Abstract Water supply infrastructures are essential to ensure the well-being of communities and to support social and economic growth and must be protected from damage in the context of future threats related to the environmental consequences of climate change. Those consequences include natural disasters, i.e., landslides, which can cause destruction of water infrastructure, causing distress for water users, cascading effects to other critical infrastructures and environmental impacts. Vulnerability analyses represent a key point in international risk management programs for protecting critical infrastructure, especially in the context of climate change. In this paper, a methodology is proposed to evaluate crucial water supply infrastructure vulnerabilities based on multiple indicators. A learning-from-experience approach is applied to establish specific indicators for vulnerability assessment. Eight different indicators are identified, divided into four categories, regarding land characteristics, service inefficiencies for users due to infrastructure failure, pipeline route characteristics, and physical characteristics of the aqueduct pipe. Along with the indicators, a graphical representation is proposed using the Kiviat chart, producing a vulnerability chart that represents a useful tool to identify the main vulnerability factors in existing water supply infrastructure, in the management of interventions, in the planning and design processes of new infrastructure, and for comparing different design solutions.
{"title":"Vulnerability assessment of water supply infrastructures through multiple indicator methodology","authors":"Iolanda Borzì","doi":"10.2166/wcc.2023.148","DOIUrl":"https://doi.org/10.2166/wcc.2023.148","url":null,"abstract":"Abstract Water supply infrastructures are essential to ensure the well-being of communities and to support social and economic growth and must be protected from damage in the context of future threats related to the environmental consequences of climate change. Those consequences include natural disasters, i.e., landslides, which can cause destruction of water infrastructure, causing distress for water users, cascading effects to other critical infrastructures and environmental impacts. Vulnerability analyses represent a key point in international risk management programs for protecting critical infrastructure, especially in the context of climate change. In this paper, a methodology is proposed to evaluate crucial water supply infrastructure vulnerabilities based on multiple indicators. A learning-from-experience approach is applied to establish specific indicators for vulnerability assessment. Eight different indicators are identified, divided into four categories, regarding land characteristics, service inefficiencies for users due to infrastructure failure, pipeline route characteristics, and physical characteristics of the aqueduct pipe. Along with the indicators, a graphical representation is proposed using the Kiviat chart, producing a vulnerability chart that represents a useful tool to identify the main vulnerability factors in existing water supply infrastructure, in the management of interventions, in the planning and design processes of new infrastructure, and for comparing different design solutions.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136210527","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 research output established that a significant proportion of the global population lives in low-income communities mostly in the Global South. These communities face severe water scarcity and persistent sanitation challenges. It emerged that greywater reuse has the potential to improve the access to sufficient clean water in low-income communities. The study sought to ascertain user perceptions and acceptance of treated greywater reuse in low-income communities. To anchor this research, a comprehensive consultation of literature was done, and key sources of data were drawn from various secondary sources of data such as bibliographic databases. This was followed by the snowballing of obtained papers. The research employed a narrative review approach in methodology. The findings of this study indicate that people living in low-income communities have a positive perception regarding reusing treated greywater. Furthermore, it was established that the majority of persons living in low-income communities accept reuse for non-potable purposes including vegetable irrigation, laundry, toilet flushing, and car washing.
{"title":"User perceptions and acceptance of treated greywater reuse in low-income communities: a narrative review","authors":"Tendai Hardwork Madzaramba, Pesanai Zanamwe","doi":"10.2166/wcc.2023.414","DOIUrl":"https://doi.org/10.2166/wcc.2023.414","url":null,"abstract":"Abstract This research output established that a significant proportion of the global population lives in low-income communities mostly in the Global South. These communities face severe water scarcity and persistent sanitation challenges. It emerged that greywater reuse has the potential to improve the access to sufficient clean water in low-income communities. The study sought to ascertain user perceptions and acceptance of treated greywater reuse in low-income communities. To anchor this research, a comprehensive consultation of literature was done, and key sources of data were drawn from various secondary sources of data such as bibliographic databases. This was followed by the snowballing of obtained papers. The research employed a narrative review approach in methodology. The findings of this study indicate that people living in low-income communities have a positive perception regarding reusing treated greywater. Furthermore, it was established that the majority of persons living in low-income communities accept reuse for non-potable purposes including vegetable irrigation, laundry, toilet flushing, and car washing.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135093911","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 Hydropower is one of the best renewable energy sources to meet India's rapidly growing energy demand. The Remote Sensing and GIS tools provide reliable information for assessing the available water of the Himalayan rivers. In this study, the basin is divided into 12 elevation zones, and temperature and precipitation were extrapolated within these zones. The MODIS (Terra&Aqua) cloud-free images have been used for mapping the Snow Cover Area and it was found that the SCA will vary from 18–72 % during the simulation period. The model simulation period is divided into calibration (2003–2015) and validation (2016–2019). During the study, it was observed that the model efficiency parameters significantly exceeded the acceptable range. In this study, the snowmelt's contribution increases until zone 8; after this, the snowmelt contribution decreases, and the snow accumulation increases. Also, the Hydro-Electric Power (HEP) generation of the basin is modeled with the help of a power equation for a turbine efficiency of 0.8. The simulation of daily streamflow and generated HEP are compared with the measured values, and both tracked the observed pattern very precisely. The findings of the present study will be implemented on the other ungauged basins and could help us to identify the potential sites for HEP with the help of RS and GIS tools.
{"title":"Evaluating hydroelectric potential in Alaknanda basin, Uttarakhand using the snowmelt runoff model (SRM)","authors":"Kuldeep Singh Rautela, Dilip Kumar, Bandaru Goutham Rajeev Gandhi, Ajay Kumar, Amit Kumar Dubey, Bhishm Singh Khati","doi":"10.2166/wcc.2023.341","DOIUrl":"https://doi.org/10.2166/wcc.2023.341","url":null,"abstract":"Abstract Hydropower is one of the best renewable energy sources to meet India's rapidly growing energy demand. The Remote Sensing and GIS tools provide reliable information for assessing the available water of the Himalayan rivers. In this study, the basin is divided into 12 elevation zones, and temperature and precipitation were extrapolated within these zones. The MODIS (Terra&Aqua) cloud-free images have been used for mapping the Snow Cover Area and it was found that the SCA will vary from 18–72 % during the simulation period. The model simulation period is divided into calibration (2003–2015) and validation (2016–2019). During the study, it was observed that the model efficiency parameters significantly exceeded the acceptable range. In this study, the snowmelt's contribution increases until zone 8; after this, the snowmelt contribution decreases, and the snow accumulation increases. Also, the Hydro-Electric Power (HEP) generation of the basin is modeled with the help of a power equation for a turbine efficiency of 0.8. The simulation of daily streamflow and generated HEP are compared with the measured values, and both tracked the observed pattern very precisely. The findings of the present study will be implemented on the other ungauged basins and could help us to identify the potential sites for HEP with the help of RS and GIS tools.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"299 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135352461","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 Understanding climate variability and trends is crucial for managing a host of sectors. Everything from water availability to agricultural productivity is affected by variability and trends in temperature, rainfall, evapotranspiration, and solar radiation. Nevertheless, their dynamics have seldom been explored together, especially in India. To address this gap, the present study investigates the variability, trend, and magnitude of those parameters individually and concurrently using fractal dimension and non-parametric statistics over the Indian state of West Bengal from 1951 to 2020. The results show a south–north gradient in overall climate variability. The Gangetic West Bengal (GWB) is experiencing higher variability, along with a rising minimum temperature (≥0.008 °C year−1) and declining rainfall (≥− 1 mm year−1). Though the Sub-Himalayan West Bengal as a whole shows less variability, its foothills reveal modest variation coupled with increasing maximum temperature (≥0.005 °C year−1), reference evapotranspiration (≥0.4 mm year−1), and decreasing rainfall in the post-monsoon and winter seasons. Based on the results, we identified the western GWB, the Sundarbans, and the sub-Himalayan foothills as the most vulnerable areas and recommended proactive crop and water management strategies. Finally, we underline the need to analyze climate dynamics holistically to manage climate-sensitive sectors efficiently and sustainably.
了解气候变率和趋势对于管理许多部门至关重要。从水资源供应到农业生产力，一切都受到温度、降雨、蒸发蒸腾和太阳辐射的变化和趋势的影响。然而，它们的动态很少被一起探讨，尤其是在印度。为了解决这一差距，本研究利用1951年至2020年印度西孟加拉邦的分形维数和非参数统计数据，分别和同时调查了这些参数的变异性、趋势和幅度。结果表明，总体气候变率呈南北梯度。恒河西孟加拉邦(GWB)正在经历更高的变异性，同时最低温度上升(≥0.008°C，年- 1)和降雨量下降(≥- 1毫米，年- 1)。尽管亚喜马拉雅西孟加拉邦整体表现出较小的变异性，但其山麓表现出适度的变化，伴随着最高温度(≥0.005°C - 1年)、参考蒸散量(≥0.4 mm - 1年)的增加，以及季风后和冬季降雨量的减少。根据研究结果，我们确定了西部GWB、孙德尔本斯和喜马拉雅山麓是最脆弱的地区，并建议了积极的作物和水资源管理策略。最后，我们强调需要全面分析气候动态，以有效和可持续地管理气候敏感部门。
{"title":"Unraveling the dynamics of climate: empirical evidence from the Indian state of West Bengal","authors":"Soumik Das, Kishor Goswami","doi":"10.2166/wcc.2023.260","DOIUrl":"https://doi.org/10.2166/wcc.2023.260","url":null,"abstract":"Abstract Understanding climate variability and trends is crucial for managing a host of sectors. Everything from water availability to agricultural productivity is affected by variability and trends in temperature, rainfall, evapotranspiration, and solar radiation. Nevertheless, their dynamics have seldom been explored together, especially in India. To address this gap, the present study investigates the variability, trend, and magnitude of those parameters individually and concurrently using fractal dimension and non-parametric statistics over the Indian state of West Bengal from 1951 to 2020. The results show a south–north gradient in overall climate variability. The Gangetic West Bengal (GWB) is experiencing higher variability, along with a rising minimum temperature (≥0.008 °C year−1) and declining rainfall (≥− 1 mm year−1). Though the Sub-Himalayan West Bengal as a whole shows less variability, its foothills reveal modest variation coupled with increasing maximum temperature (≥0.005 °C year−1), reference evapotranspiration (≥0.4 mm year−1), and decreasing rainfall in the post-monsoon and winter seasons. Based on the results, we identified the western GWB, the Sundarbans, and the sub-Himalayan foothills as the most vulnerable areas and recommended proactive crop and water management strategies. Finally, we underline the need to analyze climate dynamics holistically to manage climate-sensitive sectors efficiently and sustainably.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135592447","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 Runoff has been greatly affected by climate change and human activities. Studying nonlinear controls on runoff response is of great significance for water resource management decision-making and ecological protection. However, there is limited understanding of what physical mechanisms dominate the runoff response and of their predictability over space. This study analyzed the spatial patterns of runoff response including runoff changes and its sensitivity to climate–landscape variations in 1,003 catchments of the contiguous United States (CONUS). Then, an interpretable machine learning method was used to investigate the nonlinear relationship between watershed attributes and runoff response, which enables the importance of influencing factors. Finally, the random forest model was employed to predict runoff response according to the predictors of catchment attributes. The results show that alteration of runoff is up to 56%/10 years due to climate change and human activities. Catchment attributes substantially altered runoff over CONUS (−60% to 56%/10 years). Climate, topography, and hydrology are the top three key factors which nonlinearly control runoff response patterns which cannot be captured by the linear correlation method. The random forest can predict runoff response well with the highest R2 of 0.96 over CONUS.
{"title":"Nonlinear control of climate, hydrology, and topography on streamflow response through the use of interpretable machine learning across the contiguous United States","authors":"Yu Wu, Na Li","doi":"10.2166/wcc.2023.279","DOIUrl":"https://doi.org/10.2166/wcc.2023.279","url":null,"abstract":"Abstract Runoff has been greatly affected by climate change and human activities. Studying nonlinear controls on runoff response is of great significance for water resource management decision-making and ecological protection. However, there is limited understanding of what physical mechanisms dominate the runoff response and of their predictability over space. This study analyzed the spatial patterns of runoff response including runoff changes and its sensitivity to climate–landscape variations in 1,003 catchments of the contiguous United States (CONUS). Then, an interpretable machine learning method was used to investigate the nonlinear relationship between watershed attributes and runoff response, which enables the importance of influencing factors. Finally, the random forest model was employed to predict runoff response according to the predictors of catchment attributes. The results show that alteration of runoff is up to 56%/10 years due to climate change and human activities. Catchment attributes substantially altered runoff over CONUS (−60% to 56%/10 years). Climate, topography, and hydrology are the top three key factors which nonlinearly control runoff response patterns which cannot be captured by the linear correlation method. The random forest can predict runoff response well with the highest R2 of 0.96 over CONUS.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135695978","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 disasters occur frequently in semi-arid and sub-humid mountain watersheds, and their formation mechanism is affected by many factors, resulting in low simulation accuracy. The main purpose of this study is to evaluate the impact of adding actual river channel data on the accuracy of flood simulation. In order to obtain higher-resolution terrain data, an unmanned aerial vehicle (UAV) was used to survey the study area. Taking the Liulin Watershed in Xingtai City, Hebei Province as the research area, the HEC-HMS hydrological model and the HEC-HMS and HEC-RAS coupling model were constructed, respectively, to simulate 26 flood events during the period from 1982 to 2016. The results indicate that the coupled model can reflect the evolution process of river floods. When simulating certain major flood events, the percentage of flood peak error and Nash–Sutcliffe efficiency coefficient (NSE) have improved, such as the NSE of No. 160812 floods increasing from 0.9 to 0.95. However, the simulation accuracy of these two models for small floods in the watershed is relatively low. Future research should focus on how to accurately evaluate the parameter curve number (CN) of the watershed before rainfall and obtain more accurate runoff yield.
{"title":"Flood simulation using the hydrological model and the hydrological–hydrodynamic coupling model in a small watershed in semi-arid and sub-humid region, North China","authors":"Jianzhu Li, Ziqi Wang, Ting Zhang","doi":"10.2166/wcc.2023.161","DOIUrl":"https://doi.org/10.2166/wcc.2023.161","url":null,"abstract":"Flood disasters occur frequently in semi-arid and sub-humid mountain watersheds, and their formation mechanism is affected by many factors, resulting in low simulation accuracy. The main purpose of this study is to evaluate the impact of adding actual river channel data on the accuracy of flood simulation. In order to obtain higher-resolution terrain data, an unmanned aerial vehicle (UAV) was used to survey the study area. Taking the Liulin Watershed in Xingtai City, Hebei Province as the research area, the HEC-HMS hydrological model and the HEC-HMS and HEC-RAS coupling model were constructed, respectively, to simulate 26 flood events during the period from 1982 to 2016. The results indicate that the coupled model can reflect the evolution process of river floods. When simulating certain major flood events, the percentage of flood peak error and Nash–Sutcliffe efficiency coefficient (NSE) have improved, such as the NSE of No. 160812 floods increasing from 0.9 to 0.95. However, the simulation accuracy of these two models for small floods in the watershed is relatively low. Future research should focus on how to accurately evaluate the parameter curve number (CN) of the watershed before rainfall and obtain more accurate runoff yield.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135246868","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}
Zhenjie Qiu, Rihui Luo, Mengying Sun, Wei Liao, Yunyi Liu
Abstract In the soil column experiments, the irrigation amount varied from 4.8 to 12 L, and the nitrogen application rate was from 80 to 360 kg ha−1. Three fertigation strategies were tested. The results indicated that an increase in water input led to an increase in the area of pH decrease in the soil at 10 days after the irrigation ended for a given lateral depth of 10 cm. The measurement of nitrogen distribution showed that the nitrogen content in the soil was significantly increased with the nitrogen application rate. Fertigation strategies substantially affect the pH and nitrogen distributions in soil. The strategy of applying water at first for one-fourth of the total irrigation time (1/4W), then applying fertilizer solution for one-half of the total irrigation time (1/2N), followed by applying water for the remaining one-fourth of the total irrigation time (1/4W) made a minimal soil pH decreasing area and a homogeneous nitrate distribution at 0–20 cm depth. Therefore, to reduce NO3-N leaching and avoid deep soil acidification, a dripline depth of 10 cm with an irrigation amount of 4.8 L and a nitrogen application rate of 80 kg ha−1 through the 1/4W–1/2N–1/4W fertigation may be suggested.
在土柱试验中，灌水量为4.8 ~ 12 L，施氮量为80 ~ 360 kg ha−1。试验了三种施肥策略。结果表明，在灌水结束后10 d内，灌水量的增加导致土壤pH值下降面积的增加。氮素分布测定表明，随施氮量的增加，土壤中氮素含量显著增加。施肥策略对土壤pH和氮的分布有重要影响。先灌溉总灌溉时间的1/4 (1/4W)，再灌溉总灌溉时间的1/2 (1/2N)，再灌溉总灌溉时间的1/4 (1/4W)，使土壤pH下降面积最小，0 ~ 20 cm深度硝态氮分布均匀。因此，为减少硝态氮淋失，避免土壤深层酸化，建议采用1/ 4w - 1/ 2n - 1/ 4w施肥方式，滴深为10 cm，灌水量为4.8 L，施氮量为80 kg ha - 1。
{"title":"Effects of nitrogen fertilizer and water management practices on pH and nitrogen distributions in the wetted-soil volume using drip irrigation","authors":"Zhenjie Qiu, Rihui Luo, Mengying Sun, Wei Liao, Yunyi Liu","doi":"10.2166/wcc.2023.111","DOIUrl":"https://doi.org/10.2166/wcc.2023.111","url":null,"abstract":"Abstract In the soil column experiments, the irrigation amount varied from 4.8 to 12 L, and the nitrogen application rate was from 80 to 360 kg ha−1. Three fertigation strategies were tested. The results indicated that an increase in water input led to an increase in the area of pH decrease in the soil at 10 days after the irrigation ended for a given lateral depth of 10 cm. The measurement of nitrogen distribution showed that the nitrogen content in the soil was significantly increased with the nitrogen application rate. Fertigation strategies substantially affect the pH and nitrogen distributions in soil. The strategy of applying water at first for one-fourth of the total irrigation time (1/4W), then applying fertilizer solution for one-half of the total irrigation time (1/2N), followed by applying water for the remaining one-fourth of the total irrigation time (1/4W) made a minimal soil pH decreasing area and a homogeneous nitrate distribution at 0–20 cm depth. Therefore, to reduce NO3-N leaching and avoid deep soil acidification, a dripline depth of 10 cm with an irrigation amount of 4.8 L and a nitrogen application rate of 80 kg ha−1 through the 1/4W–1/2N–1/4W fertigation may be suggested.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135385606","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 aims to evaluate the suitability of the Tweedie generalised linear model for characterising monthly rainfall patterns across 18 meteorological stations in Peninsular Malaysia. It incorporates harmonic functions consisting of sine and cosine functions as seasonal predictors and El Niño Southern Oscillation (ENSO) indices as climatic predictors. Results indicate that three harmonic functions are essential to accurately portray rainfall dynamics in the southwestern and northwestern regions, while two suffice for the inland and western regions. However, incorporating four harmonic functions is the most optimal representation of the eastern region. An additional 1-month lag in ENSO indices is introduced to the optimal seasonal predictor model. Based on the findings, the southern oscillation index notably impacts monthly rainfall significantly in eastern and inland areas, while meteorological stations in the western and northwestern areas fit better with the multivariate ENSO index. Strikingly, no substantial impact of climate predictors is observed on the monthly rainfall within the southwestern region. Thus, the influence of climate indices is very much influenced by the geographical locations of the regions. Importantly, generating simulated data through the Tweedie model contributes to a more accurate representation of the statistical properties inherent in rainfall analysis.
{"title":"Tweedie models for Malaysia rainfall simulations with seasonal variabilities","authors":"Jamaludin Suhaila","doi":"10.2166/wcc.2023.275","DOIUrl":"https://doi.org/10.2166/wcc.2023.275","url":null,"abstract":"Abstract This study aims to evaluate the suitability of the Tweedie generalised linear model for characterising monthly rainfall patterns across 18 meteorological stations in Peninsular Malaysia. It incorporates harmonic functions consisting of sine and cosine functions as seasonal predictors and El Niño Southern Oscillation (ENSO) indices as climatic predictors. Results indicate that three harmonic functions are essential to accurately portray rainfall dynamics in the southwestern and northwestern regions, while two suffice for the inland and western regions. However, incorporating four harmonic functions is the most optimal representation of the eastern region. An additional 1-month lag in ENSO indices is introduced to the optimal seasonal predictor model. Based on the findings, the southern oscillation index notably impacts monthly rainfall significantly in eastern and inland areas, while meteorological stations in the western and northwestern areas fit better with the multivariate ENSO index. Strikingly, no substantial impact of climate predictors is observed on the monthly rainfall within the southwestern region. Thus, the influence of climate indices is very much influenced by the geographical locations of the regions. Importantly, generating simulated data through the Tweedie model contributes to a more accurate representation of the statistical properties inherent in rainfall analysis.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135420454","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}
Jing Lin Ng, Yuk Feng Huang, Aik Hang Chong, Jin Chai Lee, Muyideen Abdulkareem, Nur Ilya Farhana Md Noh, Majid Mirzaei, Ali Najah Ahmed
Abstract Drought has been the main environmental issue in Peninsular Malaysia. Hence, this study undertook a thorough evaluation of drought assessment methodologies and focused on the temporal analysis of multiple drought indices namely, the standardised precipitation index (SPI), deciles index (DI), percent of normal precipitation (PNPI), rainfall anomaly index (RAI) and Z-score index (ZSI) – across timescales of 1-, 6- and 12-month durations. This assessment incorporates the average moving range (AMR), Mann–Kendall (MK) test and Sen's slope estimator in temporal analysis and the results showed that shorter timescales lead to higher fluctuation in AMR values, indicating short-term droughts are best assessed using drought indices of shorter timescale. It was found that most drought indices exhibited a similar trend and trend magnitude in all timescales. SPI is utilised as the standard model for the accuracy evaluation of drought indices using root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The results showed that ZSI has the highest accuracy of all indices. The novelty of this study lies in evaluating the accuracy and temporal characteristics of precipitation-based drought indices in tropical areas, particularly in Peninsular Malaysia.
{"title":"Comparative assessment of drought indices for evaluating drought patterns in Peninsular Malaysia","authors":"Jing Lin Ng, Yuk Feng Huang, Aik Hang Chong, Jin Chai Lee, Muyideen Abdulkareem, Nur Ilya Farhana Md Noh, Majid Mirzaei, Ali Najah Ahmed","doi":"10.2166/wcc.2023.546","DOIUrl":"https://doi.org/10.2166/wcc.2023.546","url":null,"abstract":"Abstract Drought has been the main environmental issue in Peninsular Malaysia. Hence, this study undertook a thorough evaluation of drought assessment methodologies and focused on the temporal analysis of multiple drought indices namely, the standardised precipitation index (SPI), deciles index (DI), percent of normal precipitation (PNPI), rainfall anomaly index (RAI) and Z-score index (ZSI) – across timescales of 1-, 6- and 12-month durations. This assessment incorporates the average moving range (AMR), Mann–Kendall (MK) test and Sen's slope estimator in temporal analysis and the results showed that shorter timescales lead to higher fluctuation in AMR values, indicating short-term droughts are best assessed using drought indices of shorter timescale. It was found that most drought indices exhibited a similar trend and trend magnitude in all timescales. SPI is utilised as the standard model for the accuracy evaluation of drought indices using root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The results showed that ZSI has the highest accuracy of all indices. The novelty of this study lies in evaluating the accuracy and temporal characteristics of precipitation-based drought indices in tropical areas, particularly in Peninsular Malaysia.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135814457","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}
Abdol Rassoul Zarei, Mohammad Reza Mahmoudi, Yaser Ghasemi Aryan
Abstract In this study, the power of 12 of the most widely used meteorological drought indices was compared. For this purpose, the datasets of 12 stations (from 1967 to 2021) with different climatic conditions in Iran were used. For statistical analysis, multiple linear regression based on the relative importance metric introduced by the Lindeman, Merenda, Gold (MLR-LMG) and data visualization (DV) models were used. In the temporal assessment, the relative importance metrics (RIM) between the drought severity based on the different drought indices and the annual yield of rain-fed winter wheat (AYW) based on the fitted MLR-LMG model was investigated at the annual timescale in the chosen stations. In the spatial evaluation, the RIM between the drought severity based on the different drought indices and the AYW were investigated each year (1967, … , 2021). The results showed that in temporal assessment, the modified standardized precipitation evapotranspiration index (MSPEI) was the most suitable (58.33% of selected stations). Also, in spatial evaluation, the MSPEI and Z-score were the most efficient drought indices (65.45% and 27.27% of the years, respectively). The validation results of the fitted MLR-LMG models showed that the models were trustworthy in all stations and all years.
{"title":"Using the multiple linear regression based on the relative importance metric and data visualization models for assessing the ability of drought indices","authors":"Abdol Rassoul Zarei, Mohammad Reza Mahmoudi, Yaser Ghasemi Aryan","doi":"10.2166/wcc.2023.184","DOIUrl":"https://doi.org/10.2166/wcc.2023.184","url":null,"abstract":"Abstract In this study, the power of 12 of the most widely used meteorological drought indices was compared. For this purpose, the datasets of 12 stations (from 1967 to 2021) with different climatic conditions in Iran were used. For statistical analysis, multiple linear regression based on the relative importance metric introduced by the Lindeman, Merenda, Gold (MLR-LMG) and data visualization (DV) models were used. In the temporal assessment, the relative importance metrics (RIM) between the drought severity based on the different drought indices and the annual yield of rain-fed winter wheat (AYW) based on the fitted MLR-LMG model was investigated at the annual timescale in the chosen stations. In the spatial evaluation, the RIM between the drought severity based on the different drought indices and the AYW were investigated each year (1967, … , 2021). The results showed that in temporal assessment, the modified standardized precipitation evapotranspiration index (MSPEI) was the most suitable (58.33% of selected stations). Also, in spatial evaluation, the MSPEI and Z-score were the most efficient drought indices (65.45% and 27.27% of the years, respectively). The validation results of the fitted MLR-LMG models showed that the models were trustworthy in all stations and all years.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135814612","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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