Evaluation of future climate change impact on snow hydrology for a mountainous watershed of South Korea using SLURP model and NOAA AVHRR images

详细信息    查看全文

• 作者：Hyung Jin Shin ; Minji Park ; Seong Joon Kim
• 关键词：Snowmelt ; NOAA AVHRR ; Climate change ; SLURP
• 刊名：Paddy and Water Environment
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：14
• 期：1
• 页码：145-158
• 全文大小：950 KB
• 参考文献：Adam JC, Hamlet AF, Lettenmaier DP (2009) Implications of global climate change for snowmelt hydrology in the twenty-first century. Hydrol Process 23:962–972CrossRef
  Alcamo J, Döll P, Kaspar F, Siebert S (1997) Global change and global scenarios of water use and availability: an application of WaterGAP 1.0. Report A9701, Center for Environmental Systems Research, University of Kassel, Kassel
  Andreadis KM, Lettenmaier DP (2006) Assimilating remotely sensed snow observations into a macroscale hydrology model. Adv Water Resour 29:872–886CrossRef
  Arnell NW (1999) The effect of climate change on hydrological regimes in Europe: a continental perspective. Glob Environ Change 9:5–23CrossRef
  Arnell NW (2004) Climate-change impacts on river flows in Britain: the UKCIP02 scenarios. J Chart Inst Water Environ Manag 18:112–117CrossRef
  Aytek A, Guven A, Yuce MI, Aksoy H (2008) An explicit neural network formulation for evapotranspiration. Hydrol Sci J 53(4):893–904CrossRef
  Burn DH (1994) Hydrological effects of climatic change in west-central Canada. J Hydrol 160:53–70CrossRef
  Diaz-Nieto J, Wilby RL (2005) A comparison of statistical downscaling and climate change factor methods: impacts on low flows in the River Thames, UK. Clim Change 69:245–268CrossRef
  Droogers P, Aerts J (2005) Adaptation strategies to climate change and climate variability: a comparative study between seven contrasting river basins. Phys Chem Earth 30:339–346CrossRef
  Duan Q, Sorooshian S, Gupta VK (1994) Optimal use of the SCE-UA global optimization method for calibrating watershed models. J Hydrol 158:265–284CrossRef
  Gleick PH (1987) Regional hydrologic consequences of increases in atmospheric CO2 and other trace gases. Clim Change 10:137–160CrossRef
  Ha R, Shin HJ, Park MJ, Kim SJ (2010) Comparison of hydrological responses by two different satellite remotely sensed leaf area indices in a mountainous watershed of South Korea. KSCE J Civ Eng 14(4):785–796CrossRef
  Hamlet AF, Mote PW, Clark MP, Lettenmaier DP (2005) Effects of temperature and precipitation variability on snowpack trends in the western United States. J Climate 18:4545–4561CrossRef
  Hamlet AF, Lettenmaier DP (2007) Effects of 20th century warming and climate variability on flood risk in the Western U.S. Water Resour Res 43:W06427
  Harrison AR, Lucas RM (1989) Multi-spectral classification of snow using NOAA AVHRR imagery. Int J Remote Sens 10:907–916CrossRef
  Houser PR, Shuttleworth WJ, Famiglietti JS, Gupta HV, Syed KH, Goodrich DC (1998) Integration of soil moisture remote sensing and hydrologic modeling using data assimilation. Water Resour Res 34:3405–3420CrossRef
  IPCC-TGCIA (1999) Guidelines on the use of scenario data for climate impact and adaptation assessment, Version 1. Intergovernmental panel on climate change, task group on scenarios for climate impact assessment
  Kazama S (1995) Study on water cycle in middle scale region. Department of Civil Engineering, Tohoku University, Sendai
  Khadka D, Babel MS, Shrestha S, Tripathi NK (2014) Climate change impact on glacier and snow melt and runoff in Tamakoshi basin in the Hindu Kush Himalayan (HKH) region. J Hydrol 511:49–60CrossRef
  Kite GW (1975) Performance of two deterministic models. Application of Mathematical Models in Hydrology and Water Resources Systems. In: Proceedings of the Bratislava Symposium, September, IASH Publication. 115:136–142
  Kite GW (1993) Application of a land class hydrological model to climatic change. Water Resour Res 29(7):2377–2384CrossRef
  Kobierska F, Jonas T, Magnusson J, Zappa M, Bavay M, Bosshard T, Paul F, Bernasconi SM (2011) Climate change effects on snow melt and discharge of a partly glacierized watershed in Central Switzerland (SoilTrec Critical Zone Observatory). Appl Geochem 26:60–62
  Lettenmaier DP, Gan TY (1990) Hydrologic sensitivities of the Sacramento-San Joaquin River Basin, California, to global warming. Water Resour Res 26:69–86CrossRef
  Middelkoop H, Daamen K, Gellens D, Grabs W, Kwadijk JCJ, Lang H, Parmet BWAH, Schädler B, Schulla J, Wilke K (2001) Impact of climate change on hydrological regimes and water resources management in the Rhine Basin. Clim Change 49:105–128CrossRef
  Mote PW, Hamlet AF, Clark MP, Lettenmaier DP (2005) Declining mountain snowpack in western North America. Bull Am Meteorol Soc 86:39–49CrossRef
  Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models; Part 1—a discussion of principles. J Hydrol 10(3):282–290CrossRef
  Nijssen B, O’Donnell GM, Hamlet AF, Lettenmaier DP (2001) Hydrologic sensitivity of global rivers to climate change. Clim Change 50:143–175CrossRef
  Rango A, Martinec J (1979) Application of a snowmelt-runoff model using LANDSAT data. Nord Hydrol 10:225–238
  Rawls WJ, Brakensiek DL, Saxton KE (1982) Estimation of soil water properties. Trans ASAE 108:1316–1320CrossRef
  Schmugge TJ, Kustas WP, Ritchie JC, Jackson TJ, Rango A (2002) Remote sensing in hydrology. Adv Water Resour 25:1367–1385CrossRef
  Shin HJ, Kim SJ (2007) Assessment of climate change impact on snowmelt in the two mountainous watersheds using CCCma CGCM2. J Korean Soc Civ Eng 11(6):311–319
  Shin HJ, Park GA, Kim SJ (2007) Tracing March 2004 and December 2005 heavy snowfall of South Korea using NOAA-AVHRR images. J Korean Soc Agric Eng 49(3):33–40
  Stewart IT, Cayan DR, Dettinger MD (2005) Changes toward earlier streamflow timing across western North America. J Clim 18:1136–1155CrossRef
  Swamy AN, Brivio PA (1996) Hydrological modeling of snowmelt in the Italian Alps using visible and infrared remote sensing. Int J Remote Sens 17:3169–3188CrossRef
  Verhoef A, Feddes RA (1991) Preliminary review of revised FAO radiation and temperature methods. Report 16, Landbouwuniversiteit Wageningen, Wageningen
  Vicuna S, Dracup JA, Lund JR, Dale LL, Maurer EP (2010) Basin-scale water system operations with uncertain future climate conditions: methodology and case studies. Water Resour Res 46(4):W4505CrossRef
  Yang D, Robinson D, Zhao Y, Estilow T, Ye B (2003) Streamflow response to seasonal snow cover extent changes in large Siberian watershed. J Geophys Res 108(D18):4578CrossRef
  Zhou L, Dickinson RE, Tian Y, Zeng X, Dai Y, Yang ZL, Schaaf CB, Gao F, Jin Y, Strahler A, Myneni RB, Yu H, Shaikh M (2003) Comparison of seasonal and spatial variations of albedos from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Common Land Model. J Geophys Res 108(15):1–20
  
• 作者单位：Hyung Jin Shin (1)
  Minji Park (2)
  Seong Joon Kim (3)
  
  1. K-water Institute, Daejeon, Korea
  2. Han River Environmental Research Center, Yangpyong-gun, Gyeonggi-do, Korea
  3. Department of Civil and Environmental System Engineering, Konkuk University, Seoul, Korea
  
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Life Sciences
  Agriculture
  Hydrogeology
  Geoecology and Natural Processes
  Monitoring, Environmental Analysis and Environmental Ecotoxicology
  Soil Science and Conservation
  Waste Water Technology, Water Pollution Control, Water Management and Aquatic Pollution
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-2504

文摘

This study is to evaluate the future potential climate impact on snow hydrology using SLURP model for a 6661.0 km2 mountainous watershed of South Korea. For the model test, the NOAA AVHRR images were analyzed to prepare snow-related data of the model. Snow cover areas were extracted using channels 1, 3, and 4, and the snow depth was spatially interpolated using snowfall data of 11 ground meteorological stations. With the snowmelt parameters (snow cover area, snow water equivalent, and snow depth), the model was calibrated for 2 sets (2002–2003, 2004–2005), and verified for 2 sets (1997–1998 and 2001–2002) using the calibrated parameters. The average Nash–Sutcliffe efficiencies during the full year period (December to November) and snowmelt period (December to April) were 0.60 and 0.66, respectively. The future climate data of CCCma CGCM2 SRES A2 and B2 scenarios were adjusted and downscaled using change factor method. By the future impact of climate change, the annual dam inflows were projected to change maximum −29.3 and −30.4 % for 2090s A2 scenario and 2030s for B2 scenario, respectively. The future dam inflow increased in winter season (December to February) up to 222.0 %, while other periods decreased up to 54.8 %. The future snowmelt increased in December and January by the future temperature increase of 3.9 °C in minimum. The future snowmelt for the 2 months affected the dam inflows during the winter season. Keywords Snowmelt NOAA AVHRR Climate change SLURP