Divergent responses of permafrost degradation to precipitation increases at different seasons on the eastern Qinghai–Tibet Plateau based on modeling approach DOI Creative Commons
Jingjing Yang, Taihua Wang, Dawen Yang

et al.

Environmental Research Letters, Journal Year: 2023, Volume and Issue: 18(9), P. 094038 - 094038

Published: Aug. 15, 2023

Abstract The Qinghai–Tibet Plateau (QTP) has responded to remarkable climate warming with dramatic permafrost degradation over the past few decades. Previous studies have mostly focused on responses rising air temperature, while effects of accompanying increases in precipitation remain contentious and largely unknown. In this study, a distributed process-based model was applied quantify impacts increased thermal regimes by employing experiments source region Yellow River (SRYR) eastern QTP. results showed that active layer thickness (ALT) 0.25 m during 2010–2019 compared 2000 across SRYR, which primarily driven warming. contrast, annual played relatively limited role just slightly mitigated thickening 0.03 m. Intriguingly, cold warm seasons exerted opposite SRYR. season mainly promoted ALT increases, increases. ∼81.0% cooling wetting outweighed wetting; at transition zone where unstable degrading seasonally frozen ground, larger contributed degradation. This study explored physical mechanisms wetting, thus providing better understanding change warmer wetter

Language: Английский

Glacial melting explained lake expansion toward drying climate phase on the Tibetan Plateau DOI
Rong Wang, Yuanbo Liu, Liu Yongwei

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: 652, P. 132685 - 132685

Published: Jan. 12, 2025

Language: Английский

Citations

0
A Novel Sensitivity Analysis Framework for Quantifying Permafrost Impacts on Runoff Variability in the Yangtze River Source Region DOI Open Access

Jiaxuan Chang,

Xuefeng Sang, Yun Zhang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(4), P. 1570 - 1570

Published: Feb. 14, 2025

In the context of global climate change, understanding cryosphere degradation and its impact on water resources in alpine regions is crucial for sustainable development. This study investigates relationship between permafrost runoff variations Source Region Yangtze River (SRYR), a critical tower supply Asia. We propose novel method assessing sensitivity, which establishes correlation changes hydrological responses, contributing to resource management. Our research quantifies key uncertainties change attribution, providing essential data decision making. Results show that watershed characteristics account up 20% variation, with (−0.02 sensitivity) demonstrating greater influence than NDVI variations. The findings offer insights development adaptation strategies, particularly maintaining ecosystem services ensuring long-term security under changing conditions. offers scientific basis climate-resilient management policies high-altitude regions.

Language: Английский

Citations

0
Runoff spatiotemporal variability driven by climate change and human activity for the Nianchu River Basin in Southwestern Tibet DOI Creative Commons
Zhe Yuan, K. Liu, Dan Zeng

et al.

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 58, P. 102301 - 102301

Published: March 6, 2025

Language: Английский

Citations

0
Porous aquifers buffer the streamflow change caused by climate warming in alpine catchments, Qinghai–Tibet Plateau DOI
Zhao Pan, Rui Ma, Ziyong Sun

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 133235 - 133235

Published: April 1, 2025

Language: Английский

Citations

0
Changes in hydrological processes in the headwater area of Yellow River, China during 1956–2019 under the influences of climate change, permafrost thaw and dam DOI Creative Commons
Qiang Ma, Huijun Jin, Qingbai Wu

et al.

Advances in Climate Change Research, Journal Year: 2023, Volume and Issue: 14(2), P. 237 - 247

Published: March 30, 2023

Discharge characteristics are crucial for detecting changes in hydrological processes.Recently, the river hydrology) Headwater Area of Yellow River (HAYR) has exhibited erratic regimes (e.g., monotonously declining/low/high hydrograph, even with normal precipitation) under effects climate change, permafrost thaw and dam operation.This study integrates hydroclimatic variables (air temperature, precipitation, potential evapotranspiration) anthropogenic operation degradation impact data to systematically examine mechanisms these process during 1956e2019.The results show following: 1) compared pre-dammed gauged flow, construction (January 1998eJanuary 2000) removal (September 2018eAugust 2019) induced low (À17.2m 3 s À1 ; À61%) high (þ54.6m þ138%) hydrographs, respectively; 2) mainly controlled summereautumn processes HAYR; 3) monotonous decline hydrograph HAYR some years 1977, 1979, 1990 1995) was closely related unusually atmospheric demands evaporation low-intense rainfall seasons; 4) lengthening subsurface pathways residence time, reduced recession coefficient (À0.002 per year) winter flow altered seasonal rivers, which resulted flattened hydrographs that delayed peak (of 0.05 mm year 1.65 d year, respectively) as well boosted baseflow (0.01 year).This can provide updated systematic understanding changing typical alpine catchments on northeastern QinghaieTibet Plateau, China a warming climate.

Language: Английский

Citations

10
Monthly Streamflow Prediction of the Source Region of the Yellow River Based on Long Short-Term Memory Considering Different Lagged Months DOI Open Access

Haibo Chu,

Zhuoqi Wang,

Chong Nie

et al.

Water, Journal Year: 2024, Volume and Issue: 16(4), P. 593 - 593

Published: Feb. 17, 2024

Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation efficient utilization of water resources. In this paper, we proposed framework that integrates input variable selection method Long Short-Term Memory (LSTM). The methods, including autocorrelation function (ACF), partial (PACF), time lag cross-correlation (TLCC), were used to analyze lagged between variables. Then, performance LSTM model was compared with three other traditional methods. predict at Jimai, Maqu, Tangnaihai stations source area Yellow River. results indicated grid search cross-validation can improve efficiency determining parameters. models incorporating ACF, PACF, TLCC are evidently superior using current as inputs. Furthermore, model, which considers time, demonstrated better predicting streamflow. coefficient determination (R2) improved by an average 17.46%, 33.94%, 15.29% for each station, respectively. integrated shows promise enhancing accuracy prediction, thereby aiding strategic decision-making resources management.

Language: Английский

Citations

3
Quantifying the Regulation Capacity of the Three Gorges Reservoir on Extreme Hydrological Events and Its Impact on Flow Regime in a Changing Climate DOI Creative Commons
Han Cheng, Taihua Wang, Dawen Yang

et al.

Water Resources Research, Journal Year: 2024, Volume and Issue: 60(6)

Published: June 1, 2024

Abstract The Three Gorges Reservoir (TGR) is one of the world's largest hydropower projects and plays an important role in water resources management Yangtze River. For sake disaster prevention catchment management, it crucial to understand regulation capacity TGR on extreme hydrological events its impact flow regime a changing climate. This study obtains historical inflows from 1961 2019 uses distributed model simulate future 2021 2070. These data are adopted drive machine learning‐based operation obtain simulated outflow with operation, which then compared natural without assess TGR. results indicate that average flood peaks total flooding days period could have been reduced by 29.2% 53.4% relative declines drought indicators including duration intensity were generally less than 10%. Faced more severe future, still expected alleviate floods droughts, but cannot bring them down levels. will also evolve climate, potentially altering habitats river ecosystems. proposes feasible methods for simulating large reservoirs quantifying regime, provides insights integrated watershed upper River basin.

Language: Английский

Citations

3
Impacts of seasonally frozen soil hydrothermal dynamics on the watershed hydrological processes inferred from a spatially distributed numerical modelling approach DOI
Huiran Gao, Zhijie Zhang, Hao Chen

et al.

Journal of Hydrology, Journal Year: 2023, Volume and Issue: 624, P. 129947 - 129947

Published: July 19, 2023

Language: Английский

Citations

8
Cyclical ‘wetting’ phenomenon in the source region of Yellow River under long-term trends from 1956 to 2022 DOI Creative Commons
Jiefeng Wu, Xuan Zhang, Gaoxu Wang

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 53, P. 101821 - 101821

Published: May 21, 2024

the source region of Yellow River (SRYB) Due to environmental changes, drying and wetting processes have become increasingly intricate, it is uncertain whether phenomenon in SRYB indicates a long-term trend or temporary cyclic event. This study utilized monthly streamflow precipitation records from 1956 2022 calculate hydrological meteorological-dryness/wetness, represented by standardized indices, respectively. used detrended, wavelet, cross-wavelet methods investigate dry-wet variability identified atmospheric circulation phenomena driving dryness/wetness cyclical changes region. (i) The showed an overall fluctuating trend, which intensified after 2000. (ii) There were notable oscillatory cycles at 3–5 years, 10–12 approximately 20–25 years both meteorological variability. (iii) Transitions dry wet conditions had no significant link short-term (e.g., years), but linked decadal years). (iv) Spring winter dominated interannual (v) ENSO, AMO, PDO influenced fluctuations, while AO fluctuations. that follows pattern, intensification since 2000 consistent with signal.

Language: Английский

Citations

2
The influence of human activities on rainfall-runoff relationships at different time scales in the Minjiang River Basin DOI

Kaili Geng,

Xingwei Chen,

Meiling Zheng

et al.

Theoretical and Applied Climatology, Journal Year: 2024, Volume and Issue: 155(8), P. 8435 - 8454

Published: Aug. 1, 2024

Language: Английский

Citations

2