Subjects -> ENVIRONMENTAL STUDIES (Total: 925 journals)     - ENVIRONMENTAL STUDIES (822 journals)    - POLLUTION (31 journals)    - TOXICOLOGY AND ENVIRONMENTAL SAFETY (54 journals)    - WASTE MANAGEMENT (18 journals) ENVIRONMENTAL STUDIES (822 journals)                  1 2 3 4 5 | Last

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 Earth Systems and EnvironmentNumber of Followers: 2      Hybrid journal (It can contain Open Access articles) ISSN (Print) 2509-9426 - ISSN (Online) 2509-9434 Published by Springer-Verlag  [2484 journals]
• Rainfall Frequency Analysis Using Assessed and Corrected Satellite
Precipitation Products in Moroccan Arid Areas. The Case of Tensift
Watershed

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: 2022-01-11

• Projecting Climate Change Effect on Soil Water Fluxes and Urea Fertilizer
Fate in the Semiarid Pampas of Argentina

Abstract: The economy of the semiarid region of the Argentine Pampas is based mainly on agriculture, so climate change is a fact that may have great influence on this type of activity. Therefore, it is necessary to evaluate future climate scenarios and the responses of hydrological variables such as precipitation, actual (ETreal) and potential evapotranspiration (ETc), and recharge rate. Climate change scenarios were based on temperature and precipitation variations predicted by CMIP5. Four representative concentrations pathways (RCP) were considered according to different greenhouse emissions to the atmosphere for the nearby future until the end of the twenty-first century (RCP2.6, RCP4.5, RCP6.0 and RCP8.5). Furthermore, one more scenario called RCP0.0 was considered, which is related to the actual climate conditions and represents the base line. In the study area, nitrogen (N) fertilization is a widely used practice to increase crop yields. This work assesses the impact of future climate on soil water fluxes and N compounds fate based on numerical simulations carried out with HYDRUS 1D. Actual evapotranspiration is going to increase between 1 and 6% from low to high climate-change scenarios. Although an increase in precipitation is also expected during all months of the year, there are periods when water availability will not be enough to supply the new potential evapotranspiration demand. The worst case is RCP8.5, where the ETreal/ETc ratio is expected to decline by 4%. Annual recharge is expected to decrease by 2.5% in the RCP2.6 scenario, while the rest of the scenarios shown positive trends. N leachate in the form of nitrates showed an increase of 2.8% in the RCP4.5 scenario which was also the one with the highest recharge rate raise. The use of a mathematical model as a predictive tool in soil water fluxes and fertilizers use is essential for planning the sustainable management of agroecology adapted to climate changes.
PubDate: 2022-01-07

• Evaluation of Satellite Precipitation Estimates Over Omo–Gibe River
Basin in Ethiopia

Abstract: In this study, the accuracy of CMORPH, CMORPH-CRT, PERSIANN and PERSIANN-CDR satellite precipitation estimates (SPEs) were evaluated over the Omo–Gibe River Basin in Ethiopia across 10-year period from 2007 to 2016. The evaluation was performed at various temporal (daily, monthly, seasonal and annual) and spatial scales (point to pixel and basin scale aerial averaged precipitation) against data from 39 irregularly distributed ground rain gauge stations, using continuous and categorical statistical indices. The evaluation results show that at point to pixel scale PERSIANN-CDR estimate showed the highest performance on daily, monthly, Bega season and annual time scales whereas CMORPH-CRT outperformed on Kiremt and Belg seasonal time scales. At a basin scale, CMORPH-CRT showed the highest performance on daily, monthly, Kiremt season, Belg season, and annual time scales, whereas PERSIANN-CDR outperformed all estimates on Bega seasonal time scale. CMORPH exhibited the weakest performance on all time scales and at both spatial scales (point to pixel and basin-scale). Based on the categorical analysis PERSIANN was well able to characterize the local precipitation than others (PSS = 0.71 and POD = 0.90). The finding of this study indicates that CMORPH-CRT and PERSIANN-CDR estimates presented consistently good performance with observed precipitation at different spatiotemporal scales in the Omo–Gibe River Basin.
PubDate: 2022-01-07

• Assessment of a Geothermal Combined System with an Organic Rankine Cycle
and Multi-effect Distillation Desalination

Abstract: An analysis is reported of a geothermal-based electricity-freshwater system in which an organic Rankine cycle is integrated with a multi-effect distillation desalination unit. The system is driven by geothermal hot water extracted from the production well. Mass, energy, entropy, and exergy rate balances are written for all system components, as are energy and exergy efficiency expressions for each subsystem. The exergy destruction rate associated with the temperature and chemical disequilibrium of the freshwater and brine with the reference environment are taken into account to reveal accurate results for irreversibility sources within the desalination process. The developed thermodynamic model is simulated using thermodynamic properties of the working fluids (i.e., ammonia, seawater, distillate, and brine) at each state point. A sustainability analysis is performed that connects exergy and environmental impact concepts. That assessment expresses the extent of the contribution of the system to sustainable development and reduced environmental impact, using exergy methods. Results of the sustainability analysis indicate that, with an increase in the reference environment temperature from 20 to 35  $$^\circ{\rm C}$$ , the exergy destruction rate decreases for the multi-effect distillation and organic Rankine cycle systems respectively from 6474 to 4217 kW and from 16,270 to 13,459 kW. Also, the corresponding sustainability index for the multi-effect distillation and organic Rankine cycle systems increases from 1.16 to 1.2 and 1.5–1.6, respectively, for the same increase in reference environment temperature.
PubDate: 2022-01-01

• Hydrodynamic Modelling of Floods and Estimating Socio-economic Impacts of
Floods in Ugandan River Malaba Sub-catchment

Abstract: River Malaba sub-catchment tends to experience dramatic flooding events, with several socio-economic impacts to the nearby communities, such as loss of lives and destructions of physical infrastructure. Analysis of spatiotemporal extents to which settlements, crops and physical infrastructures tend to be inundated are vital for predictive planning of risk-based adaptation measures. This paper presents a case study on flood risk assessment for Ugandan River Malaba sub-catchment. We applied the two-dimensional Hydraulic Engineering Center’s River Analysis System (2D HEC-RAS) for modelling of flooding extents. We considered extreme flow quantiles, lower and upper quantiles corresponding to the 95% confidence interval limits aimed at determining uncertainties in the flooding extents. Spatial extents of inundation on human settlement, land cover and infrastructure were analysed with respect to return periods of extreme flow quantiles. Finally, we estimated economic loss on infrastructure due to flooding. Results from the 2D HEC-RAS model were satisfactorily comparable with the results of observations. Amongst the land use types, cropland exhibited the highest vulnerability with at least 10,234.8 hectare (ha) susceptible to flooding event of 100-year return period (YRP). Inundated built-up land-use exhibited the highest vulnerability percentage increase (90%) between 2- and 100-YRP. In US Dollar, about US$33 million and US$ 39 million losses are estimated at 2- and 100-YRP, respectively, due to inundated rice gardens and these indicate a looming high risk of household food insecurity and poverty. Several infrastructure including 15 academic institutions, 12 health facilities, 32 worshiping places remain annually vulnerable to flooding. At least 6 km and 7 km of road network are also susceptible to flooding under extreme flows of return periods 2 and 100 years, respectively. Churches exhibited the highest economic losses of US$855,065 and US$ 1,623,832 at 2-YRP and 100-YRP, respectively. This study findings are relevant for planning the development of sustainable flood risk adaptation pathways given the established destructions within the sub-catchment due to flooding.
PubDate: 2022-01-01

• Examining the Effectiveness of Catch Crops as a Nature-Based Solution to
Mitigate Surface Soil and Water Losses as an Environmental Regional
Concern

Abstract: The main goal of this research was to conduct a biophysical, economic, social, and perception-based approach to foresee the solutions that could be used to mitigate the soil loss problem cost-effectively in “La Ribera del Xúquer” district (Valencia Region, Spain). To achieve these goals, a farmer perception survey was carried out, and an assessment of the biophysical impact of catch crops on soil organic matter, bulk density, steady-state infiltration rate (double-ring infiltrometer) and runoff generation, and soil erosion (rainfall simulation experiments) was carried out in 2016. For the biophysical approach, two paired plots, i.e., catch crops vs. glyphosate herbicide treatment (in advance, control plot), were selected under clementine citrus production. The results show that soil organic matter increased from 1.14 to 1.63%, and bulk density decreased from 1.47 to 1.27 g cm−3 after 10 years of treatments using catch crops. They also facilitated higher infiltration rates from 16.7 to 171 mm h−1 and a delay in runoff generation from 149 to 654 s for control and catch crop plots. Both runoff rates (from 50.6 to 3.1%) and soil erosion (from 3.9 to 0.04 Mg ha−1 h−1) were reduced once the catch crops were deployed in the field. After surveying (2018–2019), farmers stated the use of catch crops as a speck of dirt and a cause of possible loss of reputation when used. Moreover, farmers (N = 73) would accept the catch crops as an effective nature-based alternative only if a subsidy of 131.17€ ha−1 would be paid. The survey results also demonstrated that the farmers' community would see catch crop more as a benefit for the planet's health and society. Few constraints, such as ageing of the farmers’ population, lack of education and negative perception for other management factors, are the critical detrimental factors for adopting catch crops as a nature-based solution to reduce soil and water losses. There is a need for an effective agrarian extension service to change the fate of the current agriculture and achieve sustainability by adopting new management strategies in contemporary agricultural practices.
PubDate: 2021-12-27

• Correction to: Spatio‑temporal Change of Glacier Surging and
Glacier‑dammed Lake Formation in Karakoram Pakistan

PubDate: 2021-12-01

• The Impact of Sea Level Rise Due to Global Warming on the Coastal
Population Dynamics: A Modeling Study

Abstract: Global warming and the associated sea level rise is a major environmental issue at present time. The sea level rise is expected to change the demography of the coastal areas due to submergence of land area and thereby cause the migration of population to the inland areas. This paper presents a mathematical model to investigate the effect of global warming and the associated sea level rise on the dynamics of the coastal population. The proposed model is comprised of a set of differential equations which capture the dynamical relationship between seven variables, namely the mass of melting polar ice sheets and glaciers, the seawater level, the land area submerged due to increase in seawater level, the densities of the non-coastal and coastal populations, the carbon dioxide ( $$\text {CO}_{2}$$ ) concentration, and the average surface temperature. The model is analyzed qualitatively to study the long-term behavior of the variables of the system. The sufficient conditions under which surface temperature, seawater level, and other model variables settle to the equilibrium levels are derived. The time evolution of surface temperature, seawater level, and coastal population is shown in different carbon dioxide emission scenarios. The sensitivity analysis is carried out to determine the effect of perturbations in the key parameters on the dynamics of the state variables. It is found that the changes in the parameters defining the emission and removal rates of $$\text {CO}_{2}$$ , and the declination rate of carrying capacity of the coastal population due to an increase in submerged area, significantly influence the coastal population dynamics. The study suggests that the policies aiming to limit the impact of sea level rise on coastal population must focus on mitigation of carbon dioxide emissions.
PubDate: 2021-12-01

• Characteristics and Source Identification of Environmental Trace Metals in
Beach Sediments Along the Littoral Zone of Cameroon

Abstract: Beach sediment samples collected along the central part of the Littoral zone of Cameroon were geochemically analyzed using ICP–MS to investigate the distribution characteristics and to identify trace metal concentrations. The textural characteristics of these sediments revealed that they are dominated by sand. Metal concentrations are distributed in the following decreasing order: Fe ˃ Mn ˃ Cr ˃ V ˃ Ni ˃ Co ˃ Cs. Indices of pollution, such as enrichment factor values are generally less than 1.5, except for Cr; index of geo-accumulation, where values of all metals in the sediments were < 0; contamination factor shows that in the Yoyo and Mouanko stations, values of elements, such as Co, Cs, Ni and V range between 0.1 and 0.3, while other elements have values between 0.3 and 0.6. At the Mbiako station, the values of all selected elements are between 0.1 and 0.3, except Fe and Mn, which are between 0.3 and 0.6. The degree of contamination and pollution load index shows low values in all stations, where values in all sampling sites are less than 1. The principal component analysis, cluster and correlation matrix indicate that the heavy metals maintained fair trends with both anthropogenic and natural sources. This study showed that this coastal area is not highly concentrated in heavy metals, and equally revealed that the central part of the Cameroon coastline is slightly polluted by trace metals. The results can be used for future investigations focusing on evaluation of heavy metals and their pollution sources especially in coastal regions.
PubDate: 2021-12-01

• A Review of the Neoproterozoic Global Glaciations and a Biotic Cause of
Them

Abstract: In the Neoproterozoic Era, the Earth experienced two broad intervals of global glaciation, commonly known as Snowball Earth. There was also a rapid diversification of life, with the evolution of most of the eukaryotic lineages. Here, salient evidence for the Neoproterozoic global glaciations, including the carbon isotope record, is reinterpreted, and an alternative explanation for the causes of glaciation is proposed. The proliferation of life could have led to increases in atmospheric O2 levels and concomitant decreases in CO2 and CH4. Coupled biochemical and geochemical changes would have led to global cooling and glaciation. This so-called biotic hypothesis of the Snowball Earth is consistent with the most salient features of the reported evidence and explains the consecutive episodes of global glaciation.
PubDate: 2021-12-01

• Climate Change Impacts on the South American Monsoon System and Its
Surface–Atmosphere Processes Through RegCM4 CORDEX-CORE Projections

Abstract: This study evaluates projected changes in surface water and energy balances and surface–atmosphere coupling in the South American Monsoon System (SAMS) for the end of the century (2080–2099). The analyses are based on two ensemble datasets, which follow Representative Concentration Pathway 8.5 in the future period, and cover four subdomains (Northern and Southern—NAMZ and SAMZ—Amazon, La Plata Basin—LPB, and Southern Southeast Brazil—SSB). One ensemble consists of three Global Climate Models (HadGEM2-ES, MPI-ESM-MR and NorESM1-M), while the other consists of their dynamically downscaled version at 25 km horizontal grid spacing using Regional Climate Model version 4 (RegCM4). As both ensembles are able in reproducing the annual cycle of the components of the surface water and energy balances in the present climate, they can be used in the study of future climate. During the wet season (November–March), both ensembles project a decrease in precipitation over NAMZ and SAMZ (an exception is RegCM4 that projects a slight increase in SAMZ), and an increase across the LPB and SSB. These changes do not cause retreat or expansion of the monsoon area over the continent, which is similar to the present climate (1995–2014). For the wet season, the ensembles are in line with the presence of a strong surface–atmosphere coupling in LPB and SSB, weak coupling in SAMZ and very weak coupling in NAMZ. For future climate, the coupling is even weaker in NAMZ, which may be a driver for the negative changes in precipitation. For the other subdomains, while the ensembles project similar signals of precipitation changes, they disagree with the surface-atmosphere coupling highlighting the uncertainties in future climate.
PubDate: 2021-12-01

• Estimating Soil Organic Matter: A Case Study of Soil Physical Properties
for Environment-Related Issues in Southeast Nigeria

Abstract: The different deposition periods in sedimentary geological environment have made the build-up and estimation of soil organic matter ambiguous to study. Soil organic matter has received global attention in the ambience of international policy regarding environmental health and safety. This research was to understand the inter-relationship between soil organic matter and bulk density, saturated hydraulic conductivity (Ksat), total, air-filled and capillary porosities for organic matter estimation, via different multiple linear regression functions (i.e., leapbackward, leap forward, leapseq and lmStepAIC), in soils developed over the sedimentary geological environment. Eight mapping units were obtained in Ishibori, Agoi Ibami and Mfamosing via digital elevation model. Two pits were sited within each mapping unit, and 53 soil samples were used for the study. In soils over shale–limestone–sandstone, two pits were sited, six in alluvium, four in sandstone–limestone and four in limestone. Overall correlation between SOM with Ksat (r = 0.626) and BD (r = − 0.588) was significant (p < 0.001). The strongest correlation was obtained for SOM with BD (r = − 0.783) and Ksat (r = 0.790) in soils over limestone. In contrast, soils over shale–limestone and sandstone geological environment gave the weakest relationship (r < 0.6). Linear regression gave a similar prediction output. The best performing was leapbackward (RMSE = 11.50%, R2 = 0.58, MAE = 8.48%), which produced a smaller error when compared with leap forward, leapseq and lmStepAIC functions in organic matter estimation. Therefore, we recommend applying leapback linear regression when estimating soil organic variation with physical soil properties for solving soil–environmental issues towards sustainable crop production in southeast Nigeria.
PubDate: 2021-12-01

• Optimisation of a Numerical Model to Simulate the Dispersion and Chemical
Transformations Within the Oxides of Nitrogen/Ozone System as Traffic
Pollution Enters an Urban Greenspace

Abstract: Urban greenspace has many health benefits, including cleaner air than the surrounding streets. In this study, a detailed exercise has been conducted to measure concentrations of NO/NO2/NOx and O3 within an urban greenspace, the University of Birmingham campus, using continuous analysers, as well as transects of NO2 measured with diffusion tubes. Concentrations have been simulated using the ADMS-Roads model which has been optimised initially using NOx concentrations for traffic emissions on surrounding roads, background concentrations, and meteorological data considering four candidate sites. Optimisation for prediction of NO2 shows the critical importance of the NO2:NOx ratio in traffic emissions, for which a derivation from atmospheric measurements is consistent with a value derived from optimisation of the model fit to roadside data. After optimisation, the model gives an excellent fit to continuous data measured at roadside. Comparison of model predictions with transects of NO2 across the greenspace also show generally good model performance. The incorporation of dry deposition processes for the nitrogen oxides into the model leads to a reduction of less than 1% in predicted concentrations, leading to the conclusion that the cleaner air within urban greenspace is primarily the result of dispersion rather than deposition processes.
PubDate: 2021-12-01

• Water Quality Assessment for Drinking and Irrigation Purposes in Mahananda

Abstract: This study aims to assess the water quality of the Mahananda River in Bangladesh and its suitability for drinking and agricultural uses. For water quality determination, 15 samples were collected from different sites of the Mahananda River to calculate Water Quality Index (WQI) and Entropy Water Quality Index (EWQI). Result shows that among different Hydrochemical parameters, carbonate and bicarbonate concentrations crossed the maximum limit in all the samples, while fluoride concentration exceeding in Sample-15 with the highest value found in Baroghoria area. From WQI result, water quality for the Baroghoria area was found unsuitable for drinking with WQI − 309.22, whereas another two samples of Mollikpur and Namo Neemgachi fall under ‘poor’ category with WQI of 184.49 and 198.99, respectively. EWQI reveals medium to excellent water quality. Result from different irrigation indices (Na%, sodium adsorption ratio (SAR), residual sodium carbonate (RSC), magnesium hazard (MH), total hardness, Kelly ratio (KR), and permeability index (PI) values) showed their suitability for irrigation. Principal component analysis (PCA) explained a total of 89.71% of variances in the dataset. Significant positive association within EC–Na, EC–sulfate, Ca–TH, nitrate–sulfate, etc., were reported indicating prominence in terms of both geogenic as well as anthropogenic processes such as silicate weathering and the release of untreated sewerage, respectively, which governs the water quality evolution in the study area. Cluster analysis (CA) classifies all water samples in five different clusters based on five different characteristics. Mahananda River water is found safe for both drinking and agricultural purposes, except for few samples near the dense human settlement areas. Result from this study is useful for decision makers to design management plans for the river water quality, environmental pollution and human well-being.
PubDate: 2021-11-28

• Evaluation of Spatio-Temporal Dynamics of Guyana’s Mangroves Using
SAR and GEE

Abstract: Mangrove forests are vital in many ways to coastal communities. The forests prevent coastal erosion, produce nutrients and organic matter, serve as a sink for carbon, nitrogen, and phosphorus, maintain water quality, and support food production for habitat biodiversity. However, these systems are threatened by urban development and have sea-level rise as a result of climate change. Such is evident in Guyana coastal areas where there had been a reduction of mangroves coverage from approximately 80,000 ha in 1980 to 22,000 ha in 2010 and 26,115 ha in 2019. One of the measures to restrict the depletion of this vital ecosystem is through an aggressive programme of mangrove replanting and restoration by the Government of Guyana. To monitor and measure the spatio-temporal effectiveness of this management effort require effective and advanced technologies, which remote-sensing capabilities can provide. In this study, the synthetic aperture radar (SAR) imagery was used for the mapping of mangrove regeneration and dynamics. The producer’s accuracy of the mangrove classification for each year was 96%, 95%, 97%, 99%, and 99% in 1996, 2007, 2010, 2016, and 2019, respectively, and the users’ accuracy was 95%, 95%, 95%, 99%, and 99%, respectively, demonstrated that this can be used for the monitoring spatio-temporal response of mangroves. The analysis of diameter at breast height and the heights of the mangroves also show the spatial and temporal trend of gains and losses of biomass as derived from the allometric equations of the analysed SAR images. The findings show the effectiveness of the methodology used to monitor changes and to estimate the biomass. This study could be a useful guide for planning future coastal restoration projects at the sample study sites, assist in community resilience in the face of sea-level rise and climate change, and support policymakers in multi-policy coordination involving the management of the Guyana coastal retreat.
PubDate: 2021-11-28

• Contribution of Satellite-Based Precipitation in Hydrological
Rainfall–Runoff Modeling: Case Study of the Hammam Boughrara Region in
Algeria

Abstract: Hydrological models are viewed as powerful tools that have a major importance for managing water resources and predicting flows. It should be specified that the meteorological parameter rainfall is the main input in these models. In the current study, data from only one rainfall station are available over the analysis domain, which cannot represent the entire Hammam Boughrara watershed of Algeria. The precipitation data remotely detected by the tropical rainfall measuring mission (TRMM) provide good spatial coverage in the watershed and can be used to fill in the missing data. The use of raw TRMM data gives poor results from the simulated flow rates with a Nash–Sutcliffe efficiency NSE equal to 0.34 for the validation period that ranges from year 2000 to 2005; this is mainly due to uncertainties in the TRMM data. For this reason, it was deemed necessary to carry out a performance test of the model. The results obtained give an unsatisfactory percent bias (PBIAS) of − 46.24%, which suggests the need to perform a correction to decrease the PBIAS of satellite precipitation. For this, two methods were used: the linear regression method and the multiplicative method. These two techniques can only be applied if there is at least one rainfall measurement station available in the watershed. The obtained results are very satisfactory since the PBIAS reaches − 0.62% for the linear regression method and − 11.58% for the multiplicative method. In addition, the use of corrected TRMMs gives also very good results with a Nash–Sutcliffe efficiency that ranges from 0.74 to 0.88 for both validation and calibration periods. Overall, the current study is supportive to estimate the satellite-based rainfall, one of the very sensitive to measure the meteorological parameter, in northwestern Algeria.
PubDate: 2021-09-17
DOI: 10.1007/s41748-021-00256-z

• On the Influence of Vegetation Cover Changes and Vegetation-Runoff Systems
on the Simulated Summer Potential Evapotranspiration of Tropical Africa
Using RegCM4

Abstract: The community land model version 4.5 provides two ways for treating the vegetation cover changes (a static versus an interactive) and two runoff schemes for tracking the soil moisture changes. In this study, we examined the sensitivity of the simulated boreal summer potential evapotranspiration (PET) to the aforementioned options using a regional climate model. Three different experiments with each one covering 16 years have been performed. The two runoff schemes were designated as SIMTOP (TOP) and variable infiltration capacity (VIC). Both runoff schemes were coupled to the carbon–nitrogen (CN) module, thus the vegetation status can be influenced by soil moisture changes. Results show that vegetation cover changes alone affect considerably the simulated 2-m mean air temperature (T2M). However, they do not affect the global incident solar radiation (RSDS) and PET. Conversely to the vegetation cover changes alone, the vegetation-runoff systems affect both the T2M and RSDS. Therefore, they considerably affect the simulated PET. Also, the CN-VIC overestimates the PET more than the CN-TOP compared to the Climatic Research Unit observational dataset. In comparison with the static vegetation case and CN-VIC, the CN-TOP shows the least bias of the simulated PET. Overall, our results show that the vegetation-runoff system is relevant in constraining the PET, though the CN-TOP can be recommended for future studies concerning the PET of tropical Africa.
PubDate: 2021-09-15
DOI: 10.1007/s41748-021-00252-3

• Projected Drought Conditions over Southern Slope of the Central Himalaya
Using CMIP6 Models

Abstract: Nepal is located on the southern slope of the Central Himalayas and has experienced frequent droughts in the past. In this study, we used an ensemble of 13 biased corrected models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to assess the future drought conditions over Nepal under three shared socioeconomic pathways (SSP126, SSP245, and SSP585) using the Standardized Precipitation Evapotranspiration Index (SPEI) at annual timescale. The monthly correlation between observed and CMIP6-simulated historical SPEI is 0.23 (p < 0.01), which indicates the CMIP6 model ensemble can simulate the drought characteristics over Nepal. In the future period (2020–2100), the duration and severity of droughts are projected to increase with higher emission scenarios, especially for SSP585. Our results indicate enhanced drought intensity under SSP126, whereas, under SSP245, the drought frequency will be slightly higher. The drought frequency is projected to increase in the early future (2020–2060), decreasing in the late future (2061–2100) under all SSP scenarios. The results further indicate more prolonged and severe droughts in the early future under SSP585 as compared to SSP126 and SSP245. The findings of the present study can help drought mitigation as well as long-term adaptation strategies over Nepal.
PubDate: 2021-09-09
DOI: 10.1007/s41748-021-00254-1

• Flood Risk in Rivers: Climate Driven or Morphological Adjustment

Abstract: Flooding remains one of the major natural disasters that threatens human lives and property. Flood management has taken a new look, whereby flood risk in rivers is now viewed as driven by not just climate change but also by river channel morphological adjustment which have been overlooked in the past. This study aimed at evaluating the contributions of channel morphological adjustment to flood risk in rivers using river Elbe in Germany as a case study. To achieve this, an inundation model for the June 2013 flood event was developed using the LISFLOOD-FP model. A total of thirteen additional flood inundation models were ran at varying scenarios of river width, bed elevation and channel friction coefficient under a fixed discharge series. The results of these simulations revealed that, variability in river channel morphology constitutes an integral part of flood risk in rivers, hence a complementary driving factor to flood risk in addition to climate change. Thus, the assumption of a constant river channel morphology during flood modelling should consequently be open to question for flood hazard management. Flood frequency analysis for the Elbe basin was also presented. Discharge data spanning an interrupted period of 61 years (1958–2018) from 10 gauges along river Elbe were analysed for various return periods. It was concluded that any discharge rate having a return period of 5 years (2544 m3/s) and more would likely exceed the water carrying capacity of the Elbe river. The study proposes potential measures for effective flood modelling in rivers and can also serve as important tool for informing and supporting environment related decision making in flood risk management, land use regulation and floodplain management in the study area.
PubDate: 2021-09-09
DOI: 10.1007/s41748-021-00257-y

• Is Meteorology a Factor to COVID-19 Spread in a Tropical Climate'

Abstract: It was speculated that fewer COVID-19 infections may emerge in tropical countries due to their hot climate, but India emerged as one of the leading hotspot. There is no concrete answer on the influence of meteorological parameters on COVID-19 even after more than a year of outbreak. The present study examines the impacts of Meteorological parameters during the summer and monsoon season of 2020, in different Indian mega cities having distinct climate and geography. The results indicate the sign of association, but it varies from one climatic zone to another. The principal component analysis revealed that humidity is strongly correlated with COVID-19 infections in hillocky city Pune (R = 0.70), dry Delhi (R = 0.50) and coastal Mumbai (R = 0.46), but comparatively weak correlation is found in arid climatic city of Ahmedabad. As against the expectations, no discernible correlation is found with temperature in any of the cities. As the virus in 2020 in India largely travelled with droplets, the association with absolute humidity in the dry regions has serious implications. Clarity in understanding the impact of seasonality will greatly help epidemiological research and in making strategies to control the pandemic in India and other tropical countries around the world.
PubDate: 2021-09-03
DOI: 10.1007/s41748-021-00253-2

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