Jeong-Hyeok Ma, Chulsang Yoo, Wooyoung Na, Jong-Sup Lee
Abstract This study evaluates the appropriateness of general circulation model-based future rainfall data used in Korea. The evaluation is done through the analysis of long-term occurrence characteristics of dry years, as well as the analysis of the water supply system including the daily based rainfall-runoff analysis and reservoir operation. This study considers the Boryeong Dam basin in Korea as a study basin. Summarizing the results is as follows. First, the future rainfall data show that the occurrence frequency of dry years is similar to the observed, but the occurrence frequency of consecutive multi-year dry years is far smaller than the observed. Second, the future rainfall data result in no or far less water supply shortages. This is mainly due to the fact that the Boryeong Dam has the ability to overcome the one-year drought and the future rainfall data contain far fewer multi-year droughts. However, these results clearly indicate the problems of the future rainfall data, especially in the long-term persistence of rainfall. It is thus disappointing that these future climate rainfall data may not be used to evaluate the water supply system in the future, at least in the Boryeong Dam basin.
{"title":"Reason of less water supply shortages under climate change condition: evaluation of future rainfall data","authors":"Jeong-Hyeok Ma, Chulsang Yoo, Wooyoung Na, Jong-Sup Lee","doi":"10.2166/wcc.2023.469","DOIUrl":"https://doi.org/10.2166/wcc.2023.469","url":null,"abstract":"Abstract This study evaluates the appropriateness of general circulation model-based future rainfall data used in Korea. The evaluation is done through the analysis of long-term occurrence characteristics of dry years, as well as the analysis of the water supply system including the daily based rainfall-runoff analysis and reservoir operation. This study considers the Boryeong Dam basin in Korea as a study basin. Summarizing the results is as follows. First, the future rainfall data show that the occurrence frequency of dry years is similar to the observed, but the occurrence frequency of consecutive multi-year dry years is far smaller than the observed. Second, the future rainfall data result in no or far less water supply shortages. This is mainly due to the fact that the Boryeong Dam has the ability to overcome the one-year drought and the future rainfall data contain far fewer multi-year droughts. However, these results clearly indicate the problems of the future rainfall data, especially in the long-term persistence of rainfall. It is thus disappointing that these future climate rainfall data may not be used to evaluate the water supply system in the future, at least in the Boryeong Dam basin.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135551967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Turkey's Mediterranean aquaculture industry is the world leader in European seabass aquaculture and the European leader in meagre aquaculture. In this study, carbon footprint (CF) values of four partial harvests of European seabass in earthen pond aquaculture (EPES) and meagre in earthen pond aquaculture (EPM) were determined. The average values of total CF expended for EPES and EPM, which reached a final harvest weight of approximately 1,500 g in 1,061 and 633 days were 3.38 and 2.26 kg CO2e kg−1, respectively. The lowest and highest rates of CF expended on consumed compound diet (CFCD) were 63.92 and 65.59% in EPES, and 62.44 and 66.70% in EPM, respectively. The rates of CF general management were 32.0 and 33.57% in EPES and 30.98 and 34.98% in EPM, respectively. Against this high proportion of the compound diet, the second highest value was the lowest and highest proportion of partial harvests of electricity, 28.20 and 29.59% in EPES and 27.09 and 30.51% in EPM, respectively. CF input and CF output per kg values of meagre were decreased with increasing weight, therefore meagre can be defined as a species with high global food security and resilience against climate change.
土耳其的地中海水产养殖业是欧洲海鲈鱼养殖的世界领导者，也是欧洲贫水产养殖的领导者。本研究测定了四种泥塘养殖欧洲鲈鱼的部分收获量和贫乏收获量的碳足迹(CF)值。在1061天和633天内达到最终收获重约1500 g的EPES和EPM的总CF消耗平均值分别为3.38和2.26 kg CO2e kg - 1。饲粮中CF消耗率最高、最低的分别是EPES的63.92%和65.59%，EPM的62.44%和66.70%。EPES和EPM的CF综合管理率分别为32.0和33.57%和30.98和34.98%。与这一高比例的配合饲粮相比，第二高的是部分采电比例最低和最高，EPES为28.20和29.59%，EPM为27.09和30.51%。每千克肥的CF投入和CF产出值随着体重的增加而减少，因此可以将贫定义为具有高全球粮食安全和抵御气候变化能力的物种。
{"title":"Carbon footprint values as a climate change assessment criterion of the partial harvests of European seabass and meagre in earthen pond aquaculture","authors":"Gürkan Diken, Ergi Bahrioğlu","doi":"10.2166/wcc.2023.344","DOIUrl":"https://doi.org/10.2166/wcc.2023.344","url":null,"abstract":"Abstract Turkey's Mediterranean aquaculture industry is the world leader in European seabass aquaculture and the European leader in meagre aquaculture. In this study, carbon footprint (CF) values of four partial harvests of European seabass in earthen pond aquaculture (EPES) and meagre in earthen pond aquaculture (EPM) were determined. The average values of total CF expended for EPES and EPM, which reached a final harvest weight of approximately 1,500 g in 1,061 and 633 days were 3.38 and 2.26 kg CO2e kg−1, respectively. The lowest and highest rates of CF expended on consumed compound diet (CFCD) were 63.92 and 65.59% in EPES, and 62.44 and 66.70% in EPM, respectively. The rates of CF general management were 32.0 and 33.57% in EPES and 30.98 and 34.98% in EPM, respectively. Against this high proportion of the compound diet, the second highest value was the lowest and highest proportion of partial harvests of electricity, 28.20 and 29.59% in EPES and 27.09 and 30.51% in EPM, respectively. CF input and CF output per kg values of meagre were decreased with increasing weight, therefore meagre can be defined as a species with high global food security and resilience against climate change.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135736223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Enrong Zhao, Qian Yao, Xiaolong Pan, Rong Yao, Hongzhuan Chen, Tao Su
Abstract Using meteorological analysis, composite analysis and water vapor trajectory analysis, the extreme value rainstorm process in northwest Hunan was analyzed. The results show that three types are summarized: the Southwest Vortex and Warm Shear Line Pattern (SVWSLP), the Subtropical High Edge Pattern (SHEP) and the Cold Trough and Shear Line Pattern (CTSLP). The main influence systems are upper trough, southwest vortex, shear line, low-level jet and subtropical high edge. For SVWSLP, the water vapor transport channels are only from the low-latitude ocean whether it is affected by long-distance typhoons. For SHEP, the main water vapor channel comes from the long-distance ocean and is finally transported to northwestern Hunan around 650 hPa in the form of warm and wet airflow, whether it is affected by long-distance typhoons. The CTSLP appears a significant water vapor confrontation between the north and the south and the baroclinicity of the atmosphere in the rainstorm area. The southern and western boundaries are the input boundary, while the eastern and northern boundaries are the outflow boundary. Therefore, one of the three types of weather systems appears in northwestern Hunan in May–August, with strong water vapor transport from the ocean surface, which is likely to cause extreme rainstorm.
{"title":"Weather system classification and water vapor transport characteristics of extreme value rainstorm in northwestern Hunan","authors":"Enrong Zhao, Qian Yao, Xiaolong Pan, Rong Yao, Hongzhuan Chen, Tao Su","doi":"10.2166/wcc.2023.075","DOIUrl":"https://doi.org/10.2166/wcc.2023.075","url":null,"abstract":"Abstract Using meteorological analysis, composite analysis and water vapor trajectory analysis, the extreme value rainstorm process in northwest Hunan was analyzed. The results show that three types are summarized: the Southwest Vortex and Warm Shear Line Pattern (SVWSLP), the Subtropical High Edge Pattern (SHEP) and the Cold Trough and Shear Line Pattern (CTSLP). The main influence systems are upper trough, southwest vortex, shear line, low-level jet and subtropical high edge. For SVWSLP, the water vapor transport channels are only from the low-latitude ocean whether it is affected by long-distance typhoons. For SHEP, the main water vapor channel comes from the long-distance ocean and is finally transported to northwestern Hunan around 650 hPa in the form of warm and wet airflow, whether it is affected by long-distance typhoons. The CTSLP appears a significant water vapor confrontation between the north and the south and the baroclinicity of the atmosphere in the rainstorm area. The southern and western boundaries are the input boundary, while the eastern and northern boundaries are the outflow boundary. Therefore, one of the three types of weather systems appears in northwestern Hunan in May–August, with strong water vapor transport from the ocean surface, which is likely to cause extreme rainstorm.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135740179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This study proposes a novel downscaling technique based on stacking ensemble machine learning (SEML) to predict rainfall under climate change. The SEML consists of two levels. Rainfall time series predicted by level 1 algorithms MLR, MNLR, MARS, M5, RF, LSBoost, LSSVM-GS, and a novel hybrid algorithm namely LSSVM-RUN) are used as inputs to the level 2 machine learning algorithm (MARS and LSSVM_RUN). Then, meta-algorithms of SEML predict rainfall based on eight predicted rainfall in level 1. This approach boosts prediction accuracy by utilizing the strong points of different machine learning (ML) algorithms. Results showed that MARS and LSSVM-RUN could be employed to improve the modeling results as meta-algorithms (level 2 of the SEML). Three global climate models (GCMs) in the historical period (1985–2014) and three SSP scenarios in the future period (2021–2050) were considered for downscaling and predicting rainfall at Lake Urmia and Sefidrood basins. Using meta-algorithms, the prediction results showed that rainfall in all scenarios and stations decreased between 0.02 and 0.20% (except Takab station in model CanESM5 scenarios). Hence, the proposed stacking ensemble ML has the potential for modeling and predicting precipitation with good accuracy and high reliability.
{"title":"Predicting rainfall response to climate change and uncertainty analysis: introducing a novel downscaling CMIP6 models technique based on the stacking ensemble machine learning","authors":"Mahdi Valikhan Anaraki, Mojtaba Kadkhodazadeh, Amirreza Morshed-Bozorgdel, Saeed Farzin","doi":"10.2166/wcc.2023.477","DOIUrl":"https://doi.org/10.2166/wcc.2023.477","url":null,"abstract":"Abstract This study proposes a novel downscaling technique based on stacking ensemble machine learning (SEML) to predict rainfall under climate change. The SEML consists of two levels. Rainfall time series predicted by level 1 algorithms MLR, MNLR, MARS, M5, RF, LSBoost, LSSVM-GS, and a novel hybrid algorithm namely LSSVM-RUN) are used as inputs to the level 2 machine learning algorithm (MARS and LSSVM_RUN). Then, meta-algorithms of SEML predict rainfall based on eight predicted rainfall in level 1. This approach boosts prediction accuracy by utilizing the strong points of different machine learning (ML) algorithms. Results showed that MARS and LSSVM-RUN could be employed to improve the modeling results as meta-algorithms (level 2 of the SEML). Three global climate models (GCMs) in the historical period (1985–2014) and three SSP scenarios in the future period (2021–2050) were considered for downscaling and predicting rainfall at Lake Urmia and Sefidrood basins. Using meta-algorithms, the prediction results showed that rainfall in all scenarios and stations decreased between 0.02 and 0.20% (except Takab station in model CanESM5 scenarios). Hence, the proposed stacking ensemble ML has the potential for modeling and predicting precipitation with good accuracy and high reliability.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135825432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rituraj Shukla, Deepak Khare, Anuj Kumar Dwivedi, Ramesh Pal Rudra, Santosh S. Palmate, C. S. P. Ojha, Vijay P. Singh
Abstract Statistical downscaling (SD) is preferable to dynamic downscaling to derive local-scale climate change information from large-scale datasets. Many statistical downscaling models are available these days, but comparison of their performance is still inadequately addressed for choosing a reliable SD model. Thus, it is desirable to compare the performance of SD models to ensure their adaptability in future climate studies. In this study, a statistical downscaling model (SDSM) or multi-linear regression and the Least Square Support Vector Machine (LS-SVM) were used to do downscaling and compare the results with those obtained from general circulation model (GCM) for identifying the best SD model for the Indira Sagar Canal Command area located in Madhya Pradesh, India. The GCM, Hadley Centre Coupled Model version 3 (HadCM3), was utilized to extract and downscale precipitation, maximum temperature (Tmax), and minimum temperature (Tmin) for 1961–2001 and then for 2001–2099. Before future projections, both SD models were initially calibrated (1961–1990) and validated (1991–2001) to evaluate their performance for precipitation and temperature variables at all gauge stations, namely Barwani, East Nimar, and West Nimar. Results showed that the precipitation trend was under-predicted owing to large errors in downscaling, while temperature was over-predicted by SD models.
{"title":"Evaluation of statistical downscaling model's performance in projecting future climate change scenarios","authors":"Rituraj Shukla, Deepak Khare, Anuj Kumar Dwivedi, Ramesh Pal Rudra, Santosh S. Palmate, C. S. P. Ojha, Vijay P. Singh","doi":"10.2166/wcc.2023.207","DOIUrl":"https://doi.org/10.2166/wcc.2023.207","url":null,"abstract":"Abstract Statistical downscaling (SD) is preferable to dynamic downscaling to derive local-scale climate change information from large-scale datasets. Many statistical downscaling models are available these days, but comparison of their performance is still inadequately addressed for choosing a reliable SD model. Thus, it is desirable to compare the performance of SD models to ensure their adaptability in future climate studies. In this study, a statistical downscaling model (SDSM) or multi-linear regression and the Least Square Support Vector Machine (LS-SVM) were used to do downscaling and compare the results with those obtained from general circulation model (GCM) for identifying the best SD model for the Indira Sagar Canal Command area located in Madhya Pradesh, India. The GCM, Hadley Centre Coupled Model version 3 (HadCM3), was utilized to extract and downscale precipitation, maximum temperature (Tmax), and minimum temperature (Tmin) for 1961–2001 and then for 2001–2099. Before future projections, both SD models were initially calibrated (1961–1990) and validated (1991–2001) to evaluate their performance for precipitation and temperature variables at all gauge stations, namely Barwani, East Nimar, and West Nimar. Results showed that the precipitation trend was under-predicted owing to large errors in downscaling, while temperature was over-predicted by SD models.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135887183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wan Asiah Nurjannah Wan Ahmad Tajuddin, Zainura Zainon Noor, Choong Weng Wai, Azmi Aris, Mohsen Nagheeby, Zulfaqar Sa'adi, Jaime Amezaga, Nor Atikah Abdul Wahid
Abstract The challenge of collaborative water governance often lies in the complexity of the networks involved in its processes, particularly in understanding the location of power and how the reputational power can be executed for policy decisions. A case study of the state of Johor, Malaysia, was done with the goal of figuring out a method for mapping out reputational powers in the network of actors involved in the water governance of the state. To achieve this goal, this study deconstructs the different facets of the state’s water governance system by outlining the spatial, operational, and legal boundaries of various agencies. The fundamental issues identified through this step are the complexity that leads to fragmented water governance. A research framework is thus proposed, derived from a qualitative approach whereby through in-depth interviews, respondents are asked to rank the water-related agencies based on their perceived influence. These rankings derived from qualitative interviews are given weights and subsequently measured using parameters such as density and in-degree centrality to provide quantitative evidence of the reputational powers held by actors in the water governance network. The study supports the future use of the reputational power research framework to achieve collaborative water governance solutions.
{"title":"Framing a social network analysis approach to understanding reputational power in the water governance of Johor, Malaysia","authors":"Wan Asiah Nurjannah Wan Ahmad Tajuddin, Zainura Zainon Noor, Choong Weng Wai, Azmi Aris, Mohsen Nagheeby, Zulfaqar Sa'adi, Jaime Amezaga, Nor Atikah Abdul Wahid","doi":"10.2166/wcc.2023.412","DOIUrl":"https://doi.org/10.2166/wcc.2023.412","url":null,"abstract":"Abstract The challenge of collaborative water governance often lies in the complexity of the networks involved in its processes, particularly in understanding the location of power and how the reputational power can be executed for policy decisions. A case study of the state of Johor, Malaysia, was done with the goal of figuring out a method for mapping out reputational powers in the network of actors involved in the water governance of the state. To achieve this goal, this study deconstructs the different facets of the state’s water governance system by outlining the spatial, operational, and legal boundaries of various agencies. The fundamental issues identified through this step are the complexity that leads to fragmented water governance. A research framework is thus proposed, derived from a qualitative approach whereby through in-depth interviews, respondents are asked to rank the water-related agencies based on their perceived influence. These rankings derived from qualitative interviews are given weights and subsequently measured using parameters such as density and in-degree centrality to provide quantitative evidence of the reputational powers held by actors in the water governance network. The study supports the future use of the reputational power research framework to achieve collaborative water governance solutions.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135884963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eduardo Yáñez San Francisco, Juan Antonio Pascual Aguilar, Shelley MacDonell
Abstract Globally, climate change has caused a significant reduction in snow cover in mountainous regions. To understand the impact of present and future snow changes on runoff in the semi-arid Andes, we applied the Hydro-BID hydrological model and associated datasets to the headwaters of the Elqui River basin (30°S) for current conditions and two Shared Socioeconomic Pathway (SSP) scenarios. Results show that model calibration at daily, monthly and annual time scales (R2 0.7, 0.7 and 0.8) and validation (R2 0.6, 0.7 and 0.7) were satisfactory. Future climate change scenario SSP2-4.5 indicates for 2040–2059, 2060–2079 and 2080–2099 temperature increases of 1.2, 1.6 and 1.9 °C and precipitation reductions of 26%, 29% and 36%. Discharge for SSP2-4.5 will reduce (the average annual flow decreases by 54%, 58% and 66%). For the same periods, SSP5-8.5 projects temperature increases of 1.5, 2.6 and 3.7 °C and precipitation reductions of 28%, 39% and 44%. Compared with SSP2-4.5, river discharge will experience a more acute reduction (projected annual decrease of 57%, 70% and 77%). Model results indicate that the maximum flow will be reached three months earlier than today. Results reinforce the importance of snow for runoff in the semi-arid Andes and the applicability of Hydro-BID in mountainous regions.
{"title":"Hydrological response of a headwater catchment in the semi-arid Andes (30°S) to climate change","authors":"Eduardo Yáñez San Francisco, Juan Antonio Pascual Aguilar, Shelley MacDonell","doi":"10.2166/wcc.2023.268","DOIUrl":"https://doi.org/10.2166/wcc.2023.268","url":null,"abstract":"Abstract Globally, climate change has caused a significant reduction in snow cover in mountainous regions. To understand the impact of present and future snow changes on runoff in the semi-arid Andes, we applied the Hydro-BID hydrological model and associated datasets to the headwaters of the Elqui River basin (30°S) for current conditions and two Shared Socioeconomic Pathway (SSP) scenarios. Results show that model calibration at daily, monthly and annual time scales (R2 0.7, 0.7 and 0.8) and validation (R2 0.6, 0.7 and 0.7) were satisfactory. Future climate change scenario SSP2-4.5 indicates for 2040–2059, 2060–2079 and 2080–2099 temperature increases of 1.2, 1.6 and 1.9 °C and precipitation reductions of 26%, 29% and 36%. Discharge for SSP2-4.5 will reduce (the average annual flow decreases by 54%, 58% and 66%). For the same periods, SSP5-8.5 projects temperature increases of 1.5, 2.6 and 3.7 °C and precipitation reductions of 28%, 39% and 44%. Compared with SSP2-4.5, river discharge will experience a more acute reduction (projected annual decrease of 57%, 70% and 77%). Model results indicate that the maximum flow will be reached three months earlier than today. Results reinforce the importance of snow for runoff in the semi-arid Andes and the applicability of Hydro-BID in mountainous regions.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135980634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces a novel design that uses high-emissivity materials with no hydrophobic surfaces to increase the speed of condensation and the dropping-off process in water collection systems from atmospheric moisture. The design incorporates simple and low-cost technology that takes advantage of advanced material properties to enable sustainable irrigation in regions characterized by water resource scarcity, generally favoring greening. The concept is based on the application of universal physics principles such as dew point, wetting and antiwetting, and material emissivity coefficients. The innovative collection system design and experimentation confirm the feasibility of collecting water from the air in various semi-arid regions with a low number of rainy days. The first novel aspect of the collection system design is the rapid increase in condensation and the use of materials with a high capacity to release collected water to address unwanted evaporation. The second novel feature is that the volume is reduced, and the system is flexible and inexpensive, allowing it to be distributed across a specific landscape. Reduced construction costs and ease of use demonstrate the real possibility of its use in developing and poor countries to first increase vegetation diffusion and then contribute to sustainable agriculture and green architecture.
{"title":"Toward sustainable landscape irrigation using a novel design for water collection systems that use atmospheric moisture condensation","authors":"Zaid Aldeek","doi":"10.2166/wcc.2023.135","DOIUrl":"https://doi.org/10.2166/wcc.2023.135","url":null,"abstract":"\u0000 \u0000 This paper introduces a novel design that uses high-emissivity materials with no hydrophobic surfaces to increase the speed of condensation and the dropping-off process in water collection systems from atmospheric moisture. The design incorporates simple and low-cost technology that takes advantage of advanced material properties to enable sustainable irrigation in regions characterized by water resource scarcity, generally favoring greening. The concept is based on the application of universal physics principles such as dew point, wetting and antiwetting, and material emissivity coefficients. The innovative collection system design and experimentation confirm the feasibility of collecting water from the air in various semi-arid regions with a low number of rainy days. The first novel aspect of the collection system design is the rapid increase in condensation and the use of materials with a high capacity to release collected water to address unwanted evaporation. The second novel feature is that the volume is reduced, and the system is flexible and inexpensive, allowing it to be distributed across a specific landscape. Reduced construction costs and ease of use demonstrate the real possibility of its use in developing and poor countries to first increase vegetation diffusion and then contribute to sustainable agriculture and green architecture.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47571471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Edwin Kipkirui, J. Zhao, Tao Wang, Jean Pierre Bavumiragira, Joseph Cirily James, Yves Ndizeye
Food losses threaten food security and sustainability in East Africa, a region that faces recurrent droughts and socio-economic shocks. The research utilized the water footprint method and the carbon emission factor to quantify the water footprint and the carbon footprint of food losses of five plant-based food kinds: cereals, vegetables, oil crops, fruits, and pulses. The study focused on the actual food losses in East Africa – Kenya, Uganda, and Tanzania – obtained from the enhanced food balance sheets in 2017. The study finds that the volume of the water wasted associated with the food losses (green + blue) was 6,164.1 million m3 (M.m3). Food loss also contributes to the degradation of the environment in the form of greenhouse gases (e.g. CO2 and CH4) and a source of non-point pollution of water resources. As a result, the greywater footprint was 838.1 M.m3 and carbon emissions were 5.53 million tons. In contrast to Kenya and Tanzania, Uganda had the lowest carbon and water footprint. These results can further clarify our understanding of the regional and global impacts of food losses on the environment and suggest that reducing food losses can help improve food security, conserve water resources, and protect the environment in East Africa.
{"title":"The implications of food loss on East Africa's environment and water resources","authors":"Edwin Kipkirui, J. Zhao, Tao Wang, Jean Pierre Bavumiragira, Joseph Cirily James, Yves Ndizeye","doi":"10.2166/wcc.2023.085","DOIUrl":"https://doi.org/10.2166/wcc.2023.085","url":null,"abstract":"\u0000 \u0000 Food losses threaten food security and sustainability in East Africa, a region that faces recurrent droughts and socio-economic shocks. The research utilized the water footprint method and the carbon emission factor to quantify the water footprint and the carbon footprint of food losses of five plant-based food kinds: cereals, vegetables, oil crops, fruits, and pulses. The study focused on the actual food losses in East Africa – Kenya, Uganda, and Tanzania – obtained from the enhanced food balance sheets in 2017. The study finds that the volume of the water wasted associated with the food losses (green + blue) was 6,164.1 million m3 (M.m3). Food loss also contributes to the degradation of the environment in the form of greenhouse gases (e.g. CO2 and CH4) and a source of non-point pollution of water resources. As a result, the greywater footprint was 838.1 M.m3 and carbon emissions were 5.53 million tons. In contrast to Kenya and Tanzania, Uganda had the lowest carbon and water footprint. These results can further clarify our understanding of the regional and global impacts of food losses on the environment and suggest that reducing food losses can help improve food security, conserve water resources, and protect the environment in East Africa.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42956939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ashik Rubaiyat, Md. Lokman Hossain, Md. Humayain Kabir, Md Monzer Hossain Sarker, Mir Md Abdus Salam, Jianfeng Li
Examination of greenhouse gas (GHG) fluxes (CO2, CH4, and N2O) in soils is crucial for developing effective strategies to mitigate climate change. In this study, we investigated the GHG fluxes in agricultural and forest soils to explore the changes in soil GHG fluxes, and assess the relationships of GHGs with other physico-chemical properties. Results show that forest soils have a higher CO2 flux, while agricultural soils have a higher N2O flux due to fertilizer application and heterotrophic nitrification. Forest soils act as a CH4 sink, which are connected with increased porosity and decreased bulk density. In agricultural soils, CO2 and N2O were strongly linked with NH4+, soil temperature, pH, soil organic carbon, total nitrogen, plant-available phosphorous, and microbial biomass nitrogen (mbN) but were negatively connected with bulk density and microbial biomass carbon (mbC). In contrast to CO2 and N2O, CH4 in agricultural soils exhibited inverse relationships with all physico-chemical properties. In forest soils, CO2 and CH4 were positively correlated with soil temperature and mbC, and mbN and N2O were negatively correlated with bulk density and pH. This study highlights the critical need to comprehend the complex relationship between soil physico-chemical properties and GHG fluxes for effective climate change mitigation.
{"title":"Dynamics of greenhouse gas fluxes and soil physico-chemical properties in agricultural and forest soils","authors":"Ashik Rubaiyat, Md. Lokman Hossain, Md. Humayain Kabir, Md Monzer Hossain Sarker, Mir Md Abdus Salam, Jianfeng Li","doi":"10.2166/wcc.2023.338","DOIUrl":"https://doi.org/10.2166/wcc.2023.338","url":null,"abstract":"\u0000 \u0000 Examination of greenhouse gas (GHG) fluxes (CO2, CH4, and N2O) in soils is crucial for developing effective strategies to mitigate climate change. In this study, we investigated the GHG fluxes in agricultural and forest soils to explore the changes in soil GHG fluxes, and assess the relationships of GHGs with other physico-chemical properties. Results show that forest soils have a higher CO2 flux, while agricultural soils have a higher N2O flux due to fertilizer application and heterotrophic nitrification. Forest soils act as a CH4 sink, which are connected with increased porosity and decreased bulk density. In agricultural soils, CO2 and N2O were strongly linked with NH4+, soil temperature, pH, soil organic carbon, total nitrogen, plant-available phosphorous, and microbial biomass nitrogen (mbN) but were negatively connected with bulk density and microbial biomass carbon (mbC). In contrast to CO2 and N2O, CH4 in agricultural soils exhibited inverse relationships with all physico-chemical properties. In forest soils, CO2 and CH4 were positively correlated with soil temperature and mbC, and mbN and N2O were negatively correlated with bulk density and pH. This study highlights the critical need to comprehend the complex relationship between soil physico-chemical properties and GHG fluxes for effective climate change mitigation.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49572172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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