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 Earth Systems and EnvironmentNumber of Followers: 3      Hybrid journal (It can contain Open Access articles) ISSN (Print) 2509-9426 - ISSN (Online) 2509-9434 Published by Springer-Verlag  [2469 journals]
• Cost–Benefit Analysis of Climate Change Mitigation Measures in the
Forestry Sector of Peninsular Malaysia

Abstract: Abstract Greenhouse gases (GHGs) have been increasingly dominated by carbon dioxide (CO2) with its negative effects on the global climatic system. Malaysia has forest land around 67% of the total land area which helps to mitigate climate change by absorbing atmospheric CO2 and enhancing the national carbon sink. However, there is a lack of study on the cost-effectiveness of potential mitigation measures in the forestry sector of Malaysia (e.g., forest conservation, afforestation, natural regeneration). Therefore, this article attempts to do a cost–benefit analysis (CBA) of the potential mitigation measures for 25, 50 and 75 years by considering the discount rate of 0% and 3%. The costs considered for the CBA include the establishment and maintenance cost of the mitigation measures. The CBA considered benefits associated with carbon sequestration, timber production, forest revenue, biodiversity, and other forest ecosystem services. A meta-analysis has been conducted to evaluate the carbon density in Malaysian forests, which has been used to assess the forest carbon sequestrated by each mitigation measures. This study found that the forestry sector of Malaysia has a huge potential to mitigate climate change whereas natural regeneration is the most cost-effective mitigation measure followed by forest conservation and afforestation. The outcome of this research would be useful for forest management planning to mitigate climate change in a cost-effective way. This study could encourage other countries to identify and implement the most cost-effective measure to mitigate climate change by achieving maximum carbon sink with minimum cost.
PubDate: 2022-06-01

• Spatial Pattern and Land Surface Features Associated with Cloud-to-Ground
Lightning in Bangladesh: An Exploratory Study

Abstract: Abstract Severe weather events such as lightning appear to be a significant threat to humans and property in South Asia, an area known for intense convective activity directly related to the tropical climate of these areas. The current study was conducted in Bangladesh and examined the association between cloud-to-ground (CG) lightning and ground surface properties, with the aim of improving existing knowledge regarding this phenomenon. GLD360 data from 2015 to 2020 were used to describe the seasonal lightning climatology. Elevation, land use and land cover, vegetation and surface heat flux data were used to examine all land surface features possibly associated with CG lightning occurrence. Hot and cold spot spatial patterning was calculated using local indicators of spatial association. Results indicated a strong CG lightning seasonality. CG stroke density varied considerably across seasons with the pre-monsoon exhibiting the highest density. This was followed by occurrences in the monsoon season. The March–June period experienced 73% of the total observed. Elevation appeared to influence the post-monsoon CG stroke, however, its role in the other seasons was more difficult to define. The land cover/lightning index indicated that waterbodies and herbaceous wetlands had more influence than other land cover types, both during the day and at night, and it appeared that latent heat flux played a major role. The CG stroke hot and cold spot locations varied diurnally. The findings suggest that large-scale irrigation practices, especially during the pre-monsoon months, can influence the observed spatiotemporal pattern. The production of hotspot maps could be an initial step in the development of a reliable lightning monitoring system and play a part in increasing public awareness of this issue.
PubDate: 2022-06-01

• Dynamics and Characterization of Aeolian Dust Deposition from a Burned
Shrubland at Chubut Coastal Patagonia in Argentina

Abstract: Abstract The aim of this work is to evaluate the dynamics of dust deposition and characterize its elemental composition in case study at Chubut coastal Patagonia in Argentina after a shrubland fire. On 22 December 2016, a fire took place (42°20′ S–65° W) covering ~ 30 thousand hectares (300 km2) of shrublands. Immediately after the fire (2 January 2017), monthly deposition of dust was recorded using passive collectors in burned and control regions until December 2017. The dust plume of the burned region, visible from MODIS imagery, reached more than 150 km from the coast toward the marine area. In the burned region, dust deposition rates peaked in February (84.75 mg/day m−2), decreased until May (mean value = 12 mg/day m−2), and afterward remained constant (mean value = 10 mg/day m−2) above background level during the studied period. In the control region, dust deposition was constant and significantly lower (mean value = 0.19 mg/day m−2). Overall, the dust elemental composition was mainly Si and O corresponding to silicate minerals. Material from the burned region presented peaks of C. On the other hand, C signals were not present in the dust from the control region. The presence of C, suggests a direct consequence of the burned vegetation. The burned region may become a significant source of dust due to the reduced vegetation coverage, and may constitute an additional input of C into the marine ecosystem. The present study is the first report that provides insights that a burned region in Patagonia may act as a dust source.
PubDate: 2022-06-01

• Assessment of Land Degradation in Northern Oman Using Geospatial
Techniques

Abstract: Abstract The northern coast of Oman (Al-Batinah plain), hosts the major population and irrigated agriculture of the country. Recently, it has experienced considerable land degradation, revealed by an inland shifting of cultivation. The main objective of this study was to assess the magnitude of land degradation in the past 2 decades (2001–2019) using the integration of remote sensing and geographical information system (GIS). The study relied on multi-temporal normalized difference vegetation index (NDVI), land surface temperature (LST), and surface albedo data linked with in situ groundwater salinity measurements. The degree of land degradation was determined by applying the geospatial weighted overlay analysis (WOA) combining both space-based and in situ data. Results showed that degraded lands account for almost 70% of the coastal zone, with 18.6% under severe degradation. Major degradation occurred at Barka and Shinas regions synchronized by significant groundwater salinization. Results of this study assert on the significance of geospatial modeling for mapping land degradation in arid regions.
PubDate: 2022-06-01

• Impacts of Land-Use/Land-Cover Changes on Water-Borne Soil Erosion Using
Geospatial Technologies and RUSLE Model over Chimbel Watershed of Upper
Blue Nile Basin in Ethiopia

Abstract: Abstract Land degradation in the form of soil erosion is one of the major environmental problems in the highlands of Ethiopia. This research was aimed to estimate the effects of changes in land use/land cover (LULC) on water-borne soil erosion in the Chimbel watershed of the Upper Blue Nile Basin, Ethiopia. The spatial and temporal LULC changes were analyzed using Landsat 5 TM 1989 and Landsat 8 OLI-TIRS 2019 images following a supervised classification technique with the Maximum-Likelihood Classification (MLC) algorithm. Soil erosion was estimated using the Revised Universal Soil Loss Equation (RUSLE) model. The result reveals that cultivated land and built-up area increased by 11.3 and 7%, respectively, while grassland (6.9%), forest (6.4%), bush/shrubland (4.9%), and water body (0.2%) were reduced between 1989 and 2019 periods. Consequently, the mean soil erosion rates estimated from the entire watershed were 24.0 t ha–1 year–1 in 1989 and 28.3 t ha–1 year–1in 2019, which are higher than the tolerable soil loss (1–6 t ha–1 year–1) and soil formation (10–14 t ha–1 year–1) rates of the study region. Hence, applying a land management intervention to reverse the trend of LULC changes and thereafter its soil erosion is suggested for environmental improvement of the region.
PubDate: 2022-06-01

• Landscape Changes in the Semi-closed Raya Agricultural Graben Floor of
Northern Ethiopia

Abstract: Abstract Over the last few decades, the need for landscape monitoring and assessment of changes in spatial patterns over time has grown. Landscapes sustain changes of various aspects, such as their structure, in response to continuous modifications in land cover, land management regimes and policy decisions. This study investigates changes in the landscape structure along the Raya graben bottom in northern Ethiopia from 1986 to 2017. Landsat imageries were used to analyse land cover. The spatial structure of the landscape for 3 decades was evaluated using FRAGSTATS. The number of patches increased at the class and landscape levels. At the landscape level, the patches totalled 8,147 in 1986 and increased to 886,893 in 2017. Similarly, the patch density (PD) in 1986 was 3.4 and reached 372.7 in 2017. Therefore, high landscape fragmentation occurred within the study area. The value of the Shannon diversity index is close to 1.1, and the diversity of patch types within the landscape is regular. The Shannon Evenness Index value ranges from 0.6 to 0.7. Moreover, the diversity of patches has shown an increment across the study period. Each land cover reduces in size and proximity. Those changes were caused by population size, infrastructural development and commercial agriculture. Thus, proper land use planning must be practiced to reduce fragmentation and environmental impacts in landscapes that face increasing population pressure and continuous land cover changes.
PubDate: 2022-06-01

• Assessing the Status of Glaciers in Upper Jhelum Basin of Kashmir
Himalayas Using Multi-temporal Satellite Data

Abstract: Abstract Climate change, a global challenge of our time has severely impacted mountain glaciers. This study presents a detailed and an updated glacier inventory of 2020 for the Upper Jhelum Basin (UJB), Kashmir Himalayas using Sentinel-2 data and documents 308 glaciers. The glaciers range in size from 0.01 to 10.51 km2 and cover an area of 102.1 km2. All glaciers are located in the elevation zone between 3500 and 5000 masl. About 86% of glaciers are small in size (< 0.5 km2) and constitute 38.7% of total ice cover. However, glaciers with size greater than 0.5 km2 are only 14% but constitute a major proportion 61.3% of glacier area. Majority of small glaciers are a result of defragmentation of larger ones, hence more vulnerable to melting. Multi-date satellite images were used to assess glacier fluctuations of selected glaciers ( $$\ge$$ 0.3) for the period 1990–2020. The total glacier area has reduced from 85.25 to 68.17 km2 (20%) at the rate of 0.56 km2 a−1. Glaciers in the lower elevation zone (3800–4200 masl) have lost about 35% of their area at the rate of 0.22 km2 a−1. The analysis of meteorological data using Thel–Sen method and Mann–Kendall test before examining its impact on glacier mass loss reveals that a persistent warming trend in mean annual temperatures is observed over the region. This is strictly under the influence of global climate change having a potential to cause enhanced shrinking and thinning of glaciers in the study region.
PubDate: 2022-06-01

• Rainfall Frequency Analysis Using Assessed and Corrected Satellite
Precipitation Products in Moroccan Arid Areas. The Case of Tensift
Watershed

Abstract: Abstract In this study, we apply statistical approaches based on frequency analysis and Artificial Neural Networks to map the 100-year monthly precipitation in a Moroccan watershed. This was accomplished by using assessed and corrected satellite-based rainfall products. A network of 10 rain gauges and six statistical validation criteria was used to compare in situ measurements and monthly rainfall estimates from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) product for the rainy season (from November to April). Results indicate a fairly good agreement between the two data sources, with high correlation coefficients (> 0.5) for all months and low bias values (< 17%) especially for November, January, February and April. To correct the bias, we used an ANN model, with station coordinates and the monthly CHIRPS precipitation as input. The precipitation estimated by the ANN model was then compared with ground-based measurements. This simulation of monthly precipitation seems better, with significant Nash criteria and Pearson correlation coefficients (0.83–0.9). We then used this model to correct the CHIRPS gross precipitation and to perform a frequency analysis using spatial patterns of corrected rainfall. The results show that mountainous areas are conducive to high monthly precipitation amounts. These areas contrast with a potentially arid plain. This observation requires water supply plans which would consist of water transfers from surplus areas to deficit ones.
PubDate: 2022-06-01

• Multivariate Modeling of Some Metals Concentrations in Agrarian Soils:
Distribution and Soil Fertility Implications in the Tropics

Abstract: Abstract Predicting metals concentration in agricultural soils is a sine qua non in establishing environmental policies and evaluating the soils’ agricultural potentials in an area. The relevance of metals to ecological health, agriculture and pollution has sprung a lot of related studies. This study was setup to determine the concentration and profile distribution of aqua regia (AR) extractable Fe, Al, Mn, Mg and K in agricultural soils, and to predict AR extracted elements via Al2O3 (Alx), K2O (Kx), physical and chemical properties for soil fertility interpretations. One soil pit was randomly sited in each slope transition obtained via digital elevation models (DEM), resulting in 27 composite soil samples. Soil samples meant for AR and X-ray florescence were analyzed in triplicate. The soils were dominated by AR extractable Fe with mean concentrations showing the trend; Fea > Ala > Mga > Mna ≈ Ka and ranges of 639.09–125,719.46, 1252.63–14,895.13, 67.61–2408.36, 4.51–2162.91 and 161.84–1356.23 mg/kg, respectively. The distribution of AR metals in the entire soils was quite similar, however, higher values of soluble Fe occurred in the 0–37 cm depth of IH1P1. Multiple linear regression functions were within acceptable and best prediction criteria (R2 = 0.55–0.77). The best performing models were Ka and Mna, with lower errors. The models selected Kx, Mg and CEC which contributed 89.9, 79.9 and 73.4%, respectively to the 44.2% contribution of PC1 to data variation. The dominance of Kx and Alx with ranges of 2381.0–50,401.0 and 57,766.67–119,433.35 mg/kg, respectively, over Ka and Ala is due to limitations associated with AR extraction of elements in silicate minerals, hence the necessity for extracting soil mineral elements by more than one method.
PubDate: 2022-06-01

• Skill of the Saudi-KAU CGCM in Forecasting ENSO and its Comparison with
NMME and C3S Models

Abstract: Abstract This paper assesses the skill of the Saudi-King Abdulaziz University coupled ocean–atmosphere Global Climate Model, namely Saudi-KAU CGCM, in forecasting the El Niño-Southern Oscillation (ENSO)-related sea surface temperature. The model performance is evaluated based on a reforecast of 38 years from 1982 to 2019, with 20 ensemble members of 12-month integrations. The analysis is executed on ensemble mean data separately for boreal winter (December to February: DJF), spring (March to May: MAM), summer (June to August: JJA), and autumn (September to November: SON) seasons. It is found that the Saudi-KAU model mimics the observed climatological pattern and variability of the SST in the tropical Pacific region. A cold bias of about 0.5–1.0 °C is noted in the ENSO region during all seasons at 1-month lead times. A statistically significant positive correlation coefficient is observed for the predicted SST anomalies in the tropical Pacific Ocean that lasts out to 6 months. Across varying times of the year and lead times, the model shows higher skill for autumn and winter target seasons than for spring or summer ones. The skill of the Saudi-KAU model in predicting Niño 3.4 index is comparable to that of state-of-the-art models available in the Copernicus Climate Change Service (C3S) and North American Multi-Model Ensemble (NMME) projects. The ENSO skill demonstrated in this study is potentially useful for regional climate services providing early warning for precipitation and temperature variations on sub-seasonal to seasonal time scales.
PubDate: 2022-04-29

• Assessment of Potentially Toxic Metals from Mine Tailings and Waste Rocks
Around Mining Areas of Oshiri-Ishiagu Region, Southeastern Nigeria

Abstract: Abstract Potentially toxic metals concentration and pollution in mining areas have become a major environmental concern. Predicting the toxic metals (Pb, Cd, Ni, Co, Zn, Mn, Fe, and Cu) in waste rocks and mine tailings in the study area is important in establishing environmental policies and potential pollution sources. The mine tailings and waste-rock samples were geochemically analyzed using Atomic Absorption Spectrophotometer to identify distribution of the potentially toxic metal concentrations (in mg/kg). Data obtained were standardized and assessed using risk factors namely; index of geoaccumulation, contamination, and enrichment factors to define parameters that caused the toxic metal partitions in mine tailings and waste rocks. Geochemical evaluation indicates the potentially toxic metals concentrations in the following trends: Mn > Zn > Cu > Pb > Co > Ni and Zn > Mn > Fe > Pb > Cu > Co for waste rocks and mine tailings, respectively. Results of the analysis show that Co, Cu, Mn, and Ni have values of the index of geoaccumulation (Igeo) ranging from unpolluted to moderate pollution levels in waste rocks and mine tailings; indicating insignificant contribution to contamination in the area. The index of geoaccumulation for Fe in mine tailings which ranges from 1.94 to 2.04 indicates moderate to strong pollution in tailings but devoid of significant pollution in waste rocks with values less than 0.14. However, Cd recorded the highest pollution level with maximum Igeo values of 6.81 in waste rocks and 3.83 in mine tailings. Meanwhile, some mine sites have values of pollution load index (PLI) less than 1; indicating areas around the mine province that are still unpolluted. Notwithstanding, enrichment in most of the environments produced conduits through which natural biospheric sources, such as air, water, and soil, could deteriorate. The outcome of this study would, therefore, establish a database for future environmental risk assessment of the region.
PubDate: 2022-04-05

• Spatial and Temporal Isotopic and Hydrochemical Characteristics of
Groundwater and Surface Water in the Tuul River Basin, Mongolia

Abstract: Abstract Hydrochemistry and stable isotope tracing approaches were applied to groundwater and surface waters (rivers, springs, stormwater drainage canals, and treated wastewater discharges) to study the spatiotemporal geochemical and stable isotope characteristics and their interactions. The analysis revealed spatiotemporal variations and interactions between groundwater and surface water. Ca-HCO3-type water dominated the study area; representing 70.7%, (summer) and 81% (winter) of the samples. The chemical and isotopic values presented some spatial differences but minimal temporal changes, except in Tuul River water downstream of Ulaanbaatar. The Tuul River was mostly characterized as Ca-HCO3-type water, but varied temporally and spatially, shifting to Ca-Na-HCO3-type water in summer and Na-Ca-HCO3-type in winter in the downstream region after wastewater discharge. Also, electrical conductivity (EC) values of Tuul River are increasing gradually with distance, and more than double in concentration after mixing with treated wastewater discharges and stormwater drainage canals, providing clear evidence of anthropogenic impacts. The similarity in the stable isotopes and chemical characteristics of floodplain groundwater and river water suggest that local recharge of the alluvial groundwater with Tuul River water, whereas distant groundwater quality exhibited higher levels of minerals and stable isotopes. Cluster analysis clearly indicated a connection between floodplain groundwater and river water, and also the effect of anthropogenic discharges associated with stormwater and treated wastewater discharges. The analysis results also show that cluster analysis is a useful approach for optimizing future spatial sampling strategies, and offers a reliable classification of sampling stations in the region, especially along Tuul River.
PubDate: 2022-03-29

• Assessment of Common Anion and Cation Contaminants in Surface Waterbodies
in Statesboro, Georgia, USA

Abstract: Abstract Water pollution is a growing environmental concern in southeastern Georgia. This environmental quality assessment study was conducted at the Georgia Southern University (GSU) campus in Statesboro, Georgia with the objectives of analyzing the surface water quality for common urban contaminants and identifying their sources. The campus was divided into five zones (North, East-Central, East, West-Central, and South-West) and water was collected monthly from 50 different sites (ponds, drainage ditches, creeks) for a 10-month period during the 2014–2015 school year. Twelve contaminants, including six inorganic anions (bromide, chloride, fluoride, nitrate, phosphate, and sulfate) and six metal cations (boron, copper, iron, magnesium, potassium, and zinc) were tested using ion chromatography (IC) and inductively coupled plasma-mass spectrometry (ICP-MS). The contaminant levels in the water were compared to the US Environmental Protection Agency (USEPA) and the World Health Organization (WHO) standard guidelines for water quality assessment. Results showed that the mean campus contaminant levels of eleven out of twelve contaminants were well within the regulated limits, which indicate a healthy aquatic environmental quality at the GSU Statesboro campus. The aquatic concentrations for most of the contaminants varied significantly among different parts of the campus. The South-West zone and East zone showed the highest and lowest contaminant levels, respectively. The agricultural chemicals (fertilizers, herbicides, pesticides) used on campus for landscape management were identified as key sources of pollution followed by the discharges from campus automobiles (motor oil, brake lining, tire wearing), and recycled waterlines. Contaminant concentrations also varied seasonally, with summer months and January being higher and mid-late spring being lower. The seasonal variation was influenced by the rainfall pattern, chemical application timing, and algal growth. The findings of this study will also be helpful for future surface water pollution studies, especially in managed urban landscapes.
PubDate: 2022-03-25

• Perceived Human-Induced Causes of Landslide in Chattogram Metropolitan

Abstract: Abstract This study investigates Land Use Land Cover changes in the Chattogram metropolitan area, the second-largest city in Bangladesh. Using a questionnaire survey of 150 local inhabitants, the study explores perceived human-induced causes of landslides. Using time series Landsat images, this study also analyzes Land Use Land Cover changes from 1990 to 2020. The analysis reveals built-up area extended rapidly during 1990–2020. In 1990, total built-up area was 82.13 km2, which in 30 years, stood at 451.34 km2. Conversely, total vegetative area decreased rapidly. In 1990, total vegetation area was 364.31 km2, which reduced to 130.44 km2 in 2020. The survey results show that most of the respondents faced landslide therefore; it is nothing new among them. Respondents were identified several reasons for landslide like extensive rainfall, hill cutting, steep hill, weak soil texture, etc. A large number of local people opined that diverse human activities are causes of landslide in their local area and it has impacted on their livelihood. Chi-square test suggests that there are statistically significant differences between local and non-local inhabitants regarding their opinion on whether excessive hill cutting is alone responsible for landslide and whether deforestation is the sole reason for landslide. This study also used four multinomial logistic regression (MLR) to examine the effects of independent variables like gender, age, level of education, income, housing pattern and experience of facing landslide on their perception of human-induced causes of landslide. Findings show that age and experience of facing landslide are two significant predictors for the first model, explaining excessive hill cutting was alone responsible for landslide. Level of education and experience of facing landslide are found statistically significant for explaining our second model that is building infrastructures solely causes landslide. Moreover, our third model claims only deforestation can be blamed for landslide which is significantly explained by three predictors, namely gender, age and income. Finally, we found our fourth model that is landslide occurs only due to excessive sand collection is significantly explained by participant's gender, level of education, and income.
PubDate: 2022-03-13

• Imaging Subsurface Structures at Fast Eroding Coastal Areas in Northern
Bengkulu Using 2D Seismic MASW Method

Abstract: Abstract Coastal erosion is a global problem, affecting many countries around the world. On cliffed coastlines, erosion can be intermittent and sudden, posing an additional hazard to coastal communities. To mitigate such problems, it is necessary to understand the processes leading to cliff erosion. Here, we focus on the physical properties of the subsurface structure that might contribute to cliff instability. As a specific study site, we use the coastal region of the northern part of Bengkulu Province, which is well known as being prone to coastal abrasion/erosion. Seismic field surveys were conducted at five locations, using a 92 m seismic line with geophones spaced every 2 m. The measurements were processed using the Multichannel Analysis of Surface Wave (MASW) methodology with commercially available software. Our results suggest that the subsurfaces are divided into three layers where the top layers lie at thickness between 10 and 15 m with S-wave velocity (Vs) < 200 m/s (consistent with diluvial clay). The second layer has a thickness > 10 m with Vs between 600 and 800 m/s (consistent with loose sand), and overlays a bedrock layer for which Vs is much higher. We found between the first and second layers are a narrow ‘discontinuity region’ with Vs of 300–500 m/s (consistent with soft sand/silt). The configuration/composition/orientation of layers indicate stable permeable layers overlying saturated and impermeable layers at or below the sea level. The upper permeable layers are vulnerable to instability when subjected to external disturbances such as heavy precipitation, storm waves or earthquakes. The relatively mild wave climate and absence of notching around the water line leads us to conclude that variation in saturation levels is the primary driver of the observed cliff erosion.
PubDate: 2022-03-08
DOI: 10.1007/s41748-022-00301-5

• Assessment of Health Risk Due to Consumption of Spinach (Spinacia
oleracea) Cultivated with Heavy Metal Polluted Water of Bhabadah

Abstract: Abstract Spinach is a commonly grown tropical vegetable having high metal-accumulating capacity, which might cause human health problems. This study aimed to assess heavy metal contamination in surface water and spinach samples collected from the water-logged area of Bhabadah in the Khulna division of Bangladesh. A total of 24 locations were selected. Chemical analyses were performed using appropriate methodologies. The levels of Cd in water samples were 0.0092 ± 0.004 mg L−1 which was above the allowable drinking limit and did not meet public health standards. The average level of Pb was within acceptable limits. In spinach samples, the average levels of Zn, Pb, Cd, and Cu were 96.63 ± 34.53, 12.72 ± 13.33, 0.43 ± 0.30, 21.43 ± 5.93 μg g−1, respectively. The level of Pb and Cd exceeded the prescribed limit for the vegetables in more than 70% of the total spinach samples. The Cr content was below the detectable threshold. The daily metal intake for both males and females was more than the tolerable intake limit for Pb and Cd, whereas, cumulative incremental lifetime cancer risk for males and females are 2.02E − 03 and 2.27E − 03, respectively. This implies that more than two persons per thousand are at risk of cancer as a result of long-term intake of contaminated spinach in the Bhabadah region. According to this study, water and spinach contribute to the contamination of food chains and increase the risk of cancer caused by the presence of heavy metals. This heightened risk requires prompt action to alleviate this situation and increase overall public awareness of food safety.
PubDate: 2022-03-07
DOI: 10.1007/s41748-022-00302-4

• Projected Air Temperature Extremes and Maximum Heat Conditions Over the
Middle-East-North Africa (MENA) Region

Abstract: Abstract This study analyzes projected heat extremes over the Middle-East–North Africa (MENA) region until the end of the twenty-first century with a number of temperature indices based on absolute values and thresholds to describe hot conditions. We use model projected daily near-surface air (2-m) temperature ( $$T_\mathrm{{max}}$$ and $$T_\mathrm{{min}}$$ ) to derive the indices for the period 1980–2100. The data were taken from 18 CMIP5 models combining historical (1980–2005) and scenario runs (2006–2100 under RCP2.6, RCP4.5, and RCP8.5 pathways). Results show a domain-wide projected warming for all emission scenarios. Our findings for a business-as-usual pathway indicate excessive warming of more than 8 $$^\circ$$ C in the northern part of the domain (south Europe) for the annual warmest day (TXx) and night (TNx). In the hottest parts of the domain record high temperatures reached 50 $$^\circ$$ C in the recent past, which could increase to at least 56 $$^\circ$$ C by the end of the century, while temperatures over 50 $$^\circ$$ C are expected to occur in a large part of the MENA region. A significant increase is projected in the number of hot days (TX $$>40^\circ$$ C) and nights (TN $$>30 ^\circ$$ C) all over the region. For the period of 2071–2100 excessive hot days and nights will become the normal during summer in large parts of the MENA with some locations expected to exceed 180 and 100 days, respectively. Calculations of the corresponding heat index suggest that several areas across the MENA region may reach temperature levels critical for human survival.
PubDate: 2022-02-28
DOI: 10.1007/s41748-022-00297-y

• Analysis of Diurnal Air Temperature Range Variation over Bangladesh

Abstract: Abstract Temperature is one of the most important environmental factors influencing plant growth, development and yield while diurnal temperature range (DTR) is an important climate indicator. In this study, the temporal trends and spatial patterns of DTR fluctuations over the last 35 years (1981–2015) in Bangladesh are examined. The annual mean DTR of Bangladesh has progressively increased over the last few decades and the increasing amplitude is shown to have spatial and seasonal trends. Seasonal and spatial as well as interregional changes in DTR for the four regions of northwestern, northeastern, southwestern and southeastern are investigated. Seasonal DTR trends show a decreasing with a rate of -0.03 °C/decade in winter and an increase in pre-monsoon (0.13 °C/decade), monsoon (0.17 °C/decade) and post-monsoon (0.11 °C/decade). Southeastern region in DTR has increased significantly out of four regions but the other three regions have decreased. Monsoon season (June–September) has shown a significant increase in DTR in all regions. DTR is observed to decrease significantly in the winter season for both northwest and northeast regions, and has also decreased significantly/non-significantly for the pre-monsoon season for the northwest/northeast region. Similarly, post-monsoon (October–November) seasons have experienced smaller increases in DTR for all regions except southwest regions where it has decreased. The temporal trends and regional patterns of daily maximum and minimum temperatures are also examined to get insight into DTR alterations. A significant increasing trend of 0.24, 0.14, and 0.10 °C/decade has been observed in mean maximum (TMAX), mean minimum (TMIN) and diurnal temperature range (DTR; TMAX–TMIN), respectively, during the period of analysis. These results reveal important information about wheat vulnerability in these regions due to climate change and to develop adaptation strategies.
PubDate: 2022-02-16
DOI: 10.1007/s41748-021-00282-x

• Estimation of Flood Discharge in Ungauged Basin Using GPM-IMERG
Satellite-Based Precipitation Dataset in a Moroccan Arid Zone

Abstract: Abstract The Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM-IMERG) could be an alternative solution to the data lack problem. In this regard, this work examines the ability of this satellite-based rainfall products to simulate the flow in a Moroccan ungauged basin (Bourrous) by using the Soil Conservation Service–Curve Number (SCS-CN) model. We first applied this simulation in a nearby gauged basin (Ghdat) in order to validate it over a 17-year period. The datasets used in this study range from 2000 to 2017. The results, using ground-based rainfall, gave Nash–Sutcliffe criterion between 0.4 and 0.89 for almost all events. The mean relative bias on peak flow and volume are − 16.6% and 17.7%, respectively. We then assess at daily scale the GPM Level 3 IMERGD Early and Final dataset with a spatial resolution of 10 × 10 km. 3IMERGD-F outperforms 3IMERGD-E in terms of correlation and bias. These datasets are used to simulate flood events in the Ghdat basin. Using the 3IMERGD-E product, the comparison between simulated discharges and observations at the gauge station shows an underestimation of both the peak flow and the volume with a mean relative bias of − 33.42% and − 26.56%, respectively. With 3IMERGD-F, these biases become − 42.46% and − 33.74%. After the transposition to the ungauged Bourrous basin, the maximum peak flows estimated by 3IMERGD Early and Final are 168.4m3/s and 157.8m3/s, respectively. This study has thus shown the contribution of GPM Early and Final products in the estimation of flow rates in ungauged basins.
PubDate: 2022-02-09
DOI: 10.1007/s41748-022-00296-z

• Potential Effects of Spatio-Temporal Temperature Variation for Monitoring
Coffee Leaf Rust Progress Under CMIP6 Climate Change Scenarios

Abstract: Abstract Plant diseases occur in all regions of the globe where there are susceptible hosts, aggressive and virulent pathogens, and a favorable environment. We aimed to evaluate potential effects of temperature variation on the monocyclic and polycyclic processes of coffee leaf rust in susceptible Arabica coffee cultivars cultivated in Minas Gerais state, Brazil. Historical monthly mean air temperature data, from 1970–2000, was downscaled and used as the temperature reference period and maximum and minimum temperature for four future periods, 2021–2040, 2041–2060, 2061–2080, and 2081–2100 (SSP126 scenario) from Coupled Model Intercomparison Project Phase 6 (CMIP6) were used to characterize the future mean air temperature variation were used in the modeling of areas favorable to the progress of coffee leaf rust in Minas Gerais using spatial data techniques. Digital elevation model was considered for downscaling climate data. A non-linear regression model simulating the monocyclic process of coffee leaf rust was used to simulate the potential progress of the disease in susceptible cultivars under the different scenarios evaluated. In general, coffee leaf rust progress increased in susceptible cultivars located in areas with higher ground elevation, with emphasis in the south of the state, as well as in the main Arabica coffee producing regions. There was a reduction of areas favorable to rust in the north of the state due to temperature increase considering climate change scenario, however, new areas in the south of the state became more favorable to the disease. In general, in Minas Gerais state, the temperature will increase between periods from 2021 to 2040, 2041 to 2060, 2061 to 2081, and from 2081 to 2100, by 1.2 °C, 0.6 °C, 0.2 °C, and 0.1 °C, respectively.
PubDate: 2022-01-30
DOI: 10.1007/s41748-021-00286-7

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