Jaini Umrigar, Darshan J. Mehta, T. Caloiero, H. Azamathulla, Vijendra Kumar
Environmental flows are defined as the flow required into a stream to maintain the river’s ecosystem. The notion of Environmental Flow Allocation (EFA) ensures that a sufficient amount of water is delivered to the stream to maintain ecological integrity. The objective of this study is to examine environmental flows and determine the best acceptable strategy for providing flows into the river in the Lower Tapi Basin. To achieve this objective, daily discharge data from three sites, Ukai (period 1975–2020), Motinaroli (period 1990–2021), and Ghala (period 1995–2005) were collected and analyzed using the Tennant, Tessman, variable monthly flow (VMF), and Smakhtin methodologies. A comparative analysis was carried out on all three sites using the four methodologies. The Tessman and VMF approaches have a strong connection with the computed environmental flow requirements (EFR), according to the results. The calculated EFR was found to be in the range of 30–35% of mean annual flows (MAF). The maximum EFR found at station Ghala is about 54.5% of MAF according to the Tessman method. Such research will help to prevent future degradation of the river by supplying flow in accordance with the EFR, and it will also be used by stakeholders and policymakers to allocate water to preserve the ecosystem.
{"title":"A Comparative Study for Provision of Environmental Flows in the Tapi River","authors":"Jaini Umrigar, Darshan J. Mehta, T. Caloiero, H. Azamathulla, Vijendra Kumar","doi":"10.3390/earth4030030","DOIUrl":"https://doi.org/10.3390/earth4030030","url":null,"abstract":"Environmental flows are defined as the flow required into a stream to maintain the river’s ecosystem. The notion of Environmental Flow Allocation (EFA) ensures that a sufficient amount of water is delivered to the stream to maintain ecological integrity. The objective of this study is to examine environmental flows and determine the best acceptable strategy for providing flows into the river in the Lower Tapi Basin. To achieve this objective, daily discharge data from three sites, Ukai (period 1975–2020), Motinaroli (period 1990–2021), and Ghala (period 1995–2005) were collected and analyzed using the Tennant, Tessman, variable monthly flow (VMF), and Smakhtin methodologies. A comparative analysis was carried out on all three sites using the four methodologies. The Tessman and VMF approaches have a strong connection with the computed environmental flow requirements (EFR), according to the results. The calculated EFR was found to be in the range of 30–35% of mean annual flows (MAF). The maximum EFR found at station Ghala is about 54.5% of MAF according to the Tessman method. Such research will help to prevent future degradation of the river by supplying flow in accordance with the EFR, and it will also be used by stakeholders and policymakers to allocate water to preserve the ecosystem.","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":"99 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84546880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Climate classifications supply climate visualization with inference about general vegetation types. The Köppen classification system of thermal classes and an arid class is widely used, but options are available to strengthen climate change detection. For this study, I incorporated temperature and aridity information into all climate classes to isolate climate change, added a hypertropical class to better detect warming and drying in tropical zones, and developed a consistent ruleset of thermal classes with one temperature variable for streamlined application, yet maintained primary Köppen thermal classes. I compared climate currently to 6000 years ago (ka; Mid-Holocene) and 22 ka (Last Glacial Maximum) worldwide. Growing degree days > 0 °C was the most efficient variable for modeling thermal classes. Climate classes based on growing degree days matched 86% of Köppen thermal classes. Current climate shared 80% and 23% of class assignments with the Mid-Holocene and Last Glacial Maximum, respectively, with dry conditions shifting to the tropical and hypertropical classes under current climate. Contributing to our understanding of global environmental change, this classification demonstrated that the hypertropical class experienced the greatest change in area since 6 ka and the second greatest change in area since 22 ka, and the greatest increase in percentage arid classes during both intervals. The added hypertropical class with aridity information delivered sensitive detection of warming and drying for relevant climate classes under climate change.
{"title":"Global Climate Classification and Comparison to Mid-Holocene and Last Glacial Maximum Climates, with Added Aridity Information and a Hypertropical Class","authors":"B. Hanberry","doi":"10.3390/earth4030029","DOIUrl":"https://doi.org/10.3390/earth4030029","url":null,"abstract":"Climate classifications supply climate visualization with inference about general vegetation types. The Köppen classification system of thermal classes and an arid class is widely used, but options are available to strengthen climate change detection. For this study, I incorporated temperature and aridity information into all climate classes to isolate climate change, added a hypertropical class to better detect warming and drying in tropical zones, and developed a consistent ruleset of thermal classes with one temperature variable for streamlined application, yet maintained primary Köppen thermal classes. I compared climate currently to 6000 years ago (ka; Mid-Holocene) and 22 ka (Last Glacial Maximum) worldwide. Growing degree days > 0 °C was the most efficient variable for modeling thermal classes. Climate classes based on growing degree days matched 86% of Köppen thermal classes. Current climate shared 80% and 23% of class assignments with the Mid-Holocene and Last Glacial Maximum, respectively, with dry conditions shifting to the tropical and hypertropical classes under current climate. Contributing to our understanding of global environmental change, this classification demonstrated that the hypertropical class experienced the greatest change in area since 6 ka and the second greatest change in area since 22 ka, and the greatest increase in percentage arid classes during both intervals. The added hypertropical class with aridity information delivered sensitive detection of warming and drying for relevant climate classes under climate change.","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":"44 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87547158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Consumption of fish containing elevated levels of radionuclides can lead to undesirable health effects for consumers. People in the Singida Municipality harvest fish from lakes and ponds of granite rocks which are linked with hazardous radioisotopes that may be bio-concentrated by fishes they consume. Currently, no study has ascertained the levels of radioisotopes in fish from these environments. This study was carried out to analyse the radioactivity levels of 226Ra, 228Ra and 40K isotopes in order to assess the radiological risk associated with Tilapia fish consumption and its environment in Singida Municipality. Some 51 samples, which included water (20), sediment (20), Nile tilapia (8) and Manyara tilapia (3), were randomly sampled and composited; then, they were analysed using a high-purity germanium (HPGe) detector, between May and June 2022. The results revealed that (i) the activity levels of 228Ra were below the detection limit for fish and water samples, while in sediment, the combined activity of 228Ra was within the acceptable international levels; (ii) the mean activity concentrations of 226Ra and 40K in all other samples were within the recommended levels; (iii) the activities of radionuclides in the samples analysed were high in sediments, followed by fish, and lastly water; (iv) the bioaccumulation results show that only 40K was bio-accumulated (with 1.26 in Nile tilapia), while other radionuclides (226Ra, 228Ra) were not bio-accumulated; (vi) the radionuclide transfer from water to fish was higher compared to the radionuclide transfer from sediment to fish; (vii) the human effective doses due to consumption of Nile tilapia and Manyara tilapia were 0.00973 and 0.005 mSv/y, respectively, which is below the 1 mSv/y international limit. These findings therefore show that the current levels of radioactivity in fish in the study area do not pose a significant radiological risk to fish consumers. However, more studies on other types of fish are recommended.
{"title":"A Radiological Risk Assessment of 226Ra, 228Ra and 40K Isotopes in Tilapia Fish and its Granitic Environment in Singida Municipality, Tanzania","authors":"Amin R. Kazoka, J. Mwalilino, Paul E Mtoni","doi":"10.3390/earth4030028","DOIUrl":"https://doi.org/10.3390/earth4030028","url":null,"abstract":"Consumption of fish containing elevated levels of radionuclides can lead to undesirable health effects for consumers. People in the Singida Municipality harvest fish from lakes and ponds of granite rocks which are linked with hazardous radioisotopes that may be bio-concentrated by fishes they consume. Currently, no study has ascertained the levels of radioisotopes in fish from these environments. This study was carried out to analyse the radioactivity levels of 226Ra, 228Ra and 40K isotopes in order to assess the radiological risk associated with Tilapia fish consumption and its environment in Singida Municipality. Some 51 samples, which included water (20), sediment (20), Nile tilapia (8) and Manyara tilapia (3), were randomly sampled and composited; then, they were analysed using a high-purity germanium (HPGe) detector, between May and June 2022. The results revealed that (i) the activity levels of 228Ra were below the detection limit for fish and water samples, while in sediment, the combined activity of 228Ra was within the acceptable international levels; (ii) the mean activity concentrations of 226Ra and 40K in all other samples were within the recommended levels; (iii) the activities of radionuclides in the samples analysed were high in sediments, followed by fish, and lastly water; (iv) the bioaccumulation results show that only 40K was bio-accumulated (with 1.26 in Nile tilapia), while other radionuclides (226Ra, 228Ra) were not bio-accumulated; (vi) the radionuclide transfer from water to fish was higher compared to the radionuclide transfer from sediment to fish; (vii) the human effective doses due to consumption of Nile tilapia and Manyara tilapia were 0.00973 and 0.005 mSv/y, respectively, which is below the 1 mSv/y international limit. These findings therefore show that the current levels of radioactivity in fish in the study area do not pose a significant radiological risk to fish consumers. However, more studies on other types of fish are recommended.","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":"59 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77897197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to better understand the extent to which global climate variability is linked to the frequency and intensity of heat waves and overall changes in temperature throughout the United States (US), correlations between long-term monthly mean, minimum, and maximum temperatures throughout the contiguous US on the one hand and low-frequency variability of multiple climate indices (CIs) on the other hand are analyzed for the period from 1948 to 2018. The Pearson’s correlation coefficient is used to assess correlation strength, while leave-one-out cross-validation and a bootstrapping technique (p-value) are used to address potential serial and spurious correlations and assess the significance of each correlation. Three parameters defined the sliding windows over which surface temperature and CI values were averaged: window size, lag time between the temperature and CI windows, and the beginning month of the temperature window. A 60-month sliding window size and 0 lag time resulted in the highest correlations overall; beginning months were optimized on an individual site basis. High (r ≥ 0.60) and significant (p-value ≤ 0.05) correlations were identified. The Western Hemisphere Warm Pool (WHWP) and El Niño/Southern Oscillation (ENSO) exhibited the strongest links to temperatures in the western US, tropical Atlantic sea surface temperatures to temperatures in the central US, the WHWP to temperatures throughout much of the eastern US, and atmospheric patterns over the northern Atlantic to temperatures in the Northeast and Southeast. The final results were compared to results from previous studies focused on precipitation and coastal sea levels. Regional consistency was found regarding links between the northern Atlantic and overall weather and coastal sea levels in the Northeast and Southeast as well as on weather in the upper Midwest. Though the MJO and WHWP revealed dominant links with precipitation and temperature, respectively, throughout the West, ENSO revealed consistent links to sea levels and surface temperatures along the West Coast. These results help to focus future research on specific mechanisms of large-scale climate variability linked to US regional climate variability and prediction potential.
{"title":"Statistical Connections between Large-Scale Climate Indices and Observed Mean and Extreme Temperatures in the US from 1948 to 2018","authors":"J. Giovannettone","doi":"10.3390/earth4030027","DOIUrl":"https://doi.org/10.3390/earth4030027","url":null,"abstract":"In order to better understand the extent to which global climate variability is linked to the frequency and intensity of heat waves and overall changes in temperature throughout the United States (US), correlations between long-term monthly mean, minimum, and maximum temperatures throughout the contiguous US on the one hand and low-frequency variability of multiple climate indices (CIs) on the other hand are analyzed for the period from 1948 to 2018. The Pearson’s correlation coefficient is used to assess correlation strength, while leave-one-out cross-validation and a bootstrapping technique (p-value) are used to address potential serial and spurious correlations and assess the significance of each correlation. Three parameters defined the sliding windows over which surface temperature and CI values were averaged: window size, lag time between the temperature and CI windows, and the beginning month of the temperature window. A 60-month sliding window size and 0 lag time resulted in the highest correlations overall; beginning months were optimized on an individual site basis. High (r ≥ 0.60) and significant (p-value ≤ 0.05) correlations were identified. The Western Hemisphere Warm Pool (WHWP) and El Niño/Southern Oscillation (ENSO) exhibited the strongest links to temperatures in the western US, tropical Atlantic sea surface temperatures to temperatures in the central US, the WHWP to temperatures throughout much of the eastern US, and atmospheric patterns over the northern Atlantic to temperatures in the Northeast and Southeast. The final results were compared to results from previous studies focused on precipitation and coastal sea levels. Regional consistency was found regarding links between the northern Atlantic and overall weather and coastal sea levels in the Northeast and Southeast as well as on weather in the upper Midwest. Though the MJO and WHWP revealed dominant links with precipitation and temperature, respectively, throughout the West, ENSO revealed consistent links to sea levels and surface temperatures along the West Coast. These results help to focus future research on specific mechanisms of large-scale climate variability linked to US regional climate variability and prediction potential.","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":"4 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82112410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Upasana Choudhury, S. Singh, Anand Kumar, Gowhar Meraj, Pankaj Kumar, S. Kanga
Amid global concerns regarding climate change and urbanization, understanding the interplay between land use/land cover (LULC) changes, the urban heat island (UHI) effect, and land surface temperatures (LST) is paramount. This study provides an in-depth exploration of these relationships in the context of the Kamrup Metropolitan District, Northeast India, over a period of 22 years (2000–2022) and forecasts the potential implications up to 2032. Employing a high-accuracy supervised machine learning algorithm for LULC analysis, significant transformations are revealed, including the considerable growth in urban built-up areas and the corresponding decline in cultivated land. Concurrently, a progressive rise in LST is observed, underlining the escalating UHI effect. This association is further substantiated through correlation studies involving the normalized difference built-up index (NDBI) and the normalized difference vegetation index (NDVI). The study further leverages the cellular automata–artificial neural network (CA-ANN) model to project the potential scenario in 2032, indicating a predicted intensification in LST, especially in regions undergoing rapid urban expansion. The findings underscore the environmental implications of unchecked urban growth, such as rising temperatures and the intensification of UHI effects. Consequently, this research stresses the critical need for sustainable land management and urban planning strategies, as well as proactive measures to mitigate adverse environmental changes. The results serve as a vital resource for policymakers, urban planners, and environmental scientists working towards harmonizing urban growth with environmental sustainability in the face of escalating global climate change.
{"title":"Assessing Land Use/Land Cover Changes and Urban Heat Island Intensification: A Case Study of Kamrup Metropolitan District, Northeast India (2000–2032)","authors":"Upasana Choudhury, S. Singh, Anand Kumar, Gowhar Meraj, Pankaj Kumar, S. Kanga","doi":"10.3390/earth4030026","DOIUrl":"https://doi.org/10.3390/earth4030026","url":null,"abstract":"Amid global concerns regarding climate change and urbanization, understanding the interplay between land use/land cover (LULC) changes, the urban heat island (UHI) effect, and land surface temperatures (LST) is paramount. This study provides an in-depth exploration of these relationships in the context of the Kamrup Metropolitan District, Northeast India, over a period of 22 years (2000–2022) and forecasts the potential implications up to 2032. Employing a high-accuracy supervised machine learning algorithm for LULC analysis, significant transformations are revealed, including the considerable growth in urban built-up areas and the corresponding decline in cultivated land. Concurrently, a progressive rise in LST is observed, underlining the escalating UHI effect. This association is further substantiated through correlation studies involving the normalized difference built-up index (NDBI) and the normalized difference vegetation index (NDVI). The study further leverages the cellular automata–artificial neural network (CA-ANN) model to project the potential scenario in 2032, indicating a predicted intensification in LST, especially in regions undergoing rapid urban expansion. The findings underscore the environmental implications of unchecked urban growth, such as rising temperatures and the intensification of UHI effects. Consequently, this research stresses the critical need for sustainable land management and urban planning strategies, as well as proactive measures to mitigate adverse environmental changes. The results serve as a vital resource for policymakers, urban planners, and environmental scientists working towards harmonizing urban growth with environmental sustainability in the face of escalating global climate change.","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":"166 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82883081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Greta E. M. Shum, M. Laguë, Stephanie S. Rushley, A. Swann
We explore the possible role of plant-atmosphere feedbacks in accelerating forest expansion using a simple example of forest establishment. We use an unconventional experimental design to simulate an initial forest establishment and the subsequent response of climate and nearby vegetation. We find that the forest’s existence produces favorable nearby growing-season conditions that would promote forest expansion. Specifically, we consider a hypothetical region of forest expansion in modern Alaska. We find that the forest acts as a source of heat and moisture for plants to the west, leading them to experience earlier springtime temperatures, snowmelt, and growth. Summertime cooling and cloud formation over the forest also drive a circulation change that reduces summertime cloud cover south of the forest, increasing solar radiation reaching plants there, and driving warming. By isolating these vegetation-atmosphere interactions as the mechanisms of increased growth, we demonstrate the potential for forest expansion to be accelerated in a way that has not been highlighted before. These simulations illuminate two separate mechanisms that lead to increased plant growth nearby: (1) springtime heat advection and (2) summertime cloud feedbacks and circulation changes; both have implications for our understanding of past changes in forest cover and the predictability of biophysical impacts from afforestation projects and climate change-driven forest-cover changes. By examining these feedbacks, we seek to gain a more comprehensive understanding of past and potential future land-atmosphere interactions.
{"title":"Beautiful Days in the Neighborhood: Land-Atmosphere Interactions as Drivers of Forest Expansion","authors":"Greta E. M. Shum, M. Laguë, Stephanie S. Rushley, A. Swann","doi":"10.1175/ei-d-22-0017.1","DOIUrl":"https://doi.org/10.1175/ei-d-22-0017.1","url":null,"abstract":"\u0000We explore the possible role of plant-atmosphere feedbacks in accelerating forest expansion using a simple example of forest establishment. We use an unconventional experimental design to simulate an initial forest establishment and the subsequent response of climate and nearby vegetation. We find that the forest’s existence produces favorable nearby growing-season conditions that would promote forest expansion. Specifically, we consider a hypothetical region of forest expansion in modern Alaska. We find that the forest acts as a source of heat and moisture for plants to the west, leading them to experience earlier springtime temperatures, snowmelt, and growth. Summertime cooling and cloud formation over the forest also drive a circulation change that reduces summertime cloud cover south of the forest, increasing solar radiation reaching plants there, and driving warming. By isolating these vegetation-atmosphere interactions as the mechanisms of increased growth, we demonstrate the potential for forest expansion to be accelerated in a way that has not been highlighted before. These simulations illuminate two separate mechanisms that lead to increased plant growth nearby: (1) springtime heat advection and (2) summertime cloud feedbacks and circulation changes; both have implications for our understanding of past changes in forest cover and the predictability of biophysical impacts from afforestation projects and climate change-driven forest-cover changes. By examining these feedbacks, we seek to gain a more comprehensive understanding of past and potential future land-atmosphere interactions.","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43067964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lake Mead located in the Arizona–Nevada region of the Mohave Dessert is a unique and complex water system whose flow follows that of a warm monomictic lake. Although monomictic lakes experience thermal stratification for almost the entire year with a period of complete mixing, the lake on occasion deviates from this phenomenon, undergoing incomplete turnovers categorized with light stratifications every other year. The prolonged drought and growing anthropogenic activities have the potential to considerably impact the quality of the lake. Lake Mead and by extension the Boulder Basin receive cooler flow from the Colorado River and flow with varying temperatures from the Las Vegas Wash (LVW), which impacts its stratification and complete turnovers. This study analyzes four key water quality parameters (WQPs), namely, total dissolved solids (TDS), total suspended solids (TSS), temperature, and dissolved oxygen (DO), using statistical and spatial analyses to understand their variations in light of the lake stratifications and turnovers to further maintain its overall quality and sustainability. The study also evaluates the impacts of hydrological variables including in and out flows, storage, evaporation, and water surface elevation on the WQPs. The results produced from the analysis show significant levels of TDS, TSS, and temperature from the LVW and Las Vegas Bay regions compared with the Boulder Basin. LVW is the main channel for conveying effluents from several wastewater treatment facilities into the lake. We observed an increase in the levels of TDS, TSS, and temperature water quality in the epilimnion compared with the other layers of the lake. The metalimnion and the hypolimnion layer, however, showed reduced DO due to depletion by algal blooms. We observed statistically significant differences in the WQPs throughout various months, but not in the case for season and year, an indication of relatively consistent variability throughout each season and year. We also observed a no clear trend of influence of outflows and inflows on TDS, temperature, and DO. TSS concentrations in the lake, however, remained constant, irrespective of the inflows and outflows, possibly due to the settling of the sediments and the reservoir capacity.
{"title":"Spatial and Temporal Dynamics of Key Water Quality Parameters in a Thermal Stratified Lake Ecosystem: The Case Study of Lake Mead","authors":"Godson Ebenezer Adjovu, H. Stephen, Sajjad Ahmad","doi":"10.3390/earth4030025","DOIUrl":"https://doi.org/10.3390/earth4030025","url":null,"abstract":"Lake Mead located in the Arizona–Nevada region of the Mohave Dessert is a unique and complex water system whose flow follows that of a warm monomictic lake. Although monomictic lakes experience thermal stratification for almost the entire year with a period of complete mixing, the lake on occasion deviates from this phenomenon, undergoing incomplete turnovers categorized with light stratifications every other year. The prolonged drought and growing anthropogenic activities have the potential to considerably impact the quality of the lake. Lake Mead and by extension the Boulder Basin receive cooler flow from the Colorado River and flow with varying temperatures from the Las Vegas Wash (LVW), which impacts its stratification and complete turnovers. This study analyzes four key water quality parameters (WQPs), namely, total dissolved solids (TDS), total suspended solids (TSS), temperature, and dissolved oxygen (DO), using statistical and spatial analyses to understand their variations in light of the lake stratifications and turnovers to further maintain its overall quality and sustainability. The study also evaluates the impacts of hydrological variables including in and out flows, storage, evaporation, and water surface elevation on the WQPs. The results produced from the analysis show significant levels of TDS, TSS, and temperature from the LVW and Las Vegas Bay regions compared with the Boulder Basin. LVW is the main channel for conveying effluents from several wastewater treatment facilities into the lake. We observed an increase in the levels of TDS, TSS, and temperature water quality in the epilimnion compared with the other layers of the lake. The metalimnion and the hypolimnion layer, however, showed reduced DO due to depletion by algal blooms. We observed statistically significant differences in the WQPs throughout various months, but not in the case for season and year, an indication of relatively consistent variability throughout each season and year. We also observed a no clear trend of influence of outflows and inflows on TDS, temperature, and DO. TSS concentrations in the lake, however, remained constant, irrespective of the inflows and outflows, possibly due to the settling of the sediments and the reservoir capacity.","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":"9 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81262043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The AquaCrop model is used to predict rice yield in response to different irrigation management in the Yanyun irrigation area in Yangzhou, China, and the constraints to rice production were identified to maximize water productivity based on model simulations. The model was calibrated by comparing measured and predicted canopy cover (CC), yield, and soil water content during the growing season in 2018. The results showed that, for CC simulations, R2 was 0.99, RMSE was 3.6%, and NRMSE was 5.3%; for Biomass simulation, RMSE was 0.50 t/ha, and NRMSE was 5.3%. Different irrigation strategies were analyzed for a long-term simulation period from 1955 to 2014. The simulated rice yield increased rapidly as irrigation demand increased initially, and then gradually stabilized. The simulated rice yield fluctuated in the different years. The Pearson type-III model method was used to identify different hydrological years of wet, normal, and dry years. The analysis identified the wet year as 1991, normal year as 1981, and dry year as 1966. In the different rainfall years (1991, 1981, and 1966) water use efficiency (WUE), water productivity (WPet), and irrigation water productivity (IWP) were utilized to determine the irrigation strategy. The predicted highest WPet in the wet year was 1.77kg m−3, while the lowest WPet in the dry year was 1.13 kg m−3. The highest IWP was 19.78 kg m−3 in the wet year, and 9.32 kg m−3 in the normal year; while the lowest IWP in the dry year was 1.90 kg m−3. IWP was significantly higher in the rainy year, while WUE was significantly lower. On the other hand, WPet was more extensive in the wet year because the yield was higher, and the Evapotranspiration (ET) was smaller in comparison to the dry year.
采用AquaCrop模型对扬州盐云灌区不同灌溉方式下的水稻产量进行了预测，并在模型模拟的基础上找出了制约水稻生产的制约因素，以实现水分生产力最大化。该模型通过比较2018年生长季节的实测和预测冠层盖度(CC)、产量和土壤含水量进行校准。结果表明，CC模拟的R2为0.99,RMSE为3.6%，NRMSE为5.3%;生物量模拟RMSE为0.50 t/ha, NRMSE为5.3%。对1955 ~ 2014年长期模拟期不同灌溉策略进行了分析。模拟水稻产量初期随灌溉需求的增加而迅速增加，随后逐渐稳定。模拟的水稻产量在不同年份有所波动。采用Pearson - iii型模型方法对湿年、正常年和干年的不同水文年进行了识别。分析确定1991年为湿润年，1981年为正常年，1966年为干旱年。在不同的降雨年(1991年、1981年和1966年)，利用水利用效率(WUE)、水生产力(WPet)和灌溉水生产力(IWP)来确定灌溉策略。湿年WPet预测值最高为1.77kg m−3，干年WPet预测值最低为1.13 kg m−3。丰水年IWP最高为19.78 kg m−3，平水年最高为9.32 kg m−3;枯水年最低IWP为1.90 kg m−3。在多雨年份，IWP显著高，WUE显著低。另一方面，丰水年由于产量较高，蒸散发(ET)比干旱年小，因此WPet分布更为广泛。
{"title":"Optimizing Rice Irrigation Strategies to Maximize Water Productivity: A Simulation Study Using AquaCrop Model for the Yanyun Irrigation District, Yangzhou, China","authors":"Monera Mostafa, W. Luo, J. Zou, A. Salem","doi":"10.3390/earth4030024","DOIUrl":"https://doi.org/10.3390/earth4030024","url":null,"abstract":"The AquaCrop model is used to predict rice yield in response to different irrigation management in the Yanyun irrigation area in Yangzhou, China, and the constraints to rice production were identified to maximize water productivity based on model simulations. The model was calibrated by comparing measured and predicted canopy cover (CC), yield, and soil water content during the growing season in 2018. The results showed that, for CC simulations, R2 was 0.99, RMSE was 3.6%, and NRMSE was 5.3%; for Biomass simulation, RMSE was 0.50 t/ha, and NRMSE was 5.3%. Different irrigation strategies were analyzed for a long-term simulation period from 1955 to 2014. The simulated rice yield increased rapidly as irrigation demand increased initially, and then gradually stabilized. The simulated rice yield fluctuated in the different years. The Pearson type-III model method was used to identify different hydrological years of wet, normal, and dry years. The analysis identified the wet year as 1991, normal year as 1981, and dry year as 1966. In the different rainfall years (1991, 1981, and 1966) water use efficiency (WUE), water productivity (WPet), and irrigation water productivity (IWP) were utilized to determine the irrigation strategy. The predicted highest WPet in the wet year was 1.77kg m−3, while the lowest WPet in the dry year was 1.13 kg m−3. The highest IWP was 19.78 kg m−3 in the wet year, and 9.32 kg m−3 in the normal year; while the lowest IWP in the dry year was 1.90 kg m−3. IWP was significantly higher in the rainy year, while WUE was significantly lower. On the other hand, WPet was more extensive in the wet year because the yield was higher, and the Evapotranspiration (ET) was smaller in comparison to the dry year.","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":"42 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84012118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mineral resources remain essential to contemporary society and determine the important patterns of its sustainable development [...]
矿产资源对当代社会仍然至关重要，并决定着其可持续发展的重要模式。
{"title":"Book Review: Sanz et al. Elements and Mineral Resources; Springer: Cham, Switzerland, 2022; ISBN 978-3-030-85888-9","authors":"D. Ruban","doi":"10.3390/earth4020023","DOIUrl":"https://doi.org/10.3390/earth4020023","url":null,"abstract":"Mineral resources remain essential to contemporary society and determine the important patterns of its sustainable development [...]","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":"158 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76621021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RonnyGorata Matenge., B. Parida, M. W. Letshwenyo, Gofetamang Ditalelo
Futuristic rainfall projections are used in scale and various climate impact assessments. However, the influence of climate variability on spatial distribution patterns and characteristics of rainfall at the local level, especially in semi-arid catchments that are highly variable and are not well explored. In this study, we explore the influence of climate variability on the spatial distribution and rainfall characteristics at a local scale in the semi-arid Shashe catchment, Northeastern Botswana. The LARS-WG, Long Ashton Research Station Weather Generator downscaling method, three representative scenarios (RCP 2.6, RCP 4.5, and RCP 4.5), three trend detection methods (Mann-Kendall, Sen’s slope, and innovative trend analysis) and L-moment method were used to assess climate change impacts on rainfall. Two data sets were used; one with 40 years of observed data from 1981–2020 and the other with 70 years from 1981–2050 (40 years of observed and 30 years of projected data from 2021–2050). Generally, the study found trend inconsistencies for all the trend detection methods. In most cases, Sen’s Slope has a high estimate of observed and RCP 2.6, while ITA overestimates rainfall totals under RCP 4.5 and RCP 8.5. The trend is increasing for annual total rainfall in most gauging stations while decreasing for annual maximum rainfall. The catchment is homogeneous, and Generalized Logistic distribution is the dataset’s best-fit distribution. Spatial coverage of a 100-year rainfall between 151–180 mm will be 81% based on observed data and 87% based on projected data under RCP 2.6 scenario when it happens. A 200-year rainfall between 196–240 mm under RCP 4.5 and 8.5 has high spatial areal coverage, at least 90% of the total catchment. The outcomes of this study will provide insightful information for water resource management and flood risk assessment under climate change. There is a need, however, to assess the transferability of this approach to other catchments in the country and assess the performance of other advanced modelling systems, such as machine learning, in this region.
{"title":"Impact of Climate Variability on Rainfall Characteristics in the Semi-Arid Shashe Catchment (Botswana) from 1981–2050","authors":"RonnyGorata Matenge., B. Parida, M. W. Letshwenyo, Gofetamang Ditalelo","doi":"10.3390/earth4020022","DOIUrl":"https://doi.org/10.3390/earth4020022","url":null,"abstract":"Futuristic rainfall projections are used in scale and various climate impact assessments. However, the influence of climate variability on spatial distribution patterns and characteristics of rainfall at the local level, especially in semi-arid catchments that are highly variable and are not well explored. In this study, we explore the influence of climate variability on the spatial distribution and rainfall characteristics at a local scale in the semi-arid Shashe catchment, Northeastern Botswana. The LARS-WG, Long Ashton Research Station Weather Generator downscaling method, three representative scenarios (RCP 2.6, RCP 4.5, and RCP 4.5), three trend detection methods (Mann-Kendall, Sen’s slope, and innovative trend analysis) and L-moment method were used to assess climate change impacts on rainfall. Two data sets were used; one with 40 years of observed data from 1981–2020 and the other with 70 years from 1981–2050 (40 years of observed and 30 years of projected data from 2021–2050). Generally, the study found trend inconsistencies for all the trend detection methods. In most cases, Sen’s Slope has a high estimate of observed and RCP 2.6, while ITA overestimates rainfall totals under RCP 4.5 and RCP 8.5. The trend is increasing for annual total rainfall in most gauging stations while decreasing for annual maximum rainfall. The catchment is homogeneous, and Generalized Logistic distribution is the dataset’s best-fit distribution. Spatial coverage of a 100-year rainfall between 151–180 mm will be 81% based on observed data and 87% based on projected data under RCP 2.6 scenario when it happens. A 200-year rainfall between 196–240 mm under RCP 4.5 and 8.5 has high spatial areal coverage, at least 90% of the total catchment. The outcomes of this study will provide insightful information for water resource management and flood risk assessment under climate change. There is a need, however, to assess the transferability of this approach to other catchments in the country and assess the performance of other advanced modelling systems, such as machine learning, in this region.","PeriodicalId":51020,"journal":{"name":"Earth Interactions","volume":"2014 4","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72485297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：