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  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 157)
Nature Climate Change     Full-text available via subscription   (Followers: 149)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 83)
Atmospheric Research     Hybrid Journal   (Followers: 73)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Climatic Change     Open Access   (Followers: 70)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Advances in Climate Change Research     Open Access   (Followers: 60)
Journal of Climate     Hybrid Journal   (Followers: 56)
Climate Policy     Hybrid Journal   (Followers: 53)
Climate Change Economics     Hybrid Journal   (Followers: 50)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 45)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 42)
American Journal of Climate Change     Open Access   (Followers: 42)
Atmospheric Science Letters     Open Access   (Followers: 40)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
Atmosphere     Open Access   (Followers: 34)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 32)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 32)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 32)
Journal of Space Weather and Space Climate     Open Access   (Followers: 31)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 30)
Monthly Weather Review     Hybrid Journal   (Followers: 30)
Space Weather     Full-text available via subscription   (Followers: 28)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
Advances in Meteorology     Open Access   (Followers: 27)
Climate Change Responses     Open Access   (Followers: 27)
Climate Resilience and Sustainability     Open Access   (Followers: 26)
Energy & Environment     Hybrid Journal   (Followers: 26)
Journal of Climate Change     Full-text available via subscription   (Followers: 25)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
International Journal of Environment and Climate Change     Open Access   (Followers: 24)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 24)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Current Climate Change Reports     Hybrid Journal   (Followers: 22)
Tellus A     Open Access   (Followers: 21)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 21)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 20)
Journal of Economic Literature     Hybrid Journal   (Followers: 20)
Global Meteorology     Open Access   (Followers: 20)
Tellus B     Open Access   (Followers: 20)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Weatherwise     Hybrid Journal   (Followers: 18)
Weather and Climate Extremes     Open Access   (Followers: 18)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 16)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 14)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 14)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 13)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 12)
Climate Risk Management     Open Access   (Followers: 12)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
The Cryosphere (TC)     Open Access   (Followers: 8)
Climate Research     Hybrid Journal   (Followers: 8)
Climate and Energy     Full-text available via subscription   (Followers: 8)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Climate of the Past (CP)     Open Access   (Followers: 7)
Aeolian Research     Hybrid Journal   (Followers: 7)
Climate     Open Access   (Followers: 7)
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Journal of Climate Change and Health     Open Access   (Followers: 6)
Climate Law     Hybrid Journal   (Followers: 6)
Carbon Balance and Management     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 6)
Urban Climate     Hybrid Journal   (Followers: 5)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
Journal of Climatology     Open Access   (Followers: 4)
Frontiers in Climate     Open Access   (Followers: 4)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Meteorological Applications     Open Access   (Followers: 4)
Climate Services     Open Access   (Followers: 4)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Environmental and Climate Technologies     Open Access   (Followers: 3)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
Atmospheric Environment : X     Open Access   (Followers: 3)
GeoHazards     Open Access   (Followers: 2)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Atmósfera     Open Access   (Followers: 2)
Oxford Open Climate Change     Open Access   (Followers: 2)
Mediterranean Marine Science     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
气候与环境研究     Full-text available via subscription   (Followers: 2)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Studia Geophysica et Geodaetica     Hybrid Journal   (Followers: 1)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Nīvār     Open Access   (Followers: 1)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Journal of Agricultural Meteorology     Open Access  
Mètode Science Studies Journal : Annual Review     Open Access  

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Similar Journals
Journal Cover
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]
  • Soil erosion and sediment yield modeling for the Maruba dam catchment,
           Machakos County, Kenya

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      Abstract: Abstract Soil erosion and sediment yield modeling is important for reservoir management, especially in developing countries. Previous research has focused on spatial modeling of soil erosion in large catchments, particularly in Kenya. The purpose of this research was to predict soil erosion and sediment yield at the Maruba dam catchment. This study was carried out using the Revised Universal Soil Loss Equation for spatial modeling of soil erosion and reservoir sedimentation assessment using a bathymetric survey that utilized multi-frequency acoustics, and validated using sediment core data. According to the study, annual soil loss ranged from 0 to 29 t ha−1 yr−1, with an average of 0.9708 t ha−1 yr−1. The reservoir had a total capacity of 2,395,139.5 m3, a surface area of 256,622.85 m2, and a depth range of 0 to 13.5 m, according to the bathymetric survey. The reservoir’s overall sediment accumulation was calculated to be 290,434.6 m3, which corresponds to a 10.8% overall storage loss. It was estimated that the annual rate of reservoir capacity loss was 26,403.15 m3, or around 1%, which is in line with global averages. For the RUSLE-based and reservoir-based approaches, the sediment yields were estimated to be 0.1775 and 0.0054 t ha−1 yr−1, respectively. The variation in sediment yields demonstrated that the reservoir-based approach provided accurate estimates of sediment yields, especially in small catchments. The study’s findings provide crucial scientific information that would be helpful in formulating policies and making decisions on the management of dam reservoirs.
      PubDate: 2022-08-03
       
  • Hybrid particle swarm optimization and group method of data handling for
           short-term prediction of natural daily streamflows

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      Abstract: Abstract Hydrological forecasts have been developed since the earliest civilizations allowing to plan actions such as agriculture, grain storage, and the construction of reservoirs to supply water during long periods of drought. These forecasts are becoming increasingly essential given the growing dependence on water resources in the most diverse activities such as hydroelectric power generation. In this study, we develop a hybrid approach to forecasting the daily flow of the Zambezi River at the Cahora Bassa dam in Mozambique. These forecasts use daily historical data on flow, evaporation, relative humidity, and rainfall to predict the weather one day in advance. The model employs the seven past days as inputs to the Group Method of Data Handling (GMDH) algorithm optimized by the Particle Swarm Optimization (PSO) algorithm. GMDH is a neural network composed of neurons arranged in several layers, consisting of polynomial functions with two variables combined in a cascade to produce the output at the end of the network. The PSO promotes a search for optimal GMDH parameters to minimize the error values between the predicted and the actual river flow observed values. The simulations are performed 25 times to reduce the effects of the random values characteristic of the tested models. The results obtained by the proposed approach are compared with the other neural networks, such as extreme learning machine (ELM) and Multi-layer perceptron (MLP). The models’ performances were compared using five metrics, statistical tests, and uncertainty analysis. These results show that the GMDH model produced better flow prediction capability than the other two models.
      PubDate: 2022-08-03
       
  • Estimation of atmospheric chloride deposition using new model based on the
           theory of perfect gases

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      Abstract: Abstract Understanding atmospheric circulation is essential to study particle transport in the atmosphere. This applies to certain ions (chloride, sodium, calcium, sulfate, lead, and so on) as well as certain radio-elements (cesium, polonium, tritium, etc.…). The transfer factors are primarily controlled by atmospheric dispersion and diffusion. The spatial distribution and estimation of chloride deposits in precipitation are more than necessary for such use and quantification of recharge. The aim of this paper is to calculate the annual deposition of atmospheric chloride in the semi-arid area of Djelfa using a model derived from the perfect gas theory. This model, described as parsimonious, includes two basic parameters: rainfall and temperature. It is particularly useful in semi-arid areas with varying precipitation over time and space. Overall, this new numerical modeling approach emphasizes the importance of quantifying the distribution of chloride deposition in watersheds where data is frequently missing or scarce. Its implementation on site allowed the measurement of chloride mass deposition rates ranging from 1.52 to 31.70 g/m2/year with an average of 13.41 g/m2/year. Over the entire catchment area (1300 km2), the average annual deposit is around 13,500 tons/year.
      PubDate: 2022-08-03
       
  • A modeling approach for evaluating the impacts of Land Use/Land Cover
           change for Ziway Lake Watershed hydrology in the Ethiopian Rift

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      Abstract: Abstract Many parts of the Ethiopian Rift are undergoing significant Land Use/Land Cover (LULC) changes. In many places, the natural LULCs are converted into agricultural land to sustain the increasing food demand arising from a rapidly growing population. Modelling the responses of LULC changes on the hydrology of the area at the watershed scale is crucial for sustainable development of land and water resources. This study investigates the historic LULC change and its potential impacts on the hydrology of Ziway Lake Watershed in the Ethiopian Rift. Commonly, such assessments are accomplished by integrating physically based and semi-distributed hydrological model with Remote Sensing and Geographic Information System techniques. A hybrid LULC classification approach was applied to classify Landsat images of 1985, 1995, 2005 and 2020 and detect the LULC changes in the watershed. Subsequently, Soil and Water Assessment Tool was utilized to simulate the response of the hydrological process (water balance and stream flow) to LULC changes from 1985 to 2020. The image classifications of 1985, 1995, 2005 and 2020 revealed four LULC maps with eight LULC types. The relative change assessment results in the past 35 years from 1985 to 2020 revealed that the major expansion in Settlement, Cultivation and Agroforest resulting in a reduction of Woodlands. However, 58.3% of the watershed has remained intact while 41.7% has shown some degree of change. At the watershed level, these LULC changes had increased SURQ (87.07%), WYLD (31.86%) and ET (4.91%). Conversely, the observed change had reduced PERC (63.22%). But, the spatial analysis of the water balance components due to LULC changes were found to be non-uniform across the watershed. On the other hand, the seasonal stream flow analysis results indicated that Katar flow is increased by 15.36% and declined by 3.86% during the wet and dry seasons, respectively. Similarly, Meki flow showed a decrement during the dry seasons and an increment during the wet seasons by 7.04% and 20.66%, respectively. Beside the observed change, the results of the hypothetical LULC change scenarios justified a pronounced impact of historic LULC change on the water balance components of the watershed. These change in hydrological components and stream flow substantially attributed to the transformation of Woodland to agricultural land. Among the water balance components, the increment of SURQ may have a wider implication for increasing soil erosion and lake bed siltation. The continuous decline in PERC also highly affected the available groundwater resource of the watershed. The study will have significance for watershed managers and decision makers to improve the LULC and water management practices in the area by formulating mechanisms to maintain a sustainable hydrological balance in the watershed.
      PubDate: 2022-08-02
       
  • Experimental and numerical analyzes of parallel drains series performance
           in earth dams

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      Abstract: Abstract This paper aims to provide a tool for sizing the drain spacing and length of a series of parallel drains based on the geometry of the dam and the upstream water level. This technique, adopted for small dams not exceeding 15 m in height, has certain advantages such as ease of use, construction materials’ availability, and cost-effectiveness. Before checking the influence of the spacing and the length of the drains on the leakage rate, the interstitial pressure, the phreatic line, and the hydro-mechanical stability of the structure, experiments on a physical model made it possible to validate the numerical model. Experimental and Plaxis 3D results are in good agreement for flow rates and pore pressure. The numerical parametric study carried out for several combinations of spacing and length of the drains shows that the spacing of the drains depends on several parameters, such as the drain length, the embankment height, and the downstream slope. To minimize the leakage flow rate, the maximum length of the drains should not exceed one-third of the base of the backfill. The results of the numerical application on a real dam (reservoir of Oued El Magroune) by integrating the proposed drainage system and those with the existing drainage system (horizontal drain) show the reliability of this choice.
      PubDate: 2022-08-01
       
  • Adaptation of the revised universal soil loss equation (RUSLE) to soil
           loss modeling in a semi-arid watershed: a case study from western high
           atlas, Morocco

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      Abstract: Abstract Soil loss called also soil erosion is one of the most irreversible natural phenomena that affect the topsoil of Earth’s surface worldwide, as it causes soil fertility reduction, water availability decrease, and initiation of geo-hazards, which leads to negative repercussions on agricultural production, considered the main source of income for most of the autochthonous in the moroccan High Atlas. Due to its climatic and anthropogenic conditions, this region is considered one of the most vulnerable areas to soil erosion in Morocco, with consequential environmental and socioeconomic concerns. This study assesses soil loss in the upstream part of the High Souss watershed in the moroccan western High Atlas, using an integrated analysis of Remote Sensing, GIS, and the Revised Universal Soil Loss Equation (RUSLE). This assessment is based on the integration of different influencing factors: climate, soil erodibility, topography, vegetation cover, and soil conservation practices. Results reveal that the High Souss watershed is exposed to significant erosion, with an average soil loss of 57.27 t/ha/year and an annual erosion amount of 7.3 million tons. This rate is considered to be intensively high in the moroccan context. Moreover, areas subjected to intensive erosion risk are mainly located in the upstream part of the basin, where moderate to steep slope lands are concentrated. The used methodology and results have been compounded to facilitate the analysis of this risk, providing an important basis for government decision-makers, helping the design of meaningful conservation planning programs to reduce soil erosion and conserve natural resources, thus supporting regional development.
      PubDate: 2022-08-01
       
  • Soil loss assessment by RUSLE in the cloud-based platform (GEE) in Nigeria

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      Abstract: Abstract This study was conducted to predict annual soil loss at the district level in Nigeria for proper conservation measures. The method applied was the revised universal soil loss equation (RUSLE) and all factors used in RUSLE were calculated using Earth Engine’s public data archive. The pattern of soil loss was obtained using the spatial autocorrelation (Morans I) statistic. Ordinary least squares (OLS) linear regression model was used to estimate soil loss in terms of the relationships to its factors R, K, LS, C, and P. The grouping analysis tool was used to group districts based on soil loss. The results indicate that the estimated spatial average soil erosion was 7141 t ha−1 y−1 in Nigeria. The pattern of soil loss at the district level was found highly clustered with a z score of 10.045. The results obtained from linear regression were statistically significant p value (p < 0.01) and adjusted R-Squared (0.87). Twenty-six districts were identified in the very high category of soil loss based on standardized residuals above 1.5. The grouping analysis shows that the districts within groups 2 and 3 are in the outlier positions of soil loss due to the high LS factor. This work highlights valuable information for decision-makers and planners to take suitable land administration measures to minimize the soil loss in the districts of high soil loss. It, therefore, indicates Google Earth Engine is a significant platform to analyze the RUSLE model for evaluating and mapping soil erosion quantitatively and spatially.
      PubDate: 2022-07-31
       
  • Derivation of unit hydrograph using genetic algorithm-based optimization
           model

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      Abstract: Abstract The surface runoff can be predicted using hydrographs, and hence, the hydrographs become a prerequisite in designing hydrologic structures. The concept of unit hydrograph have been used widely in the field of hydrology in the past. There are different methods for the derivation of unit hydrographs like the ordinate method, matrix method, and the method of linear programming. In this study, a Genetic Algorithm-based optimization model has been created to identify the ordinates of unit hydrograph [U] to obtain a unique solution and avoid the challenges connected with the inversion of [P]T[P] matrix. The excess rainfall and direct runoff data sets are used to create an objective function for this purpose. The sum of the squares of the difference between the observed and the simulated direct runoffs is used to get the objective function. The simulated direct runoff values can be computed using the convolution equation [P][U] = [Q]. The Genetic Algorithm is then used to minimize the objective function in order to discover the ordinates of the unit hydrograph while taking into account, respectively, the 80%, 10%, and 10% of the total population size for elitism, crossover, and mutation. The root-mean-squared error of predicted values for three datasets obtained from the literature has been computed as 0.0126, 5.108, and 5.292.
      PubDate: 2022-07-27
       
  • Impact of initial conditions on modelling extreme precipitation: case of
           November 29–30, 2010 floods over Morocco

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      Abstract: Abstract Extreme Precipitation is a weather hazard that affects the society directly and harmfully. Because of the process involved in the formation of precipitation at several spatial and temporal scales, the forecast of precipitation is still challenging the weather models. The aim of this work is to evaluate the impact of initial condition on the modelling of extreme precipitation by the Numerical Weather Prediction (NWP) limited area model ALADIN (Aire Limitée Adaptation dynamique Developpement INternational) at 10 km horizontal resolution. The case study corresponds to the extreme flooding event of November 29–30, 2010 across Morocco with daily precipitation reaching 178 mm over Casablanca city. A detailed description of the atmosphere dynamic during this event is given to help the understanding of the precipitation generation. Several experiments were performed to assess the impact of conventional and satellite data. Furthermore, sensitivity studies were carried out for the surface initialisation and the start mode. The assimilation experiment with an optimal setting had produced dynamical fields that were more favourable for the heavy precipitation occurrence. The evaluation of precipitation forecast has been performed by comparison to the surface precipitation observations. The results showed that the combined surface/upper-air assimilation of both conventional and satellite observations produced a clear improvement in term of precipitation location and intensity forecast.
      PubDate: 2022-07-26
       
  • Evaluating the dynamics of hydroclimate and streamflow for data-scarce
           areas using MIKE11-NAM model in Bilate river basin, Ethiopia

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      Abstract: Abstract Dynamics of hydroclimatic factors in Bilate basin of Ethiopia have altered rainfall–runoff and hydrological processes. The objective is to generate streamflow in the area with restricted hydrometric data and predicting rainfall–runoff under varying climatic conditions. Limited study has been done on estimating streamflow in ungauged catchments due to lack of sufficient hydrometric information in this basin. Using multiple linear regression (MLR)-based regionalization and the deterministic, lumped, and conceptual hydrological MIKE11-NAM model, surface-runoff systems and river flow conditions have been studied elaborately. Hydro-climatic data from 1995 to 2020 were utilized as input to the model. The total stretch of years is distributed into three parts that includes the warm-up period (1995–1997), calibration (1997–2012), and the remaining for validation (2012–2020). Rainfall has been observed to be in decreasing order especially during the spring and summer. Streamflow in the basin is expected to decrease during the dry months due to decrease in precipitation and rise in temperature. During calibration and validation, the R2 values and water balance error were 0.83 and 4.9, and 0.76 and 8.6, respectively. The model’s average yearly flow during calibration is 253.9 mm/year. Streams originating from the northern, northwest, and southwest highlands feed the river with a maximum inflow of 188.86 m3/s, comprising of 44% of the basin’s mean annual streamflow. The basin’s central part has the lowest mean annual streamflow of 112.62 m3/s (26% of total flow). The average streamflow in the non-observable catchment is 130.37 m3/s over the years. The MIKE11-NAM model has an advantage over any other model when the landscape is rugged, inaccessible, and availability of limited data from the gauging stations.
      PubDate: 2022-07-25
       
  • Understanding the genesis of a dense fog event over Delhi using
           observations and high-resolution model experiments

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      Abstract: Abstract The present study aims to understand the three-dimensional structure of a dense fog event during the Winter Fog Experiment (WiFEX) 2016–2017 carried out at the Indira Gandhi International Airport (IGIA). The event is analysed with the help of ground-based measurements and the Weather Research and Forecasting (WRF) model. Sensitivity experiments were conducted using different initial conditions and compared to various observations. We find that higher resolution dynamical downscaling and the initial conditions from the Indian Institute of Tropical Meteorology’s Global Forecasting System (IITM-GFS) database yield satisfactory agreements with the observations carried out during the fog event. We note that a strong surface inversion layer exists in the model and observations before the fog onset. Once the fog forms, the simulations suggest that the fog layer grows vertically, destabilizing the temperature stratification. The intensity of the longwave radiative cooling near the fog top increases as the fog grows vertically and shows maximum liquid water content (LWC) near the fog top. The vertical evolution of fog in the model is well identified by the intensity of turbulent kinetic energy (TKE), which is low before the development of dense fog and endures more TKE as the fog becomes dense and vertically thick. The results demonstrate that the WRF model captures the complexity of the physical process and their interaction during the fog evolution in a manner that can be explored further to improve the accuracy of the operational fog forecast.
      PubDate: 2022-07-25
       
  • The effect of growth compounds with different doses on physiological
           characteristics of rice in the treasury

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      Abstract: Abstract To examine the effect of application of humic acid, folic acid, and seeding treatment with various levels of phosphorous compounds on vegetative characteristics, yield and nutrient uptake capacity of rice (Tarom cultivar) in the nursery at different sowing dates, a split-split plot experiment in a randomized complete block design (RCBD) was performed with three replications in Sari in 2017 and 2018. Experimental factors included an equal combination of humic acid and folic acid as the main factor in the four levels of control and, 3, 6 and 9 g/l, the combination of phosphoric acid solution and monoammonium phosphate as the sub-factor in the four levels of control and 5, 10 and 15 g/l, and the planting date as a sub-sub-factor in three levels in March 10th, March 19th and March 30th. The results revealed that the application of humic acid and folic acid increased root length and the wet and dry weight of the plant compared with the control, and the greatest effect was obtained in the treatment of 6 g/l humic acid and folic acid. The application of humic acid and folic acid caused an increase in the grain and straw nitrogen and the grain phosphorus content but a decrease in the straw phosphorus content. Feeding the seedlings with phosphorus compounds led to a significant increase in the root length and the wet and dry weight of the plant compared with the control. The greatest effect was observed in the treatment of 10 g/l of different phosphorus compounds. Feeding the seedlings with phosphorous compounds increased the nitrogen and phosphorus contents of the grain and straw. Also, the maximum root length and the wet and dry weights of the plant were obtained on the planting dates of March 10th and 19th. In general, it was observed that the greatest dry weight of the plant was 1.017 g, belonging to the treatment of consumption of 6 g/l humic acid and folic acid with 10 g/l of various phosphorus compounds planted on March 10th. The highest amount of white rice (64.18%) was related to the treatment of 10 g/l phosphorus. On planting date, 24 April, more white rice (63.59%) was obtained than the planting dates of 14 April (62.34%) and 4 May (61.28%). The simple correlation between the measured traits showed that the amount of white rice had a positive and significant correlation (at the level of 1% probability) with all measured traits except gel consistency and hard rice and had a significant negative correlation with a gel consistency and hard rice husk.
      PubDate: 2022-07-21
       
  • Towards automating irrigation: a fuzzy logic-based water irrigation system
           using IoT and deep learning

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      Abstract: Abstract Among the developing countries, India is one of the fastest-growing economies in the world today, and a considerable part of this economy is dependent on its agricultural sector. The country also boasts the world’s second-largest population, implying that resource scarcity is constantly a concern. Fresh water is one of the most crucial and precious resources. We also have unpredictable monsoons and isotropic climate conditions to contend with. For many years, traditional techniques have been utilized to irrigate gardens and farms. This technique still needs automation in order to reduce the time and effort required for manual examination. We present a model for an automated watering system that attempts to reduce both human interaction and water usage. Our system offers a simple interface for cultivating in various settings, from home to industrial. This system will use data from soil moisture sensors and images of crops acquired by a camera and weather forecasts via the application programming interface (API). In addition, we used a deep learning model to classify captured images into a droop and healthy class. Finally, our fuzzy logic algorithm aggregates all these parameters and regulates the irrigation system’s operation time.
      PubDate: 2022-07-09
       
  • Seismic hazard assessment of the Hajiabad tunnel site, south of Iran, as
           determined from deterministic and probabilistic analysis approaches

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      Abstract: Abstract In this research, seismic hazard assessment of the Hajiabad tunnel site in the Hormozgan province, southern Iran, have been determined using deterministic and probabilistic seismic hazard analyses models, and the obtained results have been detailly analyzed and discussed. For this purpose, active seismic sources and faults in a radius of 100 km of the tunnel site have been identified, and their characteristics such as orientation and their distances from the site were determined. Then, the maximum credible earthquake and peak ground acceleration due to the activity of the faults have been calculated using the above-mentioned approaches. Finally, the maximum horizontal and vertical ground accelerations in a 50-year time period for different levels of seismic design have been calculated using the reduction relations for the input, middle, and output sections of the tunnel. In the studied site, there is possibility to occur earthquakes with magnitude higher than 4 in Richter scale, which can cause a maximum ground acceleration of 0.3 g. The annual occurrence probability of the earthquakes greater than 4, 5, 6, and 7 Richter in a 111-year time period are 1.495, 0.360, 0.081, and 0, respectively. Thus, their return periods are 0.669, 2.775, 12.333%, and ∞ years, respectively.
      PubDate: 2022-07-09
       
  • Spatiotemporal trend analysis of runoff and actual evapotranspiration in
           Northern Algeria between 1901 and 2020

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      Abstract: Abstract In water resources management, the estimation of the water balance component is mainly used to control dams, agriculture, and irrigation developments and also to provide water supply for drinking and industry. The spatial trend analysis applied to the Northern Algerian region to determine the significant changes in rainfall–runoff (IARR) and actual evapotranspiration (IAEa) required a sufficient period. In this study, we carried out this analysis in four periods between 1901 and 2020, according to the data availability of climate variables (IAR, and IAT), since the hydrological measurement posed a big problem during this period. In this regard, a set of nonparametric and empiric water balance models were applied and compared on five bioclimatic floors of Northern Algeria between 1991 and 2020 to estimate IARR and IAEa between 1901 and 1990. The results obtained from several tests, such as regression analysis, scattergram graphs, R2, R2Adj, MSE, RMSE, and DW, proved that Yang's model gives the best performance and good results in very humid regions when replacing n by 2. On the other hand, Schreiber and Pike’s models are more efficient in the humid and semi-humid regions, respectively. Furthermore, the model proposed by Sharif is well performed in the Mediterranean and semi-dry areas. The variability analysis given by the t test and the regression curves is applied on IAEa and IARR in each bioclimatic floor during intervals measurement of [1901, 1930], [1931, 1960], [1961, 1990], and [1991, 2020]. It showed a significant change in both components between 1961 and 1990 in very humid, semi-humid, and Mediterranean regions when compared with observations done between 1931 and 1960. Moreover, a large variation and significant trend in IARR were also observed in humid and semi-humid areas between 1991 and 2020 compared to the previous periods.
      PubDate: 2022-07-09
       
  • Comparison of WEAP and SWAT models for streamflow prediction in the
           Hadejia-Nguru Wetlands, Nigeria

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      Abstract: Abstract Hadejia-Nguru Wetlands (HNWs) is listed as Ramsar wetlands of international importance due to its ecological functions, wild-life biodiversity and socio-economic importance. Accurate streamflow prediction is very important for decision-making in water resources planning and management of the wetland. Two semi-distributed hydrological models, Water Evaluation and Planning (WEAP), and Soil and Water Assessment Tool (SWAT), were used for streamflow prediction in the HNWs that is located within the Hadejia-Jama’are-Komadugu-Yobe Basin, Nigeria. Precipitation and temperature data from 1980 to 2016 were obtained at stations around the wetlands. Likewise, data on streamflow from 1980 to 2010 were collected and used as input to the hydrological models. The models were calibrated (1980–2000) and validated (2001–2010) against the observed streamflow over the periods at three-gauge stations. The performance of the models was compared using Nash–Sutcliffe Efficiency (NSE), Percent Bias (PBIAS) and Root Mean Square Error—Observations Standard Deviation Ratio (RSR). Results of WEAP and SWAT simulation yielded very good performance in terms of NSE (> 0.75) and RSR (< 0.50) at both calibration and validation periods. PBIAS for both model simulations also indicated satisfactory performances at validation period in two out of the three-gauge stations. Both WEAP and SWAT performed well for streamflow prediction thus demonstrating their suitability for streamflow prediction in the HNWs.
      PubDate: 2022-07-09
       
  • Hydrochemical modeling of groundwater quality from Sinai, eastern and
           western deserts, Egypt

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      Abstract: Abstract Groundwater represents the main source of water in Egypt except the area of Nile valley which depends on Nile water. In this study, 23 groundwater samples from Egyptian desert areas were collected from Western Desert, Sinai and Eastern Desert (El Sebayia and Qussier). The present study focused on assessing the hydrochemistry and suitability of groundwater for drinking and irrigation purposes. For deducing the factors controlling water hydrochemistry; Piper, Gibbs and End-member diagrams were applied. The suitability of water for drinking was assessed by water quality index (WQI) model. The applied diagrams indicated that the studied samples are mainly of Ca–Mg–Cl-SO4 facies and controlled by water–rock interaction. The WQI revealed that Western and Eastern deserts groundwater samples are of poor quality for drinking while Sinai groundwater is of marginal quality. The main problem in the Eastern Desert is the salinity, As and Cd content, while in Sinai and Western Desert is heavy metals (e.g. As, Cd, Ni and Pb) surplus the drinking water guidelines. The application of diagrams and models give a good and fast visualization of the chemistry of water. The Western Desert and Sinai groundwater can be used for irrigation safely, but Eastern Desert samples have unacceptable salinity. The occurrence of organic compounds (especially petroleum derivatives) may be attributed to the black shale beds, especially in the Carboniferous Aquifer of Sinai.
      PubDate: 2022-07-07
       
  • Mathematical modeling and optimal control of SARS-CoV-2 and tuberculosis
           co-infection: a case study of Indonesia

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      Abstract: Abstract A new mathematical model incorporating epidemiological features of the co-dynamics of tuberculosis (TB) and SARS-CoV-2 is analyzed. Local asymptotic stability of the disease-free and endemic equilibria are shown for the sub-models when the respective reproduction numbers are below unity. Bifurcation analysis is carried out for the TB only sub-model, where it was shown that the sub-model undergoes forward bifurcation. The model is fitted to the cumulative confirmed daily SARS-CoV-2 cases for Indonesia from February 11, 2021 to August 26, 2021. The fitting was carried out using the fmincon optimization toolbox in MATLAB. Relevant parameters in the model are estimated from the fitting. The necessary conditions for the existence of optimal control and the optimality system for the co-infection model is established through the application of Pontryagin’s Principle. Different control strategies: face-mask usage and SARS-CoV-2 vaccination, TB prevention as well as treatment controls for both diseases are considered. Simulations results show that: (1) the strategy against incident SARS-CoV-2 infection averts about 27,878,840 new TB cases; (2) also, TB prevention and treatment controls could avert 5,397,795 new SARS-CoV-2 cases. (3) In addition, either SARS-CoV-2 or TB only control strategy greatly mitigates a significant number of new co-infection cases.
      PubDate: 2022-07-04
       
  • Stability analysis of rock slopes using kinematic analysis and numerical
           modeling: Foça–Bağarası State Highway, Turkey

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      Abstract: Abstract Slope failures along road cuts and highways pose significant threats to motorists and pedestrians. In this study, the stability of rock slopes along the Foça–Bağarası (FB) Highway in Turkey has been investigated using kinematic analysis and numerical modeling. The investigations were conducted at five survey stations along the highway. The results of the kinematic analysis showed that the joint sets at all the five stations along the FB Highway formed critical intersections that could result in wedge failures. Also, the kinematic analysis results showed significant toppling failure risks along the highway. The results of the finite element analysis showed that the slopes at some of the stations were in a critical state even without the influence of pore pressure. Also, the results showed that should the piezometric surface (or water table) rise to the mid-section of the slopes or higher, there would be a great likelihood of failures occurring. In addition, Strength Reduction Factor values calculated under seismic conditions showed that the slopes had a great vulnerability to seismic activity. The numerical modeling results were consistent with the kinematic analysis results as well as field observations and showed that the FB highway slopes stood a great risk of failure, especially during periods of major rainfall or seismic activity.
      PubDate: 2022-07-04
       
  • An empirical model-based framework for operational monitoring and
           prediction of heatwaves based on temperature data

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      Abstract: Abstract Heatwaves are a major cause of environmental and health hazards. In a global warming scenario, the effect of heat stress associated with the increased frequency of heatwaves makes a large number of people vulnerable over the Indian subcontinent. For the development of a proper heatwave action plan in this region, heatwaves are required to be monitored, tracked, and predicted in real-time. In this study, we propose an operationally deployable empirical model using a set of indices to monitor and predict the heatwaves in the short range over the Indian region in real-time using gridded observation data and reanalysis data. The empirical operational model framework has two major components, (a) index-based monitoring over a spatial domain, and (b) temporal prediction over different locations (i.e. grid points). In the current version of the model framework, three heatwave indices are calculated for component (a), e.g., excess heat index, heat stress index, and excess heat factor index which were found suitable for the Indian region, and elsewhere. The advantage of these percentile-based and mean monthly exceedance-based indices is that they can be used to identify the heatwave affected blocks/districts/cities masking the local fluctuations. In addition, we also incorporate the effect of synoptic information like wind and humidity on heatwave intensity and duration in this component. This model component closely follows the existing operational criteria and the results from several cases are verified. For the second component (b), we have used a simple machine learning based method for the prediction of excess heat factor index to understand the recurrence properties of these indices. This simplistic method provides some reference skills for heatwave based on evolution memories. The results indicate that the overall heatwave indices can be predicted using this simplistic model up to a lead-time of 2–3 days for most of the regions of India.
      PubDate: 2022-07-04
       
 
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