Employing gridded-based dataset for heatwave assessment and future projection in Peninsular Malaysia DOI
Zulfaqar Sa’adi, Mohammed Magdy Hamed, Mohd Khairul Idlan Muhammad

и другие.

Theoretical and Applied Climatology, Год журнала: 2024, Номер 155(6), С. 5251 - 5278

Опубликована: Апрель 3, 2024

Язык: Английский

Flood hazards and susceptibility detection for Ganga river, Bihar state, India: Employment of remote sensing and statistical approaches DOI Creative Commons
Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

Results in Engineering, Год журнала: 2023, Номер 21, С. 101665 - 101665

Опубликована: Дек. 12, 2023

Climate change and flooding are related issues on the Earth's surface, while numerous lowland areas, especially delta regions, mostly affected by flood hazards. Hence, susceptibility mapping simulation of future effect areas essential for hazard management awareness. The river floodplain Ganga River in Bihar state most due to high annual floods. Floods cause huge economic losses environmental degradation, such as deforestation, riverbank erosion, water quality loss. Thus, vulnerability measurement is a serious concern this area, which involves building proper awareness mitigation strategies achieve sustainable development goals. Remote Sensing (RS) widely applied hydrological issues. statistical approaches, Analytical Hierarchy Process (AHP), Frequency Ratio (FR), Fuzzy-AHP (FAHP) algorithms, were analysis selected plain state. suitable three different approaches 9604.21 km2 9712.48 9598.28 channel not area. flooded maps indicated lands using Google Earth Engine (GEE) years 2977.69 (2020), 10481.63 (2021), 1103.89 (2022), respectively. results current study indicate that area essentially need attention adaptation reduction addition socio-economic variability monsoon regions. Otherwise, floods destroyed cropland, increased food scarcity, caused losses.

Язык: Английский

Процитировано

36

Exploring future trends of precipitation and runoff in arid regions under different scenarios based on a bias-corrected CMIP6 model DOI
Qingzheng Wang,

Yunfan Sun,

Qingyu Guan

и другие.

Journal of Hydrology, Год журнала: 2024, Номер 630, С. 130666 - 130666

Опубликована: Янв. 24, 2024

Язык: Английский

Процитировано

18

Heatwaves in Peninsular Malaysia: a spatiotemporal analysis DOI Creative Commons
Mohd Khairul Idlan Muhammad, Mohammed Magdy Hamed, Sobri Harun

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Фев. 21, 2024

One of the direct and unavoidable consequences global warming-induced rising temperatures is more recurrent severe heatwaves. In recent years, even countries like Malaysia seldom had some mild to As Earth's average temperature continues rise, heatwaves in will undoubtedly worsen future. It crucial characterize monitor heat events across time effectively prepare for implement preventative actions lessen heatwave's social economic effects. This study proposes heatwave-related indices that take into account both daily maximum (Tmax) lowest (Tmin) evaluate shifts heatwave features Peninsular (PM). Daily ERA5 dataset with a geographical resolution 0.25° period 1950-2022 was used analyze changes frequency severity waves PM, while LandScan gridded population data from 2000 2020 calculate affected also utilized Sen's slope trend analysis characteristics, which separates multi-decadal oscillatory fluctuations secular trends. The findings demonstrated pattern PM could be reconstructed if Tmax than 95th percentile 3 or days. indicated southwest prone experienced after before. Overall, heatwave-affected area has increased by 8.98 km

Язык: Английский

Процитировано

14

Enhancing Solar Radiation Forecasting in Diverse Moroccan Climate Zones: A Comparative Study of Machine Learning Models with Sugeno Integral Aggregation DOI Creative Commons
Abderrahmane Mendyl, Vahdettin Demir, Najiya Omar

и другие.

Atmosphere, Год журнала: 2024, Номер 15(1), С. 103 - 103

Опубликована: Янв. 14, 2024

Hourly solar radiation (SR) forecasting is a vital stage in the efficient deployment of energy management systems. Single and hybrid machine learning (ML) models have been predominantly applied for precise hourly SR predictions based on pattern recognition historical heterogeneous weather data. However, integration ML has not fully investigated terms overcoming irregularities data that may degrade accuracy. This study strategy highlights interactions exist between aggregated prediction values. In first investigation stage, comparative analysis was conducted utilizing three different including support vector (SVM) regression, long short-term memory (LSTM), multilayer artificial neural networks (MLANN) to provide insights into their relative strengths weaknesses forecasting. The comparison showed proposed LSTM model had greatest contribution overall six profiles from numerous sites Morocco. To validate stability LSTM, Taylor diagrams, violin plots, Kruskal–Wallis (KW) tests were also utilized determine robustness model’s performance. Secondly, found coupling outputs with aggregation techniques can significantly improve Accordingly, novel aggerated integrates SVM, MLANN Sugeno λ-measure integral named (SLSM) proposed. SLSM provides spatially temporary information are characterized by uncertainty, emphasizing importance function mitigating associated achieving an time scale accuracy improvement 11.7 W/m2.

Язык: Английский

Процитировано

10

Large-sample hydrology – a few camels or a whole caravan? DOI Creative Commons
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri

и другие.

Hydrology and earth system sciences, Год журнала: 2024, Номер 28(17), С. 4219 - 4237

Опубликована: Сен. 12, 2024

Abstract. Large-sample datasets containing hydrometeorological time series and catchment attributes for hundreds of catchments in a country, many them known as “CAMELS” (Catchment Attributes MEteorology Studies), have revolutionized hydrological modelling enabled comparative analyses. The Caravan dataset is compilation several (CAMELS other) large-sample with uniform attribute names data structures. This simplifies hydrology across regions, continents, or the globe. However, use instead original CAMELS other may affect model results conclusions derived thereof. For dataset, meteorological forcing are based on ERA5-Land reanalysis data. Here, we describe differences between precipitation, temperature, potential evapotranspiration (Epot) 1252 CAMELS-US, CAMELS-BR, CAMELS-GB these dataset. Epot unrealistically high catchments, but there are, unsurprisingly, also considerable precipitation We show that from impairs calibration vast majority catchments; i.e. drop performance when using compared to datasets. mainly due Therefore, suggest extending included wherever possible so users can choose which they want at least indicating clearly come quality loss recommended. Moreover, not (and attributes, such aridity index) recommend should be replaced (or on) alternative estimates.

Язык: Английский

Процитировано

10

Projected climate change impacts on streamflow in the Upper Oum Er Rbia Basin, Upstream of the Ahmed El Hansali Dam, Morocco DOI Creative Commons
Tarik El Orfi,

Mohamed El Ghachi,

Sébastien Lebaut

и другие.

Environmental Challenges, Год журнала: 2025, Номер 18, С. 101101 - 101101

Опубликована: Фев. 3, 2025

Язык: Английский

Процитировано

1

Multiple dimensions of extreme weather events and their impacts on biodiversity DOI Creative Commons
Juan David González‐Trujillo, Rosa María Román-Cuesta, Aarón Israel Muñiz-Castillo

и другие.

Climatic Change, Год журнала: 2023, Номер 176(11)

Опубликована: Ноя. 1, 2023

Abstract Climate change is a multidimensional phenomenon. As such, no single metric can capture all trajectories of and associated impacts. While numerous metrics exist to measure climate change, they tend focus on central tendencies neglect the multidimensionality extreme weather events (EWEs). EWEs differ in their frequency, duration, intensity, be described for temperature, precipitation, wind speed, while considering different thresholds defining “extremeness.” We review existing EWE outline framework classifying interpreting them light foreseeable impacts biodiversity. Using an example drawn from Caribbean Central America, we show that reflect unequal spatial patterns exposure across region. Based available evidence, discuss how such relate threats biological populations, empirically demonstrating ecologically informed help processes as mangrove recovery. Unveiling complexity affecting biodiversity only possible through mobilisation plethora metrics. The proposed represents step forward over assessments using dimensions or averages highly variable time series.

Язык: Английский

Процитировано

16

Wind Speed and Vegetation Coverage in Turn Dominated Wind Erosion Change With Increasing Aridity in Africa DOI Creative Commons
Hanbing Zhang, Jian Peng, Chaonan Zhao

и другие.

Earth s Future, Год журнала: 2024, Номер 12(6)

Опубликована: Июнь 1, 2024

Abstract Wind erosion is one of the main causes land degradation and desertification. Clarifying spatiotemporal variations wind dominant factors its spatial characteristics temporal trend will contribute to establishment appropriate control management practices, which essential for combating global strengthening ecological protection in drylands. Here, we assessed Africa during 2001–2020 based on Revised Erosion Equation (RWEQ). We also analyzed influential factor variation machine learning other methods under different aridity. Results revealed that average annual modulus was 16,672 t/km 2 /a 2001–2020, with hyper‐arid areas arid accounting more than 90% total modulus. The were dominated by natural but not anthropogenic activities. Except areas, speed vegetation coverage together characteristics. change, while semi‐arid capability affect change comparable speed. It can be concluded that, although revegetation does reduction taking into account water resource constraints use conflicts, large plantations replaced windbreaks increase reducing near‐surface speed, improves sustainability projects aimed at

Язык: Английский

Процитировано

5

Assessment of solar geoengineering impact on precipitation and temperature extremes in the Muda River Basin, Malaysia using CMIP6 SSP and GeoMIP6 G6 simulations DOI
Mou Leong Tan, Yi Lin Tew, Liew Juneng

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 948, С. 174817 - 174817

Опубликована: Июль 15, 2024

Язык: Английский

Процитировано

4

Comprehensive evaluation of IMERG, ERA5-Land and their fusion products in the hydrological simulation of three karst catchments in Southwest China DOI Creative Commons
Yong Chang,

Yaoyong Qi,

Ziying Wang

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 52, С. 101671 - 101671

Опубликована: Янв. 20, 2024

The study was carried out in three karst catchments Southwest China. These catchments, Sancha, Liuzhou and Qianjiang, are located the middle reaches of Pearl River Basin with catchment area 17067 km², 46166 134137 respectively. Satellite or reanalysis precipitation data potential alternatives that can be used hydrological models for streamflow forecasting data-sparse catchments. This aims to investigate performance two widely datasets, IMERG ERA5-Land, as well their fusion rain gauge measurements by Geographically Weighted Regression method, southwest results indicate compared IMERG, ERA5-Land has a higher correlation coefficient better detection rate daily gauge-based data. However, overestimates annual all Merging further improve its rate, but does not effectively mitigate overestimation. Meanwhile, model calibration through parameter adjustment partly compensate error discharge simulation accuracy, it cannot fully cover overestimation Therefore, consistently perform badly simulation. In contrast, demonstrates good agreement shows comparable even slightly superior prediction Additionally, calibrated parameters driven closely resemble those suggest serve viable alternative simulations region.

Язык: Английский

Процитировано

3