Global estimation of long-term persistence in annual river runoff

被引:55
|
作者
Markonis, Y. [1 ]
Moustakis, Y. [2 ]
Nasika, C. [2 ]
Sychova, P. [1 ]
Dimitriadis, P. [2 ]
Hanel, M. [1 ]
Maca, P. [1 ]
Papalexiou, M. [3 ]
机构
[1] Czech Univ Life Sci, Fac Environm Sci, Prague, Czech Republic
[2] Natl Tech Univ Athens, Sch Civil Engn, Athens, Greece
[3] Univ Calif Irvine, Dept Civil & Environm Engn, Irvine, CA USA
关键词
River runoff; Long-term persistence; Long-range dependence; Self-Organizing Maps; Random forests; Catchment classification; TIME-SERIES; CATCHMENT CLASSIFICATION; RANGE PERSISTENCE; STREAMFLOW; MAP; DEPENDENCE; RAINFALL; DROUGHT; MEMORY;
D O I
10.1016/j.advwatres.2018.01.003
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Long-term persistence (LTP) of annual river runoff is a topic of ongoing hydrological research, due to its implications to water resources management. Here, we estimate its strength, measured by the Hurst coefficient H, in 696 annual, globally distributed, streamflow records with at least 80 years of data. We use three estimation methods (maximum likelihood estimator, Whittle estimator and least squares variance) resulting in similar mean values of H close to 0.65. Subsequently, we explore potential factors influencing H by two linear (Spearman's rank correlation, multiple linear regression) and two non-linear (self-organizing maps, random forests) techniques. Catchment area is found to be crucial for medium to larger watersheds, while climatic controls, such as aridity index, have higher impact to smaller ones. Our findings indicate that long-term persistence is weaker than found in other studies, suggesting that enhanced LTP is encountered in large-catchment rivers, were the effect of spatial aggregation is more intense. However, we also show that the estimated values of H can be reproduced by a short-term persistence stochastic model such as an auto-regressive AR(1) process. A direct consequence is that some of the most common methods for the estimation of H coefficient, might not be suitable for discriminating short-and long-term persistence even in long observational records.
引用
收藏
页码:1 / 12
页数:12
相关论文
共 50 条
  • [31] A Long-Term Forecast Model of Spring Runoff: The Case of the Belaya River
    D. Yu. Vasil’ev
    V. V. Vodopyanov
    G. S. Zayzeva
    Sh. I. Zakirzyanov
    V. A. Semenov
    Zh. T. Sivokhip
    A. A. Chibilev
    Doklady Earth Sciences, 2019, 486 : 724 - 727
  • [32] Trophic response of estuarine fishes to long-term changes of river runoff
    Livingston, RJ
    BULLETIN OF MARINE SCIENCE, 1997, 60 (03) : 984 - 1004
  • [33] Long-term annual water balance analysis of the Lena River
    Berezovskaya, S
    Yang, DQ
    Hinzman, L
    GLOBAL AND PLANETARY CHANGE, 2005, 48 (1-3) : 84 - 95
  • [34] The Regularities of Long-Term Annual Stream Runoff Fluctuations in Siberia and the Far East
    Bolgov, M. V.
    Korobkina, E. A.
    GEOGRAPHY AND NATURAL RESOURCES, 2011, 32 (02) : 101 - 107
  • [35] PESTICIDE RUNOFF SIMULATIONS - LONG-TERM ANNUAL MEANS VS EVENT EXTREMES
    LEONARD, RA
    TRUMAN, CC
    KNISEL, WG
    DAVIS, FM
    WEED TECHNOLOGY, 1992, 6 (03) : 725 - 730
  • [36] Long-term persistence of freshwater mussel beds in labile river channels
    Sansom, Brandon J.
    Bennett, Sean J.
    Atkinson, Joseph F.
    Vaughn, Caryn C.
    FRESHWATER BIOLOGY, 2018, 63 (11) : 1469 - 1481
  • [37] Discrete dynamic-stochastic model of long-term river runoff variations
    A. V. Frolov
    Water Resources, 2011, 38 : 583 - 592
  • [38] Discrete Dynamic-Stochastic Model of Long-Term River Runoff Variations
    Frolov, A. V.
    WATER RESOURCES, 2011, 38 (05) : 583 - 592
  • [39] Long-term memory persistence
    Izquierdo, Ivan
    Cammarota, Martin
    Medina, Jorge H.
    FUTURE NEUROLOGY, 2010, 5 (06) : 911 - 917
  • [40] LONG-TERM ANNUAL RUNOFF AND SOIL LOSS FROM CONVENTIONAL AND CONSERVATION TILLAGE OF CORN
    BURWELL, RE
    KRAMER, LA
    JOURNAL OF SOIL AND WATER CONSERVATION, 1983, 38 (03) : 315 - 319