 Subjects -> GEOGRAPHY (Total: 493 journals)
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- Evaluating the Effects of Climate Change on Thermal Bioclimatic Indices in
a Tropical Region Using Climate Projections from the Bias-Corrected CMIP6
Model-
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Abstract: Abstract As the global mean surface temperature continues to rise due to climate change, the impacts are not equally distributed worldwide, making regional assessments crucial. Bangladesh, a tropical monsoon region characterized by low-lying terrain, is particularly vulnerable to climate change effects. Yet, there has been a lack of analysis regarding potential shifts in thermal bioclimatic indicators (TBIs) in this region, a critical aspect of climate change adaptation. To address this gap, a study used a multimodel ensemble (MME) of 18 bias-corrected CMIP6 GCMs to project variations in 11 TBIs across Bangladesh for the near (2015–2044), mid (2045–2074), and far (2075–2100) futures under three SSPs: low (SSP126), medium (SSP245), and high (SSP585). By examining spatiotemporal changes in the ensemble mean, the study considered the base period (1985–2014) of each indicator for the respective future periods. The results of the study revealed that Bangladesh is likely to experience an increase in average annual temperature in the future, consistent with the global average. Depending on the SSP, the temperature rise could range from 0.62 to 1.85 °C for SSP126, 0.51–2.81 °C for SSP245, and 0.54–4.88 °C for SSP585. Furthermore, the study predicted a potential decrease in the diurnal temperature range (DTR) by − 0.17 to − 2.50 °C and a reduction of up to 30% in the ratio of mean diurnal temperature range to mean annual range. The projected temperature rise would vary significantly across regions, with the northeast and southeast experiencing increases between 0.14 and 0.39 °C, while the northwestern, central, and southwestern regions could see higher increases ranging from 0.17 to 2.66 °C. The study also highlighted a considerable increase in average temperature between the coldest and warmest quarters. Notably, the drier quarter would experience more substantial warming compared to the wettest quarter. These findings have important implications for climate change mitigation strategies in tropical monsoon regions like Bangladesh. Urgent action is needed to address the adverse consequences of global warming. Policymakers and stakeholders must understand these projected changes to implement measures that can reduce the impacts on agriculture, ecosystems, human health, and biodiversity. The study underscores the need to protect the well-being and sustainability of the nation in the face of a changing climate.
PubDate: 2023-11-27
- Trace Gases over Land and Ocean Surfaces of China: Hotspots, Trends, and
Source Contributions-
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Abstract: Abstract Trace gases in the atmosphere (NO2: nitrogen dioxide; SO2: sulfur dioxide) have a major impact on both local and global air quality, human health, climate and ecological conditions. Therefore, the present study investigated 16 years (2005– 2020) of Ozone Monitoring Instrument (OMI) based NO2 and SO2 in Dobson unit (DU) spatiotemporal distributions and variability, SO2/NO2 ratio, trends, and potential source contribution function (PSCF) across ocean and land areas of Jiangsu Province, China. Results demonstrated higher NO2 and SO2 concentrations (DU) over land (NO2: 0.58 and SO2: 0.56) than in the ocean (NO2: 0.30 and SO2: 0.38) due to more concentrated anthropogenic activities on land surfaces. There were significant seasonal variations in NO2 and SO2, with winter being the highest and summer being the lowest. The SO2/NO2 ratio shows land and ocean pollution is caused by NO2 and SO2 emissions from ships and industrial processes. Furthermore, OMI-based trace gases and anthropogenic emissions showed a good correlation (NO2 vs NOx = 0.626 and SO2 vs SO2 emission = 0.871) across land surfaces than the ocean (NO2 vs NOx = 0.366). NO2 and SO2 levels over land surfaces decreased significantly (at a 95% confidence level) compared to the ocean on annual and seasonal scales, which is attributed to a decrease in NOx and SO2 emissions. Furthermore, PSCF analysis shows that local sources have a greater impact on air quality than long-distance sources over land and ocean. It is concluded from this study that Chinese air pollution control policies achieved a satisfactory improvement in Jiangsu's air quality by reducing NO2 and SO2. It is therefore recommended to continue or extend these policies in the future to improve China’s air quality, which will benefits its citizens.
PubDate: 2023-11-16
- Statistical Models for Storm Genesis Simulations Considering Intensity
Variations in the Eastern North Pacific-
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Abstract: Abstract Storms are a type of severe weather event causing detrimental impacts on humans and the environment. Understanding the storm generation is essential for assessing storm activity and mitigating associated risks. This study aims to develop statistical models for predicting storm genesis in the Eastern North Pacific (ENP), considering intensity variations. Storm data were extracted from the International Best Track Archive for Climate Stewardship (IBTrAS) between 1971 and 2022. There are 16 parametric probability distributions used to fit recorded storm data. The most preferable ones will be determined through three criteria, comprising the Kolmogorov–Smirnov (KS) test, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The results revealed during the primary storm season (from July to September), storms originated below 15° N and proceeded westward or northwestward. Low-intensity storms (LIS) tended to form in a wide area 8° N–20° N, while medium-intensity storms (MIS) and high-intensity storms (HIS) generated in the south of 15° N. Furthermore, for LIS, the recorded storm number, and genesis longitude and latitude were found to be well fitted by the Poisson, Extreme value, and Gamma distributions, respectively. In terms of MIS, the Rician, Extreme value, and Loglogistic distributions were the best-fit to recorded storm number, and genesis longitude and latitude, respectively. Regarding HIS, the Generalized Pareto distribution matched well to storm number, while the Extreme value distribution was recommended to genesis longitude and Loglogistic distribution to latitude. 1000-Year Monte Carlo simulations demonstrated the consistency in spatial distributions of the recorded genesis and simulated ones in three cases (LIS, MIS, and HIS). The new approach for modeling storm genesis in this study can be applied to develop more accurate storm track models and may be deployed for other basins.
PubDate: 2023-11-13
- Examining the Accuracy of Using a Single Short-Term Historical Flow Period
to Assess the Nile’s Downstream Water Deficit from GERD Filling: A
Technical Note-
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Abstract: Abstract Increasing water and energy demands, hydroclimatic fluctuations, damming, and usage rights disputes present major challenges in managing transboundary rivers worldwide. Of particular interest is the Eastern Nile River Basin (ENRB), which is subject to broad debate over which modeling approach should be applied to resolve the disparities in transboundary water management among the river’s riparian nations, under increased upstream damming. Several studies have simulated the downstream High Aswan Dam (HAD) storage change during the Grand Ethiopian Renaissance Dam (GERD) filling under different hydrological conditions. However, their findings diverge regarding the impacts of GERD filling on HAD storage, especially when considering a specific, naturalized, historical 10-year period to represent the average flow condition used, as a benchmark for assessing potential downstream impacts. Our extended analysis of the Nile flow historical records demonstrates that considering a single historical 10-year period to simulate the downstream water budget, as performed in Wheeler et al. (Nat Commun 11:5222, 2020, https://doi.org/10.1038/s41467-020-19089-x), widely communicated to policymakers as a robust proof that GERD filling will not generate a deficit at HAD under average flow conditions, is inconclusive as it strongly depend on the selection of the historical inflow period, due to the river high interannual flow variability. Our simulation results of 20 average/near average historical flow periods in Wheeler et al. (Nat Commun 11:5222, 2020, https://doi.org/10.1038/s41467-020-19089-x)’s datasheet indicates that 60% of them generates a downstream water deficit ranging from 0.5 to 14.5 BCM under the same modeling conditions and filling policy. Therefore, considering the simulation results of multiple flow sequences is crucial for accurately reflecting the impact of the Nile’s high interannual flow variability on downstream water deficit assessments, thereby settling the disparities in transboundary water management forecasts for the impacts of GERD filling and operation.
PubDate: 2023-10-27
- A Multi-Tool 3D Conceptual Model to Elucidate Groundwater Processes,
Vulnerability, and Recharge Patterns in a Semi-Arid Region: A Case Study
from Morocco-
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Abstract: Abstract Under arid and semi-arid climatic conditions, groundwater is a basic resource to meet the requirements of socioeconomic development. Better conservation of this resource requires understanding the functioning of aquifer systems by informing about the degree of its vulnerability, the hydrochemical processes that control it, as well as the mode and origin of groundwater recharge. The location of vulnerable recharge areas is of crucial importance for the protection and rational management of groundwater, particularly in arid and semi-arid areas where a systematic monitoring and the master of pollution sources are lacking. In this context, this study aims to develop a 3D conceptual model of the Chiadma-South aquifer system (Essaouira basin, Morocco) based on hydrochemical, isotopic data and the DRASTIC model. The vulnerability and NO3− contents maps show that the upstream part and the downstream part of the study area are the most threatened by intrinsic pollution. The chemical characterization of the investigated aquifer shows that the mineralisation is governed by the dissolution of the surrounding formations, and evaporation phenomena and no seawater intrusion has been detected. The isotopic characterization of the input signal displayed that precipitation replenishing groundwater within the catchment have an Atlantic fingerprint, with the evaporation focused on the midstream part in the North and the upstream part in the South. However, visualisation of all highlighted processes under a 3D conceptual model could be a support for decision-makers to implement a rational management strategy for the vital resource of the study area.
PubDate: 2023-10-20
- Use of Spatial Variability of Soil Quality Index Models and Soil
Properties for Soil Quality Evaluation in the Irrigated Perimeter,
Semi-Arid Region of Morocco-
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Abstract: Abstract The aim of the current study was to assess the spatial variability of soil quality in a semi-arid area using an indexing approach based on soil parameters. A total of 1511 soil samples (0–30 cm) were collected in 2019 and analyzed for 20 soil properties. Four soil quality indexes (SQIs) were computed using Linear (L) and Non-Linear (NL) models through Additive (A) and Weighted (W) approaches. Principal component analysis (PCA) identified four principal components (PCs) with eigenvalues > 1, accounting for a total of 64.47% of the variance in the data. The total data set (TDS) was reduced by PCA, resulting in four soil parameters (Sand, Mn, EC, and Zn) as the independent minimum data set (MDS). IDW interpolation revealed an irregular distribution for each parameter individually, but the maps created based on SQI demonstrate that soil quality is generally low (SQI < 0.55) to moderate (0.55 < SQI < 0.7). The NL model shows the highest SQI values and sensitivity index, and the statistical results show that all the SQI models tested have strong relationships with crop yields and each other. However, W-NL shows the highest correlation (r = 0.306, p < 0.01). Thus, the weighted approach is the suitable method for evaluating soil quality in Moroccan semi-arid regions and aiding decision-making.
PubDate: 2023-09-26
- Climate of Syria Based on Cordex Simulations: Present and Future
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Abstract: Abstract Regional climate models are widely used to assess current and future impacts of climate change. In this study, we evaluate the performance of regional climate models from the Coordinated Regional Climate Downscaling Experiment programme integrated over the following three CORDEX domains: AFR, MNA and WAS. Four meteorological variables (temperature, precipitation, solar radiation and cloud cover) were evaluated over Syria at a grid spacing of 0.44°. The performance of five models in simulating the present climate characteristics (1989–2008) is evaluated with respect to the observations: CRU, ERA5 reanalysis and SARA and CLARA satellite data. We find that the mini-ensemble captures well the general spatial patterns and annual cycles of the selected variables. Anotheraim of this study was to assess the expected change of the mentioned four climate variables over Syria under the moderate emission scenario (RCP4.5) and the high emission scenario (RCP8.5) in the near future (2031–2050) and in the far future (2080–2099) with respect to the present climate (1989–2008). The simulations show a decreasing trend in cloud cover (between 6% and 10%) and precipitation (up to 9%) by mid and late century, regardless of the forcing scenarios. The simulations show a pronounced warming over Syria, which is expected to reach 6 °C by the end of the twenty-first century following the high greenhouse gas concentration scenario (RCP8.5). Furthermore, such an increase, combined with a decrease in precipitation, will shift Syria’s climate towards a more arid one.
PubDate: 2023-09-11
- Biostimulants in the Soil–Plant Interface: Agro-environmental
Implications—A Review-
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Abstract: Abstract Soil degradation is a global environmental problem that puts at risk food security. Improving soil health is, therefore, a major challenge for sustainable agriculture. Biostimulants are products consisting of microorganisms or substances that stimulate plant metabolism, enhance crop performance, and increase plant resistance to biotic and abiotic stresses. A viable approach to reducing chemical inputs is using biostimulants to ensure improved production yield and quality. Humic substances, seaweed extracts, hydrolysed proteins and amino acids, plant extracts, inorganic compounds, beneficial microorganisms, chitosan and other biopolymers are the major categories of biostimulants discussed in this review. Through various mechanisms, such as nutrient absorption enhancement, root growth stimulation, antioxidant activity, and soil structure improvement, these biostimulants have an impact on the interface between soils and plants. Apart from soil degradation, soil and water pollution due to high concentrations of potentially toxic elements (PTEs) is also an important issue. Phytoremediation has the potential to be an effective and environmentally friendly approach for soil remediation and regeneration. Biostimulants have shown encouraging results in the field of phytoremediation by increasing plant biomass, enhancing metal accumulation in plant tissues, as well as improving the overall efficacy of removing PTEs from contaminated soils. The specific mechanisms through which biostimulants contribute to phytoremediation include metal complexion, stabilization and transport to non-vital plant compartments. However, those agro-environmental beneficial effects of biostimulants on degraded soils have not been thoroughly reviewed to date. Therefore, the aim of this review was to present a comprehensive study concerning the use of biostimulants and their interaction in the soil–plant interface under different conditions. This review presents the state of the art about the agricultural and environmental applications of biostimulants to soils as a sustainable agronomic tool to improve soil health and ameliorate PTE contaminated soils.
PubDate: 2023-09-02
DOI: 10.1007/s41748-023-00349-x
- Impact of different land use and land cover in simulation of tropical
cyclones over Bay of Bengal-
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Abstract: Abstract This study presents an assessment on the impact of different Land Use/Land Cover datasets in simulating the movement and severity of three extremely severe cyclonic storms, namely Phailin (2013), Hudhud (2014) and Fani (2019), which developed over the Bay of Bengal (BoB). For this purpose, the Advanced Research Weather and Forecasting System (WRF) is selected and the model is forced with necessary input parameters. Two sets of numerical experiment are conducted. The first set of experiments uses U.S. Geological Survey Land Use/Land Cover datasets, and the WRF model is integrated with four different land surface parameterization schemes. The second set of experiments uses the Indian satellite IRS P6 AWiFS-derived Land Use/Land Cover obtained from the National Remote Sensing Centre (here after; AWiFS), and WRF model is integrated with four different land surface parameterization schemes. The model simulated track, mean sea-level pressure, wind, and rainfall are analysed and verified with available observation as obtained from India Meteorological Department and NASA Global Precipitation Measurement. The dynamics and thermodynamic structure are analysed in terms of model simulated vorticity and equivalent potential temperature during the landfall of the system. The results suggested that the use of AWiFS Land Use/Land Cover improves the simulation of track of all the cyclones during and after the landfall of the system. Also, it significantly reduces the landfall point error for all the land surface parameterization schemes except with thermal diffusion scheme. The AWiFS experiments could simulate both the spatial and station rainfall reasonably well. Also, it could simulate the intensity and thermodynamic structure of the cyclone reasonably well.
PubDate: 2023-08-09
DOI: 10.1007/s41748-023-00350-4
- Urbanisation and Geographical Signatures in Observed Air Temperature
Station Trends Over the Mediterranean and the Middle East–North Africa-
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Abstract: Abstract We update observed temperature trends in the Mediterranean and the Middle East–North Africa (MENA) region, assess their temporal and spatial features and investigate possible influences from urbanisation. Monthly mean temperature time-series of 370 stations are acquired from the CRUTEM4.6 and GSOD datasets and converted into suitable format for statistical analysis. The calculated annual and seasonal temperature linear trends for 1981–2020 indicate a strong warming with a MENA station average annual trend equal to \(0.36 ^\circ {\hbox {C}}\) /decade and a faster warming rate for spring ( \(0.43 ^\circ {\hbox {C}}\) /decade) and summer ( \(0.45 ^\circ {\hbox {C}}\) /decade). These trends are correlated with longitude, revealing faster warming rates over the eastern Mediterranean and Middle East. The stations are characterised as rural or urban centre with the use of the Global Human Settlement Model (GHS-SMOD) spatial grid that accounts for population, city size and shape for the year 2000. The trend derived for the urban centre stations is an annually averaged \(0.1 ^\circ {\hbox {C}}\) /decade greater than for the rural or all stations, and more prominent during summer and autumn. Hence a discernible, but small, urbanisation signature is revealed.
PubDate: 2023-07-01
DOI: 10.1007/s41748-023-00348-y
- Statistical Trend Analysis of Major Climatic Factors over Chhattisgarh
State, India-
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Abstract: Abstract Long-term changes in climatic variables have led to many past climatic disasters, and thus it is important to analyze the trends in the change of important climatic factors. For a better understanding of the climate of one of the Indian states, viz. Chhattisgarh, an exhaustive statistical trend analysis has been done on the major climatic factors such as rainfall, temperature, relative humidity, and potential evapotranspiration for the long-term records of the state. The non-parametric test popularly known as the Mann–Kendall (MK) trend test and Sen’s slope estimator for monthly, monsoon period, and annual data series are conducted in this study. Pettit’s homogeneity test and Standard Normal Homogeneity Test (SNHT) are conducted for change point detection. A regression analysis has also been done to validate the obtained results from Sen’s slope. The significance of the increasing and decreasing trends of the considered climatic factors is assessed based on the p-value. The results showed a decreasing trend in the annual rainfall and 1961 was detected as the change point year in the rainfall data. The negative slope obtained from the regression analysis indicated a downward trend in annual rainfall similar to Sen’s slope. The results showed a negative (downward) trend in rainfall for most of the months except for January, March, April, and September where an increasing (positive) trend is obtained while the trend in the month of July and the monsoon season is significantly decreasing as the obtained p-value is less than α (5% significance level i.e., 0.05). The temperature data analysis showed an increasing trend for most of the months except for January, May, and June while the months of September, October, and November and annual temperature are significantly increasing in the state of Chhattisgarh. The annual relative humidity data has a significantly increasing trend also, the increasing trend is found in all the months but is insignificant. The annual potential evapotranspiration data showed an increasing trend but the trend is insignificant. There is a positive (increasing) trend for all the months, with September, October, and November having a significant trend, while the months of January, May, and June have decreasing trend. The data of temperature, relative humidity, and potential evapotranspiration were found to be homogeneous by the Pettitt test and SNHT. The results of Sen’s slope were found in agreement with linear regression for all the data series. These trend assessments of major climatic factors may help policymakers in managing water resources projects for various purposes by speculating the possible future climatic conditions and improving our capacity to respond to natural calamities in the state.
PubDate: 2023-06-29
DOI: 10.1007/s41748-023-00345-1
- The ENSO Fingerprint on Bangladesh Summer Monsoon Rainfall
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Abstract: Abstract In South Asia (SA), the boreal summer monsoon (June to September; JJAS) and the El Niño-Southern Oscillation (ENSO) are connected, though different areas in SA respond differently to ENSO. In this paper, a new 41-year (1981 to 2021) high-resolution gridded rainfall dataset (ENACTS-BMD; Enhancing National Climate Services for Bangladesh Meteorological Department) is used to investigate the linkage between the Bangladesh Summer Monsoon Rainfall (BSMR) and ENSO. Observed BSMR shows a weak positive correlation (r = + 0.21, not statistically significant at the 5% level) with sea surface temperatures (SST) in the central-eastern (Niño3.4) Pacific region. Among the eight El Niño events, seven of them corresponded to above-normal BSMR. However, during the 11 La Niña events, the relationship was more varied, with above-normal BSMR occurring in seven instances. These findings highlight an asymmetric relationship between BSMR and ENSO. Furthermore, BSMR is negatively correlated (r = − 0.47 statistically significant at the 5% level) with Indian Summer Monsoon Rainfall (ISMR: 75°–85oE, 18°–30oN). The potential physical mechanism can be outlined as follows: during El Niño, the Walker circulation tends to be weakened, resulting in a weakening of the summer monsoon circulation, which in turn reduces the intensity of easterly winds along the Bangladesh Himalayan foothills. Subsequently, a lower-level anomalous cyclonic circulation is established, facilitating the convergence of moisture within the boundary layer. This, in turn, leads to intensified rainfall over Bangladesh and the surrounding regions during El Niño. Seasonal forecast models do not adequately capture BSMR and ENSO, BSMR and circulation, and BSMR and ISMR inverse correlations. While the observed BSMR-ENSO relationship is complex and teleconnections are weak, awareness of the inverse relationship with ISMR and the incorrect model behavior could be useful in the context of seasonal BSMR predictions.
PubDate: 2023-06-13
DOI: 10.1007/s41748-023-00347-z
- SBAS-InSAR/GNSS Surface Deformation Assessment in Arid Environments of
Najran, Saudi Arabia-
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Abstract: Abstract Multiple surface fissures were reported over the last few years within the Najran valley, southern Saudi Arabia. The earth fissures have been observed mainly in the vicinity of agricultural territories. This study maps the surface deformation of Najran valley using geodetic data and investigates the underlying mechanisms. Indeed, we use Interferometric Synthetic Aperture Radar (InSAR) technique with standard Sentinel-1 Geocoded UNWrapped interferogram (GUNW) products acquisition from 2016 to 2022 and processed by Advanced Rapid Imaging and Analysis (ARIA) project using InSAR Scientific Computing Environment (ISCE). We generate displacement time series using the Miami INsar Time series software in Python language (MintPy). The result shows a rate of subsidence within the Najran valley ranging between 0.2 and 0.6 cm/yr. We processed the Najran GNSS station with time series extended from 2017 to 2022 to validate the observed displacement field. We analyze groundwater variation and soil properties to interpret the results. This assessment verifies that the potential drivers of subsidence might be due to an excessive withdrawal of groundwater, with the potential contribution of other factors related to the sequence of drought and moisture in the soil layer. The presence of a fine-grained layer of soil (clay) suggests a potential impact on the observed deformation. The observed signal and potential underlying mechanism represent one of the classical problems in arid regions worldwide, our investigation is crucial to improve the environmental assessment of Najran valley, which may mitigate any potential future hazards.
PubDate: 2023-06-05
DOI: 10.1007/s41748-023-00346-0
- Correction to: Spatio‑temporal Change of Glacier Surging and
Glacier‑dammed Lake Formation in Karakoram Pakistan-
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PubDate: 2023-06-01
DOI: 10.1007/s41748-021-00281-y
- Correction to: Dynamics and Characterization of Aeolian Dust Deposition
from a Burned Shrubland at Chubut Coastal Patagonia in Argentina-
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PubDate: 2023-06-01
DOI: 10.1007/s41748-022-00299-w
- Correction to: A Review of the Neoproterozoic Global Glaciations and a
Biotic Cause of Them-
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PubDate: 2023-06-01
DOI: 10.1007/s41748-022-00316-y
- Correction to: Bioplastic from Renewable Biomass: A Facile Solution for a
Greener Environment-
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PubDate: 2023-06-01
DOI: 10.1007/s41748-021-00280-z
- Analysis of Precipitation and Temperature Trends Under the Impact of
Climate Change Over Ten Districts of Jimma Zone, Ethiopia-
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Abstract: Abstract This study aimed to investigates the precipitation and temperature trends over ten districts of Jimma zone in the twenty-first century using observed and model simulation data sets. The precipitation and temperature trends are analyzed for the reference (1981–2010) and two future periods, namely, mid-century (2031–2060), and end-century (2071–2100) using Innovative Trend Analysis. For future period, we analyzed the ensemble mean of precipitation and temperature based on data from four high resolution models, namely, High-Resolution Hamburg Climate Model 5, Regional Atmospheric Climate Model (RACMO22T), Climate Limited-Area Modeling Community (CCLM4), and the Rossby Centre Regional Atmospheric Model (RCA4). Based on the analysis, the annual, summer and autumn rainfall trend during the reference period are − 4.079 mm/year, 2.147 mm/year, and − 1.639 mm/year, respectively. The winter rainfall reveals a negative trend (− 0.135 mm/year) during the reference period. However, the winter rainfall shows a positive trend (0.465 mm/year and 0.067 mm/year) towards the end-century period under RCP4.5 and RCP8.5 scenarios. On the contrary, the autumn rainfall showed consistent decreasing trend during the two future periods. The maximum increasing trend (1.376 mm/year) in annual rainfall was obtained during the mid-century period under RCP4.5 scenario, whereas the maximum annual decreasing rainfall trend was obtained during the mid-century period under RCP8.5 scenario (− 0.649 mm/year). The minimum temperature showed significant increasing trend throughout the study periods. However, the maximum temperature showed decreasing trend during annual and winter in the mid-century period under RCP4.5 and RCP8.5 scenarios. The highest increasing trend of the minimum temperature was during winter and autumn, while the highest increasing trend of the maximum temperature was during the summer and autumn seasons. The result further indicate that the minimum temperature increment was faster as compared to the maximum temperature. The study can be used as a first-hand information to develop efficient adaptation policies and mitigation measures that aids to combat the adverse impact of climate change.
PubDate: 2023-06-01
DOI: 10.1007/s41748-022-00322-0
- Land Surface Temperature Relationship with the Land Use/Land Cover Indices
Leading to Thermal Field Variation in the Turkish Republic of Northern
Cyprus-
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Abstract: Abstract The increase in the Land Surface Temperature (LST) caused by global warming and extreme weather events is significantly increasing Urban Hot Spots (UHS) while impacting the environmental quality within urban areas. In this research, with the help of Landsat 5, 7, and 8 satellite images, the evolution of Land Use/Cover (LULC), LST, and Surface Urban Heat Island (SUHI) in the Turkish Republic of Northern Cyprus (TRNC) between the years 1985 and 2020 is examined. The main aim is to evaluate how these variables, together with the Normalized Difference Built-up Index (NDBI), Urban Index (UI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Built Index, and Proportion Vegetation (PV) have influenced the variability of the UHS and the level of thermal comfort according to the Thermal Field Variance Index (UTFVI). The results report significant average rises of the variables: LST (6.62 °C), SUHI (0.97 °C), UHS (8.61%) of the UI and NDBI indices and class 6 of UTFVI (88.53%) that are related to the variability of the LULC corroborated by statistical analysis. Our results provide valuable information on the future development of urban areas in Northern Cyprus to make them more resilient and sustainable to rising temperatures.
PubDate: 2023-03-23
DOI: 10.1007/s41748-023-00341-5
- Land Use Land Cover Change and Related Drivers have Livelihood
Consequences in Coastal Bangladesh-
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Abstract: Abstract Land Use Land Cover (LULC) changes differ based on geographic position, while different kinds of natural and physical components accelerate the changes along with impacts on surroundings and demographic background. Bangladesh has been experiencing significant changes in landscape settings, facilitating changes in people’s livelihoods. To understand the changing pattern of livelihood in coastal areas of Bangladesh, it is crucial to detect the LULC changes, including the influence of related drivers. Following the background, this study was conducted in Batiaghata Upazila of Khulna district to assess the LULC changes using RS and GIS techniques over 30 years (1990–2019). With the help of 15 key informant interviews and 2 focus group discussions, this study delves into the driving forces behind the ever-evolving changes in LULC. From the impact on the livelihood patterns of different groups of people, this study uncovers the mysteries behind these changes. Findings unveiled a tale of transformation in the study area. As the years passed, there was a decline in agriculture (7.6%) and fallow land (15.66%), and a surge in water bodies (20.68%) from 1990 to 2019. These significant changes in land use paint a picture of an ever-evolving landscape. From the devastating effects of natural disasters to the pursuit of profit and the drive for industrial advancement, a multitude of drivers are fueling the changes in land use. As literacy rates rise and temperatures fluctuate, the landscape is undergoing a transformation driven by these powerful forces. The ripple effects of LULC changes can be felt throughout the community, leaving a wake of disrupted livelihoods in its path. As opportunities narrow and marginalized groups feel the squeeze, it's crucial for stakeholders to act. By examining the changes in LULC and livelihoods aims to pave the way for a more sustainable future in coastal Bangladesh.
PubDate: 2023-02-11
DOI: 10.1007/s41748-023-00339-z
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