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  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Nature Climate Change     Full-text available via subscription   (Followers: 148)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 144)
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: 69)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Advances in Climate Change Research     Open Access   (Followers: 57)
Journal of Climate     Hybrid Journal   (Followers: 56)
Climate Policy     Hybrid Journal   (Followers: 51)
Climate Change Economics     Hybrid Journal   (Followers: 48)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 45)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 42)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Atmospheric Science Letters     Open Access   (Followers: 40)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
American Journal of Climate Change     Open Access   (Followers: 38)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
Atmosphere     Open Access   (Followers: 33)
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)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (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)
Energy & Environment     Hybrid Journal   (Followers: 25)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
Climate Change Responses     Open Access   (Followers: 24)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 22)
International Journal of Environment and Climate Change     Open Access   (Followers: 22)
Tellus A     Open Access   (Followers: 21)
Current Climate Change Reports     Hybrid Journal   (Followers: 21)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 21)
Climate Resilience and Sustainability     Open Access   (Followers: 21)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 20)
Global Meteorology     Open Access   (Followers: 20)
Journal of Economic Literature     Hybrid Journal   (Followers: 20)
Tellus B     Open Access   (Followers: 20)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Weather and Climate Extremes     Open Access   (Followers: 18)
Weatherwise     Hybrid Journal   (Followers: 18)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Economics of Disasters and Climate Change     Hybrid Journal   (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)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
Climate Risk Management     Open Access   (Followers: 10)
Climate Research     Hybrid Journal   (Followers: 9)
Climate     Open Access   (Followers: 8)
The Cryosphere (TC)     Open Access   (Followers: 8)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Climate and Energy     Full-text available via subscription   (Followers: 7)
Aeolian Research     Hybrid Journal   (Followers: 7)
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 6)
Journal of Climate Change and Health     Open Access   (Followers: 6)
Climate of the Past (CP)     Open Access   (Followers: 6)
Carbon Balance and Management     Open Access   (Followers: 6)
Climate Law     Hybrid Journal   (Followers: 6)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Urban Climate     Hybrid Journal   (Followers: 5)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Climate Services     Open Access   (Followers: 4)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Meteorological Applications     Open Access   (Followers: 4)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Journal of Climatology     Open Access   (Followers: 4)
Frontiers in Climate     Open Access   (Followers: 4)
Atmospheric Environment : X     Open Access   (Followers: 3)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
Environmental and Climate Technologies     Open Access   (Followers: 3)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
Atmósfera     Open Access   (Followers: 2)
气候与环境研究     Full-text available via subscription   (Followers: 2)
GeoHazards     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Mediterranean Marine Science     Open Access   (Followers: 2)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Nīvār     Open Access   (Followers: 1)
Studia Geophysica et Geodaetica     Hybrid Journal   (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]
  • Water quality sustainability assessment using the DPSIRO dynamic model: a
           case study of Ethiopian Lake Tana water

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      Abstract: Abstract Water is an essential and vital resource for global human progress and ecological stability. Water scarcity and pollution are currently very sensitive issues. The study investigates the quality and sustainability of Lake Tana water using a driving force-pressure-state-impact-response-outcome (DPSIRO) model. The assessment presented a systematic methodology of the DPSIRO framework for assessing the situation of Lake Tana in a systematic approach and applying causal relationship analysis to water management. Primary and secondary data collection methods were used along with quantitative and qualitative approaches to gather the necessary data to develop the framework. The result identified the driving forces that lead to pressure and state with expected impacts on the economy, society, and the environment. In the years between 2007 and 2020, the population and GDP of the driving forces ranged from 17,221,976 to 29,190,550 and 113,662.69 million birr to 266,880.15 million birr, respectively. The responses taken by the responsible party to reduce the impact and the expected outcomes obtained from the response are the study's main components. The findings of this study provide evidence for policymakers and form a better understanding of sustainable water management systems.
      PubDate: 2022-06-28
       
  • Dam site suitability analysis using geo-spatial technique and AHP: a case
           of flood mitigation measures at Lower Tapi Basin

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      Abstract: Abstract Dams throughout the Surat district are a key solution for mitigating flood events, enhancing surface water budgets, and creating groundwater recharge locations. The success of this initiative is largely pivotal to finding the finest dam location in the area. Recent improvements in remote sensing (RS), geographic information systems (GIS), and decision-making processes have provided useful tools for mapping Dam Sites Suitability Model (DSSM). Rainfall, stream order, geomorphology, geology, LULC, soil, distance to road, elevation, slope, and major fault fracture are among the ten thematic layers examined in the DSSM's preparation. The most prominent factors affecting the Dam Site Location Map (DSLM) were rainfall and stream order. The analytical hierarchy process (AHP) technique is one of the Multi-Criteria Decision Making (MCDM) technique which was used to establish the weights of the thematic map layers. The overlayed map visualizes five classes of suitability, from very high to very low suitability regions. On the basis of a suitability map for the constructing dams in Surat, three suitable dam locations with high and very high suitability were identified. The study provides decision-makers with a useful and very inexpensive tool for identifying the areas with high restrictions (low appropriate site) and concentrating on area with fewer restrictions for a more apposite location for the construction of dams. In terms of percentage, 15.03% of Surat lies in the range of very low suitability, and 14.33% lies in the low suitability area. A maximum of 29.51% of the area lies in the moderately suitable region of the Surat district. 27.19% for the highly suitable area of Surat city, and 13.94% of the area for very high suitability area. So this gives us approximately 40% of the area are more suitable to construct the dam in the region. A novel approach of integrating GIS and MCDM techniques in determining the suitable dam site location for the study area has been carried out effectively.
      PubDate: 2022-06-28
       
  • Integrated approach to modelling and assessing the landslide hazards at
           the regional and local scale in Kyiv urbanized area, Ukraine

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      Abstract: Abstract The landslide hazards have become a common phenomenon in the Kyiv urbanized area in Ukraine. The susceptibility mapping indicates only the relative stability of slopes without absolute predictions. For the absolute prediction at the local level the field work, monitoring and numerical modeling of landslide processes within landslide-prone slopes has been provided. Site Lysa Gora is typical for the Kyiv landslides with the unstable slopes; it is the historical place of fortress. The landslide on this slope has a great impact on the infrastructure including railway and highway. The determination of the stress-strain state of a landslide slope demonstrate the approaching to a state of marginal equilibrium. Mottled clays, which are the main deforming horizon for landslide formation have a solid to semi-solid consistency, weakly compressible, highly plastic, weakly swelling, with low resistance to shear loads (0.01 KPa) and significant deformation values (40 KPa). Electrical resistivity tomography measurements revealed two local zones of activation of landslide displacements, which are located in the range of depths of 3–8 m from the ground surface. The random distribution of the soil magnetic susceptibility (χ, MS) and frequency dependence of the magnetic susceptibility (χfd) in the topsoil as well as in the vertical soil genetic horizons confirm the occurrence of the displacement, redistribution and newly deposition of the soil and deposits related to the erosion and landslide processes. The results demonstrate that the landslide process could be activated in case of heavy precipitation and changing the safety factor.
      PubDate: 2022-06-27
       
  • Using petrophysical and geomechanical modeling of reservoir rock in well
           completion

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      Abstract: Abstract The first step in completing an oil well is determining the quality layer in the reservoir rock. To this end, it is required to assess the reservoir in terms of petrophysical and dynamic aspects. Research has shown that the geomechanical evaluation of reservoir rock can also be effective in the more accurate selection of the appropriate layer for well-completion operations. This study selected the best water saturation model and determined the failure criterion and safe and stable mud weight window for the Ahvaz oil field in southwestern Iran. First, Archie, Hossin, Simandoux, Doll, Juhasz, Schlumberger, and Indonesia Equations were used to calculate the Asmari formation’s water saturation. The results were compared with double-layer models (developed by lab data) used for measuring water saturation. It was found that the Indonesia model is the best one for measuring water saturation. Then, the geomechanical properties of the reservoir were analyzed using the information gained from the petrophysical logs. Afterward, geomechanical evaluation and analysis were performed based on Mogi–Coulomb Failure Criterion using the measured properties. The failure type of the formation was determined using the evaluation results. According to the results, the stress regime of the Asmari Formation in the Ahvaz oil field is a normal stress regime. The minimum and maximum allowable mud weight pressures follow the shear wide breakout (SWBO) model and shear deep knockout (SDKO) model, respectively. Finally, the stable mud weight window was determined by setting the allowable limits of the mud pressure.
      PubDate: 2022-06-27
       
  • Investigating the characteristic of hydraulic T-jump on rough bed based on
           experimental and numerical modeling

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      Abstract: Abstract Hydraulic jumps are recognized as inevitable phenomena that form when the supercritical flow induced by hydraulic structures transmits to the subcritical downstream flow. One of the common approaches to controlling the energy generated by hydraulic jumps is to expand the section of the stilling basin. The present paper aims to investigate the main characteristics of the gradual expanding T-jump on the rough bed open-channel. In this regard, a range of Froude numbers between 3 and 14, four diverging angles of transition (θ = 15, 22.5, 30, and 60º), and five rough beds (Ks = 2, 3, 4, 5, and 6 mm) were selected. Experimental results reveal when the height of the bed roughness is increased, it reduces the length of the T-jump, roller jump, and the secondary depth of the T-jump. Likewise, the same result is unfolded for the increase of divergence angle of the transition. The normalized length of the T-jump in terms of sequent depth of classical jump Lj/y*2 is estimated at around 3.73, confirming that the length of the gradual expanding T-jump on the rough bed is smaller than the classic jump and the smooth bed. The average amount of secondary depth reduction is accounted at approximately 30.51%, indicating that the tail-water depth required to form a T-jump is remarkably smaller than those corresponding quantities in the classic jump and the smooth bed. In addition, the results of simulated T-jumps demonstrate good agreements with the experimental ones. Numerical quantities show the secondary depths of the T-jumps on a rough bed experience approximately 12.9% and 16.8% reductions compared to the smooth bed. Besides, 2D variations of flow velocity illuminate the role of the dead zone areas that reduce the total length of the T-jumps. The findings of the present research would be of prominent importance in designing stilling basins to control significant energy induced by hydraulic jumps.
      PubDate: 2022-06-27
       
  • Modeling of complex flooding and sedimentation events on the downstream
           portion of the Yellow River using a 1-D model

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      Abstract: Abstract A river management assignment requires a good understanding of the river system. At present, river system modeling applications are used to understand a complex river system. The advantages of a relatively easy application and the reduced data requirement make 1-D models more suitable for river system modeling. As part of this research, the compatibility of the 1-D model was assessed on a complex river system in the downstream section of the Yellow River. The approach helps to understand the extent to which 1-D models can be applied to a complex river system. Most of the time, the complex river system was believed to be solved through a more advanced application. Mike Hydro Geographic Information System (GIS) component was used to process a Digital Elevation Model (DEM) to extract the cross section and the alignment of the river. The data on the modeling processes are a combination of observed data from government agencies and extracted from online sources, such as an Alaskan satellite facility. Model discharge outputs at Aishian and Lijin stations show good agreement between an observed and simulation event, which was supported by high values of performance indicators. On the other hand, the maximum suspended concentration simulated using the 1-D model was 30 kg/m3 on a single day. This value is nearly equal to the maximum average long-term suspended sediment concentration in the history of the Yellow River. Therefore, models, such as Mike 11, can be applied for an average load computation in any highly sediment concentrated rivers.
      PubDate: 2022-06-27
       
  • Rainfall-runoff modeling using airGR and airGRteaching: application to a
           catchment in Northeast Algeria

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      Abstract: Abstract The objective of this study is to apply the rainfall-runoff modeling, for the reconstruction of flows and the forecasting of hydrological risks in two sub-catchments (Bounamoussa and Kebir-Est) located in El-Taref, North-East of Algeria. Considering the geomorphological and climatic characteristics of the study region, redundant and catastrophic floods have been recorded. The available data cover a period of 39 years (1981–2019). The GR2M model (GR at monthly time step) is implemented by using two R packages; airGR and airGRteaching. These tools enable the automatic affectation of the parameters that control the two reservoirs of the GR2M model, X1 (production function) and X2 (routing function). This modeling is optimized by the parsimonious character of the model; requiring few monthly input data: rainfall, temperature and potential evapotranspiration. As for its robustness, it is provides by Michel's algorithm. The evaluation of its efficiency is determined, for the calibration and validation periods, by the Nash–Sutcliffe (NSE), Killing-Gupta (KGE) and modified Killing-Gupta (KGE′) criteria. The airGR package gives NSE (Q) and KGE (Q) values greater than 80% during the calibration period and greater than 86% during the validation period. For the airGRteaching package, the KGE′(Q) values vary from 89 to 92% for both periods. Production and routing reach values successively: (99.50 mm, 36.22 mm) in the Bounamoussa sub-catchment and (125.12 mm, 33.70 mm) in the Kebir-Est sub-catchment. Thus, this study shows the capacity of this model to correctly reproduce the flows of this basin, although heterogeneous.
      PubDate: 2022-06-27
       
  • Assessing the perceived spatial extent of a flood using cognitive mapping:
           

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      Abstract: Abstract Flooding is considered one of the disastrous natural hazards that can inflict significant damage to lives, the environment, infrastructure, and public services. With the increased magnitude and occurrence of floods, a paradigm shift in flood risk-management strategies has been observed from structural interventions to a multi-faceted resilience-oriented approach. The need is to apprehend the perception of vulnerable populations for effective social resilience, risk communication, and coping capacity. This study aims to quantify the community’s risk perception by applying a contemporary approach, i.e., cognitive mapping. A survey was conducted in rural communities of Muzaffargarh, Pakistan, where four union councils were further selected for the survey. The selection criteria included past experience with the 2010 floods and proximity to rivers. Yamane sampling technique was used to determine the required sample size, and 365 respondents were involved in outlining their 2010 flood memories. GIS was used for the visualization and conversion of these delineations into vector data. Based on the community’s perception, scoring and Kernel density were applied to rank each settlement and to show the perceived spatial extent of the 2010 flood. These cognitive maps were then assessed based on age groups and proximity to the source of risk. Results show that the spatial extent of the flood perceived by the older age group was comparatively higher. Similarly, households living far away from rivers tend to perceive a larger spatial extent of flood risk. This study proposes cognitive mapping as a potential method for assessing flood risk perception.
      PubDate: 2022-06-25
       
  • CMIP6 multi-model evaluation of summer extreme precipitation over East
           Asia

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      Abstract: Abstract We provided an overview of individual CMIP6 models and their multi-model ensemble effectiveness in representing both spatial and temporal variation of summer precipitation characteristics across East Asia. The historical runs of the eleven individual CMIP6 models and their ensemble were compared against GPCP gridded observed precipitation for the historical timescale of 1997–2014, with a particular emphasis on the summer monsoon season to evaluate their performance. We quantitatively investigated the individual skill of a selection of models from the CMIP6 experiment and the mean of their ensemble in representing summer precipitation extreme over East Asia using some selected statistical metrics, i.e., normalized mean bias error, normalized root mean square error, which are summarized by the inter-annual variability score (IVS), pattern correlation coefficient (PCC), Taylor skill score, portrait diagram, and the Taylor diagram. Based on the "portrait" diagram and skill score ranking, we indicated that E3SM-1-0, CESM2, BCC-ESM1, Ensmean, and KIOST-ESM were the top five models which performed relatively well in representing both the spatial distribution and inter-annual variability for all five extreme precipitation indices. Additionally, over the mountainous regions of Bangladesh, Nepal, Laos, and Burma, all CMIP6 models overestimated the annual mean of total precipitation on wet days. The vast majority of CMIP6 models were capable of accurately depicting the geospatial extent of all five of the summer extreme precipitation characteristics that were evaluated in the study.
      PubDate: 2022-06-25
       
  • Prediction of the compressive strength of concrete made with soap factory
           wastewater using machine learning

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      Abstract: Abstract In recent years, the reuse of wastewater for making concrete has become a major issue for actors in the field of civil engineering. This paper used artificial neural networks (ANN) to estimate the compressive strength of concrete made with soap factory effluent water. Input parameters included amount of water, amount of cement, water/cement ratio, superplasticizers, fine aggregate, coarse aggregate, and age of maturation. A prediction equation for the compressive strength of concrete has been proposed. Mean squared error (MSE), coefficient of determination (R2), and mean absolute error (MAE) were used to assess model performance. The performance of the model was then compared with that of other studies. A parametric study was carried out to evaluate the influence of the variation of the input parameters on the strength of the concrete. The results we obtained showed that the use of the ANN technique has very good performance for predicting the compressive strength of concrete made with soap factory effluent water.
      PubDate: 2022-06-25
       
  • A gamma mixture model-based approach for the estimation of natural
           background levels of $${{\mathrm{NO}}_{3}}^{-}$$ NO 3 - –
           $${\mathrm{N}}$$ N in groundwater

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      Abstract: Abstract The first stage in determining the chemical status of a groundwater body in an aquifer system is to determine natural background levels (NBLs). The various sources of \({{\mathrm{NO}}_{3}}^{-}\) – \({\mathrm{N}}\) in an environment as well as the interaction of natural and anthropogenic processes, present considerable obstacles in determining NBLs. Another constraint on NBL estimation is choosing the right statistical technique. In this paper, the \({{\mathrm{NO}}_{3}}^{-}\) – \({\mathrm{N}}\) levels of groundwater and the high-risk zones in the Densu Basin were evaluated. The evaluation was done using the Gamma mixture probability distribution and the iterative outlier removal technique. We also considered the strengths and weaknesses of these two models by assuming the \({{\mathrm{NO}}_{3}}^{-}\) – \({\mathrm{N}}\) concentration is coming from a single source. The Gamma mixture model was used to identify the sub-populations in the \({{\mathrm{NO}}_{3}}^{-}\) – \({\mathrm{N}}\) data set and also, estimate the optimal parameters for the hidden clusters. The initial component with the lower \({{\mathrm{NO}}_{3}}^{-}\) – \({\mathrm{N}}\) concentration was considered as the NBL. This was measured at \(2.56\pm 2.56\) mg/L, whereas considering a single source the iterative technique recorded the NBL at \(5.6\pm 5.3\) mg/L. Assuming the groundwater contamination is from a single source, then the iterative method introduces an error of \(3.1 \pm 2.8\) mg/L in the NBL estimation. The result suggests that the Gamma mixture model is more robust in estimating pollution with multiple sources (that is, natural and human-induced sources).
      PubDate: 2022-06-25
       
  • Diagnosing similarities in probabilistic multi-model ensembles: an
           application to soil–plant-growth-modeling

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      Abstract: Abstract There has been an increasing interest in using multi-model ensembles over the past decade. While it has been shown that ensembles often outperform individual models, there is still a lack of methods that guide the choice of the ensemble members. Previous studies found that model similarity is crucial for this choice. Therefore, we introduce a method that quantifies similarities between models based on so-called energy statistics. This method can also be used to assess the goodness-of-fit to noisy or deterministic measurements. To guide the interpretation of the results, we combine different visualization techniques, which reveal different insights and thereby support the model development. We demonstrate the proposed workflow on a case study of soil–plant-growth modeling, comparing three models from the Expert-N library. Results show that model similarity and goodness-of-fit vary depending on the quantity of interest. This confirms previous studies that found that “there is no single best model” and hence, combining several models into an ensemble can yield more robust results.
      PubDate: 2022-06-19
       
  • Assessment of integrated water vapor derived from AROME model using GPS
           data over Morocco

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      Abstract: Abstract A good prediction of water vapor is a key element to improve the forecast quality of heavy precipitation events. The aim of this work is evaluating the integrated water vapor (IWV) from AROME model, for operational meteorological purposes, using IWV data from nine Global Positioning System (GPS) permanent sites in Morocco. This validation was carried out through a statistical assessment for the period from the 20th February 2018 to the 20th March 2018 using 3-hourly forecasts of the AROME model. The results show a good ability of AROME model in simulating IWV, with a correlation coefficient of 0.83 along with a standard deviation of 4.34 mm and a bias about 0.41 mm. In addition, the analysis of an extreme precipitation event in the north part of Morocco was carried out. During this case study an increase in IWV from AROME was observed few hours before the occurrence of precipitation event followed by a sharp decrease. This study demonstrates the good potential of AROME model in predicting IWV especially during rainfall situation, which could be an efficient tool for operational forecasting.
      PubDate: 2022-06-17
       
  • Yield response to climate change and reduced water use: a comparison
           between parent and nuclear-mutant lines of soybean

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      Abstract: Abstract The current study aimed to assess the yield response of two soybean lines, i.e., parent (cultivar L17) and nuclear-mutant, to climate change as well as adopting policies to decrease water use, by benefiting the Decision Support System for Agro-technology Transfer (DSSAT) crop model. In other words, the performance of some modified genotypes was investigated in terms of improvement of crop yield which is the most important parameter of crop growth and development. The superior mutated line (SML) by nuclear method (gamma irradiation) was selected by carrying out several greenhouse and field experiments for 13 years (2001–2013). Consequently, growth and development properties were recorded to calibrate and validate the crop model. Moreover, the MarkSim weather generator was used for downscaling daily weather data (maximum and minimum temperature, precipitation, and radiation) for the period 2021–2030 under three scenarios RCP2.6, RCP4.5, and RCP8.5. Field findings showed that the yield of SML is around 26% more than the parent line. The DSSAT model could simulate this yield increment with RMSE below 7%. Under climate change conditions, the SML yield level was 20–25% higher than that of the parent line suggesting that the SML is more resistant than the parent line to plausible climate change impacts. Nevertheless, adopting policies to decrease water use reduces yield levels of both lines. It confirmed that low-irrigation condition, as an inevitable issue, overcomes possible positive impacts reported by many researchers. Hence, associated water stress should be controlled by cultivating more resilient cultivars. This study recommends cropping the SML line in soybean croplands to sustain crop yield.
      PubDate: 2022-06-08
       
  • An evaluation of Delta and SDSM Downscaling Models for simulating and
           forecasting of average wind velocity in Sistan, Iran

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      Abstract: Abstract In this study, in order to downscaling the wind speed variablilitye in Zabol station (as a representative of Sistan region), SDSM and change factor (Delta) models were used and the results of both models were compared with each other. For this purpose, monthly and daily average wind speed data of Zabol station, and average wind speed data of the Coupled Global Climate Model Version 3 (CGCM3) under A1B, A2 and B1 scenarios and Canadian Earth System Model (CanESM2) under RCP2.6, RCP4.5 and RCP8.5 scenarios for the periods 2039 − 2010, 2069 − 2040 and 2099 − 2070 were used and the output of both models were compared with each other. The results showed that the output of the CGCM3 model under scenario A2 in the Delta model is more conformity with the base period. The output results of CGCM3 and CanESM2 models showed that the average wind speed will increase in the studied periods. The SDSM model under scenarios A1B and A2 predicted an increase in average wind speeds by 2099 of 0.41 and 0.95 m/s, respectively. The Delta model also predicted an average increase in wind speed by 2099 under scenarios A1B, A2 and B1, 0.57, 0.62 and 0.52 m/s, respectively. The results showed that at Zabol station, the Delta model simulated the average wind speed data better than the SDSM model (under scenarios A1B, A2 and B1), but the accuracy of the CanESM2 model is more than other models.
      PubDate: 2022-06-04
       
  • Prediction of reference evapotranspiration in northwestern Africa with
           limited data using factorial and SVM regressions

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      Abstract: Abstract Accurate estimating of reference evapotranspiration (ETo) is of great importance for achieving irrigation scheduling and water management studies. In the absence of lysimeters measurements, which is common in many developing countries, ETo estimating represents a real challenge for the water planners community, they often have recourse to less required-data empirical equations that are frequently associated with low accuracies, or to the well-known Food and Agriculture Organization Penman–Monteith (FAO–PM) equation that necessitates a large number of climatic parameters. The present study aims to develop regional data-driven models for ETo estimating that require a limited number of measured climatic inputs (MCI) coupled with geographic coordinates as auxiliary variables. It explores two modeling methods, namely factorial (FR) and support vector machines (SVMR) regressions. The used data concerned 45 meteorological stations, situated in different climatic zones in northwestern Africa, gathered from FAO databases. Pearson matrix of correlation coefficients was used to explore the most important input combinations. The obtained FR and SVMR models were evaluated relative to FAO–PM equation estimates using the root mean square error (RMSE), the correlation coefficient (R), the RMSE–observations standard deviation ratio (RSR), and the mean absolute error (MAE). The results showed that both explored methods gave satisfactory results with a slight superiority of the SVMR that gave more accurate models. Four models (two FRs and two SVMRs) were pointed out depending on the number of MCI. The best models including two MCI were, FR-BS11 and SVMR11, with RMSEs values of 0.28 and 0.29 mm day−1, respectively; those including three MCI were, SVMR8 and FR-BS8, with RMSEs values of 0.19 and 0.20 mm day−1, respectively. The overall results were useful when dealing with limited MCIs in the study area.
      PubDate: 2022-06-04
       
  • Machine-learning and HEC-RAS integrated models for flood inundation
           mapping in Baro River Basin, Ethiopia

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      Abstract: Abstract This study presents an integrated machine-learning and HEC-RAS models for flood inundation mapping in Baro River Basin, Ethiopia. ANN and HEC-RAS models were integrated as a predictive hydrological and hydraulic model to generate runoff and the extent of flood, respectively. Daily rainfall and temperature data of 7-years (1999–2005), daily discharge (1999–2005) and 30 m × 30 m gridded Topographical Wetness Index (TWI) were used to train a predictive ANN hydrological model in RStudio. The predictive performance of the developed ANN hydrological model was evaluated in RStudio using Nash–Sutcliffe Efficiency (NSE) values of 0.86 and 0.88 during the training period (1999–2005) and testing period (2006–2008), respectively, with the corresponding observed daily discharge. The validated ANN predictive hydrological model was linked with HEC-RAS to generate the flood extent along the river course. The HEC-RAS model result was calibrated and validated using the water body delineated using Normal Difference Water Index (NDWI) from LANDSAT 8 imagery based on historical flood events of 2005 and 2008. It was found that about 96% of an agreement was made between the flood-prone areas generated in HEC-RAS and the water body delineated using NDWI. Therefore, it is logical to conclude that the integration of a machine-learning approach with the HEC-RAS model has improved the spatiotemporal uncertainties in traditional flood forecasting methods. This integrated model is powerful tool for flood inundation mapping to warn residents of this basin.
      PubDate: 2022-06-01
       
  • Modeling the effectiveness of natural and anthropogenic disturbances on
           forest health in Buxa Tiger Reserve, India, using fuzzy logic and AHP
           approach

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      Abstract: Abstract Forests are the most valuable natural resource to protect organisms as well as ecosystem at a different level. With the rising change of land use and land cover pattern due to anthropogenic and natural disturbances, this resource is now subjected to experience constant exploitation and degradation. This paper explored the level of disturbances on forest health in Buxa Tiger Reserve (BTR), a foothill ecosystem of Himalaya. Sentinel-2 data (2019) and fuzzy logic models were executed to understand the forest health status by using different vegetation indices. GIS-based Analytical Hierarchy Process (AHP) was applied to know the beat-wise spatial disturbances of natural and anthropogenic factors in the study area. Then, disturbance maps were categorized into five zones from very high to very low. The result reveal that overall imprint of natural disturbance in BTR was a little bit high (very high = 13.76%, high = 31.58%, moderate = 15.91%, low = 27.03%, very low = 11.72%) in comparison to anthropogenic disturbance (very high = 11.09%, high = 19.07%, moderate = 24.47%, low = 20.01%, very low = 25.36%), but beat wise it varies significantly. Finally, the effectiveness of both disturbances on forest health was judged through correlation statistics. The forest beats (ID: 2, 4, 6, 7) which cover the core area of BTR have experienced less natural and anthropogenic disturbances with healthy and dense forest cover. On the other hand, less disturbance with poor forest health was found in hilly areas of buxa road and chunabhati beats (ID: 9, 15). Moreover, the effective natural and anthropogenic disturbances were mainly responsible to deteriorate the forest health adequately in most of the areas of BTR.
      PubDate: 2022-06-01
       
  • COVID-19 outbreak and air quality of Lahore, Pakistan: evidence from
           asymmetric causality analysis

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      Abstract: Abstract This paper aims to examine the impact of COVID-19 restrictions on the air quality of Lahore city of Pakistan for the period 26th February, 2020 to 31st August, 2020. The study employs asymmetrical Granger causality tests for analyzing the effects of COVID-19 cases and deaths on particulate matter (PM2.5) emissions in the city. The results show positive shocks in COVID-19 cases and deaths improve the air quality of the city. This implies that the pandemic has lowered down environmental pressure in one of the top most polluted cities of the world. Further, the problem of hazardous air pollution in Lahore city is manmade mainly caused by everyday human activities. When these human activities were restricted owing to a rise in COVID-19 cases and deaths, the air pollution in the city resultantly reduces. Therefore, this study recommends controlling unnecessary production and consumption activities that degrades the environment so that air pollution in the city can be manageable after the COVID-19.
      PubDate: 2022-06-01
       
  • Application of CERES-sorghum crop simulation model DSSAT v4.7 for
           determining crop water stress in crop phenological stages

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      Abstract: Abstract The water requirement of the crop is an important phenomenon to estimate the crop yield and understanding the crop water necessity at different crop phenological stages as soil and plant water deficits cause yield reduction. The most crucial crop stages that dictate crop yield are at the vegetative and reproductive stages, reducing the crop yield by more than 35% and 50%, respectively. Our study is to determine the crop water stress using the Crop Environmental Resource Synthesis (CERES)-Sorghum model, which is a component of the Decision Support System for Agrotechnology Transfer (DSSAT)—crop simulation model (CSM). Crop water stress is simulated spatially for Rainfed Kharif Sorghum (Sorghum bicolor (L.) Moench) in 10 districts of Maharashtra state, India, from 2000 to 2018 using DSSAT-CSM. Besides other factors as well that impact crop yield, rainfall also has an impact on crop growth, development, and managing water efficiency for the crops. Simulated crop water stress above a specific threshold value of ≥ 0.5 (50%) impacts crop growth and development process. Considering the drought year 2015 with sowing dates June (15, 22, 29) and July (6, 15); it shows that late sowing of kharif sorghum for 2015 minimal crop water stress can be seen. CERES-Sorghum model can efficiently determine the crop water stress at different crop phenological stages with different dates of sowing.
      PubDate: 2022-06-01
       
 
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