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2019 | 28 | 3 |

Tytuł artykułu

Variation in runoff series regimes and the impacts of human activities in the upper Yellow River basin

Autorzy

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
It is important to manage water resources of the upper Yellow River basin for the new Silk Road economic belt. In recent decades, under the combined human activities and influence of climate, the hydrologic regime of the upper Yellow River basin shows remarkable variations that have caused many issues. So potential human indicated influence has been drawing increasing attention from hydrologists and local governments. The aim of this study is to determine the changes in the hydrological characteristic parameters and mean annual runoff series of the upper Yellow River basin. This paper took the representative Lanzhou Station in the upstream Yellow River as an example, used the TFPW-MK mutation test and rank sum test to analyze the location of the variation points of hydrological series. By contrasting two different analysis results between natural and measured river runoff series, the impacts of human activities on the long-term hydrological regime were investigated. The variation range of hydrological ecological indexes before and after variation were analyzed by the method of indicators of hydrologic alteration (IHA). The results show: a) the hydrological series of Lanzhou Station is a significant decreasing trend can be observed in the natural stream flow series in 1985 with a high degree of hydrological variability, while human activities play an important role; b) various ecological indicators have changed in different degrees that have caused the deterioration of ecological conditions around 1985; and c) continuous decreasing stream flow in the upper Yellow River basin will trigger serious shortages of fresh water in the future, which may challenge the sustainability and safety of water resource development in the river basin, and should be paid great attention before 2020. Variation analysis and diagnosis of eco-hydrological indexes in the upper reaches of the Yellow River can provide a basis for the development, utilization, and protection of water resources in this area.

Słowa kluczowe

Wydawca

-

Rocznik

Tom

28

Numer

3

Opis fizyczny

p.1071-1082,fig.,ref.

Twórcy

autor
  • School of Environmental Science and Engineering, Chang’an University, Xi’an, China
  • Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang’an University, Xi’an, China
autor
  • School of Environmental Science and Engineering, Chang’an University, Xi’an, China
  • Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang’an University, Xi’an, China

Bibliografia

  • 1. DAWEN Y., CHONG L., HEPING H., ZHIDONG L., SHIXIU Y., TETSUYA K., TOSHIO K., KATUMI M. Analysis of water resources variability in the Yellow River of China during the last half century using historical data. Water Resource Research, 40 (06), 502, 2004.
  • 2. YANG T., ZHANG Q., CHEN Y.D., TAO X., XU C.Y., CHEN X.A spatial assessment of hydrologic alteration caused by dam construction in the middle and lower Yellow River. China. Hydrology Process, 22 (18), 3829, 2008.
  • 3. TANG Q., OKI T., KANAE S., HU H.Hydrological cycles change in the Yellow River basin during the last half of the twentieth century. J Climate, 21 (8), 1790, 2008.
  • 4. OUYANG W., HAO F., SONG K., ZHANG X. Cascade dam-induced hydrological disturbance and environmental impact in the upper stream of the Yellow River. Water Resource Manage, 25( 3), 913, 2011.
  • 5. WU J., QIAN H., LI P.Y., SONG Y. A system-theory-based model for Monthly River runoff forecasting: model calibration and optimization. Journal of Hydrology and Hydromechanics, 62 (1), 82, 2014.
  • 6. WEI X., ZENGCHUAN D., ZHENCHUN H., DAYONG L., LI R. River health evaluation based on the Fuzzy matter-element extension assessment model. Polish Journal of Environmental Studies, 26 (3), 1353, 2017.
  • 7. BENESTAD R.E., HANSSEN-BAUER I., FORLAND E.J. An evaluation of statistical models for downscaling precipitation and their ability to capture long-term trends. International Journal of Climatology, 27 (5), 649, 2010.
  • 8. BEUCHAT X., SCHAEFLI B., SOUTTER M., MERMOUD A. Toward a robust method for sub daily rainfall downscaling from daily data. Water Resource Research, 47 (9), 1995, 2011.
  • 9. GUAN H., WILSON J.L., XIE H.J. A cluster-optimizing regression-based approach for precipitation spatial downscaling in mountainous terrain. Journal of Hydrology, 375 (3-4), 578, 2009.
  • 10. LAMPTEY B.L. Comparison of gridded multisatellite rainfall estimates with gridded gauge rainfall over West Africa. Journal of Applied Meteorology and Climatology, 47 (1), 185, 2008.
  • 11. APSITE E., RUDLAPA I., LATKOVSKA I., ELFERTS D. Changes in Latvian river discharge regime at the turn of the century. Hydrology Research, 44 (3), 554, 2013.
  • 12. SCHUMANN A.Y., KANTELHARDT J.W. Multifractal moving average analysis and test of multifractal model with tuned correlations. Physica A Statistical Mechanics and Its Applications, 390 (14), 2637, 2011.
  • 13. YUAN X.H., JI B., TIAN H., HUANG, Y.H. Multiscaling analysis of monthly runoff series using improved MF-DFA approach. Water Resources Management, 28 (12), 3891, 2014.
  • 14. ZHANG Q., ZHOU Y., SINGH V.P. Detrending methods for fluctuation analysis in hydrology: Amendments and comparisons of methodologies. Hydrological Processes, 28 (3), 753, 2014.
  • 15. WANG J.H., KANG L.L., YU H., WANG Y.Z. Analysis on the Effects of Climate Change on Natural Runoff Volume in the Upper Reaches of the Yellow River In Chinese. Arid land Geography, 28 (3), 288, 2005.
  • 16. LI P.Y., QIAN H., WU J.H. Accelerate research on land creation. Nature 510 (7503), 29, 2014.
  • 17. POFF N.L., ZIMMERMAN J.K.H. Ecological responses to altered flow regimes: a literature review to inform the science and management of environmental flows. Fresh Biology, 55 (1), 194, 2010.
  • 18. WANG H., YANG Z., SAITO Y., LIU J.P., SUN X., WANG Y. Stepwise decreases of the Huanghe (Yellow River) sediment load (1950-2005): impacts of climate change and human activities. Glob Planet Change, 57 (3), 331, 2007.
  • 19. CUI B., TANG N., ZHAO X., BAI J. A management-oriented valuation method to determine ecological water requirement for wetlands in the Yellow River Delta of China. Journal for Nature Conservation, 17 (3), 129, 2009.
  • 20. WANG J., HONG Y., GOURLEY J., ADHIKARI P., LI L., SU F. Quantitative assessment of climate change and human impacts on long-term hydrologic response: a case study in a sub-basin of the Yellow River China. International Journal of Climatology, 30(14), 2130, 2010.
  • 21. LI P.Y., QIAN H., HOWARD K.W.F., WU J.H, LYU X. Anthropogenic pollution and variability of manganese in alluvial sediments of the Yellow River, Ningxia, northwest China. Environmental Monitoring & Assessment, 186 (3), 1385, 2014.
  • 22. Redshaw C.H., Stahl-Timmins W.M., Fleming L.E., Davidson I., Depledge M.H. Potential Changes in Disease Patters and Pharmaceutical Use in Response to Climate Change. Journal of Toxicology and Environmental Health B, 16 (1), 285, 2013.
  • 23. Pack E.C., Kim C.H., Lee S.H., Lim C.H., Sung D.G., Kim M.H., Park K.H. Effects of Environmental Temperature Change on Mercury Absorption in Aquatic Organisms with Respect to Climate Warming. Journal of Toxicology and Environmental Health Part A, 77 (1), 1477, 2014.
  • 24. LI P.Y., QIAN H., HOWARD K.W.F., WU J. Heavy metal contamination of Yellow River alluvial sediments, northwest China. Environmental Earth Sciences, 73 (7), 3403, 2015.
  • 25. YANG Y.H., TIAN F. Abrupt Change of Runoff and Its Major Driving Factors in Haihe River Catchment, China. Journal of Hydrology, 374 (3), 373, 2009.
  • 26. VALIPOUR M., BANIHABIB M.E., BEHBAHANI S.M. Parameters Estimate of Autoregressive Moving Average and Autoregressive Integrated Moving Average Models and Compare Their Ability for Inflow Forecasting. Journal of Mathematics and Statistics, 8 (3), 330, 2012.
  • 27. VALIPOUR M., BANIHABIB M.E., BEHBAHANI S.M.R. Comparison of the ARMA, and the Autoregressive Artificial Neural Network Models in Forecasting the Monthly Inflow of Dez dam Reservoir. Journal of Hydrology, 476 (476), 433, 2013.
  • 28. KÖSE E., TOKATLI C., ÇIÇEK A. Monitoring stream water quality: a statistical evaluation. Polish Journal of Environmental Studies, 23 (5), 1637, 2014.
  • 29. GULICH D., ZUNINO L. A criterion for the determination of optimal scaling ranges in DFA and MF-DFA. Physica A Statistical Mechanics and Its Applications, 397 (397), 17, 2014.
  • 30. STONEVICIUS E., VALIUSKEVICIUS G., RIMKUS E., KAZYS, J. Climate induced changes of Lithuanian Rivers runoff in 1960-2009. Water Resources, 41 (5), 592, 2014.
  • 31. Dąbrowska J., Bawiec A., Pawęska K., Kamińska J., Stodolak R. Assessing the Impact of Wastewater Effluent Diversion on Water Quality. Polish Journal of Environmental Studies, 26 (1), 9, 2017.
  • 32. RICHTER B.D., BAUMGARTNER J.V., BRANN D.P., POWELL J. A Spatial Assessment of Hydrologic Alteration within a River Network. Regulated River: Research and Management, 14 (4), 329, 1998.
  • 33. KENDALL M.G. Rank correlation measures. London: Charles Griffin: 110, 1976.
  • 34. MANN H.B. Non-parametric tests against trend. Econometrical. 13,245, 1945.
  • 35. ZHANG D., CONG Z.T., NI G.H. Comparison of three Mann-Kendall methods based on the China’s meteorological data In Chinese. Advances in Water Science, 24 (4), 491, 2013.
  • 36. AZIZ O.I., BURN D.H. Trends and variability in the hydrological regime of the Mackenzie River Basin. Journal of Hydrology, 319 (1), 282, 2006.
  • 37. HAMED K.H. Enhancing the effectiveness of prewhitening in trend analysis of hydrologic data. Journal of Hydrology, 368 (1), 143, 2009.
  • 38. ZHANG Q., SUN P., JIANG T., TU X., CHEN X. Spatio-temporal patterns of hydrological processes and their responses to human activities in the Poyang Lake basin, China. Hydrological Sciences Journal, 6 (2), 305, 2011.
  • 39. Theil H. A Rank-Invariant Method of Linear and Polynomial Regression Analysis I-III. Springer Netherlands, 12 (2), 345-381, 1950.
  • 40. Sen P.K. Estimates of the Regression Coefficient Based on Kendall’s Tau. Journal of the American Statistical Association, 63 (324), 1379, 1968.
  • 41. SHENG Y., WANG C.T. The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resources Management, 18 (3) 201, 2004.

Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

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