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  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted alphabetically
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 45)
Advances in Climate Change Research     Open Access   (Followers: 52)
Advances in Meteorology     Open Access   (Followers: 27)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 11)
Aeolian Research     Hybrid Journal   (Followers: 7)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 20)
American Journal of Climate Change     Open Access   (Followers: 37)
Atmósfera     Open Access   (Followers: 2)
Atmosphere     Open Access   (Followers: 33)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 13)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Atmospheric Environment : X     Open Access   (Followers: 3)
Atmospheric Research     Hybrid Journal   (Followers: 73)
Atmospheric Science Letters     Open Access   (Followers: 40)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 32)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Carbon Balance and Management     Open Access   (Followers: 6)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Climate     Open Access   (Followers: 8)
Climate and Energy     Full-text available via subscription   (Followers: 6)
Climate Change Economics     Hybrid Journal   (Followers: 44)
Climate Change Responses     Open Access   (Followers: 23)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Climate Law     Hybrid Journal   (Followers: 6)
Climate of the Past (CP)     Open Access   (Followers: 6)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Climate Policy     Hybrid Journal   (Followers: 51)
Climate Research     Hybrid Journal   (Followers: 9)
Climate Resilience and Sustainability     Open Access   (Followers: 21)
Climate Risk Management     Open Access   (Followers: 10)
Climate Services     Open Access   (Followers: 4)
Climatic Change     Open Access   (Followers: 69)
Current Climate Change Reports     Hybrid Journal   (Followers: 17)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 14)
Energy & Environment     Hybrid Journal   (Followers: 25)
Environmental and Climate Technologies     Open Access   (Followers: 3)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 21)
Frontiers in Climate     Open Access   (Followers: 4)
GeoHazards     Open Access   (Followers: 2)
Global Meteorology     Open Access   (Followers: 20)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 29)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
International Journal of Environment and Climate Change     Open Access   (Followers: 22)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
Journal of Agricultural Meteorology     Open Access  
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 42)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 133)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Journal of Climate     Hybrid Journal   (Followers: 56)
Journal of Climate Change and Health     Open Access   (Followers: 4)
Journal of Climatology     Open Access   (Followers: 4)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 21)
Journal of Space Weather and Space Climate     Open Access   (Followers: 30)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 83)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
Mediterranean Marine Science     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Meteorological Applications     Open Access   (Followers: 4)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 29)
Mètode Science Studies Journal : Annual Review     Open Access  
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Monthly Weather Review     Hybrid Journal   (Followers: 30)
Nature Climate Change     Full-text available via subscription   (Followers: 145)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Nīvār     Open Access   (Followers: 1)
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 6)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
Space Weather     Full-text available via subscription   (Followers: 27)
Studia Geophysica et Geodaetica     Hybrid Journal   (Followers: 1)
Tellus A     Open Access   (Followers: 21)
Tellus B     Open Access   (Followers: 20)
The Cryosphere (TC)     Open Access   (Followers: 8)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 32)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 14)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Urban Climate     Hybrid Journal   (Followers: 5)
Weather     Hybrid Journal   (Followers: 20)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Weather and Climate Extremes     Open Access   (Followers: 18)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
Weatherwise     Hybrid Journal   (Followers: 18)
气候与环境研究     Full-text available via subscription   (Followers: 2)

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Modeling Earth Systems and Environment
Number of Followers: 1  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2363-6203 - ISSN (Online) 2363-6211
Published by Springer-Verlag Homepage  [2469 journals]
  • An AHP-based regional COVID-19 vulnerability model and its application in
           China

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      Abstract: Abstract Since the COVID-19 outbreak, four cities—Wuhan, Beijing, Urumqi and Dalian—have experienced the process from outbreak to stabilization. According to the China Statistical Yearbook and China Center for Disease Control records, regional, pathological, medical and response attributes were selected as regional vulnerability factors of infectious diseases. Then the Analytic Hierarchy Process (AHP) method was used to build a regional vulnerability index model for the infectious disease. The influence of the COVID-19 outbreak at a certain place was assessed computationally in terms of the number of days of epidemic duration and cumulative number of infections, and then fitted to the city data. The resulting correlation coefficient was 0.999952. The range of the regional vulnerability index for COVID-19 virus was from 0.0513 to 0.9379. The vulnerability indexes of Wuhan, Urumqi, Beijing and Dalian were 0.8733, 0.1951, 0.1566 and 0.1119, respectively. The lack of understanding of the virus became the biggest breakthrough point for the rapid spread of the virus in Wuhan. Due to inadequate prevention and control measures, the city of Urumqi was unable to trace the source of infection and close contacts, resulting in a relatively large impact. Beijing has both high population density and migration rate, which imply that the disease outbreak in this city had a great impact. Dalian has perfect prevention and good regional attributes. In addition, the regional vulnerability index model was used to analyze other Chinese cities. Accordingly, the regional vulnerability index and the prevention and control suggestions for them were discussed.
      PubDate: 2022-06-01
       
  • Profile distribution and soil health implication of some oxides in
           agrarian soils overlying geologic formations in Southeast Nigeria

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      Abstract: Abstract This study monitored the concentration and distribution of the oxides of Cr, Ni, Cu, Zn and As in soils overlained by different lithological materials in southeast Nigeria. A 30 × 30 m spatial resolution of digital elevation model guided the selected eight soil profile pits dug for the study. A total of n = 27 soil samples were collected from the eight soil profile pits. Samples were air dried, and milled into 3–4 µm powder and analyzed using X-ray fluorescence. The result revealed that the oxides were irregularly distributed vertically, with the least heavy metal oxides obtained in the Ap horizons. Nevertheless, Cr2O3 was the most dominant and potentially toxic alongside NiO in Ishibori. Also, As2O3 was potentially toxic in most of the studied soils, with those in Ishibori as the most prone. Using multiple linear regression, the prediction was within the acceptable range (R2 > 0.50) except for As. For the prediction function of Cr, fine and coarse sand were negatively correlated with Cr, while CEC was positively correlated with Cu and Zn.
      PubDate: 2022-06-01
       
  • Management of risk factors for breaking localised pathways of microbial
           contamination in tubewells with handpump: a case study from India

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      Abstract: Abstract Microbial contamination of handpump (HP) is common in developing countries like India. The WHO recommends sanitary inspection (SI) to assess the risk of water source contamination. In SI, all risks are given equal weightage. However, different mathematical models have shown that risks associated with localised pathways have a relatively higher influence on microbial contamination. This study aims to assess the efficacy of eliminating four risks associated with localised pathways and have shown a higher positive association with microbial contamination of HP than others in bivariate frequency analysis and four binary logistic regressions applied on 324 HPs randomly selected from nine districts of Uttar Pradesh, India. Analysis showed the four risks: (i) HP loose at base: (ii) apron cracked: (iii) apron < 1 m an: (iv) drainage broken have a higher positive association than others. In this study, the above four risks were eliminated from 154 HPs (safe 48 and unsafe 106) through standard civil structures keeping other risks untouched. Post-intervention thermotolerant coliforms (TTC) tests were carried out and unsafe HPs were reduced from 106 to 3. Therefore, managing the four risks associated with localised pathways is highly effective in preventing microbial contamination of HP water.
      PubDate: 2022-06-01
       
  • Modeling the effectiveness of social distancing interventions on the
           epidemic curve of coronavirus disease in Ethiopia

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      Abstract: Abstract SARS-CoV-2 infections are now spreading across the world. Different measures were used by governments around the world to combat the spread of COVID-19. The efficacy of social distancing approaches in reducing the spread of COVID-19 in Ethiopia was investigated using geospatial technologies and the CHIME model. The COVID-19 response was predicted, measured, and compared after 25%, 75%, and 95% social distancing interventions in Ethiopia. Social distancing strategies flatten and delay the epidemic curve, according to the model findings. The model result shows that most new events and hospitalizations were avoided when social distancing measures were in effect. Social distancing can provide a critical time for increasing healthcare capability, and the research findings could assist policymakers in estimating the immediate number of resources required and planning for potential COVID-19 initiatives in Ethiopia.
      PubDate: 2022-06-01
       
  • Modeling streamflow using multiple precipitation products in a
           topographically complex catchment

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      Abstract: Abstract Precipitation is of primary importance in hydrological modeling and streamflow prediction. However, lack of gauge stations for long-term precipitation data, particularly in the data-scarce Chitral River Basin (CRB) of Pakistan and other parts in the developing world, is a hindrance to understand surface water hydrology. Therefore, this study aims to assess different sources of precipitation data for streamflow prediction in the CRB. A modified version of the conceptual and semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) known as HBV-light is used in this study to model streamflow by forcing it with precipitation inputs of different Precipitation Products (PPs). These PPs include APHRODITE (V1101, V1801R1), CHIRPS V2.0, CPC-Global, ERA5, GPCC V.2018 (V2), GPCP-1DD V1.2, PERSIANN, CHRS CCS, CHRS CDR and TRMM (3B42V7). The model was calibrated and validated for two periods (1995–2005 and 2007–2013, respectively), and showed good performance during both periods. Prior to assessing the performance of these PPs to simulate observed streamflow, they were assessed against gauged precipitation. Results of this study showed that APHRODITE-based precipitation performed better than other precipitation products in the simulation of precipitation characteristics in the study region. Multiple efficiency evaluation metrics including KGE, NSE, and PBIAS were employed to assess streamflow prediction capability of different products. Results indicated that APHRODITE outperformed all other PPs (KGE 0.89) in terms of simulating observed streamflow in the CRB. The CPC Global precipitation product (KGE 0.71) was found to be the least suitable product for hydrological modeling in the CRB. This study provides useful guidance for the selection and application of gridded precipitation products for long-term continuous streamflow prediction in the CRB.
      PubDate: 2022-06-01
       
  • Runoff curve number-potential evapotranspiration-duration relationship for
           selected watersheds in Ethiopia

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      Abstract: Abstract This paper attempts to show a relationship between Soil Conservation Service (SCS) parameter curve number (CN), potential evapotranspiration (PET), and time duration (D) using the data of four Ethiopian watersheds. CN values were determined for various durations from observed rainfall-runoff data, and PET was derived for different watersheds utilizing the Thornthwaite method employing temperature data. The results indicate that the CN values decline exponentially with increasing PET and duration D and vice versa for all three wetness conditions of the watersheds. This study confirmed that as the duration upsurges, the CN values diminution due to the more extended time accessible for water loss in the watershed. The proposed simple model based on CN-PET-Duration also strongly supports the derived relationship for all watersheds for three wetness conditions. This relationship is also useful for the estimation of PET from the available published CN values.
      PubDate: 2022-06-01
       
  • Numerical modeling of isothermal homogeneous turbulent flows by finite
           volumes in a compound hydraulic scheme

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      Abstract: Abstract The objective of this work is to study the numerical modeling of turbulent flow in a compound hydraulic scheme. The configuration adopted to collect the water flows from the inputs of several other secondary channels is typical. Indeed, this model is almost a real representation of the existing hydraulic structure, to study the spatio-temporal dynamics of unsteady turbulent flows. In addition, the work also consists of implementing an appropriate turbulence model, to ensure a better analysis of free, homogeneous isotropic turbulent flows. To test relevance and validity of the hypotheses on the behavior of turbulent flows in a complex hydraulic system such as ours and to corroborate the results obtained, we have compelled to compare the numerical results carried out with the experimental results of the work having demonstrated a great interest for turbulent flows and having been conducted under identical conditions (Jiménez and Hanif J Hydraul Eng 114:377–395, 1988; Fennema and Chaudhry J Hydraul Eng 116:1013–1034, 1990; Bhallamudi and Chaudhry J Hydraul Res 30:77–93, 1992). Particular emphasis is placed on the geometry of the digital channel adopted as well as other parameters such as roughness and channel slope, to identify fluctuations in hydrodynamic parameters and the distribution of turbulent stresses and wall friction. The equations governing the phenomenon studied are directly related to the continuity and momentum conservation equations which form the system of nonlinear Navier–Stokes equations. The modeling by numerical simulations based on finite volumes was carried out using the Fluent software, which is a 3D numerical model, using the system of nonlinear partial differential equations of the movement of fluids in a continuous medium
      PubDate: 2022-06-01
       
  • Assessment of irrigation requirement and scheduling under canal command
           area of Upper Ganga Canal using CropWat model

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      Abstract: Abstract The sustainable water resources utilization in deferent water-based sectors is a prerequisite for any country. Agriculture water demand in the agro-climatic zone of western Uttar Pradesh is accessed in the current study. From last few decades water scarcity is a serious issue for the government and policy makers in the region. Proper water management is crucial to economize not only the water use efficiency in the region, but also improve the crop productivity efficiently. This study determined the optimum irrigation area and its other irrigation requirements in the Upper Ganga Canal command. Irrigation scheduling was also recommended using CropWat 8.0 simulation software. It is estimated that the total crop water requirement in command area is 1763 MCM which seems higher than actual water availability due to poor planning and practice of irrigation. The proposed irrigation requirements based on results are appraised with the presently followed recommendations and are discussed in details in the subsequent sections. The present study is useful for effective planning and management of irrigation water needs in UGC command area.
      PubDate: 2022-06-01
       
  • Estimation of nitrogen content in wheat from proximal hyperspectral data
           using machine learning and explainable artificial intelligence (XAI)
           approach

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      Abstract: Abstract Nitrogen (N) is a primary macronutrient essential for plant structures and metabolic processes, and the deficiency of N leads to critical plant disorders. The spectral reflectance can be used to predict the N status of plants using hyperspectral data. Therefore, the N status of wheat was predicted from hyperspectral data using machine learning techniques. Different derivative pre-processing treatments have been shown to have an impact on the spectral model performance. Therefore, we used different spectral pre-processing techniques (first derivative, deresolve and deresolve plus first derivative) coupled with six machine learning regression models (Support Vector Regression, Random Forest, k-nearest neighbours, Multilayer Perceptron, Gradient Boosting Regression and Partial Least Square Regression) to predict the N status of wheat. The deresolve plus first derivative spectral pre-processing technique along with Random Forest and Gradient Boosting Regression (R2 > 0.85) were better than the other combination of spectral pre-processing and machine learning models to predict the N status of wheat. The eXplainable Artificial Intelligence (XAI) tool was used to provide the local and global explanations of the model decisions using SHapley Additive explanations (SHAP) values. The important wavelengths predicting N status were between 790 and 862 nm (global model) for Random Forest model. However, these wavelengths varied with the growth stages of wheat. The most important wavelength were 672, 794, 804, 806, 816 and 820 nm during the first six days of wheat growth (local model), 716, 794, 804 and 806 nm after 45 days of wheat growth, 724, 806, 820, 1556 and 1582 after 63–72 days of wheat growth and 718, 720, 724 and 1272 nm after 91–97 days of wheat growth. These results suggest that XAI tools are useful to explain the complex machine learning models related to hyperspectral data for remote monitoring of N status of wheat.
      PubDate: 2022-06-01
       
  • Integration of rapid impact assessment matrix method and sustainability
           modeling for management of municipal solid waste transfer stations in cold
           regions

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      Abstract: Abstract Solid waste transfer stations (SWTS) play an essential role in the municipal waste management system as the interface between the collection and waste transportation to the final disposal. SWTS are often not good conditions in residential areas and may have environmental pollution and public complaints from citizens. Environmental impacts assessment (EIA) is a solution to minimize the environmental impact of SWTS and provide a solution to the urban manager and planners. The rapid impact assessment matrix (RIAM) was conducted in this research to evaluate the impacts of the four various options defined for SWTS in Ardabil city. These options include SWTS in enclosed space and with the construction of green space and without it (option 1 and 2), SWTS in open space with the establishment of green space (option 3), and without the establishment of green space (option 4) (the current condition of the SWTS). For a project to be consistent with sustainability principles, should be considered aspects of sustainability such as social, economic, and environmental. This paper applies a mathematical model of sustainability based on the obtained results from the RIAM analysis to determine whether the options are potentially sustainable or unsustainable and calculate the level and nature of sustainability. By results (option 1), the priority for establishing transfer stations, compared to other options, has the highest score (0.068) regarding sustainability and the adverse environmental impacts. However, the current environmental status of Ardabil SWTS (option 4) has the lowest score (− 0.215) was found to be the last priority in the establishment of SWTS.
      PubDate: 2022-06-01
       
  • Solar desalination site selection on the Caspian Sea coast using AHP and
           fuzzy logic methods

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      Abstract: Abstract Access to drinking water is a necessity in many developing countries. The most available water sources are saline or contain harmful bacteria, which are not drinkable. Desalination of saline water and choosing a suitable location for the desalination process are inevitable in most countries. GIS is a computer-based system used to generate, store, display, market, and process geographic information related to various features and phenomena. This research locates the most optimal points in the Caspian Sea coast to construct solar water desalination using Analytic Hierarchy Process (AHP) and fuzzy logic. In the primary section, important factors are identified in determining the appropriate location, and then, the effectiveness of each criterion is determined. In the next section, various maps are formed based on the nature of these factors using fuzzy membership functions (Gaussian, Large, and Linear). Criteria for locating water desalination facilities include slope, annual rainfall, distance to roads, distance to rivers, distance to faults, land use, elevation, and distance to the sea. In this research, site selection is obtained by AHP and fuzzy methods with a gamma value of 0.1–0.9. Finally, the correlation coefficient between the maps generated by AHP and the fuzzy method is then calculated. The highest correlation between AHP and fuzzy map is 0.24752 for the fuzzy map with 0.7 gamma.
      PubDate: 2022-05-16
       
  • Assessing long-term coral reef degradation in Indonesia’s Tiworo strait
           marine conservation area using remote sensing and rapid appraisal for
           fisheries approaches

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      Abstract: Abstract In Indonesia, the coral reef ecosystem in the Tiworo Strait Conservation Area (TSCA) faces various threats of natural and anthropogenic stressors that can damage the coral reef ecosystem's role and services. We analyzed changes in coral reef habitat at TSCA over the 25 years from 1994 to 2019 using multi-temporal and multi-sensor satellite imagery data combined with in-situ measurement data and social surveys. Our results show a decrease in live coral cover from 78.30 ha in 1994 to 8.01 ha in 2019, with a 2.81 ha/year degradation rate. Our analysis of 37 threat attributes shows that the TSCA coral reef ecosystem faces a “high threat” to very high threat levels. Threat scores for coral reefs assessed as facing severe conditions according to threat indices included contributions from the ecological dimension (16.87 = very high threat), economic dimension (31.00 = high threat), social dimension (34.83 = high threat), technological dimension (41.10 = high threat), and law and institutional dimension (26.83 = high threat). Coral reefs will undoubtedly go extinct if local threats continue without preventative measures. Therefore, the sustainability of coral reefs in the TSCA—one of the most important marine conservation sites in the Coral Triangle Marine Eco-region should be the primary priority for all stakeholders. Appropriate policies and supervision in the field must be carried out rigorously and measurably, implementing the analyzed set of strategies.
      PubDate: 2022-05-16
       
  • Assessment of the hydrological impact of land use/cover changes in a
           semi-arid basin using the SWAT model (case of the Oued Saïda basin in
           western Algeria)

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      Abstract: Abstract Algeria is considered a country at risk in the index of vulnerability to climate change. In terms of water resources, there has been a significant decrease in water supply in the western part for three decades. This has led to changes in agricultural practices and the viability of natural species, as well as socio-political conditions and anthropogenic action at the watershed scale, which directly affect the water cycle. This study aims to quantify the impact of land use/land cover change on the hydrological response of the Oued Saida basin using the Swat model from 1998 to 2005. Satellite image time series of 1987 and 2002 were used for land use and cover from. A supervised classification approach, using the maximum likelihood classification method was used for the land cover of 1987 and 2002. In addition, post-classification was made to detect changes in land use/land cover. FAO soil data 30 m spatial resolution ASTER DEM data and 1998 to 2005 climate data set were combined as input data to the SWAT model land cover map (2002), with. First for the calibration phase, then those from 1987 was incorporated into the model as the scenario used for the assessment of land use change impacts. Evaluation of the accuracy of classified images was made with the error matrix. The global precision (the kappa coefficient) found for the 1987 (2002) image is 89.5% (95.9%). As a result, evolutionary analysis of land use change from 1987 to 2002 showed a decrease in agricultural area (9.20%), an increase in forest land (5.42%) and an increase in urbanized areas (2.77%). The results of the model calibration using the SWAT-CUP software’s SUFI-2 algorithm were satisfactory with a Nash Sutcliffe (NSE) efficiency coefficient of 0.56 and an R2 of 0.57. In addition, parameters related to soil properties and land use are the most sensitive. Changes in land cover have affected the runoff, increasing the average annual (monthly) peak flow by 2.5 to 3.5% (0 to 6%) at the expense of the seepage water and groundwater recharge. These changes are explained by socio-economic, political and anthropogenic conditions. The results obtained provide useful information about observed and land use trends and affected hydrological behaviors and can be a tool to assist decision-making in the development and management of the catchment area in a global vision.
      PubDate: 2022-05-16
       
  • Evaluation of dry and wet spell events over West Africa using CORDEX-CORE
           regional climate models

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      Abstract: Abstract This study investigates the capability of regional climate models (RCMs) in simulating four extreme precipitation indices on an annual and monthly scale over West Africa during the period 1997–2014. Three global climate models (GCMs; HadGEM2-ES, NorESM1 and MPI-ESM) were dynamically downscaled using three high resolution ( \(0.22^{\circ }\) ) regional climate models (RCMs; RegCM4, REMO2015 and CCLM5-0-15). These simulations were from the Coordinated Output for Regional Evaluations within the Coordinated Regional Climate Downscaling Experiment framework (CORDEX-CORE) publicly available through the Earth System Grid Federation (ESGF) web portals. The capabilities of the RCMs in the representation of maximum consecutive wet day (CWD), maximum consecutive dry days (CDD), number of dry days (NDD), and number of wet days (NWD) were compared with observation/satellites datasets obtained from the Global Precipitation Climatology Project (GPCP), Tropical Rainfall Measuring Mission (TRMM) and Tropical Applications of Meteorology using SATellite data and ground-based observations (TAMSAT). The reference datasets showed similar spatial pattern and magnitude of analyzed precipitation extremes but models exhibit different pronounced discrepancies relative to them. All RCMs consistently captured the spatial patterns of the indices but with some pronounced biases along the Guinean coast and northern parts of Niger. There exists little or no biases in the representation of annual cycle along the Guinea and Sahel for all the indices based on each of the RCMs ensemble, with the exception of RegCM4 which has a more pronounced bias in CWD. Statistical evaluation of the performance of the models over the entire West Africa with respect to the 4 indices revealed that REMO2015 models and its ensemble have overall lowest root mean square error followed by the choice of MPI-ESM GCM downscaled with either of the RCMs. REMO-HAD was found to have the best performance in the representation of consecutive dry days and number of wet days with RMSE values of 25.74 and 18.91 respectively. REMO-MPI has superior performance in the estimation of consecutive wet days and number of dry days with RMSE values of 5.38 and 20.51 respectively. Generally, REMO RCMs ensemble was found to be the best ensemble in all indices except consecutive dry days where REG4 ensembles had better performance. Operational use of these 3 RCMs are recommended with compensation for over-and underestimations.
      PubDate: 2022-05-14
       
  • Comparison of two open-source digital elevation models for 1D hydrodynamic
           flow analysis: a case of Ozat River basin, Gujarat, India

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      Abstract: Abstract The Ozat River originates from the Gir forest in the Junagadh district, and the river mouth is near Navi Bandar in the Porbandar district. Before meeting the Arabian sea, the river splits into two portions; one flows towards Ghed region, while the other flows straight towards Pata village; before the separation, water is scattered throughout the low-lying terrain, which is frequent. This research aims to compare the open-source digital elevation model (DEM) for 1D hydrodynamic flow analysis, river stage analysis along the reaches from inflow to river mouths, and the calibration of Manning roughness value. This study boosts researcher’s capability to work with open-source DEM. Shuttle Radar Topography Mission (SRTM) 30 m and Advanced Land Observing Satellite (ALOS) 30 m DEMs carried with Hydrologic Engineering Centre River Analysis System for 1-Dimensional hydrodynamic analysis. For the comparative study of DEMs, there are two criteria emphasized (1) Water Surface Elevation (WSE) and (2) Cross-Section Inundation. Specific places are set for WSE changes, and all reach is considered for the cross-section inundation study. Regression analysis was employed to calculate root mean square error (RMSE) for water surface elevation changes and coefficient of determination (R2) for the cross-section inundation study. The result shows RMSE values are 0.34 and 1.31 for water surface elevation changes, R2 values are 0.81 and 0.59 for an inundation of cross sections, respectively, for SRTM and ALOS. It shows that the lower value of RMSE and a better R2 value of SRTM DEM made a close agreement with an observed data set. Most split stretches seem inundated on both river bank sides, according to the one-dimensional model. Ground survey and Unmanned Aerial Vehicle photographs have enhanced a support system for decision-makers.
      PubDate: 2022-05-14
       
  • Modelling the recent variations of water balance components and water
           availability within the Senegal River basin: using WEAP21 model

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      Abstract: Abstract The availability of water in the Senegal River basin is a basic issue for moving towards efficient resource management. Given the extent of the river and the large number of stations, hydrological modelling is a reliable means of assessing the evolution of the water balance and availability over the last 30 years. This paper aims to evaluate water balance components and to model the water balance over the Senegal River basin from 1989 to 2020. The streamflow data have been calibrated and validated with the PEST program incorporated in WEAP with a NSE equal to 0.98, a PBIAS of 7% and a R2 of 0.98. The water balance has been computed using the Soil Moisture Method which use mainly climate data and runoff data to output different results driving to an analysis of the water balance components. The results have shown that the precipitation is the main alimentation of the river with a mean rainfall of 267,255.84 Mm3; the losses by evapotranspiration are 246,892.45 Mm3. According to the conventional formula, the water balance would be equal to 20,363.38Mm3 in the Senegal River basin. The modelling of the water balance in this basin will allow a further study concerning the effect of climate change on the hydrological and ecological system of the Senegal River basin. A variation in the resource and hydrological parameters was noted. Although the 30 years see a decrease in rainfall, runoff increases. However, it remains to integrate the water use parameters for better conclusions.
      PubDate: 2022-05-14
       
  • Inhomogeneous Poisson point process for species distribution modelling:
           relative performance of methods accounting for sampling bias and imperfect
           detection

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      Abstract: Abstract Species distribution models (SDMs) have become tools of great importance in ecology, as advanced knowledge of suitable species habitat is required for the process of global biodiversity conservation. Presence-only data are the more abundant and readily available data widely used in SDM applications. These data should be treated as a thinned Poisson process to account for detection errors related to sampling bias and imperfect detection that arise in them. Failure to do so could be detrimental to SDM’s predictions. This study assesses the effects of the species abundance, the variation in detection probability, and the number of sites visited in planned surveys on the performance of SDMs accounting for detection errors using simulated data. The results show that the accuracy and precision of estimates differ depending on models and species abundance. Their main difference lies in their ability to estimate \(\beta _0\) , the model intercept. The lower the species abundance, the higher the bias and variance of \(\hat{\beta _0}\) . Furthermore, the lower the detection probability, the higher the bias and variance of \(\hat{\beta _0}\) . However, \(\beta _1\) , the slope parameter, is estimated with almost high accuracy and precision for all models. This study demonstrates the low efficiency of accounting for sampling bias and imperfect detection based on presence-only data alone. Analysing presence-only data in conjunction with point-count outperformed the other approaches, whatever the species abundance, as long as the detection probability is at least 0.25 with average values of detectability covariates. The acceptable accuracy and precision, the minimum number of sites to consider vary depending on species abundance. At least 200 sites are required for the rare species, whereas 50 sites can suffice for the abundant species. Since collecting high-quality data are very expensive, this study emphasizes the need to promote initiatives such as citizen science programs that aim to collect species occurrence data with as little bias as possible.
      PubDate: 2022-05-11
       
  • Evaluation of the hydrology and sediment load situations of the upper
           watershed of Thac Ba reservoir (Vietnam and China) under the impacts of
           climate changes

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      Abstract: Abstract The Thac Ba reservoir serves as a critical supply of water for residents in Hanoi's downstream region, who rely on it for their livelihood. Recent changes in land use have resulted in a greater input of silt and nutrients into the environment. A large number of modeling studies have not been carried out because of the challenges in obtaining data from both China and Vietnam. The reservoir is located inside an international drainage basin that connects China and Vietnam. On the basis of the findings of the calibrated and verified SWAT model on streamflow and sediment, we provide this paper. On the basis of monthly data gathered from 1992 to 2003, the model’s performance was extremely excellent in terms of the coefficient of determination (R2) and the Nash–Sutcliffe coefficient (NSE), with R2 = 0.885 and NSE = 0.914 for precipitation and R2 = 0.826 and NSE = 0.849 for sediment, respectively. It was less accurate (NSE = 0.628) but remained dependable in the daily streamflow calibration case study. Based on climate change predictions for Vietnam, four scenarios were designed and assessed for this study. The case study also provides a quantitative illustration of how successfully GIS and SWAT can function together when the amount of meteorological data available is restricted. These findings will be useful in the administration of water and soil conservation initiatives in the future.
      PubDate: 2022-05-11
       
  • Geophysical and geochemical prospecting for submarine groundwater
           discharge in a karst leaky aquifer from Valliyur Hills to Uvari Beach

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      Abstract: Abstract Coastal freshwater aquifer characteristic study is essential for drinking water and domestic purpose. SGD of groundwater flux study was carried out using geophysical methods such as Azimuthal square array resistivity, 2D electrical resistivity imaging (ERI), magneto-telluric and geochemical analysis of water samples. In the square array method, the resistivity of fractured/ faulted zone with leaky aquifer of SGD is identified using resistivity variations. The 2D ERI techniques apparent resistivity values changes and pseudo-section colour difference are used for SGD flow path. Magneto-telluric method is a tool for SGD flow in the subsurface karst topography with differentiating flow of depth. The grain size analysis of beach sediments as fine sand is encountered in the statistical analysis of grain sorting. The deeper aquifer location is identified using square array and magneto-telluric method layer by layer. The magneto-telluric resistivity profiles observation of aquifer thickness, soil, and rock hydraulic conductivity, the gradient of flow using Darcy’s law was used to estimate the flux of the Uvari beach SGD flow rate. The geochemical phases of freshwater samples U2, U3, U4 U6, U7, U8, U9 mixing of HCO3 and seawater intrusion in U1, U5 in Mix SO4 concentration is found in the study.
      PubDate: 2022-05-10
       
  • RescueNet: YOLO-based object detection model for detection and counting of
           flood survivors

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      Abstract: Abstract Floods are the common and frequent type of major natural disasters, having a large-scale economic impact on the country causing widespread damage, resulting in loss of life and damages to both public and personal property. Between 1998–2018, floods affected more than 2 billion people worldwide. Humans don't have much influence over preventing this natural calamity, but a mitigation measure can be taken to rescue the lives under such critical circumstances. But can plan ahead of time for rescue operations in the impacted areas to move people and animals to a safer location where time is very critical. When the environmental conditions are adverse or non-supportive, it is difficult to detect humans and animals using conventional approaches. Accurate, in time detection and immediate provision of life saving measures are the key to rescue the survivors during disastrous situation. Unmanned Aerial Vehicles (UAV's) can be used to collect real-time images from low altitude airspace to get the aerial view of the images which in turn supports vast emergency rescues. The major challenge wit this is to dynamically process huge amount of data to identify and locate such affected people in real time. Due to significant development in Deep learning technologies, object detection in UAV images that aims to identify humans and animals can be accomplished. This paper proposes a Deep-learning based efficient emergency response model [RescueNet] for helping Rescue system in detecting survivors in flood devastated regions during response activities. Results obtained from the implementation of the proposed model shows the effectiveness of the model in detecting and counting the affected people and animals. The model shows a precision of 0.98, recall of 0.97, an F1-score of 0.94 and means average precision (mAP) of 98% which significantly proved that, the proposed model could certainly help the rescue system in providing the on-time response for saving lives.
      PubDate: 2022-05-07
       
 
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