$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

습윤 지역의 기후-토양-식생-지하수위 상호작용을 반영한 개념적인 생태 수문 모형
Conceptual eco-hydrological model reflecting the interaction of climate-soil-vegetation-groundwater table in humid regions 원문보기

Journal of Korea Water Resources Association = 한국수자원학회논문집, v.54 no.9, 2021년, pp.681 - 692  

최정현 (부경대학교 지구환경시스템과학부 (환경공학전공)) ,  김상단 (부경대학교 환경공학과)

초록
AI-Helper 아이콘AI-Helper

식생 프로세스는 증발산 제어를 통해 강우 유출 프로세스에 상당한 영향을 미치지만, 개념적인 집중형 수문 모형에서는 거의 고려되지 않는다. 본 연구는 인공위성에서 원격으로 감지된 엽면적지수 자료를 표현하는 생태 모듈을 수문 분할 모듈에 통합하여 합천댐 유역에 대한 모형 성능을 평가하였다. 제안된 생태 수문 모형은 습윤 지역의 생태수문 프로세스를 더 잘 표현하기 위하여 크게 세 가지 주요한 특징을 가진다. 1) 식생의 성장률은 유역의 물 부족 스트레스에 의해 제약을 받는다. 2) 식생의 최대 성장은 유역 기후에 의한 에너지에 의해 제약을 받는다. 3) 식생과 대수층의 상호작용이 반영된다. 제안된 모형은 유역 단위의 수문 성분과 식생 동역학을 동시에 모의한다. SCEM 알고리즘에 의해 추정된 모형 매개변수를 이용한 검증 결과로부터 아래와 같은 발견할 수 있었다. 1) 엽면적지수와 하천유량 자료를 이용하여 생태수문모형의 매개변수를 추정하는 것이 생태 모듈이 없는 수문 모형과 비슷한 정확도 및 견고함으로 하천유량을 예측할 수 있다. 2) 필터링이 안된 원격으로 감지된 엽면적지수를 그대로 입력자료로 이용하는 것은 하천유량 예측에 도움이 안된다. 3) 통합된 생태수문모형은 엽면적지수의 계절적인 변동성에 대한 우수한 추정치를 제공할 수 있다.

Abstract AI-Helper 아이콘AI-Helper

Vegetation processes have a significant impact on rainfall runoff processes through evapotranspiration control, but are rarely considered in the conceptual lumped hydrological model. This study evaluated the model performance of the Hapcheon Dam watershed by integrating the ecological module express...

주제어

표/그림 (9)

참고문헌 (55)

  1. Allen, R., Pereira, L., Raes, D., and Smith, M. (1998). Crop evapotranspiration - guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56. Food and Agriculture Organization of the United Nations, Rome, Italy. 

  2. Berghuijs, W., Sivapalan, M., Woods, R., and Savenije, H. (2015). "Patterns of similarity of seasonal water balances: A window into streamflow variability over a range of time scales." Water Resources Research, Vol. 50, No. 7, pp. 5638-5661. 

  3. Choi, D., Choi, H., Kim, K., and Kim, S. (2012). "Development of the ecohydrologic model for simulating water balance and vegetation dynamics." Journal of Korean Society on Water Environment, Vol. 28, No. 4, pp. 582-594. (in Korean) 

  4. Choi, D., Kim, I., Kim, J., and Kim, S. (2013). "Development of distributed ecohydrologic model and its application to the Naeseong creek basin." Journal of Korea Water Resources Association, Vol. 46, No. 11, pp. 1053-1067. (in Korean) 

  5. Choi, J., Seo, J., Won, J., Lee, O., and Kim, S. (2020). "Effects of hydroclimate conditions on calibrating conceptual hydrologic partitioning model." Journal of Korean Society on Water Environment, Vol. 36, No. 6, pp. 568-580. (in Korean) 

  6. Choi, J., Won, J., Lee, O., and Kim, S. (2021). "Usefulness of global root zone soil moisture product for streamflow prediction of ungauged basins." Remote Sensing, Vol. 13, No. 4, 756. doi: 10.3390/rs13040756 

  7. Chui, T., Low, S., and Liong, S. (2011). "An ecohydrological model for studying groundwater - vegetation interactions in wetlands." Journal of Hydrology, Vol. 409, No. 1-2, pp. 291-304. 

  8. Conradt, T., Wechsung, F., and Bronstert, A. (2013). "Three perceptions of the evapotranspiration landscape: Comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances." Hydrology and Earth System Sciences, Vol. 17, No. 7, pp. 2947-2966. doi: 10.5194/hess-17-2947-2013 

  9. Glenn, E., Huete, A., Nagler, P., and Nelson, S. (2008). "Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: What vegetation indices can and cannot tell us about the landscape." Sensors, Vol. 8, No. 4, pp. 2136-2160. doi: 10.3390/s8042136 

  10. Gupta, H., Kling, H., Yilmaz, K., and Martinez, G. (2009). "Decomposition of the mean squared error and NSE performance criteria: implications for improving hydrological modelling." Journal of Hydrology, Vol. 377, No. 1-2, pp. 80-91. 

  11. Han, S., Ahn, J., and Kim, S. (2009). "The stochastic behavior of soil water and the impact of climate change on soil water." Journal of Korea Water Resources Association, Vol. 42, No. 6, pp. 433-444. (in Korean) 

  12. Islam, M., and Sado, K. (2000). "Development of flood hazard maps of Bangladesh using NOAA - AVHRR images with GIS." Hydrological Sciences Journal, Vol. 45, No. 3, pp. 337-355. 

  13. Istanbulluoglu, E., Wang, T., and Wedin, D. (2012). "Evaluation of ecohydrologic model parsimony at local and regional scales in a semiarid grassland ecosystem." Ecohydrology, Vol. 5, No. 1, pp. 121-142. 

  14. Ivanov, V., Bras, R., and Vivoni, E. (2008). "Vegetation-hydrology dynamics in complex terrain of semiarid areas: 1. A mechanistic approach to modeling dynamic feedbacks." Water Resources Research, Vol. 44, No. 3, W03429. doi: 10.1029/2006WR005588 

  15. Kim, S., Han, S., and Kim, E. (2011). "Stochastic modeling of soil water and plant water stress using cumulant expansion theory." Ecohydrology, Vol. 4, No. 1, pp. 94-105. 

  16. Kim, S., Jang, S., Yoon, Y., and Yoon, J. (2004). "Probabilistic solution to stochastic infiltrated flow equation." KSCE Journal of Civil Engineering, Vol. 8, No. 6, pp. 651-662. 

  17. Kim, S., Kavvas, M., and Chen, Z. (2005). "A root water uptake model under heterogeneous soil surface." Journal of Hydrologic Engineering, Vol. 10, pp. 160-167. 

  18. Knyazikhin, Y., Glassy, J., Privette, J.L., Tian, Y., Lotsch, A., Zhang, Y., Wang, Y., Morisette, J.T., Votava, P., Myneni, R.B., Nemani, R.R., and Running, S.W. (1999). MODIS Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation Absorbed by Vegetation (FPAR) Product (MOD15) Algorithm Theoretical Basis Document, Land Precesses Distributed Active Archive Center, accessed 26 August 2021, . 

  19. Koetz, B., Baret, F., Poilve, H., and Hill, J. (2005). "Use of coupled canopy structure dynamic and radiative transfer models to estimate biophysical canopy characteristics." Remote Sensing of Environment, Vol. 95, No. 1, pp. 115-124. 

  20. Laio, F., Tamea, S., Ridolfi, L., D'Odorico, P., and Rodriguez-Iturbe, I. (2009). "Ecohydrology of groundwater-dependent ecosystems: Stochastic water table dynamics." Water Resources Research, Vol. 45, No. 5, W05419. doi: 10.1029/2008WR007292 

  21. Lee, A., Cho, S., Kang, D., and Kim, S. (2014). "Analysis of the effect of climate change on the Nakdong river stream flow using indicators of hydrological alteration." Journal of Hydroenvironmental Research, Vol. 8, No. 3, pp. 234-247. 

  22. Lee, O., Choi, J., Sim, I., Won, J., and Kim, S. (2020a). "Stochastic parsimonious hydrologic partitioning model under East Asia Monsoon climate and its application to climate change." Water, Vol. 12, No. 1, 25. dol: 10.3390/w12010025 

  23. Lee, O., Kim, H., and Kim, S. (2020b). "Hydrological simple water balance modeling for increasing geographically isolated doline wetland functions and its application to climate change." Ecological Engineering, Vol. 149, 105812. doi: 10.1016/j.ecoleng.2020.105812 

  24. Li, H., Zhang, Y., Chiew, F., and Xu, S. (2009). "Predicting runoff in ungauged catchments by using Xinanjiang model with MODIS leaf area index." Journal of Hydrology, Vol. 370, No. 1-4, pp. 155-162. 

  25. Li, K., Coe, M., Ramankutty, N., and De Jong, R. (2007). "Modeling the hydrological impact of land-use change in West Africa." Journal of Hydrology, Vol. 337, No. 3-4, pp. 258-268. 

  26. Li, Q., and Ishidaira, H. (2012). "Development of a biosphere hydrological model considering vegetation dynamics and its evaluation at basin scale under climate change." Journal of Hydrology, Vol. 412-413, pp. 3-13. 

  27. Lindstrom, G., Johansson, B., Persson, M., Gardelin, M., and Bergstrom, S. (1997). "Development and test of the distributed HBV-96 hydrological model." Journal of Hydrology, Vol. 201, No. 1-4, pp. 272-288. 

  28. Manfreda, S., and Caylor, K. (2013). "On the vulnerability of water limited ecosystems to climate change." Water, Vol. 5, No. 2, pp. 819-833. 

  29. Montaldo, N., Rondena, R., Albertson, J., and Mancini, M. (2005). "Parsimonious modeling of vegetation dynamics for ecohydrologic studies of water limited ecosystems." Water Resources Research, Vol. 41, No. 10, W10416. doi: 10.1029/2005WR004094 

  30. Muneepeerakul, C., Miralles-Wilhelm, F., Tamea, S., Rinaldo, A., and Rodriguez-Iturbe, I. (2008). "Coupled hydrologic and vegetation dynamics in wetland ecosystems." Water Resources Research, Vol. 44, No. 7, W07421. doi: 10.1029/2007WR006528 

  31. Mwangi, H., Julich, S., Patil, S., Mcdonald, M., and Feger, K. (2016). "Modelling the impact of agroforestry on hydrology of Mara river basin in East Africa." Hydrological Process, Vol. 30, No. 18, pp. 3139-3155. 

  32. Naseem, B., Ajami, H., Liu, Y., Cordery, I., and Sharma, A. (2016). "Multi-objective assessment of three remote sensing vegetation products for streamflow prediction in a conceptual ecohydrological model." Journal of Hydrology, Vol. 543, pp. 686-705. 

  33. Patil, S., and Stieglitz, M. (2015). "Comparing spatial and temporal transferability of hydrological model parameters." Journal of Hydrology, Vol. 525, pp. 409-417. 

  34. Porporato, A, Laio, F, Ridolfi, L., and Rodriguez-Iturbe I. (2001). "Plants in water-controlled ecosystems: Active role in hydrologic processes and response to water stress - III. Vegetation water stress." Advances in Water Resources, Vol. 24, No. 7, pp. 725-744. 

  35. Quevedo, D., and Frances, F. (2008). "A conceptual dynamic vegetationsoil model for arid and semiarid zones." Hydrology Earth System and Sciences, Vol. 12, No. 5, pp. 1175-1187. 

  36. Rodriguez-Iturbe, I., D'Odorico, P., Laio, F., Ridolfi, L., and Tamea, S. (2007). "Challenges in humid land ecohydrology: Interactions of water table and u nsatu rated zone with climate, soil, and vegetation." Water Resources Research, Vol. 43, No. 9, W09301. doi: 10.1029/2007WR006073 

  37. Rodriguez-Iturbe, I., Porporato, A., Laio, F., and Ridolfi, L. (2001). "Plants in water-controlled ecosystems: Active role in hydrologic processes and response to water stress, I. Scope and general outline." Advances in Water Resources, Vol. 24, No. 7, pp. 695-705. 

  38. Rodriguez-Iturbe, I., Porporato, A., Ridolfi, L., Isham, V., and Coxi, D.R. (1999). "Probabilistic modelling of water balance at a point: the role of climate, soil and vegetation." Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, Vol. 455, pp. 3789-3805. 

  39. Ruiz-Perez, G., Koch, J., Manfreda, S., Caylor, K., and Frances, F. (2017). "Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI." Hydrology Earth System and Sciences, Vol. 21, No. 12, pp. 6235-6251. 

  40. Sorooshian, S., Duan, Q., and Gupta, V. (1993). "Calibration of rainfall-runoff models: Application of global optimization to the Sacramento soil moisture accounting model." Water Resources Research, Vol. 29, No. 4, pp. 1185-1194. 

  41. Sugawara, M. (1961). "On the analysis of runoff structure about several Japanese rivers." Japanese Journal of Geophysics, Vol. 2, No. 4, pp. 1-76. 

  42. Sun, L., and Schulz, K. (2017). "Spatio-temporal LAI modelling by integrating climate and MODIS LAI data in a mesoscale catchment." Remote Sensing, Vol. 9, No. 2, 144. doi: 10.3390/rs9020144 

  43. Tague, C., and Band, L. (2004). "RHESSys: REgional hydro-ecologic simulation system-an object-oriented approach to spatially distributed modeling of carbon, water, and nutrient cycling." Earth Interactions, Vol. 8, No. 19, pp. 1-42. 

  44. Tesemma, Z., Wei, Y., Western, A., and Peel, M. (2014). "Leaf Area Index variation for crop, pasture, and tree in response to climatic variation in the goulburn - broken catchment, Australia." Journal of Hydrometeorology, Vol. 15, No. 4, pp. 1592-1606. 

  45. Tuteja, N., Vaze, J., Teng, J., and Mutendeudzi, M. (2007). "Partitioning the effects of pine plantations and climate variability on runoff from a large catchment in southeastern Australia." Water Resources Research, Vol. 43, No. 8, W0841. doi: 10.1029/2006WR005016 

  46. Verhulst, P. (1838). "Notice sur la loi que la population poursuit dans son accroissement." Correspondance Mathematique et Physique, Vol. 10, pp. 113-121. 

  47. Viola, F., Pumo, D., and Noto, L. (2013). "EHSM: A conceptual ecohydrological model for daily streamflow simulation." Hydrological Process, Vol. 28, pp. 3361-3372. 

  48. Vrugt, J., Gupta, H., Bouten, W., and Sorooshian, S. (2003). "A shuffled complex evolution metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters." Water Resources Research, Vol. 39, No. 8, 1201. doi: 10.1029/2002WR001642 

  49. Watson, D. (1947). "Comparative physiological studies on the growth of field crops: I. Variation in net assimilation rate and leaf area between species and varieties, and within and between years." Annals of Botany, Vol. 11, pp. 41-76. 

  50. Wegehenkel, M. (2002). "Estimating of the impact of land use changes using the conceptual hydrological model THESEUS-a case study." Physics and Chemistry of the Earth, Parts A/B/C, Vol. 27, No. 9, pp. 631-640. 

  51. Weiss, M., Baret, F., Garrigues, S., and Lacaze, R. (2007). "LAI and fAPAR CYCLOPES global products derived from vegetation. part 2: validation and comparison with MODIS collection 4 products." Remote Sensing of Environment, Vol. 110, No. 3, pp. 317-331. 

  52. Won, J., Choi, J., Lee, O., and Kim, S. (2020). "Copula-based Joint Drought Index using SPI and EDDI and its application to climate change." Science of The Total Environment, Vol. 744, 140701. doi: 10.1016/j.scitotenv.2020.140701 

  53. Yildiz, O., and Barros, A. (2007). "Elucidating vegetation controls on the hydroclimatology of a mid-latitude basin." Journal of Hydrology, Vol. 333, No. 2-4, pp. 431-448. 

  54. Zhang, Y., and Wegehenkel, M. (2006). "Integration of MODIS data into a simple model for the spatial distributed simulation of soil water content and evapotranspiration." Remote Sensing of Environment, Vol. 104, No. 4, pp. 393-408. 

  55. Zhou, X., Istanbulluoglu, E., and Vivoni, E. (2013). "Modeling the ecohydrological role of aspect-controlled radiation on tree-grass-shrub coexistence in a semiarid climate." Water Resources Research, Vol. 49, No. 5, pp. 2872-2895. doi: 10.1002/wrcr.20259 

저자의 다른 논문 :

섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로