use of finer scale of climate data sets was recommended.
Seung Beom Seo; Young-Oh Kim. Impact of Spatial Aggregation Level of Climate Indicators on a National-Level Selection for Representative Climate Change Scenarios. Sustainability 2018, 10, 2409 .
AMA StyleSeung Beom Seo, Young-Oh Kim. Impact of Spatial Aggregation Level of Climate Indicators on a National-Level Selection for Representative Climate Change Scenarios. Sustainability. 2018; 10 (7):2409.
Chicago/Turabian StyleSeung Beom Seo; Young-Oh Kim. 2018. "Impact of Spatial Aggregation Level of Climate Indicators on a National-Level Selection for Representative Climate Change Scenarios." Sustainability 10, no. 7: 2409.
Statistical models for hydrologic simulation are a common choice among researchers particularly when catchment information is limited. In this study, we adopt a new statistical approach, namely Bayesian regression with multivariate linear spline (BMLS) for long-term simulation of streamflow on a Hydroclimate Data Network (HCDN) site in the United States. The study aims to: (i) evaluate the performance of the BMLS model; (ii) compare the performance of climate model outputs as predictors in hydrologic simulation; and (iii) estimate the changes in streamflow caused by anthropogenic climate change which is defined as the projected change in precipitation and temperature under different greenhouse gas emission scenarios. Performance of the BMLS model is compared with climatology for the validation period. Results suggest that the BMLS model forced with observed monthly precipitation and average temperature exhibits information that is not presented in the climatology of the validation period. Later, we consider Coupled Model Intercomparison Project Phase 5 (CMIP5) historical and hindcast runs to simulate streamflow at the HCDN site. The study found that sea-surface temperature-initialized decadal hindcast runs are performing no better than 20th century historical runs regarding hydrologic simulation. Finally, the changes in mean and variability in streamflow at the HCDN site are estimated by forcing the model with CMIP5 future projections for the period 2000–2049.
Rajarshi Das Bhowmik; Seung Beom Seo; Saswata Sahoo. Streamflow Simulation Using Bayesian Regression with Multivariate Linear Spline to Estimate Future Changes. Water 2018, 10, 875 .
AMA StyleRajarshi Das Bhowmik, Seung Beom Seo, Saswata Sahoo. Streamflow Simulation Using Bayesian Regression with Multivariate Linear Spline to Estimate Future Changes. Water. 2018; 10 (7):875.
Chicago/Turabian StyleRajarshi Das Bhowmik; Seung Beom Seo; Saswata Sahoo. 2018. "Streamflow Simulation Using Bayesian Regression with Multivariate Linear Spline to Estimate Future Changes." Water 10, no. 7: 875.
Since surface water and groundwater systems are fully coupled and integrated, increased groundwater withdrawal during drought may reduce groundwater discharges into the stream, thereby prolonging both systems’ recovery from drought. To analyze watershed response to basin-level groundwater pumping, we propose a modelling framework to understand the resiliency of surface water and groundwater systems using an integrated hydrologic model under transient pumping. The proposed framework incorporates uncertainties in initial conditions to develop robust estimates of restoration times of both surface water and groundwater and quantifies how pumping impacts state variables such as soil moisture. Groundwater pumping impacts over a watershed were also analyzed under different pumping volumes and different potential climate scenarios. Our analyses show that groundwater restoration time is more sensitive to variability in climate forcings as opposed to changes in pumping volumes. After the cessation of pumping, streamflow recovers quickly in comparison to groundwater, which has higher persistence. Pumping impacts on various hydrologic variables were also discussed. Potential for developing optimal conjunctive management plans using seasonal-to-interannual climate forecasts is also discussed.
S. B. Seo; G. Mahinthakumar; A. Sankarasubramanian; M. Kumar. Assessing the restoration time of surface water and groundwater systems under groundwater pumping. Stochastic Environmental Research and Risk Assessment 2018, 32, 2741 -2759.
AMA StyleS. B. Seo, G. Mahinthakumar, A. Sankarasubramanian, M. Kumar. Assessing the restoration time of surface water and groundwater systems under groundwater pumping. Stochastic Environmental Research and Risk Assessment. 2018; 32 (9):2741-2759.
Chicago/Turabian StyleS. B. Seo; G. Mahinthakumar; A. Sankarasubramanian; M. Kumar. 2018. "Assessing the restoration time of surface water and groundwater systems under groundwater pumping." Stochastic Environmental Research and Risk Assessment 32, no. 9: 2741-2759.
When selecting a subset of climate change scenarios (GCM models), the priority is to ensure that the subset reflects the comprehensive range of possible model results for all variables concerned. Though many studies have attempted to improve the scenario selection, there is a lack of studies that discuss methods to ensure that the results from a subset of climate models contain the same range of uncertainty in hydrologic variables as when all models are considered. We applied the Katsavounidis–Kuo–Zhang (KKZ) algorithm to select a subset of climate change scenarios and demonstrated its ability to reduce the number of GCM models in an ensemble, while the ranges of multiple climate extremes indices were preserved. First, we analyzed the role of 27 ETCCDI climate extremes indices for scenario selection and selected the representative climate extreme indices. Before the selection of a subset, we excluded a few deficient GCM models that could not represent the observed climate regime. Subsequently, we discovered that a subset of GCM models selected by the KKZ algorithm with the representative climate extreme indices could not capture the full potential range of changes in hydrologic extremes (e.g., 3-day peak flow and 7-day low flow) in some regional case studies. However, the application of the KKZ algorithm with a different set of climate indices, which are correlated to the hydrologic extremes, enabled the overcoming of this limitation. Key climate indices, dependent on the hydrologic extremes to be projected, must therefore be determined prior to the selection of a subset of GCM models.
Seung Beom Seo; Young-Oh Kim; Youngil Kim; Hyung-Il Eum. Selecting climate change scenarios for regional hydrologic impact studies based on climate extremes indices. Climate Dynamics 2018, 52, 1595 -1611.
AMA StyleSeung Beom Seo, Young-Oh Kim, Youngil Kim, Hyung-Il Eum. Selecting climate change scenarios for regional hydrologic impact studies based on climate extremes indices. Climate Dynamics. 2018; 52 (3-4):1595-1611.
Chicago/Turabian StyleSeung Beom Seo; Young-Oh Kim; Youngil Kim; Hyung-Il Eum. 2018. "Selecting climate change scenarios for regional hydrologic impact studies based on climate extremes indices." Climate Dynamics 52, no. 3-4: 1595-1611.
With concerns regarding global climate change increasing, recent studies on adapting to nonstationary climate change recommended a different planning strategy that could spread risks. Uncertainty in global climate change should be considered in any decision-making processes for flood mitigation strategies, especially in areas within a monsoon climate regime. This study applied a novel planning method called real option analysis (ROA) to an important water resources planning practice in Korea. The proposed method can easily be applied to other watersheds that are threatened by flood risk under climate change. ROA offers flexibility for decision-makers to reflect uncertainty at every stage during the project planning period. We successfully implemented ROA using a binomial tree model, including two real options—delay and abandon—to evaluate flood mitigation alternatives for the Yeongsan River Basin in Korea. The priority ranking of the four alternatives between the traditional discount cash flow (DCF) and ROA remained the same; however, two alternatives that were assessed as economically infeasible using DCF, were economically feasible using ROA. The binomial decision trees generated in this study are expected to be informative for decision-makers to conceptualize their adaptive planning procedure.
Young Ryu; Young-Oh Kim; Seung Beom Seo; Il Won Seo. Application of real option analysis for planning under climate change uncertainty: a case study for evaluation of flood mitigation plans in Korea. Mitigation and Adaptation Strategies for Global Change 2017, 23, 803 -819.
AMA StyleYoung Ryu, Young-Oh Kim, Seung Beom Seo, Il Won Seo. Application of real option analysis for planning under climate change uncertainty: a case study for evaluation of flood mitigation plans in Korea. Mitigation and Adaptation Strategies for Global Change. 2017; 23 (6):803-819.
Chicago/Turabian StyleYoung Ryu; Young-Oh Kim; Seung Beom Seo; Il Won Seo. 2017. "Application of real option analysis for planning under climate change uncertainty: a case study for evaluation of flood mitigation plans in Korea." Mitigation and Adaptation Strategies for Global Change 23, no. 6: 803-819.
Recent U.S. Geological Survey water-use report suggests that increasing water-use efficiency could mitigate the supply-and-demand imbalance arising from changing climate and growing population. However, this rich data have neither analyzed to understand the underlying patterns, nor have been investigated to identify the factors contributing to this increased efficiency. A national-scale synthesis of public supply withdrawals (“withdrawals”) reveals a strong North–south gradient in public supply water use with the increasing population in the South contributing to increased withdrawal. Contrastingly, a reverse South–north gradient exists in per capita withdrawals (“efficiency”), with northern states consistently improving the efficiency, while the southern states' efficiency declined. Our analyses of spatial patterns of per capita withdrawals further demonstrate that urban counties exhibit improved efficiency over rural counties. Improved efficiency is also demonstrated over high-income and well-educated counties. Given the potential implications of the findings in developing long-term water conservation measures (i.e., increasing block rates), we argue the need for frequent updates, perhaps monthly to annual, of water-use data for identifying effective strategies that control the water-use efficiency in various geographic settings under a changing climate.
A. Sankarasubramanian; J. L. Sabo; K. L. Larson; S. B. Seo; T. Sinha; R. Bhowmik; A. Ruhi Vidal; K. Kunkel; G. Mahinthakumar; E. Z. Berglund; J. Kominoski. Synthesis of public water supply use in the United States: Spatio‐temporal patterns and socio‐economic controls. Earth's Future 2017, 5, 771 -788.
AMA StyleA. Sankarasubramanian, J. L. Sabo, K. L. Larson, S. B. Seo, T. Sinha, R. Bhowmik, A. Ruhi Vidal, K. Kunkel, G. Mahinthakumar, E. Z. Berglund, J. Kominoski. Synthesis of public water supply use in the United States: Spatio‐temporal patterns and socio‐economic controls. Earth's Future. 2017; 5 (7):771-788.
Chicago/Turabian StyleA. Sankarasubramanian; J. L. Sabo; K. L. Larson; S. B. Seo; T. Sinha; R. Bhowmik; A. Ruhi Vidal; K. Kunkel; G. Mahinthakumar; E. Z. Berglund; J. Kominoski. 2017. "Synthesis of public water supply use in the United States: Spatio‐temporal patterns and socio‐economic controls." Earth's Future 5, no. 7: 771-788.