Estimation of Annual Maximum and Minimum Flow Trends in a Data-Scarce Basin. Case Study of the Allipen River Watershed, Chile

被引:6
|
作者
Medina, Yelena [1 ,2 ]
Munoz, Enrique [1 ,2 ]
机构
[1] Univ Catolica Santisima Concepcion, Dept Civil Engn, Concepcion 4090541, Chile
[2] Univ Catolica Santisima Concepcion, CIBAS, Concepcion 4090541, Chile
关键词
long-term flow trends; data scarce; hydrological modeling; CLIMATE-CHANGE; SENSITIVITY-ANALYSIS; STREAMFLOW CHANGES; TREE-RINGS; MODEL; VARIABILITY; UNCERTAINTY; CATCHMENT; IMPACTS; URBANIZATION;
D O I
10.3390/w12010162
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Data on historical extreme events provides information not only for water resources planning and management but also for the design of disaster-prevention measures. However, most basins around the globe lack long-term hydro-meteorological information to derive the trend of hydrological extremes. This study aims to investigate a method to estimate maximum and minimum flow trends in basins with limited streamflow records. To carry out this study, data from the Allipen River watershed (Chile), the Hydrologiska Byrans Vattenbalansavdelning (HBV) hydrological model at a daily time step, and an uncertainty analysis were used. Through a calibration using only five years of records, 21-year mean daily flow series were generated and the extreme values derived. To analyze the effect of the length of data availability, 2, 5, and 10 years of flows were eliminated from the analyses. The results show that in the case of 11 years of simulated flows, the annual maximum and minimum flow trends present greater uncertainty than in the cases of 16 and 19 years of simulated flows. Simulating 16 years, however, proved to properly simulate the observed long-term trends. Therefore, in data-scarce areas, the use of a hydrological model to simulate extreme mean daily flows and estimate long-term trends with at least 16 years of meteorological data could be a valid option.
引用
收藏
页数:15
相关论文
共 21 条
  • [1] Application of hydrological model to assess river flow in the transboundary cryosphere and data-scarce watershed, a case study: Chitral-Kabul river basin (C-KRB) in Pakistan
    Azzam, Abdullah
    Zhang, Wanchang
    Shahid, Muhammad Adnan
    Elbeltagi, Ahmed
    WATER SUPPLY, 2022, 22 (04) : 3842 - 3862
  • [2] Identification and mapping of surface irrigation potential in the data-scarce Jewuha watershed, Middle Awash River Basin, Ethiopia
    Dinku, Manamno Beza
    Kebede, Habtamu Hailu
    HYDROLOGY RESEARCH, 2023, 54 (10): : 1227 - 1245
  • [3] Probabilistic rainfall threshold of landslides in Data-Scarce mountainous Areas: A case study of the Bailong River Basin, China
    Jiang, Wanyu
    Chen, Guan
    Meng, Xingmin
    Jin, Jiacheng
    Zhao, Yan
    Lin, Linxin
    Li, Yajun
    Zhang, Yi
    CATENA, 2022, 213
  • [4] Metrics Assessment and Streamflow Modeling under Changing Climate in a Data-Scarce Heterogeneous Region: A Case Study of the Kabul River Basin
    Akhtar, Fazlullah
    Borgemeister, Christian
    Tischbein, Bernhard
    Awan, Usman Khalid
    WATER, 2022, 14 (11)
  • [5] Predicting peakflows in mountain river basins and data-scarce areas: a case study in northeastern Italy
    Arnone, Elisa
    Zoratti, Veronica
    Formetta, Giuseppe
    Bosa, Silvia
    Petti, Marco
    HYDROLOGICAL SCIENCES JOURNAL, 2023, 68 (03) : 432 - 447
  • [6] Daily suspended sediment yield estimation using soft-computing algorithms for hilly watersheds in a data-scarce situation: a case study of Bino watershed, Uttarakhand
    Tulla, Paramjeet Singh
    Kumar, Pravendra
    Vishwakarma, Dinesh Kumar
    Kumar, Rohitashw
    Kuriqi, Alban
    Kushwaha, Nand Lal
    Rajput, Jitendra
    Srivastava, Aman
    Pham, Quoc Bao
    Panda, Kanhu Charan
    Kisi, Ozgur
    THEORETICAL AND APPLIED CLIMATOLOGY, 2024, 155 (05) : 4023 - 4047
  • [7] Comparison of Downscaled Precipitation Data over a Mountainous Watershed: A Case Study in the Heihe River Basin
    Pan, Xiaoduo
    Li, Xin
    Yang, Kun
    He, Jie
    Zhang, Yanlin
    Han, Xujun
    JOURNAL OF HYDROMETEOROLOGY, 2014, 15 (04) : 1560 - 1574
  • [8] Modelling stream flow and quantifying blue water using a modified STREAM model for a heterogeneous, highly utilized and data-scarce river basin in Africa
    Kiptala, J. K.
    Mul, M. L.
    Mohamed, Y. A.
    van der Zaag, P.
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2014, 18 (06) : 2287 - 2303
  • [9] Challenges on modelling a large river basin with scarce data: A case study of the Indus upper catchment
    Sugiura, A.
    Fujioka, S.
    Nabesaka, S.
    Sayama, T.
    Iwami, Y.
    Fukami, K.
    Tanaka, S.
    Takeuchi, K.
    20TH INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION (MODSIM2013), 2013, : 2346 - 2352
  • [10] New Framework for Dynamic Water Environmental Capacity Estimation Integrating the Hydro-Environmental Model and Load-Duration Curve Method-A Case Study in Data-Scarce Luanhe River Basin
    Jin, Huiyu
    Chen, Wanqi
    Zhao, Zhenghong
    Wang, Jiajia
    Ma, Weichun
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (14)