Please wait a minute...
Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

Postal Subscription Code 80-963

2018 Impact Factor: 1.205

Front. Earth Sci.    2020, Vol. 14 Issue (3) : 568-577    https://doi.org/10.1007/s11707-019-0811-7
RESEARCH ARTICLE
Quantifying the impact of mountain precipitation on runoff in Hotan River, northwestern China
Baofu LI1,2(), Jili ZHENG1,2, Xun SHI3, Yaning CHEN4
1. School of Geography and Tourism, Qufu Normal University, Rizhao 276826, China
2. Rizhao Key Laboratory of Territory Spatial Planning and Ecological Construction, Rizhao 276826, China
3. Department of Geography, Dartmouth College, Hanover, NH 03755, USA
4. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
 Download: PDF(1796 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

It is of great significance to quantitatively assess the impact of mountain precipitation on inland river runoff in data scarce regions. Based on the corrected TRMM precipitation and runoff data, a variety of statistical methods were used to identify which areas of precipitation have an important impact on runoff in the Hotan River Basin, and to evaluate the effects that precipitation changes have on runoff at low, mid, high, and extremely high altitudes of mountainous areas. The results showed that: 1) From 1998 to 2015, the annual runoff showed a fluctuating upward trend with a rate of 11.21 × 108 m3/10 a (P<0.05). Runoff in every season also had an increasing trend, with summer runoff the most significant at a rate of 6.09×108 m3/10 a. 2) The annual runoff and precipitation changes had certain synchronization, with a correlation coefficient of 0.45 (P<0.05). Among them, the correlations between precipitation and runoff changes were highest at low and mid- altitudes, with coefficients of 0.62 and 0.55, respectively (P<0.05). 3) 65.95% of the regional precipitation at low altitudes and 48.34% at high altitudes were significantly correlated with runoff (P<0.05), while only 38.84% and 26.58% of regional precipitation levels at mid- and extremely high altitudes were significantly correlated with runoff. 4) The annual precipitation change in the basin was 1%, which would cause the annual runoff to change by 0.24%. In 1998–2015, the change of annual runoff caused by precipitation change at high altitudes was largest at a rate of −6.01%; the change rates of annual runoff caused by precipitation change in the low, mid-, and extremely high altitudes were −3.66%, −3.62%, and −3.67%, respectively. The results have significant scientific guidance for water resource management in arid basins.

Keywords precipitation      mountainous areas      runoff      TRMM      arid region of northwestern China     
Corresponding Author(s): Baofu LI   
Online First Date: 12 June 2020    Issue Date: 04 December 2020
 Cite this article:   
Baofu LI,Jili ZHENG,Xun SHI, et al. Quantifying the impact of mountain precipitation on runoff in Hotan River, northwestern China[J]. Front. Earth Sci., 2020, 14(3): 568-577.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-019-0811-7
https://academic.hep.com.cn/fesci/EN/Y2020/V14/I3/568
Fig.1  Location of the Hotan River Basin and distribution of surrounding meteorological stations and hydrological stations.
Fig.2  Annual runoff trends of the Hotan River from 1998 to 2015
Fig.3  Seasonal runoff trends in the Hotan River from 1998 to 2015
Fig.4  In calibration period (a: 1998–2010) and verification period (b: 2011–2015), the trends in precipitation based on TRMM and stations in the Hotan River Basin
Correction R BIAS RMSE
Before correction 0.56*** 0.10 57.66
After correction 0.94*** −0.05 47.98
Tab.1  Relationship between TRMM data and measured precipitation data in Hotan River basin during calibration period (1998–2010)
Fig.5  Spatial variation of annual precipitation in the Hotan River Basin from 1998 to 2015 based on correction TRMM data.
Fig.6  (a) Annual and (b) monthly runoff and precipitation changes in the Hotan River Basin.
Period Low altitude Mid- altitude High altitude Extremely high altitude Hotan River Basin
Year 0.62* 0.55* 0.42 0.25 0.45*
Spring 0.05 0.04 0.01 -0.02 0.01
Summer 0.59* 0.39 0.38 0.27 0.39
Autumn 0.13 0.09 -0.06 -0.11 -0.03
Winter 0.00 0.13 0.08 0.05 0.07
Tab.2  Pearson correlation coefficient between precipitation and runoff in Hotan River Basin from 1998 to 2015
Fig.7  Spatial distribution of correlation coefficient between (a) annual, (b) summer runoff and precipitation in the Hotan River Basin from 1998 to 2015
Fig.8  The area ratio of significant (P<0.05) correlation between annual, summer runoff and precipitation in the Hotan River Basin from 1998 to 2015
Fig.9  Sensitivity coefficient of annual runoff in Hotan River Basin to precipitation changes in mountainous areas and the change rate of annual runoff caused by precipitation changes
1 Y Chen, B Li, Y Fan, C Sun, G Fang (2019). Hydrological and water cycle processes of inland river basins in the arid region of Northwest China. J Arid Land, 11(2): 161–179
https://doi.org/10.1007/s40333-019-0050-5
2 Y Chen, B Li, Z Li, W Li (2016). Water resource formation and conversion and water security in arid region of northwest China. J Geogr Sci, 26(7): 939–952
https://doi.org/10.1007/s11442-016-1308-x
3 H Deng, Y Chen, H Wang, S Zhang (2015). Climate change with elevation and its potential impact on water resources in the Tianshan Mountains, Central Asia. Global Planet Change, 135: 28–37
https://doi.org/10.1016/j.gloplacha.2015.09.015
4 Z Duan, W G M Bastiaanssen (2013). First results from Version 7 TRMM 3B43 precipitation product in combination with a new downscaling–calibration procedure. Remote Sens Environ, 131: 1–13
https://doi.org/10.1016/j.rse.2012.12.002
5 G K Gould, M Liu, M E Barber, K A Cherkauer, P R Robichaud, J C Adam (2016). The effects of climate change and extreme wildfire events on runoff erosion over a mountain watershed. J Hydrol (Amst), 536: 74–91
https://doi.org/10.1016/j.jhydrol.2016.02.025
6 B Jongjin, P Jongmin, R Dongryeol, C Minha (2016). Geospatial blending to improve spatial mapping of precipitation with high spatial resolution by merging satellite-based and ground-based data. Hydrol Processes, 30(16): 2789–2803
https://doi.org/10.1002/hyp.10786
7 C Kummerow, W Barnes, T Kozu, J Shiue, J Simpson (1998). The tropical rainfall measuring mission (TRMM) sensor package. J Atmos Ocean Technol, 15(3): 809–817
https://doi.org/10.1175/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2
8 B Li, Y Chen, Z Chen, W Li (2012). Trends in runoff versus climate change in typical rivers in the arid region of northwest China. Quat Int, 282: 87–95
https://doi.org/10.1016/j.quaint.2012.06.005
9 B Li, Y Chen, Z Chen, H Xiong, L Lian (2016a). Why does precipitation in northwest China show a significant increasing trend from 1960 to 2010? Atmos Res, 167: 275–284
https://doi.org/10.1016/j.atmosres.2015.08.017
10 B Li, Y Chen, H Xiong (2016b). Quantitatively evaluating the effects of climate factors on runoff change for Aksu River in northwestern China. Theor Appl Climatol, 123(1–2): 97–105
https://doi.org/10.1007/s00704-014-1341-6
11 B Li, Y Chen, Z Chen, W Li, B Zhang (2013). Variations of temperature and precipitation of snowmelt period and its effect on runoff in the mountainous areas of northwest China. J Geogr Sci, 23(1): 17–30
https://doi.org/10.1007/s11442-013-0990-1
12 B Li, Y Chen, J W Chipman, X Shi, Z Chen (2018a). Why does the runoff in Hotan River show a slight decreased trend in northwestern China? Atmos Sci Lett, 19(1): e800
https://doi.org/10.1002/asl.800
13 B Li, Y Chen, X Shi (2020a). Does elevation dependent warming exist in high mountain Asia? Environ Res Lett, 15(2):024012
https://doi.org/10.1088/1748-9326/ab6d7f
14 B Li, X Shi, L Lian, Y Chen, Z Chen, X Sun (2020b). Quantifying the effects of climate variability, direct and indirect land use change, and human activities on runoff. J Hydrol (Amst), 584:124684
https://doi.org/10.1016/j.jhydrol.2020.124684
15 Y Li, Y Chen, Z Li, G Fang (2018b). Recent recovery of surface wind speed in northwest China. Inter J Clim, 38(12): 4445–4458
https://doi.org/10.1002/joc.5679
16 J Liu, Q Zhang, V P Singh, P Shi (2017). Contribution of multiple climatic variables and human activities to streamflow changes across China. J Hydrol (Amst), 545: 145–162
https://doi.org/10.1016/j.jhydrol.2016.12.016
17 J Liu, W Li, Y Chen, S Jing, R Ma (2018). Analysis on desertification of degraded riparian forest in the lower reaches of Peacock River. J Liaocheng U Natura, 117(01):65–71+103
18 K Luo, F Tao, X Deng, J P Moiwo (2017). Changes in potential evapotranspiration and surface runoff in 1981–2010 and the driving factors in Upper Heihe River Basin in northwest China. Hydrol Processes, 31(1): 90–103
https://doi.org/10.1002/hyp.10974
19 Y Luo, J Arnold, S Liu, X Wang, X Chen (2013). Inclusion of glacier processes for distributed hydrological modeling at basin scale with application to a watershed in Tianshan Mountains, northwest China. J Hydrol (Amst), 477: 72–85
https://doi.org/10.1016/j.jhydrol.2012.11.005
20 S Mo, Z Li, K Gou, L Qin, B Shen (2018). Quantifying the effects of climate variability and direct human activities on the change in mean annual runoff for the Bahe river (northwest China). J Coast Res, 34(1): 81–89
https://doi.org/10.2112/JCOASTRES-D-16-00159.1
21 J Qin, Y Liu, Y Chang, S Liu, H Pu, J Zhou (2016). Regional runoff variation and its response to climate change and human activities in northwest China. Environ Earth Sci, 75(20): 1366
https://doi.org/10.1007/s12665-016-6187-z
22 J Rozante, D Vila, J Barboza Chiquetto, A Fernandes, D Souza Alvim (2018). Evaluation of trmm/gpm blended daily products over Brazil. Remote Sens, 10(6): 882
https://doi.org/10.3390/rs10060882
23 X Tian, B Li, X Li, T Li, M Zhu, L Wang (2019). Spatiotemporal variation of precipitable water and its influencing factors in the north China Plain during 1970–2012. J Liaocheng U Nature, 32(3): 81–88
24 H Wang, Y Chen, Z Chen (2013). Spatial distribution and temporal trends of mean precipitation and extremes in the arid region, northwest of China, during 1960–2010. Hydrol Processes, 27(12): 1807–1818
https://doi.org/10.1002/hyp.9339
25 H Wang, Y Pan, Y Chen, Z Ye (2017). Linear trend and abrupt changes of climate indices in the arid region of northwestern China. Atmos Res, 196: 108–118
https://doi.org/10.1016/j.atmosres.2017.06.008
26 R Wang, Q Cheng, L Liu, C Yan, G Huang (2019). Multi-Model projections of climate change in different RCP scenarios in an arid inland region, northwest China. Water, 11(2): 347
https://doi.org/10.3390/w11020347
27 C Xu, J Zhao, H Deng, G Fang, J Tan, D He, Y Chen, Y Chen, A Fu (2016a). Scenario-based runoff prediction for the Kaidu River basin of the Tianshan Mountains, northwest China. Environ Earth Sci, 75(15): 1126
https://doi.org/10.1007/s12665-016-5930-9
28 F Xu, B Guo, B Ye, Q Ye, H Chen, X Ju, J Guo, Z Wang (2019). Systematical evaluation of GPM IMERG and TRMM 3B42V7 precipitation products in the Huang-Huai-Hai Plain, China. Remote Sens, 11(6): 697
https://doi.org/10.3390/rs11060697
29 J Xu, Y Chen, L Bai, Y Xu (2016b). A hybrid model to simulate the annual runoff of the Kaidu River in northwest China. Hydrol Earth Syst Sci, 20(4): 1447–1457
https://doi.org/10.5194/hess-20-1447-2016
30 P Yang, J Xia, Y Zhang, S Hong (2017). Temporal and spatial variations of precipitation in northwest China during 1960–2013. Atmos Res, 183: 283–295
https://doi.org/10.1016/j.atmosres.2016.09.014
31 Z Yang (1991). Glacier Water Resources in China. Lanzhou: Gansu Sci & Tech Press
32 J Yao, Q Yang, W Mao, Y Zhao, X Xu (2016). Precipitation trend-elevation relationship in arid regions of the China. Global Planet Change, 143: 1–9
https://doi.org/10.1016/j.gloplacha.2016.05.007
33 Z Yin, Q Feng, S Liu, S Zou, J Li, L Yang, R Deo (2017). The spatial and temporal contribution of glacier runoff to watershed discharge in the Yarkant River Basin, northwest China. Water, 9(3): 159
https://doi.org/10.3390/w9030159
34 F Zhang, H Zhang, S C Hagen, M Ye, D Wang, D Gui, C Zeng, L Tian, J Liu (2015). Snow cover and runoff modelling in a high mountain catchment with scarce data: effects of temperature and precipitation parameters. Hydrol Processes, 29(1): 52–65
https://doi.org/10.1002/hyp.10125
35 Q Zhang, P Shi, V P Singh, K Fan, J Huang (2017). Spatial downscaling of TRMM-based precipitation data using vegetative response in Xinjiang, China. Inter J Clim, 37(10): 3895–3909
https://doi.org/10.1002/joc.4964
36 Y Zhang, Y Li, X Ji, X Luo, X Li (2018). Fine-resolution precipitation mapping in a mountainous watershed: geostatistical downscaling of TRMM products based on environmental variables. Remote Sens, 10(1): 119
https://doi.org/10.3390/rs10010119
37 H Zheng, L Zhang, R Zhu, C Liu, Y Sato, Y Fukushima (2009). Responses of streamflow to climate and land surface change in the headwaters of the Yellow River Basin. Water Resour Res, 45(7)
https://doi.org/10.1029/2007WR006665
38 J Zheng, B Li, Y Chen, Z Chen, L Lian (2018). Spatiotemporal variation of upper-air and surface wind speed and its influencing factors in northwestern China during 1980–2012. Theor Appl Climatol, 133(3–4): 1303–1314
https://doi.org/10.1007/s00704-017-2346-8
39 X Zhu, X Qiu, Y Zeng, W Ren, B Tao, H Pan, T Gao, J Gao (2018). High-resolution precipitation downscaling in mountainous areas over China: development and application of a statistical mapping approach. Inter J Clim, 38(1): 77–93
https://doi.org/10.1002/joc.5162
[1] Boyuan ZHU, Jinyun DENG, Jinwu TANG, Wenjun YU, Alistair G.L. BORTHWICK, Yuanfang CHAI, Zhaohua SUN, Yitian LI. Erosion-deposition patterns and depo-center movements in branching channels at the near-estuary reach of the Yangtze River[J]. Front. Earth Sci., 2020, 14(3): 537-552.
[2] Sukh TUMENJARGAL, Steven R. FASSNACHT, Niah B.H. VENABLE, Alison P. KINGSTON, Maria E. FERNÁNDEZ-GIMÉNEZ, Batjav BATBUYAN, Melinda J. LAITURI, Martin KAPPAS, G. ADYABADAM. Variability and change of climate extremes from indigenous herder knowledge and at meteorological stations across central Mongolia[J]. Front. Earth Sci., 2020, 14(2): 286-297.
[3] Linna ZHAO, Xuemei BAI, Dan QI, Cheng XING. BMA probability quantitative precipitation forecasting of land-falling typhoons in south-east China[J]. Front. Earth Sci., 2019, 13(4): 758-777.
[4] Jia ZHU, Jiong SHU, Xing YU. Improvement of typhoon rainfall prediction based on optimization of the Kain-Fritsch convection parameterization scheme using a micro-genetic algorithm[J]. Front. Earth Sci., 2019, 13(4): 721-732.
[5] Peiyan CHEN, Hui YU, Ming XU, Xiaotu LEI, Feng ZENG. A simplified index to assess the combined impact of tropical cyclone precipitation and wind on China[J]. Front. Earth Sci., 2019, 13(4): 672-681.
[6] Xuerongzi HUANG, Dashan WANG, Yu LIU, Zhizhou FENG, Dagang WANG. Evaluation of extreme precipitation based on satellite retrievals over China[J]. Front. Earth Sci., 2018, 12(4): 846-861.
[7] Xiaoting WANG, Zhan’e YIN, Xuan WANG, Pengfei TIAN, Yonghua HUANG. A study on flooding scenario simulation of future extreme precipitation in Shanghai[J]. Front. Earth Sci., 2018, 12(4): 834-845.
[8] Qianfeng WANG, Jingyu ZENG, Song LENG, Bingxiong FAN, Jia TANG, Cong JIANG, Yi HUANG, Qing ZHANG, Yanping QU, Wulin WANG, Wei SHUI. The effects of air temperature and precipitation on the net primary productivity in China during the early 21st century[J]. Front. Earth Sci., 2018, 12(4): 818-833.
[9] Alba SANMIGUEL-VALLELADO, Enrique MORÁN-TEJEDA, Esteban ALONSO-GONZÁLEZ, Juan Ignacio LÓPEZ-MORENO. Effect of snow on mountain river regimes: an example from the Pyrenees[J]. Front. Earth Sci., 2017, 11(3): 515-530.
[10] T. STOICHEV, J. ESPINHA MARQUES, C.M. ALMEIDA, A. DE DIEGO, M.C.P. BASTO, R. MOURA, V.M. VASCONCELOS. Simple statistical models for relating river discharge with precipitation and air temperature—Case study of River Vouga (Portugal)[J]. Front. Earth Sci., 2017, 11(2): 203-213.
[11] Qing TIAN, Qing WANG, Yalong LIU. Geomorphic change in Dingzi Bay, East China since the 1950s: impacts of human activity and fluvial input[J]. Front. Earth Sci., 2017, 11(2): 385-396.
[12] Le Wang,Shenglian Guo,Xingjun Hong,Dedi Liu,Lihua Xiong. Projected hydrologic regime changes in the Poyang Lake Basin due to climate change[J]. Front. Earth Sci., 2017, 11(1): 95-113.
[13] Zhiyong WU,Juan WU,Guihua LU. A one-way coupled atmospheric-hydrological modeling system with combination of high-resolution and ensemble precipitation forecasting[J]. Front. Earth Sci., 2016, 10(3): 432-443.
[14] Rui XING,Zhiying DING,Sangjie YOU,Haiming XU. Relationship of tropical-cyclone-induced remote precipitation with tropical cyclones and the subtropical high[J]. Front. Earth Sci., 2016, 10(3): 595-606.
[15] Ziniu XIAO,Xiuhua ZHOU,Ping YANG,Hua LIU. Variation and future trends in precipitation over summer and autumn across the Yunnan region[J]. Front. Earth Sci., 2016, 10(3): 498-512.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed