A Comparative Study for Evaluating the Groundwater Inflow and Drainage Effect of Jinzhai Pumped Storage Power Station, China DOI Creative Commons

Jian Wu,

Zhifang Zhou,

Hao Wang

и другие.

Applied Sciences, Год журнала: 2024, Номер 14(19), С. 9123 - 9123

Опубликована: Окт. 9, 2024

Various hydrogeological problems like groundwater inflow, water table drawdown, and pressure redistribution may be encountered in the construction of hydraulic projects. How to accurately predict occurrence inflow assess drainage effect during are still challenging for engineering designers. Taking Jinzhai pumped storage power station (JPSPS) China as an example, this paper aims use different methods calculate rates underground powerhouse evaluate caused by tunnel construction. The consist analytical formulas, site rating (SGR) method, Signorini type variational inequality formulation. results show that considering stable overestimate caverns drained conditions, whereas SGR method with available hydro-geological parameters obtains a qualitative hazard assessment preliminary phase. numerical solutions provide more precise reliable values complex geological structures seepage control measures. Moreover, effects, including seepage-free surface, pore redistribution, gradient, have been evaluated using various synthetic cases. Specifically, faults intersecting on significantly change flow regime around caverns. This comparative study can not only exactly identify capabilities cavern but also comprehensively

Язык: Английский

Seasonal dynamics of water quality in response to land use changes in the Chi and Mun River Basins Thailand DOI Creative Commons
Kwanchai Pakoksung, Nantawoot Inseeyong,

Nattawin Chawaloesphonsiya

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 27, 2025

The Chi and Mun River Basins, the primary tributary of Mekong Basin in Thailand, is undergoing significant land use changes that impact water quality. Understanding relationship between quality crucial for effective river basin management, providing insights applicable to global systems. While past studies have examined Basin, research specifically focusing on Chi-Mun remains limited. This study analyzes spatial temporal effects from 2007 2021 using change estimation, 11 parameters, redundancy analysis (RDA). Water samples were collected January, March, May, August across multiple years. Seasonal variations assessed, with dry season January March wet May August. Key findings include: (1) pH, Biochemical Oxygen Demand, Total Coliform Bacteria, Fecal Phosphorus, Nitrate Nitrogen, Ammonia-Nitrogen, Suspended Solids increased during season, while (2) Dissolved Oxygen, Electrical Conductivity, Quality Index higher season. (3) Land had a greater driven by runoff expanding urban agricultural areas declining paddy forest cover. (4) Forests aquatic improved quality, expansion contributed its deterioration. These underscore need sustainable management strategies balance regional development ecological conservation Basin.

Язык: Английский

Процитировано

0
Prediction of Pan Evaporation in diverse climates and scenarios using Temporal Attention Clockwork Recurrent Neural Networks coupled with Long-Short Term Memory DOI Creative Commons
Azadeh Goodarzi,

Mahdi Mohammadi Sergini,

Ali Saber

и другие.

Water Cycle, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Assessment of future water availability and seasonal patterns of dry seasons under climate change in Cidanau Watershed Banten Province, Indonesia DOI
Septian Fauzi Dwi Saputra, Budi Setiawan, Chusnul Arif

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2025, Номер 59, С. 102344 - 102344

Опубликована: Март 30, 2025

Язык: Английский

Процитировано

0
SWAT and CMIP6-driven hydro-climate modeling of future flood risks and vegetation dynamics in the White Oak Bayou Watershed, United States DOI

Stephanie Marshall,

Thanh‐Nhan‐Duc Tran, Arfan Arshad

и другие.

Earth Systems and Environment, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Assessment of flood risk based on CMIP6 for the Northern foothills of Qinling mountain DOI
Adnan Ahmed, Aidi Huo,

YANG Luying

и другие.

Theoretical and Applied Climatology, Год журнала: 2025, Номер 156(4)

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Decoding of long-term spatio-temporal precipitation dynamics over India: Insights from 115 years of meteorological data DOI Creative Commons
Deepak Kumar Soni, Avinash Dass, Pramod N. Kamble

и другие.

Global and earth surface processes change., Год журнала: 2025, Номер unknown, С. 100005 - 100005

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Impact of rapid urbanization on groundwater storage variation amid climate change in the Yangtze River Basin DOI
Weijun Zhou, Lu Hao

Journal of Hydrology Regional Studies, Год журнала: 2025, Номер 59, С. 102360 - 102360

Опубликована: Апрель 8, 2025

Язык: Английский

Процитировано

0
The impact of rainfall and slope on hillslope runoff and erosion depending on machine learning DOI Creative Commons

Naichang Zhang,

Zhaohui Xia, Peng Li

и другие.

Frontiers in Environmental Science, Год журнала: 2025, Номер 13

Опубликована: Апрель 24, 2025

Introduction Soil erosion is a critical issue faced by many regions around the world, especially in purple soil hilly areas. Rainfall and slope, as major driving factors of erosion, pose significant challenge quantifying their impact on hillslope runoff sediment yield. While existing studies have revealed effects rainfall intensity slope comprehensive analysis interactions between different types still lacking. To address this gap, study, based machine learning methods, explores type, amount, maximum 30-min (I30), depth (H) erosion-induced yield (S), unveils among these factors. Methods The K-means clustering algorithm was used to classify 43 events into three types: A-type, B-type, C-type. A-type characterized long duration, large amounts, moderate intensity; B-type short small high C-type intermediate B-type. Random Forest (RF) employed assess impacts yield, along with feature importance analysis. Results results show that amount has most Under types, ranking I30 H S follows: (C>A>B), (A>B>C). follows trend first increasing then decreasing, varying degrees influence depending type. Discussion novelty study lies combining techniques systematically evaluate, for time, type This research not only provides theoretical basis control but also offers scientific support precise prediction management conservation measures regions.

Язык: Английский

Процитировано

0
Assessing climate change impacts on extreme hydrological characteristics of reservoir inflow in Tianshan Mountain Range, China DOI Creative Commons
Xiaobo Yun, Jianwen Wang,

Hongjun Bao

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 28, 2025

The hydrological extremes, caused by increasing regional extreme precipitation and melting glaciers or snow under climate change, pose a major challenge to reservoir management in Tianshan Mountain Range of China. Modeling assessment extremes are important measures ensure the safety operations water resources. However, insufficient faced reservoirs has limited development flood risk early warning methods for mountain reservoirs. To this end, based on VIC-CAS-R model that coupled with glacier snowmelt modules, study analyzed evaluated changing characteristics streamflow selected from 1961 2014, Standardized Streamflow Index (SSI) Mann-Kendall test were used identify as well trends. result indicated (1) showed segmented change trend "increasing-decreasing-increasing"; (2) notable variations temporal spatial distribution, located western area decrease wet (up 70.8%) an increase dry 73.9%), while eastern region experienced simultaneous 119.8%). These insights help deepen comprehension induced reservoirs, provide support predicting other arid inland regions.

Язык: Английский

Процитировано

0
How Do Satellite Precipitation Products Affect Water Quality Simulations? A Comparative Analysis of Rainfall Datasets for River Flow and Riverine Nitrate Load in an Agricultural Watershed DOI Creative Commons
Mahesh R. Tapas

Nitrogen, Год журнала: 2024, Номер 5(4), С. 1015 - 1030

Опубликована: Ноя. 1, 2024

Excessive nitrate loading from agricultural runoff leads to substantial environmental and economic harm, although hydrological models are used mitigate these effects, the influence of various satellite precipitation products (SPPs) on load simulations is often overlooked. This study addresses this research gap by evaluating impacts using different products—ERA5, IMERG, gridMET—on flow with Soil Water Assessment Tool Plus (SWAT+), Tar-Pamlico watershed as a case study. Although activities higher in summer, found lowest during season due reduced runoff. In contrast, was winter because increased runoff, highlighting dominance water driving riverine load. that IMERG predicts highest annual average (120 m3/s Pamlico Sound), it unexpectedly results (1750 metric tons/year). gridMET estimates significantly loads (3850 discrepancy underscores crucial impact rainfall datasets transport predictions highlights how choice dataset can simulations.

Язык: Английский

Процитировано

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