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Streamflow changes in the headwater area of Yellow river, NE Qinghai-Tibet plateau during 1955–2040 and their implications
- Source :
- Water (Switzerland) 13 (2021) 10, Water (Switzerland), 13(10), Water, Vol 13, Iss 1360, p 1360 (2021), Water; Volume 13; Issue 10; Pages: 1360
- Publication Year :
- 2021
-
Abstract
- Human activities have substantially altered present-day flow regimes. The Headwater Area of the Yellow River (HAYR, above Huanghe’yan Hydrological Station, with a catchment area of 21,000 km2 and an areal extent of alpine permafrost at ~86%) on the northeastern Qinghai-Tibet Plateau, Southwest China has been undergoing extensive changes in streamflow regimes and groundwater dynamics, permafrost degradation, and ecological deterioration under a warming climate. In general, hydrological gauges provide reliable flow records over many decades and these data are extremely valuable for assessment of changing rates and trends of streamflow. In 1998–2003, the damming of the Yellow River by the First Hydropower Station of the HAYR complicated the examination of the relations between hydroclimatic variables and streamflow dynamics. In this study, the monthly streamflow rate of the Yellow River at Huanghe’yan is reconstructed for the period of 1955–2019 using the double mass curve method, and then the streamflow at Huagnhe’yan is forecasted for the next 20 years (2020–2040) using the Elman neural network time-series method. The dam construction (1998–2000) has caused a reduction of annual streamflow by 53.5–68.4%, and a more substantial reduction of 71.8–94.4% in the drier years (2003–2005), in the HAYR. The recent removal of the First Hydropower Station of the HAYR dam (September 2018) has boosted annual streamflow by 123–210% (2018–2019). Post-correction trends of annual maximum (QMax) and minimum (QMin) streamflow rates and the ratio of the QMax/QMin of the Yellow River in the HAYR (0.18 and 0.03 m3·s−1·yr−1 and −0.04 yr−1, respectively), in comparison with those of precorrection values (−0.11 and −0.004 m3·s−1·yr−1 and 0.001 yr−1, respectively), have more truthfully revealed a relatively large hydrological impact of degrading permafrost. Based on the Elman neural network model predictions, over the next 20 years, the increasing trend of flow in the HAYR would generally accelerate at a rate of 0.42 m3·s−1·yr−1. Rising rates of spring (0.57 m3·s−1·yr−1) and autumn (0.18 m3·s−1·yr−1) discharge would see the benefits from an earlier snow-melt season and delayed arrival of winter conditions. This suggests a longer growing season, which indicates ameliorating phonology, soil nutrient availability, and hydrothermal environments for vegetation in the HAYR. These trends for hydrological and ecological changes in the HAYR may potentially improve ecological safety and water supplies security in the HAYR and downstream Yellow River basins.
- Subjects :
- Streamflow forecasting
010504 meteorology & atmospheric sciences
0208 environmental biotechnology
Geography, Planning and Development
Drainage basin
Growing season
02 engineering and technology
Aquatic Science
Permafrost
Hydrology and Quantitative Water Management
01 natural sciences
Biochemistry
Double mass analysis
Streamflow
Warming climate
TD201-500
Hydropower
0105 earth and related environmental sciences
Water Science and Technology
Hydrology
geography
Streamflow data correction for damming
geography.geographical_feature_category
Plateau
WIMEK
Water supply for domestic and industrial purposes
Headwater Area of Yellow River
business.industry
Artificial neural network time-series method
Vegetation
Hydraulic engineering
020801 environmental engineering
warming climate
streamflow data correction for damming
streamflow forecasting
artificial neural network time-series method
Environmental science
business
TC1-978
Hydrologie en Kwantitatief Waterbeheer
Subjects
Details
- Language :
- English
- ISSN :
- 20734441
- Database :
- OpenAIRE
- Journal :
- Water (Switzerland) 13 (2021) 10, Water (Switzerland), 13(10), Water, Vol 13, Iss 1360, p 1360 (2021), Water; Volume 13; Issue 10; Pages: 1360
- Accession number :
- edsair.doi.dedup.....235d37c3b6cd0a613ae3c2ec78355998