Sorghum has an enormous role in the economy of sorghum-growing nations. Supplying a precise amount of water to a crop based on crop needs is the main agenda in implementing water-saving agriculture. Non-weighing type lysimeters were used to determine actual crop evapotranspiration and crop coefficient of sorghum at the experimental farm of Melkassa Agricultural Research Center situated in the semi-arid area of Ethiopia. Soil-water balance approaches were applied to obtain actual crop evapotranspiration, while the Penman-Monteith technique was used to determine reference evapotranspiration. Growth stages-wise crop coefficient was computed as a ratio of actual crop evapotranspiration to reference evapotranspiration. The total seasonal sorghum actual crop evapotranspiration during the 2017 and 2018 experimental years was 358.6 and 377.54 mm, respectively. The 2 years average sorghum actual crop evapotranspiration was 368.07 mm. The mean locally developed actual crop coefficient values of 0.55, 1.15, and 0.59 were observed for the initial, mid, and end-season, respectively. The FAO-adjusted crop coefficient values for mid and end-season were 1.01 and 0.52, respectively. The developed Kc values considerably differed from the FAO-adjusted Kc values. So, the determination of actual crop evapotranspiration and crop coefficient for crop growth at local climate conditions is vital for decision-making concerning water management in the area where irrigation is practiced.
{"title":"Evapotranspiration and Crop Coefficient of Sorghum (Sorghum bicolor L.) at Melkassa Farmland, Semi-Arid Area of Ethiopia","authors":"Tatek Wondimu Negash, Gobena Dirirsa Bayisa, Abera Tesfaye Tefera, Ketema Tezera Bizuneh, Aynalem Gurms Dinku, Tigist Worku Awulachew, Gebeyehu Ashemi Bikela","doi":"10.1177/11786221231184206","DOIUrl":"https://doi.org/10.1177/11786221231184206","url":null,"abstract":"Sorghum has an enormous role in the economy of sorghum-growing nations. Supplying a precise amount of water to a crop based on crop needs is the main agenda in implementing water-saving agriculture. Non-weighing type lysimeters were used to determine actual crop evapotranspiration and crop coefficient of sorghum at the experimental farm of Melkassa Agricultural Research Center situated in the semi-arid area of Ethiopia. Soil-water balance approaches were applied to obtain actual crop evapotranspiration, while the Penman-Monteith technique was used to determine reference evapotranspiration. Growth stages-wise crop coefficient was computed as a ratio of actual crop evapotranspiration to reference evapotranspiration. The total seasonal sorghum actual crop evapotranspiration during the 2017 and 2018 experimental years was 358.6 and 377.54 mm, respectively. The 2 years average sorghum actual crop evapotranspiration was 368.07 mm. The mean locally developed actual crop coefficient values of 0.55, 1.15, and 0.59 were observed for the initial, mid, and end-season, respectively. The FAO-adjusted crop coefficient values for mid and end-season were 1.01 and 0.52, respectively. The developed Kc values considerably differed from the FAO-adjusted Kc values. So, the determination of actual crop evapotranspiration and crop coefficient for crop growth at local climate conditions is vital for decision-making concerning water management in the area where irrigation is practiced.","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41462740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/11786221231195824
J. Vega, F. H. Sepúlveda-Murillo, M. Parra
Landslides are a geological hazard commonly induced by rainfall, earthquakes, deforestation, or human activity causing loss of human life every year specially on highlands or mountain slopes with serious impacts that threaten communities and its infrastructure. The incidence and recurrence of landslides are conditioned by several aspects related to soil properties, geological structure, climatic conditions, soil cover, and water flow. Precisely, Colombia is one of the most affected by this type of natural hazard, as well as by floods, since they are the natural phenomena that bring with them the most severe risks for communities. In this work, we articulated the statistical approach of the landslide conditioning factors, Machine Learning Algorithms (MLA), and Geographic Information System (GIS), evaluating a flexible and agile methodology to estimate the landslide susceptibility defining areas prone to the landslide occurrence. The MLA were validated in a case study in the “La Liboriana” River basin, located in the Municipality of Salgar in the Colombian mountains Andes where Landslide Susceptibility Maps (LSMs) were obtained. The obtained MLA results hold immense potential in the field of regional landslide mapping, facilitating the development of effective strategies aimed at minimizing the devastating impacts on human lives, infrastructure, and the natural environment. By leveraging these findings, proactive measures can be devised to safeguard vulnerable areas, mitigate risks, and ensure the safety and well-being of communities. Seven supervised MLA were employed, two regression algorithms (Logistic) and five decision tree algorithms (Recursive Partitioning and Regression Trees [RPART], Conditional Inference Trees [CTREE], Random Forest [RF], Ranger, and Extreme Gradient Boosting Algorithm [XGBoost]). The LSMs were produced for each MLA. Considering different performance metrics, the RF model yields the best classification accuracy with an area under receiver operating characteristic (ROC) curve of 95% and 90% of accuracy, providing the most representative results. Finally, the contribution of each landslide conditioning factor on predictions with RF model is explained using the SHAP method.
{"title":"Landslide Modeling in a Tropical Mountain Basin Using Machine Learning Algorithms and Shapley Additive Explanations","authors":"J. Vega, F. H. Sepúlveda-Murillo, M. Parra","doi":"10.1177/11786221231195824","DOIUrl":"https://doi.org/10.1177/11786221231195824","url":null,"abstract":"Landslides are a geological hazard commonly induced by rainfall, earthquakes, deforestation, or human activity causing loss of human life every year specially on highlands or mountain slopes with serious impacts that threaten communities and its infrastructure. The incidence and recurrence of landslides are conditioned by several aspects related to soil properties, geological structure, climatic conditions, soil cover, and water flow. Precisely, Colombia is one of the most affected by this type of natural hazard, as well as by floods, since they are the natural phenomena that bring with them the most severe risks for communities. In this work, we articulated the statistical approach of the landslide conditioning factors, Machine Learning Algorithms (MLA), and Geographic Information System (GIS), evaluating a flexible and agile methodology to estimate the landslide susceptibility defining areas prone to the landslide occurrence. The MLA were validated in a case study in the “La Liboriana” River basin, located in the Municipality of Salgar in the Colombian mountains Andes where Landslide Susceptibility Maps (LSMs) were obtained. The obtained MLA results hold immense potential in the field of regional landslide mapping, facilitating the development of effective strategies aimed at minimizing the devastating impacts on human lives, infrastructure, and the natural environment. By leveraging these findings, proactive measures can be devised to safeguard vulnerable areas, mitigate risks, and ensure the safety and well-being of communities. Seven supervised MLA were employed, two regression algorithms (Logistic) and five decision tree algorithms (Recursive Partitioning and Regression Trees [RPART], Conditional Inference Trees [CTREE], Random Forest [RF], Ranger, and Extreme Gradient Boosting Algorithm [XGBoost]). The LSMs were produced for each MLA. Considering different performance metrics, the RF model yields the best classification accuracy with an area under receiver operating characteristic (ROC) curve of 95% and 90% of accuracy, providing the most representative results. Finally, the contribution of each landslide conditioning factor on predictions with RF model is explained using the SHAP method.","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42327263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/11786221231154659
S. Maji, Sirajuddin Ahmed, Maninder Kaur-Sidhu, S. Mor, K. Ravindra
The impact of increasing air pollution on human health and the environment is a major concern worldwide. Exposure to air pollution is one of the leading risk factors and substantially contributes to morbidity and premature mortality. This review paper aims to examine the exposure of major air pollutants (i.e., particulate matter, sulfur dioxide, oxides of nitrogen, carbon monoxide) and its association with respiratory, cardiovascular, reproductive, and genotoxic adverse health outcomes that can cause DNA damage leading to genetic mutations. The study emphasized how a better understanding of source-receptor relationships and exposure assessment methodologies can support effective air quality management planning. Hence, there is a need to augment various exposure indicators (spatial modeling, personal/area monitoring, emphasizing central/rural site measurements, etc.) to generate reliable surrogates for informed decision-making. The critical drivers of anthropogenic interference for air pollution remain urbanization, growing vehicle use, and industrialization. This requires innovative approaches, such as energy-efficient and technologically sustainable solutions to gradually replace conventional fossil fuel from primary energy mix with renewable energy. It holds the key to meet future energy challenges and minimizing air pollution emissions. Further, there is an urgent need to frame effective public policy with graded mitigation actions to reduce the adverse impact of air pollution on human health and the environment.
{"title":"Health Risks of Major Air Pollutants, their Drivers and Mitigation Strategies: A Review","authors":"S. Maji, Sirajuddin Ahmed, Maninder Kaur-Sidhu, S. Mor, K. Ravindra","doi":"10.1177/11786221231154659","DOIUrl":"https://doi.org/10.1177/11786221231154659","url":null,"abstract":"The impact of increasing air pollution on human health and the environment is a major concern worldwide. Exposure to air pollution is one of the leading risk factors and substantially contributes to morbidity and premature mortality. This review paper aims to examine the exposure of major air pollutants (i.e., particulate matter, sulfur dioxide, oxides of nitrogen, carbon monoxide) and its association with respiratory, cardiovascular, reproductive, and genotoxic adverse health outcomes that can cause DNA damage leading to genetic mutations. The study emphasized how a better understanding of source-receptor relationships and exposure assessment methodologies can support effective air quality management planning. Hence, there is a need to augment various exposure indicators (spatial modeling, personal/area monitoring, emphasizing central/rural site measurements, etc.) to generate reliable surrogates for informed decision-making. The critical drivers of anthropogenic interference for air pollution remain urbanization, growing vehicle use, and industrialization. This requires innovative approaches, such as energy-efficient and technologically sustainable solutions to gradually replace conventional fossil fuel from primary energy mix with renewable energy. It holds the key to meet future energy challenges and minimizing air pollution emissions. Further, there is an urgent need to frame effective public policy with graded mitigation actions to reduce the adverse impact of air pollution on human health and the environment.","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47539320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/11786221231185104
Julián Molina, J. A. Sillero-Medina, J. D. Ruiz-Sinoga
In areas with scarce water resources, it is so important to analyze the connection between the different elements of a river basin and the water collected by the basin’s reservoir, to determine and predict the spatial and temporal variability of water on it. In this paper, we use the basic principles of hydrological modelling to develop a model for the exploitation of rainfall in reservoir basins in the province of Malaga, Spain. The monthly water input data of the seven reservoirs in the province of Malaga, provided by the Hidrosur Network of the Automatic Hydrological Information System (SAIH), as well as the precipitation and daily temperature of the stations of the State Meteorological Agency (AEMET) associated with the basins of each of these reservoirs were used. We assume that the entrance to a reservoir in a given month must depend on the precipitation produced in its watershed (both the amount of rain and the intensity with which it fell), the precipitation collected from the previous months (and the way in which it was produced) and the evapotranspiration produced during that period. For each reservoir, we propose a model with nine parameters to simulate the arrival of rainfall to the reservoir, covering aspects from the amount and intensity of rain, past and present, to the level of evapotranspiration on a given area for a given date. These nine parameters are optimally adjusted through an artificial intelligence algorithm to maximize the correlation between real and simulated contributions. The results show how this model, adjusted for each reservoir, will let us predict how changes in the rainfall and temperature patterns, predicted, for example, by the IPCC models, will affect the future water levels at the studied reservoirs.
{"title":"Modeling the Rainfall Exploitation of the Reservoirs in Malaga Province, Spain","authors":"Julián Molina, J. A. Sillero-Medina, J. D. Ruiz-Sinoga","doi":"10.1177/11786221231185104","DOIUrl":"https://doi.org/10.1177/11786221231185104","url":null,"abstract":"In areas with scarce water resources, it is so important to analyze the connection between the different elements of a river basin and the water collected by the basin’s reservoir, to determine and predict the spatial and temporal variability of water on it. In this paper, we use the basic principles of hydrological modelling to develop a model for the exploitation of rainfall in reservoir basins in the province of Malaga, Spain. The monthly water input data of the seven reservoirs in the province of Malaga, provided by the Hidrosur Network of the Automatic Hydrological Information System (SAIH), as well as the precipitation and daily temperature of the stations of the State Meteorological Agency (AEMET) associated with the basins of each of these reservoirs were used. We assume that the entrance to a reservoir in a given month must depend on the precipitation produced in its watershed (both the amount of rain and the intensity with which it fell), the precipitation collected from the previous months (and the way in which it was produced) and the evapotranspiration produced during that period. For each reservoir, we propose a model with nine parameters to simulate the arrival of rainfall to the reservoir, covering aspects from the amount and intensity of rain, past and present, to the level of evapotranspiration on a given area for a given date. These nine parameters are optimally adjusted through an artificial intelligence algorithm to maximize the correlation between real and simulated contributions. The results show how this model, adjusted for each reservoir, will let us predict how changes in the rainfall and temperature patterns, predicted, for example, by the IPCC models, will affect the future water levels at the studied reservoirs.","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42265573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rainfed agriculture in Ethiopia has failed to produce enough food, to achieve the increasing demand for food. Pinpointing the appropriate site for rainwater harvesting (RWH) have a substantial contribution to increasing the available water and enhancing agricultural productivity. The current study related to the identification of the potential RWH sites was conducted at the Chacha watershed central highlands of Ethiopia which is endowed with rugged topography. The Geographic Information System with Analytical Hierarchy Process was used to generate the different maps for identifying appropriate sites for RWH. In this study, 11 factors that determine the RWH locations including slope, soil texture, runoff depth, land cover type, annual average rainfall, drainage density, lineament intensity, hydrologic soil group, antecedent moisture content, and distance to the roads were considered. The overall analyzed result shows that 10.50%, 71.10%, 17.90%, and 0.50% of the areas were found under highly, moderately, marginally suitable, and unsuitable areas for RWH, respectively. The RWH site selection was found highly dependent on a slope, soil texture, and runoff depth; moderately dependent on drainage density, annual average rainfall, and land use land cover; but less dependent on the other factors. The highly suitable areas for rainwater harvesting expansion are lands having a flat topography with a soil textural class of high-water holding capacity that can produce high runoff depth. The application of this study could be a baseline for planners and decision-makers and support any strategy adoption for appropriate RWH site selection.
{"title":"Identification of Suitable Rainwater Harvesting Sites Using Geospatial Techniques With AHP in Chacha Watershed, Jemma Sub-Basin Upper Blue Nile, Ethiopia","authors":"Abrha Ybeyn Gebremedhn, Yitea Seneshaw Getahun, Alebachew Shumye Moges, Fikrey Tesfay","doi":"10.1177/11786221231195831","DOIUrl":"https://doi.org/10.1177/11786221231195831","url":null,"abstract":"Rainfed agriculture in Ethiopia has failed to produce enough food, to achieve the increasing demand for food. Pinpointing the appropriate site for rainwater harvesting (RWH) have a substantial contribution to increasing the available water and enhancing agricultural productivity. The current study related to the identification of the potential RWH sites was conducted at the Chacha watershed central highlands of Ethiopia which is endowed with rugged topography. The Geographic Information System with Analytical Hierarchy Process was used to generate the different maps for identifying appropriate sites for RWH. In this study, 11 factors that determine the RWH locations including slope, soil texture, runoff depth, land cover type, annual average rainfall, drainage density, lineament intensity, hydrologic soil group, antecedent moisture content, and distance to the roads were considered. The overall analyzed result shows that 10.50%, 71.10%, 17.90%, and 0.50% of the areas were found under highly, moderately, marginally suitable, and unsuitable areas for RWH, respectively. The RWH site selection was found highly dependent on a slope, soil texture, and runoff depth; moderately dependent on drainage density, annual average rainfall, and land use land cover; but less dependent on the other factors. The highly suitable areas for rainwater harvesting expansion are lands having a flat topography with a soil textural class of high-water holding capacity that can produce high runoff depth. The application of this study could be a baseline for planners and decision-makers and support any strategy adoption for appropriate RWH site selection.","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135401546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/11786221231180079
A. Dzvene, W. Tesfuhuney, S. Walker, G. Ceronio
Cover crops are a valuable tool for improving resources use, soil health, and productivity. However, the effects of intercropping cover crops as live mulches with cash crops can vary depending on the species, management practices, and environmental conditions. This study reviewed the literature on cover crop intercropping and identified key factors to consider for improved plant productivity and resources use when managing these cropping systems. Science Direct, Scopus, and Google Scholar were used to search for literature on managing cover crop intercropping as live mulches. Research has shown that annual cover crops are typically used in annual field crop systems, while perennial cover crops are typically used in orchards and vineyards. The effects of intercropping annual or perennial cover crops in vineyards, orchards, and field crop systems can vary from positive to negative, depending on the climate, soil, management, and production system. Therefore, there is no one-size-fits-all management strategy. However, there are some key factors that should be considered when managing cover crops, such as: compatibility, intercropping time, planting density, and termination time. The benefits of appropriate cover crop management include: extended growing season, increased soil fertility, resource use optimization, and increased biomass productivity. Cover crop intercropping can be a successful way to improve resource use, soil health and productivity, but it is important to carefully consider the specific crop and management practices to ensure success. Therefore, future research should optimize cover crop intercropping time and planting density in maize-based rainwater harvesting systems on productivity and resource use.
{"title":"Management of Cover Crop Intercropping for Live Mulch on Plant Productivity and Growth Resources: A Review","authors":"A. Dzvene, W. Tesfuhuney, S. Walker, G. Ceronio","doi":"10.1177/11786221231180079","DOIUrl":"https://doi.org/10.1177/11786221231180079","url":null,"abstract":"Cover crops are a valuable tool for improving resources use, soil health, and productivity. However, the effects of intercropping cover crops as live mulches with cash crops can vary depending on the species, management practices, and environmental conditions. This study reviewed the literature on cover crop intercropping and identified key factors to consider for improved plant productivity and resources use when managing these cropping systems. Science Direct, Scopus, and Google Scholar were used to search for literature on managing cover crop intercropping as live mulches. Research has shown that annual cover crops are typically used in annual field crop systems, while perennial cover crops are typically used in orchards and vineyards. The effects of intercropping annual or perennial cover crops in vineyards, orchards, and field crop systems can vary from positive to negative, depending on the climate, soil, management, and production system. Therefore, there is no one-size-fits-all management strategy. However, there are some key factors that should be considered when managing cover crops, such as: compatibility, intercropping time, planting density, and termination time. The benefits of appropriate cover crop management include: extended growing season, increased soil fertility, resource use optimization, and increased biomass productivity. Cover crop intercropping can be a successful way to improve resource use, soil health and productivity, but it is important to carefully consider the specific crop and management practices to ensure success. Therefore, future research should optimize cover crop intercropping time and planting density in maize-based rainwater harvesting systems on productivity and resource use.","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43356195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/11786221231176676
J. Ruiz‐Fernández, C. García‐Hernández, Mirella Ochoa-Álvarez, Mariana Van den Bergh, David Gallinar Cañedo, Benjamín González-Díaz
Even when the influence of climate on the geomorphological dynamics of mountain areas is well known, the ground and near-rock surface air thermal regimes of the highest altitude Cantabrian massifs still being poorly understood. This study, based on the examination of the thermal data obtained through the use of air and soil temperature dataloggers, aims to characterize the thermal regime of one of the most representative high mountain massifs of the Cantabrian Mountains: the Western Massif of the Picos de Europa. Results show the severe climatic conditions that prevail in the highest areas, where the snow cover lasts for 8 months on average, exerting an important insulating role of the soil. Thus, except on the uncovered rocky walls, the number of freeze-thaw cycles per year is low (0–16), with these cycles having a short duration and a low thermal amplitude. Significantly differences on annual thermal regimes have been confirmed; with two main phases (continued thaw phase and isothermal phase) and two minor transition phases at the ground, and only two main phases in near-rock surfaces (continued thaw phase and phase with a high number of FTCs).
{"title":"Ground and Near-Rock Surface Air Thermal Regimes in the High Mountain of the Picos De Europa (Cantabrian Mountains, NW Spain)","authors":"J. Ruiz‐Fernández, C. García‐Hernández, Mirella Ochoa-Álvarez, Mariana Van den Bergh, David Gallinar Cañedo, Benjamín González-Díaz","doi":"10.1177/11786221231176676","DOIUrl":"https://doi.org/10.1177/11786221231176676","url":null,"abstract":"Even when the influence of climate on the geomorphological dynamics of mountain areas is well known, the ground and near-rock surface air thermal regimes of the highest altitude Cantabrian massifs still being poorly understood. This study, based on the examination of the thermal data obtained through the use of air and soil temperature dataloggers, aims to characterize the thermal regime of one of the most representative high mountain massifs of the Cantabrian Mountains: the Western Massif of the Picos de Europa. Results show the severe climatic conditions that prevail in the highest areas, where the snow cover lasts for 8 months on average, exerting an important insulating role of the soil. Thus, except on the uncovered rocky walls, the number of freeze-thaw cycles per year is low (0–16), with these cycles having a short duration and a low thermal amplitude. Significantly differences on annual thermal regimes have been confirmed; with two main phases (continued thaw phase and isothermal phase) and two minor transition phases at the ground, and only two main phases in near-rock surfaces (continued thaw phase and phase with a high number of FTCs).","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45829999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/11786221231197416
Ruzhen Wang, Baitao Gu
Rhizodeposition, as transported from photosynthates and exudated in soils via fine roots, is the pivot linking above- and belowground carbon (C) cycling pathways. Meanwhile, rhizodeposit C serves as “currency” for plant nutrient acquisition because of its critical roles in priming soil microorganisms, maintaining plant-mycorrhizal symbionts, and elongating plant roots. Therefore, a conceptual framework integrating knowledge on the biogeochemical fate of rhizodeposit C can help understand plant nutrient economics and soil C sink function. However, it still remains a great challenge to efficiently delineate the dynamics of rhizodeposit C in soils. In the framework, we present the possible stabilization pathways of rhizodeposit C via formation of mineral-associated organic matter (MAOM) or encapsulation by microaggregates. We further propose that continuous and pulse 13CO2 labeling are powerful techniques to track the fate of rhizodeposit C and to quantify how much C could eventually be sequestrated in soils as the component of MAOM or microaggregates. This framework would provide future research possibilities to better optimize plant C allocation and productivity and preserve soil C stocks.
{"title":"A Conceptual Framework on the Fate of Rhizodeposits in Forming Mineral-Associated Organic Matter or Encapsulating Into Microaggreagtes","authors":"Ruzhen Wang, Baitao Gu","doi":"10.1177/11786221231197416","DOIUrl":"https://doi.org/10.1177/11786221231197416","url":null,"abstract":"Rhizodeposition, as transported from photosynthates and exudated in soils via fine roots, is the pivot linking above- and belowground carbon (C) cycling pathways. Meanwhile, rhizodeposit C serves as “currency” for plant nutrient acquisition because of its critical roles in priming soil microorganisms, maintaining plant-mycorrhizal symbionts, and elongating plant roots. Therefore, a conceptual framework integrating knowledge on the biogeochemical fate of rhizodeposit C can help understand plant nutrient economics and soil C sink function. However, it still remains a great challenge to efficiently delineate the dynamics of rhizodeposit C in soils. In the framework, we present the possible stabilization pathways of rhizodeposit C via formation of mineral-associated organic matter (MAOM) or encapsulation by microaggregates. We further propose that continuous and pulse 13CO2 labeling are powerful techniques to track the fate of rhizodeposit C and to quantify how much C could eventually be sequestrated in soils as the component of MAOM or microaggregates. This framework would provide future research possibilities to better optimize plant C allocation and productivity and preserve soil C stocks.","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45882213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/11786221231200106
Abay Mustefa Abdule, Alemayehu Muluneh, Abraham Woldemichael
Climate and land use/cover (LULC) changes are essential factors that influence hydrological regimes by altering the groundwater recharge and river flow. This study investigated the separate and combined impact of climate and LULC changes on streamflow. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow under near-term (2021–2050) and mid-term (2051–2080) period against 1985 to 2015 baseline period. The Cellular Automata (CA)-Markov chain model was used to predict the future LULC change. The three-ensemble average of regional climate models (CCLM4.8, RACMO22T, EC-EARTH) under RCP 4.5 and RCP 8.5 emission scenarios were applied for future climate projection. The LULC predictions between 2035 and 2055 showed an increase in agricultural land, grassland, settlement areas and woodlands by 44.02%, 30.35%, 69.2%, and 55.05%, respectively, while forest and scrub/bush lands showed a decrease by decrease by 21.53% and 11.08%, respectively. The annual, wet, and dry seasons rainfall projections increased by 0.13%, 0.02%, and 0.85% respectively, during the near term period under RCP 4.5 scenarios. Overall, the annual, wet, and dry season rainfall projections showed slightly increasing tendency. The temperature projection consistently indicated a warmer future with the highest mean annual projected temperature being 2.0°C under high emission scenario during the midterm period. The projected streamflow under the combined impact of climate and LULC changes will increase by up to 8.72% in wet seasons and by up to 6.62% in dry seasons during the near-term period under RCP4.5 scenarios. Similarly, the projected mean annual streamflow will increase by up to 8.13%. The annual, wet and dry season’s streamflow projections showed a consistent increase during both near and midterm periods under both climate scenarios. Understanding the future response of streamflow under climate and LULC changes is crucial to plan adaptation options for water resources management under future warming condition.
{"title":"Impact of Climate and Land Use/Cover Changes on Streamflow in Yadot Watershed, Genale Dawa Basin, Ethiopia","authors":"Abay Mustefa Abdule, Alemayehu Muluneh, Abraham Woldemichael","doi":"10.1177/11786221231200106","DOIUrl":"https://doi.org/10.1177/11786221231200106","url":null,"abstract":"Climate and land use/cover (LULC) changes are essential factors that influence hydrological regimes by altering the groundwater recharge and river flow. This study investigated the separate and combined impact of climate and LULC changes on streamflow. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow under near-term (2021–2050) and mid-term (2051–2080) period against 1985 to 2015 baseline period. The Cellular Automata (CA)-Markov chain model was used to predict the future LULC change. The three-ensemble average of regional climate models (CCLM4.8, RACMO22T, EC-EARTH) under RCP 4.5 and RCP 8.5 emission scenarios were applied for future climate projection. The LULC predictions between 2035 and 2055 showed an increase in agricultural land, grassland, settlement areas and woodlands by 44.02%, 30.35%, 69.2%, and 55.05%, respectively, while forest and scrub/bush lands showed a decrease by decrease by 21.53% and 11.08%, respectively. The annual, wet, and dry seasons rainfall projections increased by 0.13%, 0.02%, and 0.85% respectively, during the near term period under RCP 4.5 scenarios. Overall, the annual, wet, and dry season rainfall projections showed slightly increasing tendency. The temperature projection consistently indicated a warmer future with the highest mean annual projected temperature being 2.0°C under high emission scenario during the midterm period. The projected streamflow under the combined impact of climate and LULC changes will increase by up to 8.72% in wet seasons and by up to 6.62% in dry seasons during the near-term period under RCP4.5 scenarios. Similarly, the projected mean annual streamflow will increase by up to 8.13%. The annual, wet and dry season’s streamflow projections showed a consistent increase during both near and midterm periods under both climate scenarios. Understanding the future response of streamflow under climate and LULC changes is crucial to plan adaptation options for water resources management under future warming condition.","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1177/11786221221145379
L. Salami, L. Popoola
Air pollutants generated as a result of operations of landfill sites pose a threat not only the environment but also to human life. This work focuses on comprehensive review of atmospheric air pollutants around landfill sites with a view of identifying areas where future studies can be conducted. Environmental and health effects of air pollutants within the vicinity of landfill sites and the ways of minimizing the level of the air pollutants were presented. Previous works carried out by scholars for the past two decades were critically examined. Mathematical models for prediction of gaseous pollutants for landfill sites and assessment of human health risk due of inhalation of poisonous gases from landfill sites were discussed. Amongst conclusions made were: (1) Further studies on health impacts of particulate matters (PMs) within the vicinity of landfill sites should focus on low-income countries (LIC) especially in Nigeria which has been perceived as the capital poverty of the world. (2) Developing countries have not been practicing Circular Municipal Solid Waste Management System (CMSW) due to some militating factors hence further works should look into how the militating factors can be surmounted and provide way forward for the implementation of CMSW in developing countries. (3) More works still need to be conducted especially in temperate region to mechanistically explain the positive correlation between PMs and Coronavirus disease. (4) Future works should dive into the cost and economic implications of assessing atmospheric air pollutants within the vicinity of landfill sites for policy making decisions.
{"title":"A Comprehensive Review of Atmospheric Air Pollutants Assessment Around Landfill Sites","authors":"L. Salami, L. Popoola","doi":"10.1177/11786221221145379","DOIUrl":"https://doi.org/10.1177/11786221221145379","url":null,"abstract":"Air pollutants generated as a result of operations of landfill sites pose a threat not only the environment but also to human life. This work focuses on comprehensive review of atmospheric air pollutants around landfill sites with a view of identifying areas where future studies can be conducted. Environmental and health effects of air pollutants within the vicinity of landfill sites and the ways of minimizing the level of the air pollutants were presented. Previous works carried out by scholars for the past two decades were critically examined. Mathematical models for prediction of gaseous pollutants for landfill sites and assessment of human health risk due of inhalation of poisonous gases from landfill sites were discussed. Amongst conclusions made were: (1) Further studies on health impacts of particulate matters (PMs) within the vicinity of landfill sites should focus on low-income countries (LIC) especially in Nigeria which has been perceived as the capital poverty of the world. (2) Developing countries have not been practicing Circular Municipal Solid Waste Management System (CMSW) due to some militating factors hence further works should look into how the militating factors can be surmounted and provide way forward for the implementation of CMSW in developing countries. (3) More works still need to be conducted especially in temperate region to mechanistically explain the positive correlation between PMs and Coronavirus disease. (4) Future works should dive into the cost and economic implications of assessing atmospheric air pollutants within the vicinity of landfill sites for policy making decisions.","PeriodicalId":44801,"journal":{"name":"Air Soil and Water Research","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44986760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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