Hydrological Modeling to Unravel the Spatiotemporal Heterogeneity and Attribution of Baseflow in the Yangtze River Source Area, China DOI Open Access
Huazhun Ren, Guangdong Wu, Longcang Shu

и другие.

Water, Год журнала: 2024, Номер 16(20), С. 2892 - 2892

Опубликована: Окт. 11, 2024

Revealing the spatiotemporal variation in baseflow and its underlying mechanisms is critical for preserving health ecological functions of alpine rivers, but this has rarely been conducted source region Yangtze River (SRYR). Our study employed Soil Water Assessment Tool (SWAT) model coupled with two-parameter digital filtering geostatistical approaches to obtain a visual representation heterogeneity characteristics index (BFI) SRYR. The SWAT multiple linear regression (MLR) were used quantitatively estimate contribution climate change human activities BFI changes. results underscore robust applicability within Temporally, precipitation, temperature, exhibited significant upward trends, showed contrasting intra-annual distribution patterns, which unimodal bimodal distribution, respectively. Spatially, increased from northwest southeast, watershed perspective, Tongtian higher values compared other regions Dangqu greater than those tributaries. More 50% entire basin had an annual value 0.7, indicates that was major contributor runoff generation. Moreover, contributions variability 122% −22%, variability, 60% 40%. Specifically, precipitation contributed 116% variations, while temperature 6% 8%, Overall, it concluded distributions are controlled by various factors, main factor variation. offers valuable insights management quantitative assessment groundwater resources SRYR amidst change.

Язык: Английский

Interpretable baseflow segmentation and prediction based on numerical experiments and deep learning DOI
Qiying Yu,

Shi Chen,

Yungang Bai

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 360, С. 121089 - 121089

Опубликована: Май 10, 2024

Язык: Английский

Процитировано

10

Multi-Scenario land cover changes and carbon emissions prediction for peak carbon emissions in the Yellow River Basin, China DOI Creative Commons

Haipeng Niu,

Si Chen,

Dongyang Xiao

и другие.

Ecological Indicators, Год журнала: 2024, Номер 168, С. 112794 - 112794

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

5

Comprehensive evaluation and attribution analysis of baseflow variation in a typical karst basin, Southwest China DOI

Chongxun Mo,

Changhao Jiang,

S. P. Long

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2025, Номер 57, С. 102185 - 102185

Опубликована: Янв. 10, 2025

Язык: Английский

Процитировано

0

Impact of land use intensity changes on ecosystem services in the Yellow River Basin, China DOI
Nan Li,

Piling Sun,

Jinye Zhang

и другие.

Journal of Geographical Sciences, Год журнала: 2025, Номер 35(5), С. 1003 - 1023

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Trend changes of flow regime metrics in the water conservation zone of the Yellow River caused by observation uncertainty DOI
Yongyong Zhang, Bing Han,

Chun-Li Cao

и другие.

Journal of Geographical Sciences, Год журнала: 2025, Номер 35(5), С. 964 - 978

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Analysis of Variation Trend and Driving Factors of Baseflow in Typical Yellow River Basins DOI Open Access

Liyu Quan,

Chengshuai Liu,

Chaojie Niu

и другие.

Water, Год журнала: 2023, Номер 15(20), С. 3647 - 3647

Опубликована: Окт. 18, 2023

Baseflow is a stable part of streamflow and the main component during dry season. plays an important role in water cycle, ecological environment protection Yellow River basin (YRB). Taking Zuli, Kuye, Tuwei basins, Jingle sub-basin as examples, baseflow was separated using recursive digital filtering method. The intra-annual, inter-annual, chronological characteristics index (BFI) were analyzed, driving factors analyzed from perspective climate-change human-impact factors. results showed that: (1) annual basins mainly declined, trending downward all four test while BFI increased two remained nearly constant other basins; however, distributions more uniform. (2) intra-annual patterns for changes between earlier later periods. (3) Precipitation soil conservation measures primary forces change basins. influence former weakened latter strengthened, coal mining Kuye also influenced significantly. (4) When normalized difference vegetation (NDVI) < 0.375, watersheds gradually decreased with increase NDVI. 0.375 NDVI 0.65, underlying surface continued to improve. > rate capacity tended be stable.

Язык: Английский

Процитировано

7

Impact of urbanization on baseflow characteristics in the central catchment of North China Plain, China DOI Creative Commons

Yuhua Tan,

Xin Yi,

Chunling Guo

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2023, Номер 50, С. 101527 - 101527

Опубликована: Сен. 15, 2023

The Dawenhe River and Xiaoqinghe Basins (116°21′–118°41′E, 35°43′–37°15′N) in the center of North China Plain (NCP), China. To quantitatively assess influence urbanization (two indicators including Impervious Surface Percentage (ISP) Average Night Light Index (ANLI)) on baseflow hydrological behavior (nine signatures), this study selects typical urbanized catchment sub-catchments) within central NCP, where was estimated from total daily streamflow 2006 to 2016. Findings show that: (i) Baseflow signatures had a notable spatial variability, which magnitude (Qb10, Qb25, Qb50, Qb90), (BFI), Concavity (CI), Slope duration curve (SBDC) demonstrated greater values north versus south. (ii) Both ISP ANLI exhibited an upward trend over time with some fluctuations (R2 > 0.65, p < 0.05). For ANLI, there were higher northwest northeast regions, mainly located northern region. (iii) Overall, effects two catchment-variability, model performance between is better than ANLI. This provides scientific reference elucidate water balance NCP under background urbanization.

Язык: Английский

Процитировано

6

Influence of human-induced land use change on hydrological processes in semi-humid and semi-arid region: A case in the Fenhe River Basin DOI Creative Commons

Xianglin Lyu,

Yangwen Jia,

Yaqin Qiu

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2023, Номер 51, С. 101605 - 101605

Опубликована: Дек. 12, 2023

Study Region: The Fenhe River Basin (FRB) is an important tributary of the Yellow and locate in a semi-arid semi-humid region northwest China. Over past four decades, significant anthropogenic activities have resulted land use cover change (LUCC) that markedly impacted hydrological processes FRB. Focus: To analyze changes under multiple historical scenarios from LU1980 to LU2015, establish Water Energy transfer Processes Large basins (WEP-L) model quantify influences LUCC on processes, particularly baseflow. New insights for region: LU2015 14.5 % increase water yield (WY) 2.7 1.4 decrease baseflow (BF) evapotranspiration, respectively. Urbanization led WY reduction BF, exhibiting strong spatial gradients between urban centers their peripheries. Increases forestland decreased WY, while ET showed no due large absolute values moisture limitations. Furthermore, response BF forest exhibits variation. A negative correlation was evident upstream, whereas observed downstream. findings this study offer valuable planning sustainable watershed management region.

Язык: Английский

Процитировано

6

Baseflow characteristics and drivers in headwater catchment of the Yellow River, Tibetan Plateau DOI Creative Commons
Jiao Zhang,

Yu Lan,

Xinsen Chen

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 56, С. 101991 - 101991

Опубликована: Окт. 7, 2024

Язык: Английский

Процитировано

1

Quantitative assessment of ecological flow in the Yellow River under changing environments DOI Creative Commons

Wenxian Guo,

Xuyang Jiao,

Baoliang Wang

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Март 1, 2024

Abstract Studying the streamflow characteristics of Yellow River mainstem under changing environments is great significance to management and sustainable development utilization water resources in its basin. In this paper, a long short-term memory (LSTM) model used restore flow mainstream natural conditions, range variation approach (RVA) nonparametric kernel density estimation (KDE) method are combined quantitatively assess impact environment on streamflow. The study shows that: (1) hydrological variability occurred 1985, degree ranged from 26–58%, which moderate. (2) annual ecological value ranges 560 ~ 1001 m 3 /s, average guarantee 43%; (3) Through LSTM simulation (NSE > 0.7, R 2 0.8), it concluded that assurance situation higher than measured value, mainly affected by human activities, contribution rate more 52%. This river ecosystem relatively unstable needs further management.

Язык: Английский

Процитировано

0