Alonso Arias, Nicolás Núñez, Pedro Rau, Patrick Venail
Increase in average global temperature over the last few decades has caused an accelerated retreat of tropical glaciers. Andean populations live in strict dependence on the water services provided by mountains and glaciers. The present study aims to generate a glacier melt projection map in the Peruvian Central Cordillera based on vulnerability maps over the 1990–2021 period. Seven satellite images were selected to determine the changes in glacier coverage based on normalized indexes. Subsequently, seven parametric maps consisting of terrain and climate characteristics were assimilated into a vulnerability analysis based on the frequency index and the Shannon entropy index model, allowing one to identify areas most susceptible to glacial retreat. The results show that the most important criteria for the southern and northern glacial study areas are surface temperature, elevation, precipitation, aspect, orientation, and slope. The validation results revealed the most accurate set of parameters from the vulnerability map in terms of projecting melting areas and were used to produce a spatial projection map for the period 2021–2055. From 2021, a glacier loss in the range of 84–98% would be reached by 2050s.
{"title":"Development of a spatial projection map of glacial retreat based on vulnerability maps in the Central Cordillera, Peru","authors":"Alonso Arias, Nicolás Núñez, Pedro Rau, Patrick Venail","doi":"10.2166/wcc.2024.151","DOIUrl":"https://doi.org/10.2166/wcc.2024.151","url":null,"abstract":"\u0000 \u0000 Increase in average global temperature over the last few decades has caused an accelerated retreat of tropical glaciers. Andean populations live in strict dependence on the water services provided by mountains and glaciers. The present study aims to generate a glacier melt projection map in the Peruvian Central Cordillera based on vulnerability maps over the 1990–2021 period. Seven satellite images were selected to determine the changes in glacier coverage based on normalized indexes. Subsequently, seven parametric maps consisting of terrain and climate characteristics were assimilated into a vulnerability analysis based on the frequency index and the Shannon entropy index model, allowing one to identify areas most susceptible to glacial retreat. The results show that the most important criteria for the southern and northern glacial study areas are surface temperature, elevation, precipitation, aspect, orientation, and slope. The validation results revealed the most accurate set of parameters from the vulnerability map in terms of projecting melting areas and were used to produce a spatial projection map for the period 2021–2055. From 2021, a glacier loss in the range of 84–98% would be reached by 2050s.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141115868","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}
Using a combination of the long short-term memory model and hydrological change indicators, this study proposes an assessment framework at inter-annual and intra-annual scales to quantify the hydrological regime changes and ecological event responses caused by the regulation of the Three Gorges Dam (TGD) in the upper reaches of the Yangtze River. The results indicate that during the post-TGD period (2004–2019), 2 indicators of the natural flow regime undergo a high degree of alteration at the inter-annual scale, which increase to 12 when regulated flows are considered. Furthermore, we find that while climate and incoming water change significantly reduces the annual flow and monthly flow during the flood season, it increases the complexity (79%) and ecodeficit at the seasonal scale (94%). Among the 32 indicators of hydrologic alteration, TGD is the dominant factor influencing changes in 20 indicators, increasing the magnitude of low-flow events, decreasing the frequency of high-flow pulses, and advancing the timing of 1-day minimum flow (43 Julian date). From the hydrological perspective, the altered rising water conditions due to TGD regulation may cause an average decrease of 19.5% in the fry abundance for the Four Famous Major Carps.
{"title":"Assessing the effects of dam regulation on multiscale variations in river hydrological regime and ecological responses","authors":"Hongxiang Wang, Xiangyu Bai, Huan Yang, Xuyang Jiao, Lintong Huang, Wenxian Guo","doi":"10.2166/wcc.2024.660","DOIUrl":"https://doi.org/10.2166/wcc.2024.660","url":null,"abstract":"\u0000 \u0000 Using a combination of the long short-term memory model and hydrological change indicators, this study proposes an assessment framework at inter-annual and intra-annual scales to quantify the hydrological regime changes and ecological event responses caused by the regulation of the Three Gorges Dam (TGD) in the upper reaches of the Yangtze River. The results indicate that during the post-TGD period (2004–2019), 2 indicators of the natural flow regime undergo a high degree of alteration at the inter-annual scale, which increase to 12 when regulated flows are considered. Furthermore, we find that while climate and incoming water change significantly reduces the annual flow and monthly flow during the flood season, it increases the complexity (79%) and ecodeficit at the seasonal scale (94%). Among the 32 indicators of hydrologic alteration, TGD is the dominant factor influencing changes in 20 indicators, increasing the magnitude of low-flow events, decreasing the frequency of high-flow pulses, and advancing the timing of 1-day minimum flow (43 Julian date). From the hydrological perspective, the altered rising water conditions due to TGD regulation may cause an average decrease of 19.5% in the fry abundance for the Four Famous Major Carps.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141119566","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}
The objective of this study was to evaluate the best performed bias correction methods to simulate the regional climate models for future climate change projections in Muger Subbasin. Delta change methods perform very good with a coefficient of correlation of 0.99 and a percent of bias –3. When we compare its corrected simulation result with observed data, delta change method seems to be with no biases for maximum temperature, but it increases by 1.67 °C from the mean for minimum temperature of 0.39 and 38.41 mm for monthly and annual precipitation, respectively. Delta change methods underestimate the model result for both temperature and precipitation. Linear scaling and variance scaling methods overestimate the maximum temperature of the simulation by 0.002 and 0.004 °C amount from the mean of the observed data, but it underestimates 1.59 and 1.56 °C the minimum temperature, respectively. The long-term temperature projection values (2060–2090) are higher than the near-term projections (2030–2060) for both RCP2.6 and RCP8.5 scenarios. Similarly, the change in annual precipitation for the long-term is higher than the near-term projections. As a conclusion, the results draw attention to the fact that bias-adjusted regional climate models data are crucial for the provision of local climate change impact studies in the Muger Subbasin.
{"title":"Comparison of bias correction methods to regional climate model simulations for climate change projection in Muger Subbasin, Upper Blue Nile Basin, Ethiopia","authors":"Manamno Beza Dinku, Alene Moshe Gibre","doi":"10.2166/wcc.2024.591","DOIUrl":"https://doi.org/10.2166/wcc.2024.591","url":null,"abstract":"\u0000 \u0000 The objective of this study was to evaluate the best performed bias correction methods to simulate the regional climate models for future climate change projections in Muger Subbasin. Delta change methods perform very good with a coefficient of correlation of 0.99 and a percent of bias –3. When we compare its corrected simulation result with observed data, delta change method seems to be with no biases for maximum temperature, but it increases by 1.67 °C from the mean for minimum temperature of 0.39 and 38.41 mm for monthly and annual precipitation, respectively. Delta change methods underestimate the model result for both temperature and precipitation. Linear scaling and variance scaling methods overestimate the maximum temperature of the simulation by 0.002 and 0.004 °C amount from the mean of the observed data, but it underestimates 1.59 and 1.56 °C the minimum temperature, respectively. The long-term temperature projection values (2060–2090) are higher than the near-term projections (2030–2060) for both RCP2.6 and RCP8.5 scenarios. Similarly, the change in annual precipitation for the long-term is higher than the near-term projections. As a conclusion, the results draw attention to the fact that bias-adjusted regional climate models data are crucial for the provision of local climate change impact studies in the Muger Subbasin.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141121836","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}
Flood risk assessment remains a crucial element, particularly within locations highly susceptible to repeated flood occurrences. This study seeks to conduct an elaborate flood risk analysis for Mumbai, India based on an integrated method of geographic information systems and analytic hierarchy process (AHP). In this study, land use/land cover, average annual rainfall, elevation, drainage density, normalized difference vegetation index, distance from rivers as well as distance from roads are identified and considered. For this reason, the expert survey utilizes the AHP weights so as to find out the significance of these factors towards flooding danger. Investigations show a flood risk index and a corresponding map for Mumbai, where all areas are divided into risk zones very low to very high. ‘High’ risk or ‘Very High’ risks are particularly situated along the rivers. Such details offer critical knowledge to policymakers who will undertake informed emergency preparedness measures designed to shield Mumbai's citizens and assets. Therefore, this research is considered as one of the modern techniques flood risk evaluation, which can be applied in other flood-affected areas worldwide.
{"title":"Flood hazard analysis in Mumbai using geospatial and multi-criteria decision-making techniques","authors":"Yash Parshottambhai Solanki, Vijendra Kumar, Kul Vaibhav Sharma, Arpan Deshmukh, Deepak Kumar Tiwari","doi":"10.2166/wcc.2024.053","DOIUrl":"https://doi.org/10.2166/wcc.2024.053","url":null,"abstract":"\u0000 Flood risk assessment remains a crucial element, particularly within locations highly susceptible to repeated flood occurrences. This study seeks to conduct an elaborate flood risk analysis for Mumbai, India based on an integrated method of geographic information systems and analytic hierarchy process (AHP). In this study, land use/land cover, average annual rainfall, elevation, drainage density, normalized difference vegetation index, distance from rivers as well as distance from roads are identified and considered. For this reason, the expert survey utilizes the AHP weights so as to find out the significance of these factors towards flooding danger. Investigations show a flood risk index and a corresponding map for Mumbai, where all areas are divided into risk zones very low to very high. ‘High’ risk or ‘Very High’ risks are particularly situated along the rivers. Such details offer critical knowledge to policymakers who will undertake informed emergency preparedness measures designed to shield Mumbai's citizens and assets. Therefore, this research is considered as one of the modern techniques flood risk evaluation, which can be applied in other flood-affected areas worldwide.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140655521","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}
V. Banda, Rimuka Dzwairo, Sudhir Kumar Singh, T. Kanyerere
This study integrated climate projections from five global climate models (GCMs) into the soil and water assessment tool to evaluate the potential impact of climate alterations on the Rietspruit River sub-basin under two representative concentration pathways (RCP4.5 and 8.5). The model's performance was evaluated based on the coefficient of determination (R2), percent bias (PBIAS), Nash–Sutcliffe efficiency (NSE), probability (P)-factor and correlation coefficient (R)-factor. Calibration results showed an R2 of 0.62, NSE of 0.60, PBIAS of 20, P-factor of 0.86 and R-factor of 0.91, while validation produced an R2 of 0.64, NSE of 0.61, PBIAS of 40 and P-factor of 0.85 and R-factor of 1.22. Precipitation is predicted to increase under both RCPs. Maximum temperature is projected to increase under both RCPs, with a major increase in the winter months. Minimum temperatures are projected to decrease under RCP4.5 in the near (−0.99 °C) and mid (−0.23 °C) futures, while the far future is projected to experience an increase of 0.14 °C. Precipitation and temperature changes correspond to increases in streamflow by an average of 53% (RCP4.5) and 47% (RCP8.5). These results indicate a need for an integrated approach in catchment water resource management amid potential climate and land use variations.
{"title":"Quantifying the influence of climate change on streamflow of Rietspruit sub-basin, South Africa","authors":"V. Banda, Rimuka Dzwairo, Sudhir Kumar Singh, T. Kanyerere","doi":"10.2166/wcc.2024.690","DOIUrl":"https://doi.org/10.2166/wcc.2024.690","url":null,"abstract":"\u0000 \u0000 This study integrated climate projections from five global climate models (GCMs) into the soil and water assessment tool to evaluate the potential impact of climate alterations on the Rietspruit River sub-basin under two representative concentration pathways (RCP4.5 and 8.5). The model's performance was evaluated based on the coefficient of determination (R2), percent bias (PBIAS), Nash–Sutcliffe efficiency (NSE), probability (P)-factor and correlation coefficient (R)-factor. Calibration results showed an R2 of 0.62, NSE of 0.60, PBIAS of 20, P-factor of 0.86 and R-factor of 0.91, while validation produced an R2 of 0.64, NSE of 0.61, PBIAS of 40 and P-factor of 0.85 and R-factor of 1.22. Precipitation is predicted to increase under both RCPs. Maximum temperature is projected to increase under both RCPs, with a major increase in the winter months. Minimum temperatures are projected to decrease under RCP4.5 in the near (−0.99 °C) and mid (−0.23 °C) futures, while the far future is projected to experience an increase of 0.14 °C. Precipitation and temperature changes correspond to increases in streamflow by an average of 53% (RCP4.5) and 47% (RCP8.5). These results indicate a need for an integrated approach in catchment water resource management amid potential climate and land use variations.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140655735","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}
The interchange of water vapor between the land and the atmosphere is influenced by actual evapotranspiration (AET). A nonlinear model (AET-SWC-PET-GPP, ASPG) was developed in this study to combine potential evapotranspiration (PET), soil water content (SWC), and gross primary productivity (GPP) in order to quantitatively estimate AET. The Fluxnet Network 2015 global flux station dataset was used to compared to the AET models (AET-SWC, AS; AET-SWC-PET, ASP and AET-SWC-PET2, ASP2) with various combinations of influencing factors. The results show that the simulation accuracy of the ASPG model is higher than that of AS, ASP, and ASP2, with improvements in a coefficient of determination (R2) of 45.3, 8.1, and 5.7%, respectively.The ASPG performed well for various vegetation types, geographical regions, and time scales. It was also discovered that the fitting coefficients vary depending on the type of vegetation, each with its own range of values.The ASPG model put forth in this study can be used to more effectively estimate AET quantitatively on a global scale and can serve as a theoretical foundation for the accurate calculation of global evapotranspiration and the wise use of water resources.
{"title":"Modeling and prediction of high-precision global evapotranspiration: based on a different model of physical relationships","authors":"Yongxi Sun, Chao He, Yuru Dong, Yanfei Chen","doi":"10.2166/wcc.2024.162","DOIUrl":"https://doi.org/10.2166/wcc.2024.162","url":null,"abstract":"\u0000 \u0000 The interchange of water vapor between the land and the atmosphere is influenced by actual evapotranspiration (AET). A nonlinear model (AET-SWC-PET-GPP, ASPG) was developed in this study to combine potential evapotranspiration (PET), soil water content (SWC), and gross primary productivity (GPP) in order to quantitatively estimate AET. The Fluxnet Network 2015 global flux station dataset was used to compared to the AET models (AET-SWC, AS; AET-SWC-PET, ASP and AET-SWC-PET2, ASP2) with various combinations of influencing factors. The results show that the simulation accuracy of the ASPG model is higher than that of AS, ASP, and ASP2, with improvements in a coefficient of determination (R2) of 45.3, 8.1, and 5.7%, respectively.The ASPG performed well for various vegetation types, geographical regions, and time scales. It was also discovered that the fitting coefficients vary depending on the type of vegetation, each with its own range of values.The ASPG model put forth in this study can be used to more effectively estimate AET quantitatively on a global scale and can serve as a theoretical foundation for the accurate calculation of global evapotranspiration and the wise use of water resources.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140655552","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}
Venkatesh Gaddikeri, A. Sarangi, D. K. Singh, Malkhan Singh Jatav, Jitendra Rajput, N. L. Kushwaha
Climate change (CC) significantly influences agricultural water productivity, necessitating increased irrigation. Therefore, the present study was undertaken to assess the trend and change-point analyses of weather variables such as temperature (T), rainfall (R), and reference evapotranspiration (ET0) using 31-year long-term data for semi-arid climate. The analysis was carried out employing Mann–Kendall (MK), Modified Mann–Kendall (MMK), Innovative Trend Analysis (ITA), and Innovative Polygon Trend Analysis (IPTA) methods. Homogeneity tests, including Pettitt's test, Standard Normal Homogeneity Test (SNHT) , Buishand range test, and Von Neumann Ratio Test (VNRT), were employed to detect change points (CPs) in the time series data. The results indicated that, for maximum temperature, MK and MMK revealed a positive trend for September and July, respectively, while minimum temperatures indicated increasing trends in August and September. Rainfall exhibited an increasing trend during the Zaid season (April–May). ET0 exhibited a negative trend in January. ITA and IPTA displayed a mixture of positive and negative trends across months and seasons. The change-point analysis revealed that for Tmax, the CP occurred in 1998 for time-series data for the month of April. Likewise, for Tmin, the change points for April and August time series were found in 1997.
{"title":"Trend and change-point analyses of meteorological variables using Mann–Kendall family tests and innovative trend assessment techniques in New Bhupania command (India)","authors":"Venkatesh Gaddikeri, A. Sarangi, D. K. Singh, Malkhan Singh Jatav, Jitendra Rajput, N. L. Kushwaha","doi":"10.2166/wcc.2024.462","DOIUrl":"https://doi.org/10.2166/wcc.2024.462","url":null,"abstract":"\u0000 Climate change (CC) significantly influences agricultural water productivity, necessitating increased irrigation. Therefore, the present study was undertaken to assess the trend and change-point analyses of weather variables such as temperature (T), rainfall (R), and reference evapotranspiration (ET0) using 31-year long-term data for semi-arid climate. The analysis was carried out employing Mann–Kendall (MK), Modified Mann–Kendall (MMK), Innovative Trend Analysis (ITA), and Innovative Polygon Trend Analysis (IPTA) methods. Homogeneity tests, including Pettitt's test, Standard Normal Homogeneity Test (SNHT) , Buishand range test, and Von Neumann Ratio Test (VNRT), were employed to detect change points (CPs) in the time series data. The results indicated that, for maximum temperature, MK and MMK revealed a positive trend for September and July, respectively, while minimum temperatures indicated increasing trends in August and September. Rainfall exhibited an increasing trend during the Zaid season (April–May). ET0 exhibited a negative trend in January. ITA and IPTA displayed a mixture of positive and negative trends across months and seasons. The change-point analysis revealed that for Tmax, the CP occurred in 1998 for time-series data for the month of April. Likewise, for Tmin, the change points for April and August time series were found in 1997.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140656026","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}
Muhammad Muhitur Rahman, M. I. Chowdhury, Md Iqram Uddin Al Amran, Karim Malik, I. Abubakar, Y. Aina, Md Arif Hasan, M. S. Rahman, Syed Masiur Rahman
Climate change poses a significant threat to the security and sustainability of global food systems, particularly in vulnerable regions such as Bangladesh. This paper comprehensively reviews the impact of climate change on food system security and sustainability in Bangladesh. Specifically, it examines the country's food system, the climatic conditions endangering food security, and the impacts of climate change on food systems and associated vulnerabilities. A systematic review methodology was adopted to select the relevant literature, based on predefined inclusion criteria and research questions. To mitigate selection bias, the research team independently screened and evaluated the articles for inclusion in the review process. Our review reveals increasing trends in temperature fluctuations and irregular rainfall occurrences, posing significant challenges in terms of crop management and planning. The occurrence of floods due to extreme rainfall and sea-level rise exacerbates food insecurity in affected areas. Additionally, moderate to severe droughts have been identified in some regions. The paper also evaluates the effectiveness of current adaptation initiatives and the degree of integration among relevant stakeholders. Through this analysis, the paper emphasizes the importance of local climate change adaptation strategies and stakeholder collaboration in mitigating the adverse impacts of climate change on the food system security.
{"title":"Climate change impacts on the food system security and sustainability in Bangladesh","authors":"Muhammad Muhitur Rahman, M. I. Chowdhury, Md Iqram Uddin Al Amran, Karim Malik, I. Abubakar, Y. Aina, Md Arif Hasan, M. S. Rahman, Syed Masiur Rahman","doi":"10.2166/wcc.2024.631","DOIUrl":"https://doi.org/10.2166/wcc.2024.631","url":null,"abstract":"\u0000 \u0000 Climate change poses a significant threat to the security and sustainability of global food systems, particularly in vulnerable regions such as Bangladesh. This paper comprehensively reviews the impact of climate change on food system security and sustainability in Bangladesh. Specifically, it examines the country's food system, the climatic conditions endangering food security, and the impacts of climate change on food systems and associated vulnerabilities. A systematic review methodology was adopted to select the relevant literature, based on predefined inclusion criteria and research questions. To mitigate selection bias, the research team independently screened and evaluated the articles for inclusion in the review process. Our review reveals increasing trends in temperature fluctuations and irregular rainfall occurrences, posing significant challenges in terms of crop management and planning. The occurrence of floods due to extreme rainfall and sea-level rise exacerbates food insecurity in affected areas. Additionally, moderate to severe droughts have been identified in some regions. The paper also evaluates the effectiveness of current adaptation initiatives and the degree of integration among relevant stakeholders. Through this analysis, the paper emphasizes the importance of local climate change adaptation strategies and stakeholder collaboration in mitigating the adverse impacts of climate change on the food system security.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140668601","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}
In this study, we developed a probabilistic model using the surrogate/model mixed ensemble (SMME) method to project temperature and rainfall in Vietnam under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. The SMME model combines patterns from 31 global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and their weighted model surrogates. Testing for the period of 2006–2018 demonstrated the SMME's ability to encompass observed temperature and rainfall changes. By the end of the 21st century, there is a 5% probability of average temperature increase exceeding 6.29 °C, and a 95% probability of minimum temperature increasing by more than 2.21 °C during 2080–2099 under RCP8.5 compared to 1986–2005. Meanwhile, rainfall is projected to slightly increase, with an average rise of 6.12% at the 5% probability level. The study also quantified the contributions of uncertainty sources – unforced, forced, and scenario-related – to the projection results, revealing that unforced uncertainty dominates the total signal at the beginning of the 21st century and gradually decreases, while forced uncertainty remains relatively moderate but increases gradually over time. As we approach the end of the century, scenario uncertainty dominates, accounting for 75–80% of the total signal.
{"title":"Probabilistic projections of temperature and rainfall for climate risk assessment in Vietnam","authors":"Quan Tran-Anh, T. Ngo‐Duc","doi":"10.2166/wcc.2024.461","DOIUrl":"https://doi.org/10.2166/wcc.2024.461","url":null,"abstract":"\u0000 \u0000 In this study, we developed a probabilistic model using the surrogate/model mixed ensemble (SMME) method to project temperature and rainfall in Vietnam under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. The SMME model combines patterns from 31 global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and their weighted model surrogates. Testing for the period of 2006–2018 demonstrated the SMME's ability to encompass observed temperature and rainfall changes. By the end of the 21st century, there is a 5% probability of average temperature increase exceeding 6.29 °C, and a 95% probability of minimum temperature increasing by more than 2.21 °C during 2080–2099 under RCP8.5 compared to 1986–2005. Meanwhile, rainfall is projected to slightly increase, with an average rise of 6.12% at the 5% probability level. The study also quantified the contributions of uncertainty sources – unforced, forced, and scenario-related – to the projection results, revealing that unforced uncertainty dominates the total signal at the beginning of the 21st century and gradually decreases, while forced uncertainty remains relatively moderate but increases gradually over time. As we approach the end of the century, scenario uncertainty dominates, accounting for 75–80% of the total signal.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140672924","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}
The objective of this study was the critical challenge of accurately predicting water balance components in the Upper Bhima River basin, which is also facing significant challenges due to climate change. A major challenge faced in water balance studies is inadequacy of existing hydrological models to account for the effects of storage structures. The study utilized the variable infiltration capacity–routing application for parallel computation of discharge hydrological model with a newly developed storage structure scheme to simulate water balance components for historical (1999–2010) and future (2019–2040) periods, with future climate forcing from 19 CMIP5 GCMs under RCP4.5 and RCP8.5 scenarios. The performance of the model was evaluated against observed streamflow data and around 30% improvement is noticed for the Nash–Sutcliffe efficiency score. The results signify the adverse impacts of climate change in the region, particularly a significant decrease in monsoon precipitation which may intensify drought scenarios and affect monsoon-driven agriculture. Furthermore, the study emphasizes the high sensitivity of baseflow in the Upper Bhima River to climate alterations, indicating potential threats to biodiversity and river ecosystem health. This research offers indispensable findings crucial for future strategies concerning hydropower, flood management, and water resource management in the region.
{"title":"Investigating the projected changes in water balance components under climate change considering the effect of storage structures","authors":"S. Nandi, Manne Janga Reddy","doi":"10.2166/wcc.2024.371","DOIUrl":"https://doi.org/10.2166/wcc.2024.371","url":null,"abstract":"\u0000 \u0000 The objective of this study was the critical challenge of accurately predicting water balance components in the Upper Bhima River basin, which is also facing significant challenges due to climate change. A major challenge faced in water balance studies is inadequacy of existing hydrological models to account for the effects of storage structures. The study utilized the variable infiltration capacity–routing application for parallel computation of discharge hydrological model with a newly developed storage structure scheme to simulate water balance components for historical (1999–2010) and future (2019–2040) periods, with future climate forcing from 19 CMIP5 GCMs under RCP4.5 and RCP8.5 scenarios. The performance of the model was evaluated against observed streamflow data and around 30% improvement is noticed for the Nash–Sutcliffe efficiency score. The results signify the adverse impacts of climate change in the region, particularly a significant decrease in monsoon precipitation which may intensify drought scenarios and affect monsoon-driven agriculture. Furthermore, the study emphasizes the high sensitivity of baseflow in the Upper Bhima River to climate alterations, indicating potential threats to biodiversity and river ecosystem health. This research offers indispensable findings crucial for future strategies concerning hydropower, flood management, and water resource management in the region.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140676365","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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