Impact of climate change on water resources in Yongdam Dam Basin, Korea

Kim, Byung Sik; Kim, Hung Soo; Seoh, Byung Ha; Kim, Namwoon

doi:10.1007/s00477-006-0081-2

Cited by 32 publications

(25 citation statements)

References 36 publications

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“…These range from small Canadian wetland basins of less than 1 km 2 (Su, 2000), through catchments of hundreds of square kilometres with very different climatologies including studies in Canada (Armstrong and Martz, 2008), Germany (Viney et al, 2009), Turkey (Apaydin et al, 2006) and South Korea (Kim et al, 2007;Park et al, 2009), to major river basins including upper tributaries of the Indus and Yangtze (Jain et al, 1998;Woo et al, 2009).…”

Section: The Slurp Hydrological Modelmentioning

confidence: 99%

Uncertainty in climate change projections of discharge for the Mekong River Basin

Kingston

Thompson

Kite³

2011

Hydrol. Earth Syst. Sci.

157

140

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Abstract. The Mekong River Basin is a key regional resource in Southeast Asia for sectors that include agriculture, fisheries and electricity production. Here we explore the potential impacts of climate change on freshwater resources within the river basin. We quantify uncertainty in these projections associated with GCM structure and climate sensitivity, as well as from hydrological model parameter specification. This is achieved by running patternscaled GCM scenarios through a semi-distributed hydrological model (SLURP) of the basin. Pattern-scaling allows investigation of specific thresholds of global climate change including the postulated 2 • C threshold of "dangerous" climate change. Impacts of a 2 • C rise in global mean temperature are investigated using seven different GCMs, providing an implicit analysis of uncertainty associated with GCM structure. Analysis of progressive changes in global mean temperature from 0.5 to 6 • C above the 1961-1990 baseline (using the HadCM3 GCM) reveals a relatively small but non-linear response of annual river discharge to increasing global mean temperature, ranging from a 5.4 % decrease to 4.5 % increase. Changes in mean monthly river discharge are greater (from −16 % to +55 %, with greatest decreases in July and August, greatest increases in May and June) and result from complex and contrasting intra-basin changes in precipitation, evaporation and snow storage/melt. Whilst overall results are highly GCM dependent (in both direction and magnitude), this uncertainty is primarily driven by differences in GCM projections of future precipitation. In contrast, there is strong consistency between GCMs in terms of both increased potential evapotranspiration and a shift to an earlier

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Section: The Slurp Hydrological Modelmentioning

confidence: 99%

Uncertainty in climate change projections of discharge for the Mekong River Basin

Kingston

Thompson

Kite³

2011

Hydrol. Earth Syst. Sci.

157

140

View full text Add to dashboard Cite

show abstract

“…Among the statistical downscaling techniques used by hydrologists to obtain station-scale climatic information, multiple regression models and stochastic weather generators have far more applications than the others (e.g. Wilks 1992Wilks , 1999, as they are computationally less demanding, simple to apply, and efficient (Semenov et al 1998;Dibike and Coulibaly 2005;Kilsby et al 2007;Kim et al 2007 Regression-based downscaling methods involve developing empirical relationships between large-scale GCM data or observed data as ''predictor'' variables and local-or small-scale climate variables as ''predictand'' variables (e.g. temperature, precipitation) using traditional linear and nonlinear regression methods (e.g.…”

Section: Introductionmentioning

confidence: 99%

Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed

Hashmi

Shamseldin

Melville

2010

Stoch Environ Res Risk Assess

173

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Future climate projections of Global Climate Models (GCMs) under different emission scenarios are usually used for developing climate change mitigation and adaptation strategies. However, the existing GCMs have only limited ability to simulate the complex and local climate features, such as precipitation. Furthermore, the outputs provided by GCMs are too coarse to be useful in hydrologic impact assessment models, as these models require information at much finer scales. Therefore, downscaling of GCM outputs is usually employed to provide fine-resolution information required for impact models. Among the downscaling techniques based on statistical principles, multiple regression and weather generator are considered to be more popular, as they are computationally less demanding than the other downscaling techniques. In the present study, the performances of a multiple regression model (called SDSM) and a weather generator (called LARS-WG) are evaluated in terms of their ability to simulate the frequency of extreme precipitation events of current climate and downscaling of future extreme events. Areal average daily precipitation data of the Clutha watershed located in South Island, New Zealand, are used as baseline data in the analysis. Precipitation frequency analysis is performed by fitting the Generalized Extreme Value (GEV) distribution to the observed, the SDSM simulated/downscaled, and the LARS-WG simulated/ downscaled annual maximum (AM) series. The computations are performed for five return periods: 10-, 20-, 40-, 50-and 100-year. The present results illustrate that both models have similar and good ability to simulate the extreme precipitation events and, thus, can be adopted with confidence for climate change impact studies of this nature.

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“…Bae et al, 2008b;Bae et al, 2011;Jung et al, 2007;Kim et al, 2005;Kim et al, 2007;Lee et al, 2011) (Fowler et al, 2007). 이미 여러 기후변화 연구 (Snover et al, 2003;Elsner et al, 2010;Liu et al, 2010 (Fig.…”

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Future Projections of Köppen Climate Shifts in the Asia Regions Using A2 Scenario

Shin¹,

Bae²

2013

Journal of Korea Water Resources Association

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The objective of this study is to analyse the current climate zone applied by Köppen climate classification and the future climate zone projected by the A2 scenario in Asia regions. The spatial and temporal variations of precipitation and temperature were also analyzed. As regards to the result of analysis on the variation of climate factor, temperature and precipitation will be increasing 4.0℃ and 12% respectively in the 2080s comparing with the reference period (1991∼2010). Spatially, the range of temperature increase on the high latitude area is higher than that on the low latitude area. The precipitation will be increasing averagely in the overall area, but the spatial unequal distribution of precipitation will be intensified. At the result of the future climate zone, the area of warm climates will be increasing while the area of cold climates will be decreasing. In 2080s, the temperature will be increasing as much as 7.2% and 1.9% on the Tropical climates and Arid climates respectively, but it will be decreasing as -2.4%, -4.9% and -1.8% on the Warm temperate climates, Cold climates and Polar climates respectively. Furthermore, the part of Savannah climates and Desert climates will be mostly increasing. It is mainly caused by the temperature increase and desertification impact according to global warming.

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Impact of climate change on water resources in Yongdam Dam Basin, Korea

Cited by 32 publications

References 36 publications

Uncertainty in climate change projections of discharge for the Mekong River Basin

Uncertainty in climate change projections of discharge for the Mekong River Basin

Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed

Future Projections of Köppen Climate Shifts in the Asia Regions Using A2 Scenario

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