Abstract This study examined the physical properties of agricultural drought (i.e., intensity, duration, and severity) in Hungary from 1961 to 2010 based on Standardized Precipitation Index (SPI) Evapotranspiration (SPEI). The analyzed interaction between crop yield for maize wheat using standardized residual series (SYRS), crop-drought resilient factor (CDRF). results both SPI SPEI (-3, -6) showed that western part has significantly more prone than eastern country. Drought frequency...

During the last three decades, Delhi has witnessed extensive and rapid urban expansion in all directions, especially East South zone. The total built-up area risen dramatically, from 195.3 sq. km to 435.1 km, during 1989–2020, which led habitat fragmentation, deforestation, difficulties running utility services effectively new extensions. This research aimed simulate based on various driving factors using a logistic regression model. recent of was mapped LANDSAT images 1989, 2000, 2010,...

Drought is a natural hazard which affects ecosystems in the eastern Mediterranean. However, limited historical data for drought monitoring and forecasting are available Thus, implementing machine learning (ML) algorithms could allow prediction of future events. In this context, main goals research were to capture agricultural hydrological trends by using Standardized Precipitation Index (SPI) assess applicability four ML (bagging (BG), random subspace (RSS), tree (RT), forest (RF))...

Water availability for agricultural practices is dynamically influenced by climatic variables, particularly droughts. Consequently, the assessment of drought events directly related to strategic water management in sector. The application machine learning (ML) algorithms different scenarios variables a new approach that needs be evaluated. In this context, current research aims forecast short-term i.e., SPI-3 from predictors under historical (1901–2020) and future (2021–2100) employing...

Sodium hazard poses a critical threat to agricultural production globally and regionally which has been previously predicted from ground or surface water. Monitoring rainwater quality in this context is ignored but essential for water management central Europe. Our study focused predict sodium adsorption ratio (SAR) 1985 2021 ten ionic species of (pH, EC, Cl-, SO4−2, NO3-, NH4+, Na+, K+, Mg2+, Ca2+) employing four machine learning (random forest (RF), gaussian process regression (GU), random...

Flash floods are one of the most common and destructive natural hazards, recent flood events show their severe impact on Saudi Arabia. increasing year by in duration intensity, resulting huge impacts for nation concerned. Anticipating spatial patterns occurrence rainfall-induced is high demand. Recent technique-based studies comprehensive results aid understanding potential drainage basins minimizing risks a threat to humans economic damage. Jeddah City located at western coast Red Sea...

Artificial intelligence, specifically machine learning (ML), serves as a valuable tool for decision support in crop management under ongoing climate change. However, ML implementation to predict maize yield is still limited Central Europe, especially Hungary. In this context, we assessed the performance of four algorithms (Bagging (BG), Decision Table (DT), Random Forest (RF) and Neural Network-Multi Layer Perceptron (ANN-MLP)) predicting based on different input scenarios. The collected...

Global warming has resulted in increases the intensity, frequency, and duration of drought most land areas at regional global scales. Nevertheless, comprehensive understanding how water use efficiency (WUE), gross primary production (GPP), actual evapotranspiration (AET)-induced losses respond to exceptional whether responses are influenced by severity (DS) is still limited. Herein, we assess fluctuation standardized precipitation index (SPEI) over Middle East from 1982 2017 detect events...

Evaluating and predicting the occurrence spatial remarks of climate rainfall-related destructive hazards is a big challenge. Periodically, Sinai Peninsula suffering from natural risks that enthuse researchers to provide area more attention scientific investigation. Extracted information morpho-metric indices aids in understanding flood potentiality over various sizes drainage catchments. In this work, analysis has been used order model relative signals vulnerability 16 catchments northern...

Purpose Slope stability analysis is essential for ensuring the safe design of road embankments. While various conventional methods, such as finite element approach, are used to determine safety factor embankments, there ongoing interest in exploring potential machine learning techniques this purpose. Design/methodology/approach Within study context, outcomes ensemble models will be compared and benchmarked against predict parameter. Findings Generally, results have shown that proposed...

Quantitative analysis of LULC changes and their effects on carbon stock sequestration is important for mitigating climate change. Therefore, this study examines in relation to using the Land Change Modeler (LCM) Ecosystem Services (ESM) tropical dry deciduous forests West Bengal, India. The 2006, 2014, 2021 were classified Google Earth Engine (GEE), while predictions analyzed LCM. Carbon present future scenarios estimated ESM. highest was stored forest land (124.167 Mg/ha), storage outside...

Egypt is highly exposed to flash flood hazards, particularly in Sinai Peninsula and along the Red Sea coast, causing sudden huge damages constructions losses human lives during a very short time. This paper investigates dominant characterization of morphometrical features their relationships with hydrological behaviors an important strip western coast. The study focuses on analyzing October 2009 2019 storm events coastal area between EL-Qussier Marsa Alam order intiate preliminary risk...

Image semantic segmentation using deep learning algorithms plays a vital role in identifying different rock-forming minerals. In this paper, we employ the U-net model for its architecture that guarantees precise localization and efficient data utilization. We implement across two distinct datasets: (1) first dataset from ALEX Streckeisen website, (2) second Gabal Nikeiba area, South Eastern Desert of Egypt. Our exhibits excellent performance both datasets, with an average accuracy precision...

The rapid urbanization occurring globally has significantly intensified the challenges of waste management in densely populated metropolitan areas. A growing amount become a major concern for municipal authorities and local governments due to limited availability suitable land. Geospatial techniques, such as Geographic Information Systems (GISs) remote sensing, combined with machine learning, play crucial role identifying sites urban management. These techniques assist planners making...

A principal and independent component analysis (PCA ICA) a minimum noise fraction (MNFA) were applied in this study to Landsat 8 Operational Land Imager (OLI) images along the Adıyaman fault zone Eastern Turkey. These analyses indicated that lithologic units, patterns, morphological structural features can be mapped highly accurately by using spectral-matching techniques regions where rocks are well exposed. An inspection of all possible band combinations PCA 134 231 ICA 132 give best false...

Abstract The development of new techniques, such as machine learning (ML), can provide better insight into the processes and drivers soil erosion runoff. However, performance these techniques to assess in agricultural landscapes is poorly understood. aim this study was evaluate four algorithms, generalized linear model (GLM), Random Forest (RF), elastic net regression (EN) multiple adaptive splines (MARS), predicting runoff Syria. Soil were measured on three experimental plots (2.25 m × 1.50...

Against the backdrop of global climate change, frequency drought events is increasing, leading to significant impacts on human society and development. Therefore, it crucial study propagation patterns trends characteristics over a long-time scale. The main objective this delineate dynamics by examining their in China from 1951 2020. In study, precipitation data meteorological stations across mainland were used. A comprehensive dataset consisting 700 past 70 years was collected analyzed. To...

Neom city is a unique cross-border connecting Saudi Arabia, Jordan, and Egypt. Although of great critical importance for few hydrological, natural hazard, geomorphological studies have been undertaken on this region. This work aims to investigate the hydro-geomorphological characteristics assess flash flood hazards in by investigating several valuable morphometric parameters. The Shutter Radar Topography Mission (SRTM) digital elevation model hydrological geological data were analyzed study...

In the last few decades, agricultural drought (Ag.D) has seriously affected crop production and food security worldwide. Hungary, little research been carried out to assess impacts of climate change, particularly regarding droughts production, especially on regional scales. Thus, main aim this study was evaluate impact sunflower across Hungary. Drought data for Standardized Precipitation Index (SPI) Evapotranspiration (SPEI) were collected from CARBATCLIM database (1961–2010), whereas...

The inclusion of physiographic and atmospheric influences is critical for spatial modeling orographic precipitation in complex terrains. However, attempts to incorporate cloud cover frequency (CCF) data when interpolating are limited. CCF considers the rain shadow effect during interpolation avoid an overly strong relationship between elevation areas at equivalent altitudes across shadows. Conventional multivariate regression or geostatistical methods assume precipitation–explanatory...

Globally, countries are legitimizing actions to curtail the malevolent impacts of environmental degradation. This study examined interaction between CO2 emissions and selected economic variables within framework Saudi Arabia's Vision 2030. The Autoregressive distributed lag model (ARDL) was used analyze long-run relationships short-run dynamics studied (1970–2020). Mann-Kendall (MK) test revealed a significant (p < 0.05) positive increase GHGs from all sectors across KSA. highest increased...

The Abu-Dabbab area, located in the central part of Egyptian Eastern Desert, is an active seismic region where micro-earthquakes (≈ML &lt; 2.0) are recorded regularly. Earthquake epicenters concentrated along ENE–WSW trending pattern. In this study, we used morphological indexes, including valley floor width-to-valley height ratio (Vf), mountain front sinuosity (Smf), asymmetry factor index (Af), drainage basin shape (Bs), stream length–gradient (SL), hypsometric integral (Hi) water systems,...

Drought is one of the natural hazards that have negatively affected agricultural sector worldwide. The aims this study were to track drought characteristics (duration (DD), severity (DS), and frequency (DF)) in South Africa between 2002 2021 evaluate its impact on wheat production. Climate data collected from African Weather Service (SAWS) along with yield Department Agriculture, Forestry Fisheries (2002–2021). standard precipitation index (SPI) was calculated 3-, 6-, 9-, 12-month time...