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  Subjects -> METEOROLOGY (Total: 113 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: 39)
Advances in Meteorology     Open Access   (Followers: 28)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 10)
Aeolian Research     Hybrid Journal   (Followers: 6)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 20)
American Journal of Climate Change     Open Access   (Followers: 34)
Atmósfera     Open Access   (Followers: 3)
Atmosphere     Open Access   (Followers: 29)
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: 48)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 16)
Atmospheric Environment     Hybrid Journal   (Followers: 75)
Atmospheric Environment : X     Open Access   (Followers: 3)
Atmospheric Research     Hybrid Journal   (Followers: 71)
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: 51)
Carbon Balance and Management     Open Access   (Followers: 5)
Ciencia, Ambiente y Clima     Open Access   (Followers: 3)
Climate     Open Access   (Followers: 6)
Climate and Energy     Full-text available via subscription   (Followers: 7)
Climate Change Economics     Hybrid Journal   (Followers: 33)
Climate Change Responses     Open Access   (Followers: 18)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Climate of the Past (CP)     Open Access   (Followers: 5)
Climate of the Past Discussions (CPD)     Open Access  
Climate Policy     Hybrid Journal   (Followers: 51)
Climate Research     Hybrid Journal   (Followers: 6)
Climate Resilience and Sustainability     Open Access   (Followers: 21)
Climate Risk Management     Open Access   (Followers: 7)
Climate Services     Open Access   (Followers: 3)
Climatic Change     Open Access   (Followers: 68)
Current Climate Change Reports     Hybrid Journal   (Followers: 10)
Developments in Atmospheric Science     Full-text available via subscription   (Followers: 31)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 5)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Earth Perspectives - Transdisciplinarity Enabled     Open Access  
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 9)
Energy & Environment     Hybrid Journal   (Followers: 24)
Environmental and Climate Technologies     Open Access   (Followers: 4)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 17)
Frontiers in Climate     Open Access   (Followers: 3)
GeoHazards     Open Access   (Followers: 2)
Global Meteorology     Open Access   (Followers: 18)
International Journal of Atmospheric Sciences     Open Access   (Followers: 23)
International Journal of Biometeorology     Hybrid Journal   (Followers: 1)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 27)
International Journal of Climatology     Hybrid Journal   (Followers: 30)
International Journal of Environment and Climate Change     Open Access   (Followers: 12)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 2)
Journal of Agricultural Meteorology     Open Access  
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 36)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 34)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 212)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 22)
Journal of Climate     Hybrid Journal   (Followers: 57)
Journal of Climate Change     Full-text available via subscription   (Followers: 16)
Journal of Climatology     Open Access   (Followers: 3)
Journal of Hydrology and Meteorology     Open Access   (Followers: 36)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 11)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 1)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 17)
Journal of Space Weather and Space Climate     Open Access   (Followers: 28)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 84)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 6)
Journal of Weather Modification     Full-text available via subscription   (Followers: 2)
Large Marine Ecosystems     Full-text available via subscription   (Followers: 1)
Mediterranean Marine Science     Open Access   (Followers: 1)
Meteorologica     Open Access   (Followers: 2)
Meteorological Applications     Hybrid Journal   (Followers: 4)
Meteorological Monographs     Hybrid Journal   (Followers: 2)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 3)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 27)
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: 16)
Monthly Weather Review     Hybrid Journal   (Followers: 33)
Nature Climate Change     Full-text available via subscription   (Followers: 144)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 38)
Nīvār     Open Access  
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 4)
Open Journal of Modern Hydrology     Open Access   (Followers: 7)
Revista Brasileira de Meteorologia     Open Access  
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access  
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 3)
Space Weather     Full-text available via subscription   (Followers: 25)
Studia Geophysica et Geodaetica     Hybrid Journal  
Tellus A     Open Access   (Followers: 22)
Tellus B     Open Access   (Followers: 21)
The Cryosphere (TC)     Open Access   (Followers: 6)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 28)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 13)
Tropical Cyclone Research and Review     Open Access  
Urban Climate     Hybrid Journal   (Followers: 4)
Weather     Hybrid Journal   (Followers: 18)
Weather and Climate Dynamics     Open Access  
Weather and Climate Extremes     Open Access   (Followers: 16)
Weather and Forecasting     Hybrid Journal   (Followers: 27)
Weatherwise     Hybrid Journal   (Followers: 4)
气候与环境研究     Full-text available via subscription   (Followers: 1)

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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  [2658 journals]
  • Retraction Note to: Investigating the effects of drought on the
           environment in northwestern province of Iran, Ardabil, using combined
           indices, Iran

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      PubDate: 2021-11-01
       
  • Microfacies analysis and depositional development of Shuaiba formation in
           the West Qurna oil field, Southern Iraq

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      Abstract: Abstract The Aptian carbonate succession in this study is represented by the Shuaiba Formation which was deposited during the Early Cretaceous. The present study is including petrography and microfacies analysis for four boreholes WQ-12, WQ-13, WQ-15, and WQ-178 within the West Qurna oil field. There are four major microfacies recognized in the succession of the Shuaiba Formation, bioclastic mudstones to wackestone, Orbitolina wackestone to packstone, Peloidal wackestone to packstone, Miliolids wackestone, and Planktonic and small benthic mudstone to wackestone. The four depositional environments deposited in the Shuaiba Formation are; shallow open marine, Semi-restricted, restricted, and outer ramp environments. The Shuaiba Formation was deposited during two stages of transgression and a high stand of sea level. The first during the change of deltaic—fluvial environment of the Zubair Formation which became open shallow marine environment of the lower part of Shuaiba Formation. The presence of restricted facies overlying the shallow open marine refers to still stand sea level and deposition of high stand deposits and marked the first maximum flooding surface (mfs1). After the high stand deposits and within the upper part the Shuaiba Formation, the facies appeared further deepening upward with observed outer ramp facies to mark the transgressive stage. The second time, overlying the semi-restricted facies for the deeper facies refers to the second stage of still standing sea level (high stand deposits) within the Shuaiba Formation and marks maximum flooding surface (mfs2). The high stand deposits continued shallowing upward until the sea level and fell in all parts of southern Iraq to deposit the deltaic-fluvial deposits of Nahr Umr Formation. This marks the regression stage and sequence boundary type which separates the Shuaiba Formation and Nahr Umr Formation.
      PubDate: 2021-11-01
       
  • Numerical simulation of an extremely severe cyclonic storm over the Bay of
           Bengal using WRF modelling system: influence of model initial condition

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      Abstract: Abstract This study evaluated the performance of advanced research weather research and forecasting (WRF) modelling system in the forecast of extremely severe cyclonic storm (ESCS) over the Bay of Bengal region that made landfall in Bangladesh on 15 November 2007. Model initial conditions were improved using the three-dimensional variational data assimilation (3D-VAR) system of the WRF model. A set of four numerical experiments were also performed with and without data assimilation techniques at two different grid resolutions (1° × 1° and 0.5° × 0.5°) using NCEP global forecasting system (GFS). Satellite and conventional observations were assimilated using the 3D-VAR modelling system. Results from the assimilation experiment confirms that the analysis using 3D-VAR is better compared to the global datasets in both grid resolutions, attributed due to the availability of quality satellite observations during the analysis period. In addition, the forecasted track, landfall location, maximum wind speed and minimum central pressure of ESCS are better predicted with the data assimilation. The study also presents the forecasted structure in terms of rainfall, wind speed, potential vorticity, and cross-section of horizontal wind speed. Overall, the results clearly revealed that modelling using the 3D-VAR assimilation system is very important in the high-resolution WRF model that enhanced the prediction capability.
      PubDate: 2021-11-01
       
  • Mapping and modeling mangrove biophysical and biochemical parameters using
           Sentinel-2A satellite data in Bhitarkanika National Park, Odisha

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      Abstract: Abstract Mangroves are Earth's most active and diversified saline wetlands, which play an essential role in protecting coastal communities from storm surge, cyclonic winds, tsunami, and tidal waves. Space-borne satellite data provide vital information for monitoring mangrove and retrieving health-related parameters. The objective of this study is to map and model biophysical and biochemical parameters of mangrove forests over the Bhitarkanika reserve forest located on the eastern coast of Odisha. The present study has employed Sentinel–2A sensor's red-edge bands to derive both the aforementioned parameters. Furthermore, the near-proximal sensor (NPS) data were integrated with satellite data for mapping leaf chlorophyll and nitrogen contents with the help of an empirical model. The key findings indicate that EVI (Enhanced Vegetation Index) and measured leaf chlorophyll were significantly and positively correlated (R2 = 0.78). EVI showed a stronger relationship with foliage pigments, such as leaf chlorophyll and nitrogen. Leaf area index (LAI) of mangrove ranged between 1 and 4, with healthy dense mangrove depicted LAI more than 2.5. Leaf chlorophyll content for dense mangrove forests showed between 40 and 90 μg/cm2 as estimated from satellite-based (i.e. NAOC index) and empirical model. However, the NAOC (Normalized Area Over reflectance Curve) index has relatively overestimated the chlorophyll. A similar pattern was also obtained for leaf nitrogen. Nevertheless, integrating both satellite and handheld NPS instruments has provided a robust and dynamic way to monitor mangrove forests' health conditions. Satellite-derived biophysical and biochemical parameters offer vital information on mangrove, which could be crucial towards conservation, plantation, and mangrove management.
      PubDate: 2021-11-01
       
  • Evaluating a finer resolution global hydrological model’s simulation of
           discharge in four West-African river basins

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      Abstract: Abstract Performance evaluation of hydrological models enables their consolidation, thereby allowing for the evaluation of water resource conservation approaches. This research aims to evaluate the performance of a finer resolution version (5 arcmin) of the PCRaster Global Water Balance (PCR-GLOBWB) for discharge estimation, in four basins in data-scarce West Africa; the Niger, Komadugu-Yobe, Jama'are, and Ogun. At the Ogun, discharge simulation was validated in a proxy basin, Ouémé, which is hydrologically comparable. The model performance was evaluated using Nash–Sutcliffe efficiency (NSE), coefficient of determination (r2), Kling–Gupta efficiency (KGE), RMSE—observations standard deviation ratio (RSR), percent bias (PBIAS) and visual plots. PCR-GLOBWB was found to be suitable in all four basins but yielded better performance at three of the basins; the Niger, Jama'are, and Komadugu-Yobe (NSE, KGE, and r2 above 0.7) compared to the Ogun basin where a proxy validation approach was followed. Results at the Ogun underlined the importance of measured data in hydrological studies. Still, model performance was satisfactory in the Ogun. PCR-GLOBWB performances across the four basins, in the area, validate its reliability as a tool applicable for water resources management strategies and further investigation of impacts of climate variations on river dynamics.
      PubDate: 2021-11-01
       
  • Assessment of hydrology and optimal water allocation under changing
           climate conditions: the case of Megech river sub basin reservoir, Upper
           Blue Nile Basin, Ethiopia

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      Abstract: Abstract The main aim of this study was to assess climate change impact on hydrology and water allocation of Megech river sub basin reservoir, Upper Blue Nile Basin, Ethiopia by integrating rainfall runoff HBV-light and Water Evaluation and Planning (WEAP21) model. GCM of the CMIP5 output for RCP2.6, RCP4.5 and RCP8.5 scenarios were obtained from CORDEX-Africa database. The HBV-light model was calibrated and validated to simulate upcoming Megech Reservoir inflow volume and had good performance. WEAP21 was used to assess the water demand requirements, supplied delivered, unmet demand and prepare rule curves for demand sites. The results indicated that the basin average temperature, potential evaporation and open water evaporation would all have increasing trends with pronounced increment in RCP8.5 than RCP4.5 and RCP2.6. However, the inflow volume to the upcoming Megech Reservoir would have decreasing and increasing trend and consistent with precipitation patterns. The total annual water demand requirement was 147.18 Mm3, 179.14 Mm3and 300.44 Mm3 for baseline, lower and higher growth scenarios, respectively. The supply delivered would be 146.92 Mm3 for baseline period and maximum 155.49 Mm3 and minimum 143.77 Mm3 for 2055–2090 under RCP2.6 and RCP8.5, respectively. The annual sum of Megech reservoir capacity under baseline year was 1045.54 Mm3. But it reduced to 570.1955 Mm3, 570.66 Mm3 and 587.59 Mm3 for 2019–2054 period. And also reduced to 448.31 Mm3, 395.88 Mm3 and 383.61 Mm3 for 20552090 demand projection periods under RCP2.6, RCP4.5 and RCP8.5 emission scenarios, respectively. So, in order to guarantee the water resource development project further studies should incorporate impact of land use, sedimentation, adaptation option of climate change, find other supply preference and use crops which have low water requirements.
      PubDate: 2021-11-01
       
  • Modeling climate change impact on the hydropower potential of the Bamboi
           catchment

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      Abstract: Abstract Understanding climate change impacts helps adaptation efforts in the energy sector. This study evaluates the impact of future climate change on the hydropower potential (HPP) of the Bamboi catchment in West Africa combining the HBV-light rainfall-runoff model and a hydropower generation model. Two regional climate simulation datasets MPI-ESM-REMO and WASCAL under RCP 4.5 were applied to the validated HBV light to simulate the catchment discharge. Based on reference and future simulated discharges, a 1.3 MW run-of-river hydropower plant was designed to evaluate the HPP of the catchment. Hydrological and HPP changes were expressed as the difference between two future periods (2020–2049 and 2070–2099) and a reference period (1983–2005). The climate datasets projected a mean annual precipitation increase by 8.8% and 7.3% and discharge increases by 11.4% and 9.735% for the 2020–2049 and 2070–2099 periods, respectively. However, an overall decrease of hydropower generation by − 9.1% and − 8.4% for the 2020–2049 and 2070–2099 periods, respectively, was projected. These results stem from an increase in discharge for the rainy season not convertible into hydropower, combined with a decrease in discharge during the dry months that leads to important HPP losses.
      PubDate: 2021-11-01
       
  • Application of hydrodynamic models for designing structural measures for
           river flood mitigation: the case of Kulfo River in southern Ethiopia

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      Abstract: Abstract Flood is one of life-threatening events in different parts of Ethiopia. The causes of flood might vary from place to place, for instance, rates of deforestation, agricultural expansion, urbanization, wetland drainage, climate change, siltation of river bed, and several other types of land use change might be the cause for flood in different rivers banks. This study aims to assess, investigate, and design suitable river training works on lower Kulfo river reach. The study reach has been seriously affected by extreme floods due to the above reasons. For minimizing the loss due to flood, and to use the advantage of flood for different developmental activities various flood control measures should be adopted. The flood control measures which should more correctly be termed as “flood management” can be planed either through structural engineering measures or non-structural measures. Structural measures comprise retarding structures which store flood water, channel improvements which increase flood-carrying capacity of the river, embankments, and levees which keep the waterway from flood-prone area, detention basin which retards and absorbs most of the floodwater. Within the identified 6 km reach, field investigation including secondary data collection has been done to predict the flood extent using 1D hydrodynamic model, HECRAS and HEC Geo RAS. Estimated flood depth and extent helped us in fixing the dimension of different river training structures selected. The modelling result indicates a maximum channel bed flood depth of 4.3 m and flood plain flood depth 2.3 m obtained using a 100-year return flow. Analysis of soil samples indicates that the lower reach of Kulfo river is gravel and sand dominated meandering river, with estimated scour depth up to 3.41 m along the river course. Levees have been designed in conjunction with Groynes to protect the Upstream farm located at the prison and upper part of the Limat households. Frequent floods happening near both bridges shall be reduced by using Guide banks without influencing the bridges and diversion structures. Consideration is given for the ecosystem to stay in equilibrium, by providing suitable outer slopes so that plantation is possible on the top and side slope of the levees and guide banks.
      PubDate: 2021-11-01
       
  • Spatiotemporal modeling of parasite aggregation among fish hosts in a
           lentic ecosystem

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      Abstract: Abstract Parasite aggregation is a frequently occurring phenomenon where majority of the parasites accumulate in the smaller fraction of the host population while many individual hosts have low parasite load. One of the mechanisms of parasite aggregation is heterogeneity in the host-parasite interaction. Here, we aim to develop and analyze a spatiotemporal model to explain the details of this mechanism. We construct an agent-based simulation involving fish hosts that forage on zooplanktons harboring macroparasites. In this study, we restrict our simulations to a lentic ecosystem, i.e., still, closed freshwater environment. Our simulations show that (i) the initial sizes of the population of both the fish and zooplanktons have minimal effect on the aggregation of parasites; (ii) increasing the probabilities of reproduction of both fish and zooplankton lead to parasite aggregation among fish hosts; and (iii) aggregation occurs either by decreasing the size of the infection area or increasing the size of the zooplankton-free area in the lentic ecosystem. Our results can be used to provide insights and visualization of the underlying processes leading to aggregation. These can also be used to aid experimentalists in determining the statistical distribution of parasites in hosts for disease prevention and control.
      PubDate: 2021-11-01
       
  • Artificial neural network model for reservoir petrophysical properties:
           porosity, permeability and water saturation prediction

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      Abstract: Abstract Prediction of reservoir petrophysical properties from well-logs data has evolved from the use of experts’ knowledge and statistics to the use of artificial intelligence (AI) models. Several AI models for this purpose are available in the literature; regrettably, most of them are multiple-inputs single-output (MISO) models. Meaning, these models used numerous well-logs to predict a single reservoir petrophysical property. In this study, multiple-inputs multiple-outputs (MIMO) artificial neural network (ANN) model to predict reservoir petrophysical properties: porosity ( \(\varphi\) ), permeability ( \(k\) ), and water saturation ( \(S_{{\text{w}}}\) ), was developed based on wireline logs (gamma ray, resistivity, density and depth interval logs) from 15 fields in the Niger Delta region. The developed ANN model is a feed-forward back-propagation (FFBP) network with 12 neurons in its hidden layer with the Levenberg–Marquardt algorithm as the best learning algorithm than Bayesian regularization and Scaled conjugate gradient. The performance of the developed model resulted in the overall correlation coefficient (R) and Mean Square Error (MSE) values of 0.9945 and 0.7310, respectively. Again, the generalization potential of the developed ANN model with new datasets was determined using five performance indicators: R, coefficient of determination (R2), MSE, root mean square error (RMSE) and average relative error (ARE). The results obtained showed that \(\varphi\) had R of 0.9243, R2 of 0.8544, MSE of 1.7243, RMSE of 1.3131 and ARE of 0.0652, while \(k\) had R of 0.9810, R2 of 0.9624, MSE of 0.0003, RMSE of 0.0173 and ARE of 0.0036. Also, \(S_{{\text{w}}}\) resulted in R, R2, MSE, RMSE and ARE values of 0.9631, 0.9276, 0.0049, 0.0700 and 0.0158, respectively. Furthermore, comparing the performance of the developed ANN model with some existing ones indicated that it performed better than some existing models. Additionally, the developed ANN model is replicable as its threshold weights and biases required to replicate the model are made available, unlike other models in the literature. Furthermore, average contribution factor analysis of the input variables depicted that resistivity log, density log, gamma-ray log and depth interval had the factor of 44.23%, 22.68%, 20.16% and 12.98%, respectively, on the developed ANN model. Hence, the developed ANN model is a more robust tool to predict reservoir’s porosity, permeability and water saturation in the Niger Delta region.
      PubDate: 2021-11-01
       
  • Drastic model application to groundwater vulnerability elucidation for
           decision making: the case of south western coastal basin, Ghana

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      Abstract: Abstract The health of the population is intertwined with the availability and supply of potable water. With many people around the world resorting to groundwater resources as a source potable water supply, it becomes imperative that the state of groundwater susceptibility to contamination is known. The DRASTIC model has been applied to determine the state of aquifer vulnerability to contaminants. The seven hydrogeological parameters were considered in the standard model and the resulting vulnerability, DI were classified into three vulnerability zones; low, moderate and high. The model was then modified to include land use/land cover (LU) and lineament density (LIN) parameters and net recharge (rm). The modified vulnerability indices were designated as DI-LU, DI-LIN, DIrm and MDI (combined modification). The results revealed the land area under high vulnerability under DI, DI-LU, DI-LIN, DIrm and MDI were 32.2, 26.2, 33.7, 26.2 and 40.4% respectively. There were no significant difference between the standard moderate vulnerability class and the modified derivatives (DI + LU, DI + Lin). The combined modification (MDI) however led to 17% decrease in this class of vulnerability. The model was validated using a nitrate concentration of 36 samples collected for the purpose. The validation assessment revealed that the performance of the model was improved with modification.
      PubDate: 2021-11-01
       
  • Evaluation of tree regression analysis for estimation of river basin
           discharge

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      Abstract: Abstract River discharge links the hydrologic and geologic cycles in addition to climate components; therefore, it forms an important source of hydraulic and hydrologic quantity. The ability to quantify river discharge accurately is very important for estimating water availability and distribution for better water resources management. In this study, the performance of ARIMA, random forest (RF), the M5P and Bagged M5P (BM5P) methods, for modeling the daily discharge of the Baitarani Riverwere compared and evaluated against measured values. Fifteen different input combinations under two groups (i.e., discharge and rainfall) were considered, and a suitable modeling approach with appropriate model input combination is proposed on the basis of various goodness fit parameters. Four statistical assessment methods implemented to determine the best performing models include the correlation coefficient (CC), Mean square error (MSE), Root mean square error (RMSE) and Scattering Index (SI).The outcomes of this study indicated that the Bagged M5P modeling approach is outperforming than ARIMA, RF and M5P. This model recorded up to 0.8676, 10.7279, 39.836 m3/s and 0.9599 for (CC), (MAE), (RMSE) and (SI), respectively, for testing data set.
      PubDate: 2021-11-01
       
  • Identification of the coastal hazard zone between the areas of Rasulpur
           and Subarnarekha estuary, east coast of India using multi-criteria
           evaluation method

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      Abstract: Abstract An increasing number of coastal hazards such as cyclones, tsunami and coastal erosion are the consequences of global climate change, creating an immense impact on the coastal habitat and coastal ecosystem. The study area (Subarnarekha to Rasulpur estuary) part of the Bay of Bengal is under a potentially vulnerable condition to coastal erosion. The area has witnessed cyclones during the pre-monsoon and retreat or post-monsoon season. The present study aimed to assess the coastal hazard zone (CHZ) along the 70 km coastal stretch within 119.49 km2 area near the shoreline. The present study follows the multi-criteria evaluation (MCE) method to identify the CHZ. Multi-resolution satellite images and ASTER DEM image are used to complete the study. Six influencing factors are applied in method MCE such as coastal slope, aspect, distance to river and estuaries, land use/land cover, shoreline change rate and distance to shoreline. Various GIS techniques are used to prepare the raster layer map from these six influencing factors in Arc GIS 10.3 software. Finally, weighted overlay analysis was implemented to obtain the CHZ map from multi-criteria, assigning the weights according to their vulnerability. Five zonation classes are selected based on their vulnerability rank: very high, high, moderate, low and very low hazard zone. The acquired result will enable identification of vulnerable and hazard-prone areas and will also be helpful for coastal management and to decision makers for future implementation in coastal conservation.
      PubDate: 2021-11-01
       
  • Investigating sea-level change on the coastal aquifer, case study:
           Jafakendeh aquifer

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      Abstract: Abstract Do the sea-level changes affect the quantity and quality of groundwater on the coastal Jafakendeh aquifer' More than half of the world's population now lives near the coastline. Surface water in the coastal basin and the island interacts with adjacent groundwater. This interaction affects the quantity and quality of water in surface and subsurface waters. In this study, the relationship between the Jafakendeh aquifer and groundwater of the Caspian Sea in northern Iran has been investigated. Therefore, this study aimed to examine the trend, changes in surface groundwater level, and groundwater quality variables of the groundwater aquifer by the Mann–Kendall nonparametric method and detect point change by the Pettitt method. Four piezometer wells were measured, where is only one piezometer located at the artificial recharge site and piezometer one near the Caspian Sea. In the present study, the statistics were used to find a sudden change in groundwater data quantity and quality. The analysis shows that sea-level changes and wells near the sea do not affect the amount and quality of coastal aquifer and adjacent wells' significance.
      PubDate: 2021-11-01
       
  • Transformation of climate and its sway on hydro-climatology using
           

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      Abstract: Abstract Frequent change in climate and its inconsistent characteristic across Ethiopia at the behest in regional scale encourages researchers in suitable planning of the strategies for adaptive capacity. Geba catchment in this region not only put influence by the hydro-climatic conditions but also extends to assess the ongoing impacts. Regional Climate model (RCM) outputs using representative concentration pathways (RCP) including climate change scenarios of precipitation, temperature, and stream flow for three span of time firstly 1976–2005, second 2021–2050, and the last 2051–2080 has been evaluated. Non-linear power transformation for precipitation and linear shifting and scaling for temperature climate datasets was applied by extrapolating existing climate dataset. Pragmatic use of HEC-HMS, the hydrological model was pledged to generate current and future climatic condition in stream flow of Geba catchment. In an average, the respective performance of the model reveals a Nash Sutcliffe Efficiency (NSE) of 0.83 and 0.80 during calibration and validation. The trends of projected climate variables have shown positive change for temperature and potential evapotranspiration whereas stream flow showed a declining trend with manifestation in precipitation. In comparison to the base period, the average maximum temperature may rise by 1.25 °C, 2.01 °C for RCP4.5, 1.67 °C, and 3.39 °C for RCP8.5 for a period 2021–2050 and 2051–2080 respectively. For the same period, an increase in minimum temperature was recorded under RCP4.5 and RCP8.5. The annual precipitation may decrease by 2.94% and 3.32% for RCP4.5 and 2.01% and 3.1% for RCP8.5 for 2021–2050 and 2051–2080 respectively. Besides, annual evapotranspiration may increase up to 2.6% and 4.3% for RCP4.5 and 2.5% and 3.0% for RCP8.5. Overall, the mean annual stream flow indicates a decreasing order from 0.93 to 1.67% for RCP4.5 and by 1.3 to 1.76% for RCP8.5. This provides a detail analysis that climate change affects the water balance of Geba catchment.
      PubDate: 2021-11-01
       
  • Modelling of earth’s geothermal subtle traps using gravity Euler
           deconvolution

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      Abstract: Abstract Euler deconvolution technique is one of the methods that predicts the subsurface features and structures with help of gravity modelling. The present study was performed to identify the earth’s geothermal potentials in Dholera, Unai, and Gandhar regions of Gujarat, India using gravity technique. The structures and layers of the subsurface were determined by performing the gravity survey and the interpretation of data was carried out using Euler Deconvolution. The survey was conducted along six profile lines: five horizontal and one perpendicular to others in the study areas. After acquiring gravity data, various corrections were applied to convert raw gravity data to corrected Bouguer gravity data. In this paper density of the subsurface formation has been determined using Nettleton and Parasnis methods, which suggests that the subsurface of Dholera, Unai, and Gandhar have densities close to sedimentary rocks. After density determination, regional and residual separation was performed on the Bouguer gravity data to get information on geothermal causative bodies. In this paper, the Euler Deconvolution method was applied to interoperate the spatial position and depth of the subtle geothermal bodies. The Euler solutions for depth in Dholera, Unai, and Gandhar range between 1324–4300 m, 1877–4813 m, and 2345–5536 m. The results of gravity Euler Deconvolution suggests the presence of geothermal potential in these regions.
      PubDate: 2021-11-01
       
  • A spatial analysis and modeling study of sedimentation impacts on dams
           found in south Gondar zone, Ethiopia

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      Abstract: Abstract Sedimentation is a significant issue for agricultural dams in Ethiopia, as it diminishes the capacity limit and life expectancy of the repositories. The procedure of sedimentation begins from the very first moment of the seizing of water in some random supply. Even though an arrangement is made for each reservoir during anticipating a specific stockpiling limit, explicitly for silt testimony, called dead storing, a significant part of the sediments gets kept for a long time of the supply's life in zones other than the dead storing, and this pattern cannot be turned around at a simple expense. This investigation is focused on the examination of persuasive sedimentation forms in the close by many dams found in the south Gondar zone catchment situated inside the Upper Blue Nile Basin of Ethiopia and spotlights on the appraisal of yearly sedimentation rate. Spatial investigation and displaying examines were directed dependent on the Revised Universal Soil Loss Equation and GIS to decide silts yield and level of effect of every store for a given scene, precipitation, and catchment heterogeneity. Field perceptions and soil testing were done to decide the components that lead to repository sedimentation. Spatial Data on the dams in south Gondar zone catchment were likewise gathered from the Ministry of Agriculture, which were utilized for ground-truthing, GIS-based computations, and model approval. The average specific sediment rate and silt delivery proportion were seen as 4059.2 t km−2 year−1 and 72.67%, individually. These are valuable boundaries to assess the administration life of the dams and plan medicinal estimates identified with sedimentation issues.
      PubDate: 2021-11-01
       
  • Future climate and its impact on streamflow: a case study of the
           Brahmaputra river basin

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      Abstract: Abstract Using various GCM (general circulation model), the present study attempted to analyze the impact of climate change on the entire stretch of one of the major rivers in South Asia, the Brahmaputra river basin. Initially, we identified a suitable GCM based on some statistical measures of the interpolated and bias-corrected variables. The results of the trend analysis show a significant impact on the climatic variables during future periods. The Brahmaputra basin is likely to experience an increase in rainfall, maximum temperature, and minimum temperature at the rates of 2.5 mm/year, 0.062 °C/year and 0.05 °C/year, respectively, corresponding to representative concentration pathway (RCP) 8.5 scenarios till the end of the current century. Moreover, the climate change impact analysis on streamflow indicates a rise of up to 13.06% in annual discharge at Pandughat, India. The findings of this study will provide a basis for water resource management of the transboundary Brahmaputra basin in the coming decades.
      PubDate: 2021-11-01
       
  • Development of rainfall-infiltration measurement system and recharge
           strategies for urban flooding areas: a case study of Delhi, India

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      Abstract: Abstract Cities need strategies to cope with urban floods which arise due to encroachment of low lying areas and lack of storm water drains. The current study was carried out to evaluate the properties of urban soil, a key variable in the urban ecosystem which contributes to building more resilient cities. The study reveals that the soil profile of Delhi has low infiltration rates which are a cause for concern as they form a very important part of rainfall attenuation in storm events, the pervious cover is unable to contribute to ground water recharge, due to reduced subsurface. It was also found that accurate infiltration modeling requires site specific data based on local site conditions to assess the soil infiltration rate status in other similar areas. Therefore, a mathematical model has been developed based on different physical parameters of soil to calculate soil infiltration prediction rate. Various maps such as soil texture map, urban drainage pattern map, flooded junctions map and land use land cover map are studied to evaluate the need for sustainable drainage practices to mitigate urban flooding. Urban parks which are major sinks for rainfall, along with rejuvenation of water bodies need innovative management including active citizen partnership, urban local bodies and district park authorities to reduce urban flooding. Urban design guidelines, including urban open space planning standards need to be reviewed so as redesign utilization of open urban spaces.
      PubDate: 2021-11-01
       
  • Drought prediction using hybrid soft-computing methods for semi-arid
           region

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      Abstract: Abstract Drought is one of the most significant natural disaster and prediction of drought is a key aspect in effective management of water resources and reducing the effect of a drought with preliminary studies plays significant role. In this study, we predicted one of the meteorological drought indices, the self-calibrated Palmer Drought Severity Index (sc-PDSI), values for Adana, Turkey. First, we used adaptive neuro fuzzy inference system (ANFIS) as a standalone technique to predict sc-PDSI. Second, we used empirical mode decomposition (EMD) as a pre-processing technique to decompose the sc-PDSI time series into the sub-series and applied ANFIS to each sub-series. Following the prediction, results are summed each other and final prediction of the hybrid EMD-ANFIS method is obtained. Within the scope of the study, 1, 3and 6-months lead time sc-PDSI values are predicted. We utilized the mean square error (MSE) and Nash–Sutcliffe efficiency coefficient (NSE) as performance indicators in order to perform statistical evaluation. For ANFIS, we obtained NSE = 0.52 and NSE = 0.17 for 3-month and 6-month lead times, respectively. Also, NSE values are obtained as 0.81 and 0.77 for the hybrid model in 3-month and 6-month lead time predictions, respectively. The results revealed that the hybrid EMD-ANFIS model outperforms the standalone ANFIS model. Also, the predicted and actual sc-PDSI series investigated according to the statistical distributions. At last, error histograms of both predicted and actual series are compared according to the Kolmogorov–Smirnov test and the p values are calculated. The results illustrated the predictions are statistically significant.
      PubDate: 2021-11-01
       
 
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