Comprehensive evaluation of extreme hydrometeorological events coincidence and their interrelationships in the Hanjiang River Basin, China DOI
Haoyu Jin, Patrick Willems, Xiaohong Chen

и другие.

Journal of Hydrology, Год журнала: 2024, Номер 638, С. 131506 - 131506

Опубликована: Июнь 14, 2024

Язык: Английский

A Multidecadal Assessment of Drought Intensification in the Middle East and North Africa: The Role of Global Warming and Rainfall Deficit DOI Creative Commons
Ahmed El Kenawy, Talal Al‐Awadhi, Meshal M. Abdullah

и другие.

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

Опубликована: Фев. 14, 2025

Язык: Английский

Процитировано

3

Climate extremes and land use carbon emissions: Insight from the perspective of sustainable land use in the eastern coast of China DOI
Lin Zhao, Cuifang Zhang, Qian Wang

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 452, С. 142219 - 142219

Опубликована: Апрель 11, 2024

Язык: Английский

Процитировано

16

Forecasting climate risk and heat stress hazards in arid ecosystems: Machine learning and ensemble models for specific humidity prediction in Dammam, Saudi Arabia DOI
Adel S. Aldosary, Baqer Al-Ramadan, Abdulla ‐ Al Kafy

и другие.

Natural Hazards, Год журнала: 2025, Номер unknown

Опубликована: Фев. 18, 2025

Язык: Английский

Процитировано

2

Analysis of future climate variability under CMIP6 scenarios based on a downscaling method considering wet days in the upper Yangtze River basin, China DOI Creative Commons
Hanqiu Xu, Daniele Bocchiola

Theoretical and Applied Climatology, Год журнала: 2025, Номер 156(2)

Опубликована: Янв. 13, 2025

Abstract According to recent studies, the past decade was hottest on record, and climate change is accelerating. As part of Yangtze River Basin, largest river basin in China, Upper Basin (UYRB) plays a crucial role as primary source hydropower. However, UYRB also one most climate-sensitive regions within basin, making impact this area particularly critical. We downscaled CMIP6 GCMs’ outputs precipitation (including wet/dry spells sequence correction), temperature projections (2024–2100), under four typical Shared Socioeconomic Pathways (SSPs), we pursued trend analysis upon these potential future series. found significant upward trends across all SSPs August, but no for same month. Additionally, SSP370 SSP585, there are December, while showed during that This may result drier winters than now, increased evapotranspiration, reduced surface (snow) water storage, impacting resources availability. Consecutive dry/wet days at station, scale show spatial-temporal heterogeneity, generally wet longer, dry shorten moving from South-East North-West.

Язык: Английский

Процитировано

1

A novel approach for evaluation of CMIP6 GCMs in simulating temperature and precipitation extremes of Pakistan DOI
Zulfiqar Ali, Mohammed Magdy Hamed, Mohd Khairul Idlan Muhammad

и другие.

International Journal of Climatology, Год журнала: 2024, Номер 44(2), С. 592 - 612

Опубликована: Янв. 18, 2024

Abstract The study used a hybrid approach to evaluate the performance of 20 global climate models (GCMs) from CMIP6 in reproducing extreme temperature and precipitation indices over Pakistan. This first analysed future simulations extremes discarded GCMs whose projections fell outside 95% confidence interval. remaining GCMs' was evaluated using Kling Gupta Efficiency‐based criteria. changes climatic events Pakistan were projected multi‐model ensemble (MME) median selected for four shared socioeconomic pathways (SSPs) two periods, 2020–2059 2060–2099. Four showed inconsistency projecting initially. past revealed EC‐Earth3‐Veg‐LR, GFDL‐ESM4, MRI‐ESM2‐0 NOR‐ESM2‐MM be effective historical period. MME gradual increase most periods all SSPs across country. Specifically, it higher daily maximum (TXx) by 4.5–5°C, minimum (TNn) more than 4.5°C, consecutive days with 95th percentile (WSDI) >160 days, one‐day rainfall 9–15 mm above >50 northern high‐elevated areas during 2060–2099 SSP585. Similarly, TXx TNn >4.5°C, WSDI 140 tropical nights 40–60 also found western arid region highlights that regions are at risk temperatures due change.

Язык: Английский

Процитировано

7

Enhancing Soil Resilience to Climatic Wetting‐Drying Cycles Through a Bio‐Mediated Approach DOI
Chao‐Sheng Tang, Бо Лю, Farshid Vahedifard

и другие.

Journal of Geophysical Research Earth Surface, Год журнала: 2024, Номер 129(5)

Опубликована: Май 1, 2024

Abstract Climatic wetting‐drying cycles exacerbated by climate change can trigger several weakening mechanisms in surface soils, potentially leading to instability and failure of slopes earthen structures. This study proposes a bio‐mediated approach based on microbially induced calcite precipitation (MICP) increase soil resilience cycles. To explore its viability the underlying mechanisms, we conducted series laboratory tests clayey that underwent six The were with different treatment methods investigate effect sequence cementation solution concentration. After MICP treatment, initial evaporation rate, crack ratio during drying, total weight loss rainfall erosion reduced up 32%, 85%, 90%, respectively. Spraying first proves more effective improving water retention capacity. On other hand, initiating bacterial demonstrates pronounced reducing desiccation cracks erosion. Microstructure analysis reveals content distribution CaCO 3 are major factors controlling effectiveness for soil. Employing minimize carbon footprint contribute developing environmentally friendly solutions improvement regions affected climatic

Язык: Английский

Процитировано

7

Effects of urban stormwater pollution on watershed diffuse loads under extreme precipitation conditions DOI
Jingyi Hu, Wei Ouyang, Congyu Hou

и другие.

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 132802 - 132802

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1

Basin-Scale Daily Drought Prediction Using Convolutional Neural Networks in Fenhe River Basin, China DOI Creative Commons

Zixuan Chen,

Guojie Wang,

Xikun Wei

и другие.

Atmosphere, Год журнала: 2024, Номер 15(2), С. 155 - 155

Опубликована: Янв. 25, 2024

Drought is a natural disaster that occurs globally and can damage the environment, disrupt agricultural production cause large economic losses. The accurate prediction of drought effectively reduce impacts droughts. Deep learning methods have shown promise in prediction, with convolutional neural networks (CNNs) being particularly effective handling spatial information. In this study, we employed deep approach to predict Fenhe River (FHR) basin, taking into account meteorological conditions surrounding regions. We used daily SAPEI (Standardized Antecedent Precipitation Evapotranspiration Index) as evaluation index. Our results demonstrate effectiveness CNN model predicting events 1~10 days advance. evaluated predictions made by model; average Nash–Sutcliffe efficiency (NSE) between predicted true values for next 10 was 0.71. While accuracy slightly decreased longer lengths, remained stable heavy are typically difficult predict. Additionally, key variables were identified, found training these led higher than it all variables. This study approves an when considering

Язык: Английский

Процитировано

6

Compound dry and hot events over major river basins of the world from 1921 to 2020 DOI Creative Commons
Tongtiegang Zhao,

Shaotang Xiong,

Yu Tian

и другие.

Weather and Climate Extremes, Год журнала: 2024, Номер 44, С. 100679 - 100679

Опубликована: Май 9, 2024

Compound dry and hot events (CDHEs) are among the most destructive compound extremes. Under global warming, changes in precipitation, temperature their dependence make profound contributions to CDHEs. In this paper, of these three factors explicitly quantified based on a novel mathematical method. Specifically, time series precipitation employed identify CDHEs then attributed by using partial derivatives-based sensitivity analysis. Based Climatic Research Unit Time-Series (CRU TS), case study is devised for major river basins (MRBs) world. The results highlight that from period 1921-1970 1971-2020, did occur more frequently across MRBs. tended largest contribution, followed between temperature. Africa, South America Western Europe, rising generally dominant factor increases heatwaves contribute Asia, droughts along with raise risk For MRBs moderate temperature, increasing shown mitigate or even offset risks meantime, observed reduce frequency Huai He Mississippi though therein increasing. Overall, attributing 1921 2020 can serve as reference preparation mitigation

Язык: Английский

Процитировано

4

Forecasting drought using machine learning: a systematic literature review DOI
Ricardo S. Oyarzabal, Leonardo Bacelar Lima Santos, Christopher Cunningham

и другие.

Natural Hazards, Год журнала: 2025, Номер unknown

Опубликована: Март 7, 2025

Язык: Английский

Процитировано

0