This study first defined the concept of the water–energy–food nexus system risk (WEF-R). Then, the WEF-R evaluation index system was established from three aspects: stability, coordination, and sustainability subsystems. Finally, the set pair analysis-variable fuzzy set model was used to evaluate the risk levels of subsystems, and the risk matrix was applied to assess provincial WEF-R levels in China from 2009 to 2018. The results showed that the stability subsystem had the greatest influence on provincial WEF-R, followed by the sustainability subsystem. The provinces with a higher risk of the stability subsystem and lower risk of the sustainability subsystem were mainly centralized in southeast coastal and central regions, which were consistent with the provinces with better socio-economic development. The provinces with lower risk of the stability subsystem and higher risk of the sustainability subsystem were mainly concentrated in northwest regions, which correspond with the provinces with better natural resources endowment but lower socio-economic development. As for the temporal evolution of risk levels, the risk levels of the coordination and sustainability subsystems showed downward trends during the study period, while the risk level of the stability subsystem displayed a small fluctuation, and the provincial WEF-R level in China presented a decreasing trend.
{"title":"Spatio-temporal evaluation of water-energy-food nexus system risk from the provincial perspective: A case study of China","authors":"Tonghui Ding, Junfei Chen","doi":"10.2166/ws.2023.142","DOIUrl":"https://doi.org/10.2166/ws.2023.142","url":null,"abstract":"\u0000 \u0000 This study first defined the concept of the water–energy–food nexus system risk (WEF-R). Then, the WEF-R evaluation index system was established from three aspects: stability, coordination, and sustainability subsystems. Finally, the set pair analysis-variable fuzzy set model was used to evaluate the risk levels of subsystems, and the risk matrix was applied to assess provincial WEF-R levels in China from 2009 to 2018. The results showed that the stability subsystem had the greatest influence on provincial WEF-R, followed by the sustainability subsystem. The provinces with a higher risk of the stability subsystem and lower risk of the sustainability subsystem were mainly centralized in southeast coastal and central regions, which were consistent with the provinces with better socio-economic development. The provinces with lower risk of the stability subsystem and higher risk of the sustainability subsystem were mainly concentrated in northwest regions, which correspond with the provinces with better natural resources endowment but lower socio-economic development. As for the temporal evolution of risk levels, the risk levels of the coordination and sustainability subsystems showed downward trends during the study period, while the risk level of the stability subsystem displayed a small fluctuation, and the provincial WEF-R level in China presented a decreasing trend.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90512126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Khatib, Mohamad Daoud, W. Arairo, Marianne Saba, Hussein Mortada
Lebanon's natural water resources are facing serious problems related to quality and quantity. Unregulated resource planning and rising demand are the main factors. Water resources are used in several ways. However, due to the over-exploitation, and random use of surface water resources, Lebanon is facing severe problems related to water need and accessibility. This study focused on the Ras El-Ain area located in the South of Lebanon that dedicated, along with other reservoirs, to supply potable water for Tyr and the surrounding villages. Nowadays, the water of these natural ponds has been polluted significantly due to unrestricted liquid and solid waste disposal. Physicochemical and microbiological water characteristics, following the LIBNOR guidelines, of four selected samples from each natural pond were tested. In addition, another sample was taken from a water reservoir that collects water from these natural ponds. The obtained results were used to evaluate the extent of pollution in these natural ponds using PhreeQC software. The novelty of this study stems from the fact that it is the first to shed light on the degree of pollution level in the Ras El-Ain ponds, Lebanon (an unstudied area).
{"title":"Water quality parameters assessment of Ras El-Ain Natural Ponds, Tyr, Lebanon","authors":"M. Khatib, Mohamad Daoud, W. Arairo, Marianne Saba, Hussein Mortada","doi":"10.2166/ws.2023.140","DOIUrl":"https://doi.org/10.2166/ws.2023.140","url":null,"abstract":"\u0000 \u0000 Lebanon's natural water resources are facing serious problems related to quality and quantity. Unregulated resource planning and rising demand are the main factors. Water resources are used in several ways. However, due to the over-exploitation, and random use of surface water resources, Lebanon is facing severe problems related to water need and accessibility. This study focused on the Ras El-Ain area located in the South of Lebanon that dedicated, along with other reservoirs, to supply potable water for Tyr and the surrounding villages. Nowadays, the water of these natural ponds has been polluted significantly due to unrestricted liquid and solid waste disposal. Physicochemical and microbiological water characteristics, following the LIBNOR guidelines, of four selected samples from each natural pond were tested. In addition, another sample was taken from a water reservoir that collects water from these natural ponds. The obtained results were used to evaluate the extent of pollution in these natural ponds using PhreeQC software. The novelty of this study stems from the fact that it is the first to shed light on the degree of pollution level in the Ras El-Ain ponds, Lebanon (an unstudied area).","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75060277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kerala's Idukki district, which is situated on the Western Ghats of India, is susceptible to flooding and landslides. As a result of the 2018 Kerala floods, this disaster-prone region experienced drought conditions. In order to lessen the effects of future disasters, it is also necessary to identify and evaluate the district's groundwater potential (GWP). This work used three machine-learning (ML) algorithms – Random Forest (RF), Adaptive Boosting (AdaBoost), and Gradient Boosting (GB) – to model and produce GWP zonation maps for the Idukki district. Fourteen conditioning factors include elevation, slope, curvature, Topographic Roughness Index, lineament density, soil, geology, geomorphology, Topographic Wetness Index, Sediment Transport Index, drainage density, rainfall, land-use/land-cover (LULC), and Normalised Difference Vegetation Index that were adopted as input parameters in the modelling. All showed prominence when they were examined for feature importance using the recursive feature elimination (RFE) method. The RF model outperformed the other two ML models in terms of fit, with an area under curve (AUC) value of 0.92, while the GB and AdaBoost models displayed less fit, with AUC values of 0.90 and 0.88, respectively. GWP maps produced by each model were reclassified into five zones – very high to very low – it was discovered that the zones were evenly spread throughout the Idukki region.
{"title":"Identification of groundwater potential zones of Idukki district using remote sensing and GIS-based machine-learning approach","authors":"Zohaib Khan, Bharat Jhamnani","doi":"10.2166/ws.2023.134","DOIUrl":"https://doi.org/10.2166/ws.2023.134","url":null,"abstract":"\u0000 \u0000 Kerala's Idukki district, which is situated on the Western Ghats of India, is susceptible to flooding and landslides. As a result of the 2018 Kerala floods, this disaster-prone region experienced drought conditions. In order to lessen the effects of future disasters, it is also necessary to identify and evaluate the district's groundwater potential (GWP). This work used three machine-learning (ML) algorithms – Random Forest (RF), Adaptive Boosting (AdaBoost), and Gradient Boosting (GB) – to model and produce GWP zonation maps for the Idukki district. Fourteen conditioning factors include elevation, slope, curvature, Topographic Roughness Index, lineament density, soil, geology, geomorphology, Topographic Wetness Index, Sediment Transport Index, drainage density, rainfall, land-use/land-cover (LULC), and Normalised Difference Vegetation Index that were adopted as input parameters in the modelling. All showed prominence when they were examined for feature importance using the recursive feature elimination (RFE) method. The RF model outperformed the other two ML models in terms of fit, with an area under curve (AUC) value of 0.92, while the GB and AdaBoost models displayed less fit, with AUC values of 0.90 and 0.88, respectively. GWP maps produced by each model were reclassified into five zones – very high to very low – it was discovered that the zones were evenly spread throughout the Idukki region.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89727723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper further modifies soil conservation service curve number (SCS-CN) based on the concept of adjusting the rainfall in accordance with rain duration and considering the initial abstraction (Ia) as a fraction of rainfall for runoff estimation. The former yields Model M3 and its explicit form with constant parameter λ = 0.2 is designated as Model M4. Model M5 couples both the concepts and thus all these models are the advanced versions. The applicability of all the five models is tested using a large number of rainfall-runoff events (25,502) derived from 53 U.S. Department of Agriculture-Agricultural Research Service watersheds. Models M3–M5 performed better than Models M1 and M2. Model performance is evaluated by employing six statistical measures, namely, root mean square error, mean absolute error, normalized root mean square error, Nash–Sutcliffe coefficient (%), percent Bias, RSR, n(t), and several grading criteria. Results show Model M5 to have performed the best of all in both calibration and validation largely due to its incorporating the impact of rain duration and allowing Ia to vary with rainfall, which is close to reality and not accounted for in any other models considered in this study.
{"title":"SCS-CN methodology further modified","authors":"S. Verma, R. K. Verma","doi":"10.2166/ws.2023.129","DOIUrl":"https://doi.org/10.2166/ws.2023.129","url":null,"abstract":"\u0000 \u0000 This paper further modifies soil conservation service curve number (SCS-CN) based on the concept of adjusting the rainfall in accordance with rain duration and considering the initial abstraction (Ia) as a fraction of rainfall for runoff estimation. The former yields Model M3 and its explicit form with constant parameter λ = 0.2 is designated as Model M4. Model M5 couples both the concepts and thus all these models are the advanced versions. The applicability of all the five models is tested using a large number of rainfall-runoff events (25,502) derived from 53 U.S. Department of Agriculture-Agricultural Research Service watersheds. Models M3–M5 performed better than Models M1 and M2. Model performance is evaluated by employing six statistical measures, namely, root mean square error, mean absolute error, normalized root mean square error, Nash–Sutcliffe coefficient (%), percent Bias, RSR, n(t), and several grading criteria. Results show Model M5 to have performed the best of all in both calibration and validation largely due to its incorporating the impact of rain duration and allowing Ia to vary with rainfall, which is close to reality and not accounted for in any other models considered in this study.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90373460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In arid and semi-arid regions, managing agricultural water for irrigation is essential to cope with water scarcity and maximize crop yields. In this study, an experiment was conducted on a potato crop in the Manouba region (lower valley of Medjerda, Tunisia). The experimental protocol consisted of four water treatments utilizing water-saving irrigation techniques: FI (Full Irrigation 100%): irrigation with 100% of crop water requirements. DI (Irrigation 75%): deficit irrigation with the application of 75% of crop water requirements. PRDRight (Irrigation 50% on the right side): Irrigation by partial root drying. PRDLeft (Irrigation 50% on the left side): Irrigation by partial root drying. Simulation of soil water profiles was carried out by the Hydrus-1D model. The soil hydraulic properties were calibrated according to the experimental conditions using an inverse modeling technique. According to the obtained results, simulated soil water profiles were close to those measured. Indeed, the calculated NRMSE values are low, indicating the reliability of Hydrus-1D as a decision support tool to optimize water irrigation management. These results were then used to investigate the effects of a 2 °C temperature increase on soil water loss, and it was determined that the impact was insignificant.
{"title":"Evaluation of soil water losses under irrigation saving techniques in a semi-arid region in Tunisia","authors":"H. Ammar, Rebh Fridhi, S. Kanzari, B. B. Nouna","doi":"10.2166/ws.2023.128","DOIUrl":"https://doi.org/10.2166/ws.2023.128","url":null,"abstract":"\u0000 In arid and semi-arid regions, managing agricultural water for irrigation is essential to cope with water scarcity and maximize crop yields. In this study, an experiment was conducted on a potato crop in the Manouba region (lower valley of Medjerda, Tunisia). The experimental protocol consisted of four water treatments utilizing water-saving irrigation techniques: FI (Full Irrigation 100%): irrigation with 100% of crop water requirements. DI (Irrigation 75%): deficit irrigation with the application of 75% of crop water requirements. PRDRight (Irrigation 50% on the right side): Irrigation by partial root drying. PRDLeft (Irrigation 50% on the left side): Irrigation by partial root drying. Simulation of soil water profiles was carried out by the Hydrus-1D model. The soil hydraulic properties were calibrated according to the experimental conditions using an inverse modeling technique. According to the obtained results, simulated soil water profiles were close to those measured. Indeed, the calculated NRMSE values are low, indicating the reliability of Hydrus-1D as a decision support tool to optimize water irrigation management. These results were then used to investigate the effects of a 2 °C temperature increase on soil water loss, and it was determined that the impact was insignificant.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82169414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Roushangar, M. Alami, H. Golmohammadi, S. Shahnazi
As one of the largest super-saline lakes in the world, Lake Urmia in northwestern Iran has been facing severe drying in recent years. Drought and rapid expansion of agricultural activities are considered to be the main driving factors for the shrinking of the lake. To address this problem, an analysis of the spatiotemporal dynamics of land use/land cover (LULC) is important. This research implemented a multi-source satellite image analysis through support vector machine (SVM) for mapping LULC distributions for the years 2000, 2010, and 2020. Cellular automata (CA)–Markov was prepared for modeling the future landscape changes for 2030 and 2040. In the last step, the water requirement of agriculture in the catchment area of the Urmia Lake was simulated through the NETWAT model. Through the employed future LULC modeling, it was found that the areas covered by irrigated agriculture and gardens will grow from 1,450 and 395 km2 to 3,600 and 1,650 km2 in 2040, respectively, as deduced from the changes that occurred from 2000 to 2020. This will increase the water requirement of agriculture from 1,500 billion cubic meters in 2000 to more than 4,100 billion cubic meters in 2040.
{"title":"Monitoring and prediction of land use/land cover changes and water requirements in the basin of the Urmia Lake, Iran","authors":"K. Roushangar, M. Alami, H. Golmohammadi, S. Shahnazi","doi":"10.2166/ws.2023.132","DOIUrl":"https://doi.org/10.2166/ws.2023.132","url":null,"abstract":"\u0000 As one of the largest super-saline lakes in the world, Lake Urmia in northwestern Iran has been facing severe drying in recent years. Drought and rapid expansion of agricultural activities are considered to be the main driving factors for the shrinking of the lake. To address this problem, an analysis of the spatiotemporal dynamics of land use/land cover (LULC) is important. This research implemented a multi-source satellite image analysis through support vector machine (SVM) for mapping LULC distributions for the years 2000, 2010, and 2020. Cellular automata (CA)–Markov was prepared for modeling the future landscape changes for 2030 and 2040. In the last step, the water requirement of agriculture in the catchment area of the Urmia Lake was simulated through the NETWAT model. Through the employed future LULC modeling, it was found that the areas covered by irrigated agriculture and gardens will grow from 1,450 and 395 km2 to 3,600 and 1,650 km2 in 2040, respectively, as deduced from the changes that occurred from 2000 to 2020. This will increase the water requirement of agriculture from 1,500 billion cubic meters in 2000 to more than 4,100 billion cubic meters in 2040.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88224535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this research, the quality of drainage water was studied by using the water quality index (WQI). Water samples were taken from the Al-Dujaila River and Al-Dujaila drainage. Drainage water was diluted to different ratios with river water to decrease its salinity and increase its potential for agricultural uses. The diluted samples contained between 0 and 100% drainage water, and between 100 and 0% river water, in 10% steps – i.e., 0:10, 1:9, 2:8, 3:7, 4:6, 9:1, 8:2, 7:3, 6:4, and 5:5. After dilution of water, chemical properties, ion activities, electrical conductivity (EC), soil reaction (pH), sodium (Na+), calcium (Ca+2), magnesium (Mg+2), and total dissolved solid (TDS)) were measured in the laboratory of the University of Wasit/College of Agriculture, for computing the drainage water quality index (DWQI), sodium adsorption ratio (SAR), exchangeable sodium percentage (ESP), and soluble magnesium percentage (Mg%). Mathematical models were generated to predict the DWQI using DataFit software, depending on the water's chemical properties, and to find the best dilution ratio, which was 9:1. Model 2 includes the DWQI with SAR, ESP that gave the best results (R2 = 99.99%, RE = 0.0007, MAE = 0.425, RMSE = 0.6, and SEE = 1.992). The diluted drainage water used in this study was not suitable for either irrigation or human use.
本研究采用水质指数(WQI)对排水水质进行了研究。水样取自Al-Dujaila河和Al-Dujaila排水系统。排水与河水按不同比例稀释，以降低其盐度，增加其农业利用潜力。稀释后的样品含有0 - 100%的排水，100 - 0%的河水，按10%的步骤-即0:10,1:9,2:8,3:7,4:6,9:1,8:2,7:3,6:4和5:5。水稀释后，在Wasit大学农学院实验室测定土壤化学性质、离子活度、电导率(EC)、土壤反应(pH)、钠(Na+)、钙(Ca+2)、镁(Mg+2)和总溶解固形物(TDS)，计算排水水质指数(DWQI)、钠吸附比(SAR)、交换钠百分率(ESP)和可溶性镁百分率(Mg%)。根据水的化学性质，利用DataFit软件建立数学模型来预测DWQI，并找到最佳稀释比，该稀释比为9:1。模型2包含SAR、ESP的DWQI，结果最佳(R2 = 99.99%， RE = 0.0007, MAE = 0.425, RMSE = 0.6, SEE = 1.992)。本研究使用的稀释排水既不适合灌溉，也不适合人类使用。
{"title":"Assessing drainage water quality for irrigation using the water quality index and DataFit software","authors":"B. Al-humairi, N. Rahal","doi":"10.2166/ws.2023.131","DOIUrl":"https://doi.org/10.2166/ws.2023.131","url":null,"abstract":"\u0000 \u0000 In this research, the quality of drainage water was studied by using the water quality index (WQI). Water samples were taken from the Al-Dujaila River and Al-Dujaila drainage. Drainage water was diluted to different ratios with river water to decrease its salinity and increase its potential for agricultural uses. The diluted samples contained between 0 and 100% drainage water, and between 100 and 0% river water, in 10% steps – i.e., 0:10, 1:9, 2:8, 3:7, 4:6, 9:1, 8:2, 7:3, 6:4, and 5:5. After dilution of water, chemical properties, ion activities, electrical conductivity (EC), soil reaction (pH), sodium (Na+), calcium (Ca+2), magnesium (Mg+2), and total dissolved solid (TDS)) were measured in the laboratory of the University of Wasit/College of Agriculture, for computing the drainage water quality index (DWQI), sodium adsorption ratio (SAR), exchangeable sodium percentage (ESP), and soluble magnesium percentage (Mg%). Mathematical models were generated to predict the DWQI using DataFit software, depending on the water's chemical properties, and to find the best dilution ratio, which was 9:1. Model 2 includes the DWQI with SAR, ESP that gave the best results (R2 = 99.99%, RE = 0.0007, MAE = 0.425, RMSE = 0.6, and SEE = 1.992). The diluted drainage water used in this study was not suitable for either irrigation or human use.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83790414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohsen Hekmat, H. Sarkardeh, E. Jabbari, M. Samadi
Cavitation is a common and complex hydraulic phenomenon on the chute spillways and may cause damage to the structure. Aeration in the water flow is one of the best ways to prevent cavitation. To design an aerator, estimation of aeration coefficient (β), jet length (L/h0), and jet impact angle on chute (tanγ) are important in this study. The potential of a hybrid Adaptive Neuro-Fuzzy Interface System (ANFIS) with metaheuristic algorithms was investigated to estimate the required parameters to design an aerator. The ANFIS was combined with four metaheuristic algorithms, including Differential Evolution (DE), Ant Colony Optimization (ACO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Experimental data and dimensionless parameters were used to develop the proposed hybrid ANFIS models. Three statistical indicators, including Root Mean Square Error (RMSE), Mean Average Error (MAE), and coefficient of determination (R2), were employed to compare the proposed methods with empirical relations. According to the statistical indicators, among the data-driven methods, the ANFIS–DE method had the best prediction in estimating β (RMSE = 0.018, R2 = 0.984, MAE = 0.013), L/h0 (RMSE = 1.293, R2 = 0.963, MAE = 1.082), and tanγ (RMSE = 0.009, R2 = 0.939, MAE = 0.007).
{"title":"Application of a hybrid ANFIS with metaheuristic algorithms to estimate the aeration design parameters","authors":"Mohsen Hekmat, H. Sarkardeh, E. Jabbari, M. Samadi","doi":"10.2166/ws.2023.127","DOIUrl":"https://doi.org/10.2166/ws.2023.127","url":null,"abstract":"\u0000 Cavitation is a common and complex hydraulic phenomenon on the chute spillways and may cause damage to the structure. Aeration in the water flow is one of the best ways to prevent cavitation. To design an aerator, estimation of aeration coefficient (β), jet length (L/h0), and jet impact angle on chute (tanγ) are important in this study. The potential of a hybrid Adaptive Neuro-Fuzzy Interface System (ANFIS) with metaheuristic algorithms was investigated to estimate the required parameters to design an aerator. The ANFIS was combined with four metaheuristic algorithms, including Differential Evolution (DE), Ant Colony Optimization (ACO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Experimental data and dimensionless parameters were used to develop the proposed hybrid ANFIS models. Three statistical indicators, including Root Mean Square Error (RMSE), Mean Average Error (MAE), and coefficient of determination (R2), were employed to compare the proposed methods with empirical relations. According to the statistical indicators, among the data-driven methods, the ANFIS–DE method had the best prediction in estimating β (RMSE = 0.018, R2 = 0.984, MAE = 0.013), L/h0 (RMSE = 1.293, R2 = 0.963, MAE = 1.082), and tanγ (RMSE = 0.009, R2 = 0.939, MAE = 0.007).","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86979902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lily Suhana, M. Tan, Z. Luhaim, Mohd Hilmi P. Ramli, N. S. Subki, F. Tangang, A. Ishak
Climate change exacerbates dry seasons in Southeast Asia, leading to water supply shortage for agricultural use. However, the link between hydro-meteorological droughts and large-scale atmospheric circulations, such as the El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Madden–Julian oscillation (MJO), has received very little attention. Therefore, this study aims to analyse the hydro-meteorological droughts that occurred in the Kelantan River Basin (KRB) between 1985 and 2020 using the Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) as well as their connections to ENSO, IOD, and MJO. Sens’ slope and Mann–Kendall test were employed to evaluate the trends and magnitude changes of the historical droughts, respectively. In addition, the response rate of SSI to SPI was considered to understand how precipitation affects streamflow. The results show that extremely dry events occurred in 1986, 1987, 1989, 1990, 1992, 1997–1998, 2015–2016, and 2020. Based on the SSI results, more than 70% of extremely dry periods last 6 months or longer. Interestingly, from January to May, when there was low precipitation, SSI had a higher response rate to SPI. The ENSO, as opposed to the IOD and MJO, had a stronger impact on the dry conditions over the KRB.
{"title":"Spatiotemporal characteristics of hydro-meteorological droughts and their connections to large-scale atmospheric circulations in the Kelantan River Basin, Malaysia","authors":"Lily Suhana, M. Tan, Z. Luhaim, Mohd Hilmi P. Ramli, N. S. Subki, F. Tangang, A. Ishak","doi":"10.2166/ws.2023.126","DOIUrl":"https://doi.org/10.2166/ws.2023.126","url":null,"abstract":"\u0000 Climate change exacerbates dry seasons in Southeast Asia, leading to water supply shortage for agricultural use. However, the link between hydro-meteorological droughts and large-scale atmospheric circulations, such as the El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Madden–Julian oscillation (MJO), has received very little attention. Therefore, this study aims to analyse the hydro-meteorological droughts that occurred in the Kelantan River Basin (KRB) between 1985 and 2020 using the Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) as well as their connections to ENSO, IOD, and MJO. Sens’ slope and Mann–Kendall test were employed to evaluate the trends and magnitude changes of the historical droughts, respectively. In addition, the response rate of SSI to SPI was considered to understand how precipitation affects streamflow. The results show that extremely dry events occurred in 1986, 1987, 1989, 1990, 1992, 1997–1998, 2015–2016, and 2020. Based on the SSI results, more than 70% of extremely dry periods last 6 months or longer. Interestingly, from January to May, when there was low precipitation, SSI had a higher response rate to SPI. The ENSO, as opposed to the IOD and MJO, had a stronger impact on the dry conditions over the KRB.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76000037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines the context of climate change and land use in the second Songhua River basin with the goal of improving runoff. The report begins by introducing the history of watershed runoff and the study area. The differences between various land use types and land use efficiency are examined through literature research on the basis of the watershed hydrology model. The novelty of the paper is to compare the evapotranspiration of the model in different periods with the depth data of surface runoff. The results show that the simulation analysis and collaborative response strategy proposed here can adapt to the meteorological changes in the basin. The evapotranspiration of a watershed that was converted from woodland to grassland in 1970 was 34 mm, while that of a watershed that was converted from grassland to woodland was 32 mm, according to the results of the model test. The evapotranspiration of a watershed that gone from woodland to grassland in 2010 is 45 mm, compared to 39 mm for a watershed that has gone from grassland to woodland. The second Songhua River basin's surface water yield data can therefore be used to model and study the basin's runoff in real time.
{"title":"Runoff simulation analysis and collaborative response research based on the second Songhua River basin under the background of land use","authors":"Hongxue Liu","doi":"10.2166/ws.2023.125","DOIUrl":"https://doi.org/10.2166/ws.2023.125","url":null,"abstract":"\u0000 \u0000 This paper examines the context of climate change and land use in the second Songhua River basin with the goal of improving runoff. The report begins by introducing the history of watershed runoff and the study area. The differences between various land use types and land use efficiency are examined through literature research on the basis of the watershed hydrology model. The novelty of the paper is to compare the evapotranspiration of the model in different periods with the depth data of surface runoff. The results show that the simulation analysis and collaborative response strategy proposed here can adapt to the meteorological changes in the basin. The evapotranspiration of a watershed that was converted from woodland to grassland in 1970 was 34 mm, while that of a watershed that was converted from grassland to woodland was 32 mm, according to the results of the model test. The evapotranspiration of a watershed that gone from woodland to grassland in 2010 is 45 mm, compared to 39 mm for a watershed that has gone from grassland to woodland. The second Songhua River basin's surface water yield data can therefore be used to model and study the basin's runoff in real time.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84297656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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