Linkage detection between climate oscillations and water and sediment discharge of 10 rivers in Eastern China DOI Creative Commons
Feng Zhang, Li Zhang, Yaozhao Zhong

et al.

Frontiers in Marine Science, Journal Year: 2024, Volume and Issue: 11

Published: Dec. 24, 2024

Water discharge and sediment load are often controlled by a combination of factors. However, the relationship between water changes meteorological oscillations has rarely been explored for different river sizes. Explanations various responses water-sediment to factors in rivers is important understanding global hydrology. In this study, we analyzed data from 2002-2022 using cross-wavelet wavelet coherence an attempt characterize effects large-scale climatic on 10 eastern China. Comparing results shows that releases lag three months or more behind SST variations. It also oscillates interannually (mostly every 8-16 months). Most runoff lags PDO more. The impact ENSO (El Niño-Southern Oscillation) each basin gradually decreases south north. impacts northern such as Yellow River, Huai Riverand Liao River weaker. At same time, Pearl Minjiang basins southeastern China extremely rapid sensitive events. Meanwhile, large lasted throughout study period, while smaller had intermittent periods, response rates geographically similar mountain stream-type were not same. effect (Pacific Decadal warm cold phases was region. Our research contributes climate oscillations, advancing Water-Sediment Balance Global Sustainability—key goals United Nations 2030 Agenda Sustainable Development.

Language: Английский

Dynamics and impacts of monsoon-induced geological hazards: a 2022 flood study along the Swat River in Pakistan DOI Creative Commons
Nazir Ahmed Bazai, Mehtab Alam, Peng Cui

et al.

Natural hazards and earth system sciences, Journal Year: 2025, Volume and Issue: 25(3), P. 1071 - 1093

Published: March 11, 2025

Abstract. This study examines the impacts of unprecedented 2022 monsoon season in Pakistan's Swat River basin, where rainfall exceeded historical averages by 7 %–8 %. extreme weather led to catastrophic debris flows and floods, worsening challenges for low-income communities. The resulting financial instability affected millions, causing significant damage homes, crops, transportation. employs a multidisciplinary approach, combining field investigations, remote sensing data interpretation, numerical simulations identify factors contributing flow incidents. Analysis land cover changes reveals decrease grasslands an increase barren land, indicating adverse effects deforestation on region. Topography gully morphology are crucial initiating flows, with steep gradients shallow-slope failures predominant. Numerical show that reached high velocities 18 m s−1 depths 40 within 45 min. Two resulted formation dams along River, intensifying subsequent floods. emphasizes interplay during rainy season, rendering region susceptible hindering restoration efforts. Recommendations include climate change mitigation, reforestation initiatives, discouraging construction activities flood-prone debris-flow-prone regions. advocates enhanced early warning systems rigorous use planning protect environment local communities, highlighting imperative proactive measures face escalating challenges. Additionally, investigates spatial distribution various events their consequences, including potential hydrometeorological triggers, how such initiate processes mountain landscapes. It also assesses extent which can be classified as abnormal. combination empirical evidence practical insights presented this highlights research gaps proposes routes toward deeper understanding monsoon-triggered geological hazards consequences.

Language: Английский

Citations

1
Recent increase in soil moisture levels concerning climate variability in the karst region of southwest China using wavelet coherence and multi-linear regression DOI
Azfar Hussain, Huizeng Liu, Jianhua Cao

et al.

Gondwana Research, Journal Year: 2025, Volume and Issue: 141, P. 40 - 54

Published: Feb. 7, 2025

Language: Английский

Citations

0
Localized environmental variability within the Hindukush-Himalayan region of Pakistan DOI Creative Commons
Fazlul Haq,

Munazza Afreen,

Bryan G. Mark

et al.

Environmental Earth Sciences, Journal Year: 2025, Volume and Issue: 84(4)

Published: Feb. 1, 2025

Abstract The Hindukush-Himalayan (HKH) region, known for its eco-environmental importance, has been witnessing transformations in recent years governed by factors such as climate variability, land use shifts, and population growth. These changes have profound implications regional sustainability, water resources, livelihood. This study attempts to explore the spatial temporal variability selected environmental parameters including surface temperature (LST), normalized difference vegetation index (NDVI), precipitation patterns, snow (NDSI), cover (LULC) from 1990 2022 using Landsat imageries (30 m resolution), CHIRPS data at 0.05° resolution. area spans 32,000 km 2 covering two major political/administrative divisions (Malakand Hazara) HKH region of Pakistan. was primarily because unprecedented over last three decades. For detailed analysis, divided into five elevation zones LST, NDVI, NDSI, LULC analyses were conducted utilizing Google Earth Engine (GEE) platform engine. results revealed a notable rise LST lowest zone. NDVI noticeable decline 5988 1990, 4225 2010, followed growth 7669 2022, since 2010 after launching Billion Tree Tsunami Afforestation Project (BTTAP) 2013. Likewise, patterns exhibit transitioning low high levels. However, most finding is marked covered 7000 3800 between 2022.

Language: Английский

Citations

0
Comparison of CMIP6 GCMs historical precipitation with measured precipitation over Pakistan DOI Creative Commons
Adnan Abbas, Waheed Ullah, Safi Ullah

et al.

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(3), P. e0319999 - e0319999

Published: March 31, 2025

Comparison of Coupled Model Intercomparison Project Phase 6 (CMIP6) General Circulation Models (GCMs) with observations under different climatic conditions is necessary to determine their respective strengths and differences. In the current study, ten CMIP6 GCMs are compared measured gauge precipitation data 51 stations across Pakistan. Results show reasonable agreement between CMIP6-GCMs in capturing days ≤10 mm/day. The intensity events ≥10 mm/day shows a significant resemblance at 95% confidence level (K-S test). Furthermore, results regional differences demonstrate relatively good CMCC-CM2-SR5, EC-Earth3-AerChem, EC-Earth3-CC arid semiarid regions FGOALS-f3-L humid extremely regions. Significant variability reported interannual standard deviation ratio (STD) for all seasons, implying more dynamics intense GCMs. magnitude STD sensitive time space rather than climate classes, higher lower monsoon autumn respectively. climatological mean northeastern southeastern parts during winters complementing station data. Based on selected metrics, CMCC-ESM2 has highest skill simulating distributions over Pakistan, followed by CMCC-CM2-SR5 EC-Earth3-CC, while NorCPM1 ranked worst reproducing precipitation. findings can serve as benchmark region applying water food security studies.

Language: Английский

Citations

0
Precipitation dynamics and its interactions with possible drivers over global highlands DOI
Haider Abbas, Azfar Hussain, Ming Xu

et al.

Global and Planetary Change, Journal Year: 2024, Volume and Issue: 240, P. 104529 - 104529

Published: July 26, 2024

Language: Английский

Citations

3
Validation of CRU TS v4.08, ERA5-Land, IMERG v07B, and MSWEP v2.8 Precipitation Estimates Against Observed Values over Pakistan DOI Creative Commons
Haider Abbas, Wenlong Song, Yicheng Wang

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(24), P. 4803 - 4803

Published: Dec. 23, 2024

Global precipitation products (GPPs) are vital in weather forecasting, efficient water management, and monitoring floods droughts. However, the precision of these datasets varies considerably across different climatic regions topographic conditions. Therefore, accuracy assessment dataset is crucial at local scale before its application. The current study initially compared performance recently modified upgraded datasets, including Climate Research Unit Time-Series (CRU TS v4.08), fifth-generation ERA5-Land (ERA-5), Integrated Multi-satellite Retrievals for GPM (IMERG) final run (IMERG v07B), Multi-Source Weighted-Ensemble Precipitation (MSWEP v2.8), against ground observations on provincial basis Pakistan from 2003 to 2020. Later, area was categorized into four based elevation observe impact gradients GPPs’ skills. monthly seasonal estimations each product were validated situ using statistical matrices, correlation coefficient (CC), root mean square error (RMSE), percent bias (PBias), Kling–Gupta efficiency (KGE). results reveal that IMERG7 consistently outperformed all provinces, with highest CC lowest RMSE values. Meanwhile, KGE (0.69) PBias (−0.65%) elucidated, comparatively, best MSWEP2.8 Sindh province. Additionally, demonstrated their agreement reference data toward southern part (0–500 m elevation) Pakistan, while notably declined northern high-elevation glaciated mountain (above 3000 elevation), considerable overestimations. superior elevation-based also revealed study. According evaluation, except ERA-5 showed good estimation ability a scale, followed by winter season, pre-monsoon monsoon during post-monsoon weak observed data. Overall, exhibited comparatively performance, season. CRU moderate association observations, whereas performed poorly time scales. In scenario, this recommends hydrological climate studies region. emphasizes need further research experiments minimize scales make GPPs more reliable future studies.

Language: Английский

Citations

1
Risk Assessment of Rainstorm Flood Disasters in the China-Pakistan Economic Corridor DOI
Mengting Liu, Xu Min, Xingdong Li

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Linkage detection between climate oscillations and water and sediment discharge of 10 rivers in Eastern China DOI Creative Commons
Feng Zhang, Li Zhang, Yaozhao Zhong

et al.

Frontiers in Marine Science, Journal Year: 2024, Volume and Issue: 11

Published: Dec. 24, 2024

Water discharge and sediment load are often controlled by a combination of factors. However, the relationship between water changes meteorological oscillations has rarely been explored for different river sizes. Explanations various responses water-sediment to factors in rivers is important understanding global hydrology. In this study, we analyzed data from 2002-2022 using cross-wavelet wavelet coherence an attempt characterize effects large-scale climatic on 10 eastern China. Comparing results shows that releases lag three months or more behind SST variations. It also oscillates interannually (mostly every 8-16 months). Most runoff lags PDO more. The impact ENSO (El Niño-Southern Oscillation) each basin gradually decreases south north. impacts northern such as Yellow River, Huai Riverand Liao River weaker. At same time, Pearl Minjiang basins southeastern China extremely rapid sensitive events. Meanwhile, large lasted throughout study period, while smaller had intermittent periods, response rates geographically similar mountain stream-type were not same. effect (Pacific Decadal warm cold phases was region. Our research contributes climate oscillations, advancing Water-Sediment Balance Global Sustainability—key goals United Nations 2030 Agenda Sustainable Development.

Language: Английский

Citations

0