Search

This study quantified uncertainties involved in assessing the future flood vulnerability in 33 urban areas with population exceeding designated thresholds in South Korea. The driver-pressure-state-impact-response (DPSIR) framework was utilized as the study procedure, integrating social, economic, and environmental factors. In addition, a total of 220 cases of combinations were examined, encompassing twenty general circulation models combined with shared socioeconomic pathway scenarios, five weight determination methods, and three multi-criteria decision-making (MCDM) techniques, as sources of inherent uncertainties in the process. The rankings of urban flood vulnerability (UFV) for the selected cities were comprehensively assessed considering all combinations, followed by an analysis of variance test to investigate contributing sources of uncertainties. As a result, Incheon and Busan were found to be vulnerable to flooding, while Yeongcheon and Andong appeared to be safe cities. Some cities exhibited wide ranges in their rankings, such as Daegu, Yangpyeon, and Jeongeup. The identified contributing sources were weighting (58%), MCDM (27%), and the combination of weighting and MCDM methods together (15%). This study revealed that weight determination methods and MCDM techniques are the primary sources of uncertainties in the assessment of future UFV instead of multiple GCMs and SSPs. This finding underscores the importance for decision-makers and stakeholders to carefully consider these uncertainties for sustainable flood risk management and prevention. [ABSTRACT FROM AUTHOR]

In this study, the uncertainty in runoff simulations using hydrological models was quantified based on the selection of five evaluation metrics and calibration data length. The calibration data length was considered to vary from 1 to 11 years, and runoff analysis was performed using a soil and water assessment tool (SWAT). SWAT parameter optimization was then performed using R-SWAT. The results show that the uncertainty was lower when using a calibration data length of five to seven years, with seven years achieving the lowest uncertainty. Runoff simulations using a calibration data length of more than seven years yielded higher uncertainty overall but lower uncertainty for extreme runoff simulations compared to parameters with less than five years of calibration data. Different uncertainty evaluation metrics show different levels of uncertainty, which means it is necessary to consider multiple evaluation metrics rather than relying on any one single metric. Among the evaluation metrics, the Nash–Sutcliffe model efficiency coefficient (NSE) and normalized root-mean-squared error (NRMSE) had large uncertainties at short calibration data lengths, whereas the Kling–Gupta efficiency (KGE) and Percent Bias (Pbias) had large uncertainties at long calibration data lengths. [ABSTRACT FROM AUTHOR]

Climate change has significantly increased human thermal stress, particularly in tropical regions, exacerbating associated risks and consequences, such as heat-related illnesses, decreased workability, and economic losses. Understanding the changes in human thermal stress and its drivers is crucial to identify adaptation measures. This study aims to assess various meteorological variables' spatial and seasonal impact on Wet Bulb Globe Temperature (WBGT), an indicator of human thermal stress, in Peninsular Malaysia. The Liljegren method is used to estimate WBGT using ERA5 hourly data from 1959 to the present. The trends in WBGT and its influencing factors are evaluated using a modified Mann-Kendall test to determine the region's primary driver of WBGT change. The results indicate that air temperature influences WBGT the most, accounting for nearly 60% of the variation. Solar radiation contributes between 20% and 30% in different seasons. Relative humidity, zenith, and wind speed have relatively lesser impacts, ranging from −5% to 20%. Air temperature has the highest influence in the northern areas (>60%) and the lowest in the coastal regions (40%). On the other hand, solar radiation has the highest influence in the southern areas (20–40%) and the least in the north. The study also reveals a significant annual increase in temperature across all seasons, ranging from 0.06 to 0.24 °C. This rapid temperature rise in the study area region has led to a substantial increase in WBGT. The higher increase in WBGT occurred in the coastal regions, particularly densely populated western coastal regions, indicating potential implications for public health. These findings provide valuable insights into the factors driving WBGT and emphasize the importance of considering air temperature as a key variable when assessing heat stress. [ABSTRACT FROM AUTHOR]

Changes in precipitation and temperature have crucial implications in the arid region due to their fragile environment. This study was an attempt to estimate possible spatiotemporal alteration of annual and seasonal precipitation and temperature in Iraq. Statistical downscaling of Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model (GCM) simulations for different shared socioeconomic pathways (SSP) was utilized. The GCMs were ranked according to their skills in simulating climate research unit (CRU) precipitation and temperature climatology along with their seasonality. Nonlocal model output statistics (MOS) models were implemented using a support vector machine (SVM) for downscaling and projection of selected GCM precipitation and temperature. Results revealed ACCESS‐CM2, BCC‐CSM2‐MR, GISS‐E2‐1‐G and MRI‐ESM2‐0 GCMs are most suitable for Iraq. The spatiotemporal changes in precipitation indicated a substantial decrease to north (up to −7.8%·mm−1) while an increase (around 3.0%) to south for different SSPs. Far future (2060–2099) showed both increase and decrease in precipitation than near future (2020–2059). The precipitation was projected to reduce in winter and increase in summer for all climate zones during both periods. The maximum temperature was projected to increase by 4.5°C to the north and 0.9–2°C to the south. In contrast, the minimum temperature was projected to rise by 1.0–3.5°C to both north and south. Both maximum and minimum temperatures may increase; however, more increases might be in winter and less in summer. The minimum temperature increase will be higher than the maximum temperature in the cold northern region and vice versa. Uncertainty in precipitation and temperature projections was higher for the far‐future period with higher SSPs than for the near‐future period with lower SSPs. The results of this study can guide the development of strategic policies for climate resiliency development in Iraq. [ABSTRACT FROM AUTHOR]

Climate change has caused a shift in aridity, particularly in the world's dry regions, affecting several sectors, predominantly the agricultural and water resources. This research examined the climate change effects on crop water demand (CWD) in Syria during 1951–2010. Given the lack of observed data, this analysis relied on Global Precipitation Climatology Center (GPCC) precipitation and Climatic Research Unit (CRU) temperature. Potential evapotranspiration (PET) at each grid was estimated using the Penman–Monteith model and the CWD using the FAO-56 method. The analysis revealed that CWD in Syria increased during 1981 − 2010 compared to that during 1951 − 1980. The increase in CWD was found for grapes, tobacco, barley, and cotton, whereas the maximum changes were during April and May. The most remarkable changes in CWD were for barley, between − 20 and 40 mm. It showed a decreased CWD in the south and a rise in the north (0 − 40 mm). The CWD for wheat showed a decline in most parts of the country, except in the north. The increase in CWD for barley and wheat caused an increase in agricultural water stress in the region. Agriculture planning needs to be developed according to the expected future climate changes to maintain the agricultural production in the region. [ABSTRACT FROM AUTHOR]

A major challenge in flood mapping using multi‐criteria decision analysis (MCDA) is the selection of the flood risk factors and the estimation of their relative importance. A novel MCDA method through the integration of two state‐of‐the‐art MCDA methods based on catastrophe and entropy theory is proposed for mapping flood risk in the Peninsular Malaysia, an area very susceptible to flooding events, is presented. A literature review was undertaken which identified the various socioeconomic, physical and environmental factors which can influence flood vulnerability and risk. A set of variables was selected using an importance index which was developed based on a questionnaire survey. Population density, percentage of vulnerable people, household income, local economy, percentage of foreign nationals, elevation and forest cover were all deemed highly relevant in mapping flood risk and determining the zones of maximum vulnerability. Spatial integration of factors using the proposed MCDA revealed that coastal regions are highly vulnerable to floods when compared to inland locations. Flood risk maps indicate that the northeastern coastal region of Malaysia is at greatest risk of flooding. The prediction capability of the integrated method was found to be 0.93, which suggests good accuracy of the proposed method in flood risk mapping. [ABSTRACT FROM AUTHOR]

Climate change is supposed to alter not only the mean and variability but also the distribution of rainfall. Changes in rainfall distribution during the monsoon months (June to September) of Bangladesh are evaluated in this study using quantile regression. Monthly rainfall data for the period 1961–2014 recorded at 18 locations distributed over the country were used for this purpose. Distributional changes of monthly rainfall showed downward convergent lines are dominant in peak monsoon months of June, July and August at 28%, 50% and 28% stations, respectively, followed by horizontally divergent lines at 17% of stations during those months. The dominating category of last monsoon month (September) rainfall was found upward divergent lines at 50% stations. The results revealed a decrease in many rainfall quantiles from June to August and increase in September in most of the stations. The increasing trend lines of September rainfall quantiles were found to become more diverse with time, which indicates an increase in rainfall extremes and the possibility of more floods which are already very common in the last month of monsoon in Bangladesh. The decrease in lower quantiles of rainfall in most of the monsoon months may cause an increase in the probability of droughts in the country. The study provided more insight on monsoon rainfall changes and improved understanding of climate change impacts on monsoon rainfall regime which can help in planning climate change adaptations in Bangladesh. [ABSTRACT FROM AUTHOR]

An approach is proposed in the present study to estimate the soil erosion in data-scarce Kokcha subbasin in Afghanistan. The Revised Universal Soil Loss Equation (RUSLE) model is used to estimate soil erosion. The satellite-based data are used to obtain the RUSLE factors. The results show that the slight (71.34%) and moderate (25.46%) erosion are dominated in the basin. In contrast, the high erosion (0.01%) is insignificant in the study area. The highest amount of erosion is observed in Rangeland (52.2%) followed by rainfed agriculture (15.1%) and barren land (9.8%) while a little or no erosion is found in areas with fruit trees, forest and shrubs, and irrigated agriculture land. The highest soil erosion was observed in summer (June–August) due to snow melting from high mountains. The spatial distribution of soil erosion revealed higher risk in foothills and degraded lands. It is expected that the methodology presented in this study for estimation of spatial and seasonal variability soil erosion in a remote mountainous river basin can be replicated in other similar regions for management of soil, agriculture, and water resources. [ABSTRACT FROM AUTHOR]

Expansion of arid lands due to climate change, particularly in water stressed regions of the world can have severe implications on the economy and people's livelihoods. The spatiotemporal trends in aridity, the shift of land from lower to higher arid classes and the effect of this shift on different land uses in Syria have been evaluated in this study for the period 1951–2010 using high-resolution monthly climate data of the Terrestrial Hydrology Research Group of Princeton University. The trends in rainfall, temperature and potential evapotranspiration were also evaluated to understand the causes of aridity shifts. The results revealed an expansion of aridity in Syria during 1951–1980 compared to 1981–2010. About 6.21% of semi-arid land was observed to shift to arid class and 5.91% dry-subhumid land to semi-arid land between the two periods. Analysis of results revealed that the decrease in rainfall is the major cause of increasing aridity in Syria. About 28.3% of agriculture land located in the north and the northwest was found to shift from humid to dry-subhumid or dry-subhumid to semi-arid. Analysis of results revealed that the shifting of drylands mostly occurred in the northern agricultural areas of Syria. The land productivity and irrigation needs can be severely affected by increasing aridity which may affect food security and the economy of the country. [ABSTRACT FROM AUTHOR]