Impacts of Climate Change and Land Use/Cover Change on Runoff in the Huangfuchuan River Basin DOI Creative Commons
Xin Huang, Lin Qiu

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2048 - 2048

Published: Nov. 29, 2024

Studying the response of runoff to climate change and land use/cover has guiding significance for watershed planning, water resource ecological environment protection. Especially in Yellow River Basin, which a variable fragile ecology, such research is more important. This article takes Huangfuchuan Basin (HFCRB) middle reaches as area, analyzes impact scenarios on by constructing SWAT model. Using CMIP6 GCMs obtain future data CA–Markov model predict use data, two are coupled estimate process HFCRB, uncertainty estimated decomposed quantified. The results were follows: ① good adaptability HFCRB. During calibrated period validation period, R2 ≥ 0.84, NSE 0.8, |PBIAS| ≤ 17.5%, all meet evaluation criteria. ② There negative correlation between temperature runoff, positive precipitation runoff. Runoff sensitive rise increase. ③ types order cultivated > grassland forest land. ④ variation range under combined effects LUCC that single or scenarios. increase SSP126, SSP245, SSP585 10.57%, 25.55%, 31.28%, respectively. Precipitation main factor affecting changes Model source prediction.

Language: Английский

An efficient parallel runoff forecasting model for capturing global and local feature information DOI Creative Commons

Yang-hao Hong,

Dongmei Xu, Wenchuan Wang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 11, 2025

Language: Английский

Citations

0
Assessing water resource vulnerability based on remote sensing data-enhanced SWAT+ and High-Resolution precipitation data DOI Creative Commons
Yu Qi, Xianqi Zhang, Qiuwen Yin

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 169, P. 112943 - 112943

Published: Dec. 1, 2024

Language: Английский

Citations

1
Incorporating Multi-Temporal Scale Data in Mts-Lstm to Enhance Reservoir-Regulated Streamflow Simulation DOI
Laura Lang, Xing Gao, Yongkun Li

et al.

Published: Jan. 1, 2024

Water security and its sustainable management are critical to human survival livelihoods, especially under the dual pressures of climate change population growth. In response these challenges, an increasing number natural watersheds being regulated by dams reservoirs, introducing significant complexity streamflow modeling. However, operation man-made infrastructures, small-scale ones managed local governments, is highly flexible irregular, making them difficult investigate model thoroughly. Remote sensing products can reveal reservoir dynamics at larger spatial scales, providing valuable data for data-scarce catchments. This study aims evaluate a deep learning architecture, namely Multi-TimeScale Long Short-Term Memory (MTS-LSTM), which capable incorporating multi-source multi-timescale simulate streamflow. Furthermore, role remote sensing-derived monthly storage anomalies in MTS-LSTM enhancing daily reservoir-regulated simulation investigated. The results case on Yuanjiang River Basin demonstrated that effectively bridge gap between SWAT-simulated observed streamflow, attributed regulations. simulated satisfactory performance both (mean values Correlation Coefficients [CC]=0.92, Nash–Sutcliffe Efficiency [NSE]=0.81 Kling-Gupta [KGE]=0.80) CC=0.79, NSE=0.58 KGE=0.71) timescales. integration into has significantly enhanced simulation. mean CC, NSE, KGE simulations showed improvements 5%, 14%, respectively. led higher level accuracy than achieved naive LSTM model. presents systematic methodology enhance simulations, with particular focus regions limited hybrid cascade systems.

Language: Английский

Citations

0
Runoff Simulation and Analysis of Water Source in the High-Elevation and Cold Area of the Shaliu River Basin DOI
Yunying Wang, Zongxing Li

Published: Jan. 1, 2024

Language: Английский

Citations

0
Hydrological Response and Soil Water-Soluble Antimony (Sb) and Arsenic (as) Transport Under Climate Change: A Swat Model Analysis DOI

Chujie Bu,

Pan Wu,

Jie Niu

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Runoff Prediction for Hydrological Applications Using an INFO-Optimized Deep Learning Model DOI Open Access
Weisheng Wang,

Yongkang Hao,

Xiaozhen Zheng

et al.

Processes, Journal Year: 2024, Volume and Issue: 12(8), P. 1776 - 1776

Published: Aug. 22, 2024

Runoff prediction is essential in water resource management, environmental protection, and agricultural development. Due to the large randomness, high non-stationarity, low accuracy of nonlinear effects traditional model, this study proposes a runoff model based on improved vector weighted average algorithm (INFO) optimize convolutional neural network (CNN)-bidirectional long short-term memory (Bi-LSTM)-Attention mechanism. First, historical data are analyzed normalized. Secondly, CNN combined with Attention used extract depth local features input weights Bi-LSTM. Then, Bi-LSTM time series feature analysis from both positive negative directions simultaneously. The INFO parameters optimized provide optimal parameter guarantee for CNN-Bi-LSTM-Attention model. Based hydrology station’s level flow data, influence three main models two optimization algorithms compared analyzed. results show that fitting coefficient, R2, proposed 0.948, which 7.91% 3.38% higher than CNN-Bi-LSTM, respectively. R2 vector-weighted 0.993, 0.61% Bayesian (BOA), indicating method adopted paper has more significant forecasting ability can be as reliable tool long-term prediction.

Language: Английский

Citations

0
Ecological Flow Research in Response to Hydrological Variation: A Case Study of the Jinsha River Basin, China DOI Creative Commons

Hong Lv,

Zhiqiang Gao, Dengming Yan

et al.

Desalination and Water Treatment, Journal Year: 2024, Volume and Issue: unknown, P. 100777 - 100777

Published: Sept. 1, 2024

Language: Английский

Citations

0
Impacts of Climate Change and Land Use/Cover Change on Runoff in the Huangfuchuan River Basin DOI Creative Commons
Xin Huang, Lin Qiu

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2048 - 2048

Published: Nov. 29, 2024

Studying the response of runoff to climate change and land use/cover has guiding significance for watershed planning, water resource ecological environment protection. Especially in Yellow River Basin, which a variable fragile ecology, such research is more important. This article takes Huangfuchuan Basin (HFCRB) middle reaches as area, analyzes impact scenarios on by constructing SWAT model. Using CMIP6 GCMs obtain future data CA–Markov model predict use data, two are coupled estimate process HFCRB, uncertainty estimated decomposed quantified. The results were follows: ① good adaptability HFCRB. During calibrated period validation period, R2 ≥ 0.84, NSE 0.8, |PBIAS| ≤ 17.5%, all meet evaluation criteria. ② There negative correlation between temperature runoff, positive precipitation runoff. Runoff sensitive rise increase. ③ types order cultivated > grassland forest land. ④ variation range under combined effects LUCC that single or scenarios. increase SSP126, SSP245, SSP585 10.57%, 25.55%, 31.28%, respectively. Precipitation main factor affecting changes Model source prediction.

Language: Английский

Citations

0