Esmatullah Sangin, Pravin R. Patil, S. K. Mishra, Sumit Sen
The probability distribution function (PDF)-based unit hydrographs (UHs) are gaining momentum in an application for more accurate rainfall-runoff transformation. Employing seven statistical performance indices, R2, NSE, MSE, RMSE, MAE, MAPE, and SE in GRG-NLP optimization, 18 known and 12 adaptable UHs were assessed against UHs derived from 18 storms in 7 basins across the United States, Turkey, and India. To this end, 27 Maple codes were proposed for UH-application requiring only peak discharge (qp), time to peak (tp), and time base (tb) for derivation. The introduced PDFs, such as Dagum, Generalized Gamma, Log-Logistic, Gumbel Type-I, and Shifted Gompertz, replicated the observed data-derived UHs more closed than did the known PDFs, like Inverse Gaussian, 2-PGD, Log-Normal, Inverse-Gamma, and Nagakami. Among the three-parameter (6 nos.), two-parameter (21 nos.), and single-parameter (3 nos.) PDFs, the Dagum, Log-Logistic, and Poisson consistently outperformed their respective counterparts in replication.
{"title":"Proficiency of probability distributions in unit hydrograph derivation","authors":"Esmatullah Sangin, Pravin R. Patil, S. K. Mishra, Sumit Sen","doi":"10.2166/nh.2024.151","DOIUrl":"https://doi.org/10.2166/nh.2024.151","url":null,"abstract":"\u0000 \u0000 The probability distribution function (PDF)-based unit hydrographs (UHs) are gaining momentum in an application for more accurate rainfall-runoff transformation. Employing seven statistical performance indices, R2, NSE, MSE, RMSE, MAE, MAPE, and SE in GRG-NLP optimization, 18 known and 12 adaptable UHs were assessed against UHs derived from 18 storms in 7 basins across the United States, Turkey, and India. To this end, 27 Maple codes were proposed for UH-application requiring only peak discharge (qp), time to peak (tp), and time base (tb) for derivation. The introduced PDFs, such as Dagum, Generalized Gamma, Log-Logistic, Gumbel Type-I, and Shifted Gompertz, replicated the observed data-derived UHs more closed than did the known PDFs, like Inverse Gaussian, 2-PGD, Log-Normal, Inverse-Gamma, and Nagakami. Among the three-parameter (6 nos.), two-parameter (21 nos.), and single-parameter (3 nos.) PDFs, the Dagum, Log-Logistic, and Poisson consistently outperformed their respective counterparts in replication.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"19 7","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140257837","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 hydrological dynamics and sources of karst tidal springs are difficult to capture and quantify due to fluctuations in their flow velocity. In this study, the Laolongshui (LLS) karst tidal spring in the Maocun underground river basin of Guilin City was taken as an example, with a 2-year continuous monitoring of the electrical conductivity, and water level,as well as water chemical analysis. The results showed the following: (1) discovered the variation pattern of LLS water level in different seasons, the water level fluctuates regularly on a daily scale, with a rise and fall time of 43.6 min after heavy rainfall in the rainy season, while in the dry season, it lasts for about 74–80 h. (2) Four peaks were extracted from the frequency distribution of electrical conductivity, representing the response of springwater under different rainfall conditions. (3) The annual average frequencies of the occurrence of P1, P2, P3, and P4 in terms of time are 53.82, 39.29, 6.18, and 0.72%, respectively. The results provide a new method for analyzing groundwater's source and dynamic changes in karst areas.
{"title":"Temporal dynamics of water level and water sources analyses of karst tidal springs in Guilin, China","authors":"Jie Ma, Shilong Zhu, Xiaomei Wei, Yongli Guo, Jianhua Cao, Fen Huang","doi":"10.2166/nh.2024.178","DOIUrl":"https://doi.org/10.2166/nh.2024.178","url":null,"abstract":"\u0000 The hydrological dynamics and sources of karst tidal springs are difficult to capture and quantify due to fluctuations in their flow velocity. In this study, the Laolongshui (LLS) karst tidal spring in the Maocun underground river basin of Guilin City was taken as an example, with a 2-year continuous monitoring of the electrical conductivity, and water level,as well as water chemical analysis. The results showed the following: (1) discovered the variation pattern of LLS water level in different seasons, the water level fluctuates regularly on a daily scale, with a rise and fall time of 43.6 min after heavy rainfall in the rainy season, while in the dry season, it lasts for about 74–80 h. (2) Four peaks were extracted from the frequency distribution of electrical conductivity, representing the response of springwater under different rainfall conditions. (3) The annual average frequencies of the occurrence of P1, P2, P3, and P4 in terms of time are 53.82, 39.29, 6.18, and 0.72%, respectively. The results provide a new method for analyzing groundwater's source and dynamic changes in karst areas.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"84 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139779423","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 hydrological dynamics and sources of karst tidal springs are difficult to capture and quantify due to fluctuations in their flow velocity. In this study, the Laolongshui (LLS) karst tidal spring in the Maocun underground river basin of Guilin City was taken as an example, with a 2-year continuous monitoring of the electrical conductivity, and water level,as well as water chemical analysis. The results showed the following: (1) discovered the variation pattern of LLS water level in different seasons, the water level fluctuates regularly on a daily scale, with a rise and fall time of 43.6 min after heavy rainfall in the rainy season, while in the dry season, it lasts for about 74–80 h. (2) Four peaks were extracted from the frequency distribution of electrical conductivity, representing the response of springwater under different rainfall conditions. (3) The annual average frequencies of the occurrence of P1, P2, P3, and P4 in terms of time are 53.82, 39.29, 6.18, and 0.72%, respectively. The results provide a new method for analyzing groundwater's source and dynamic changes in karst areas.
{"title":"Temporal dynamics of water level and water sources analyses of karst tidal springs in Guilin, China","authors":"Jie Ma, Shilong Zhu, Xiaomei Wei, Yongli Guo, Jianhua Cao, Fen Huang","doi":"10.2166/nh.2024.178","DOIUrl":"https://doi.org/10.2166/nh.2024.178","url":null,"abstract":"\u0000 The hydrological dynamics and sources of karst tidal springs are difficult to capture and quantify due to fluctuations in their flow velocity. In this study, the Laolongshui (LLS) karst tidal spring in the Maocun underground river basin of Guilin City was taken as an example, with a 2-year continuous monitoring of the electrical conductivity, and water level,as well as water chemical analysis. The results showed the following: (1) discovered the variation pattern of LLS water level in different seasons, the water level fluctuates regularly on a daily scale, with a rise and fall time of 43.6 min after heavy rainfall in the rainy season, while in the dry season, it lasts for about 74–80 h. (2) Four peaks were extracted from the frequency distribution of electrical conductivity, representing the response of springwater under different rainfall conditions. (3) The annual average frequencies of the occurrence of P1, P2, P3, and P4 in terms of time are 53.82, 39.29, 6.18, and 0.72%, respectively. The results provide a new method for analyzing groundwater's source and dynamic changes in karst areas.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"476 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139839096","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}
Hanie Pashaie, S. S. M. Nadoushani, Ali Moridi, Ali Ahani
Bivariate approaches in Regional Frequency Analysis (RFA) address two issues: first, to evaluate the homogeneity of regions, and second, to estimate the joint return periods. This study was conducted to investigate the joint return period of a severe historical drought in southwestern Iran. Fifty-nine rain gauges were first clustered into three, four, and five regions using the fuzzy c-means clustering (FCM) algorithm. Then bivariate discordancy and homogeneity tests were applied to adjust the initial clusters. The results showed that only in the case of three clusters all the regions were homogeneous. Therefore, it can be inferred that combining clustering analysis and discordancy test is insufficient to form homogeneous regions. Finally, the joint return period, by choosing Generalized Logistic and Wakeby as marginal distributions and Clayton as a copula, was estimated for all the sites in the three regions. Since no three-parameter distribution function fitted well to the variable severity, the bivariate homogeneity index does not necessarily attest to region homogeneity regarding the marginal distribution functions. it is also deduced that sites with higher mean annual precipiataion (MAP) and, correspondingly, higher elevation are more likely to experience shorter return periods of same drought events, in contrast to sites with lower MAP or lower elevation.
{"title":"Bivariate regional drought frequency analysis using multivariate approaches: a case study in southwestern Iran","authors":"Hanie Pashaie, S. S. M. Nadoushani, Ali Moridi, Ali Ahani","doi":"10.2166/nh.2024.160","DOIUrl":"https://doi.org/10.2166/nh.2024.160","url":null,"abstract":"\u0000 Bivariate approaches in Regional Frequency Analysis (RFA) address two issues: first, to evaluate the homogeneity of regions, and second, to estimate the joint return periods. This study was conducted to investigate the joint return period of a severe historical drought in southwestern Iran. Fifty-nine rain gauges were first clustered into three, four, and five regions using the fuzzy c-means clustering (FCM) algorithm. Then bivariate discordancy and homogeneity tests were applied to adjust the initial clusters. The results showed that only in the case of three clusters all the regions were homogeneous. Therefore, it can be inferred that combining clustering analysis and discordancy test is insufficient to form homogeneous regions. Finally, the joint return period, by choosing Generalized Logistic and Wakeby as marginal distributions and Clayton as a copula, was estimated for all the sites in the three regions. Since no three-parameter distribution function fitted well to the variable severity, the bivariate homogeneity index does not necessarily attest to region homogeneity regarding the marginal distribution functions. it is also deduced that sites with higher mean annual precipiataion (MAP) and, correspondingly, higher elevation are more likely to experience shorter return periods of same drought events, in contrast to sites with lower MAP or lower elevation.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"1207 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139831192","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}
Reliable quantification of groundwater recharge rate is crucial for the sustainable utilization of groundwater resources. However, little information is documented about the uncertainty associated with recharge rate estimation from the different combinations of model complexity and objective function perspectives. Therefore, this study aims to (i) analyze the sensitivity of the model parameters under different combinations of model complexities and objective functions and (ii) estimate the groundwater recharge rate in the Hombele catchment, Upper Awash Basin, Ethiopia, for different combinations of objective functions and model complexities. The effect of these model complexities in estimating groundwater recharge rate and parametrizing model parameters was quantified for the period 1986–2013. A total of 10 combinations of model complexities and objective functions were used for the analysis. The Kling–Gupta efficiency (Nash–Sutcliffe efficiency) values for calibration, validation, and the whole period are 0.89 (0.80), 0.80 (0.73), and 0.87 (0.77), respectively, when a semi-distributed HBV-light model was used. For all objective functions, we found that the average annual recharge rate of the study catchment ranges from 185.9 to 280.5 mm when the HBV-light model was considered as a semi-distributed model. In contrast, the average annual recharge rate ranges from 185.3 to 321.7 mm when applying the HBV-light model as a lumped model.
{"title":"Estimating groundwater recharge rates in the Upper Awash Basin, Ethiopia under different combinations of model complexity and objective functions","authors":"Muauz Amare Redda, Behailu Birhanu, Bediru Hussien","doi":"10.2166/nh.2024.059","DOIUrl":"https://doi.org/10.2166/nh.2024.059","url":null,"abstract":"\u0000 Reliable quantification of groundwater recharge rate is crucial for the sustainable utilization of groundwater resources. However, little information is documented about the uncertainty associated with recharge rate estimation from the different combinations of model complexity and objective function perspectives. Therefore, this study aims to (i) analyze the sensitivity of the model parameters under different combinations of model complexities and objective functions and (ii) estimate the groundwater recharge rate in the Hombele catchment, Upper Awash Basin, Ethiopia, for different combinations of objective functions and model complexities. The effect of these model complexities in estimating groundwater recharge rate and parametrizing model parameters was quantified for the period 1986–2013. A total of 10 combinations of model complexities and objective functions were used for the analysis. The Kling–Gupta efficiency (Nash–Sutcliffe efficiency) values for calibration, validation, and the whole period are 0.89 (0.80), 0.80 (0.73), and 0.87 (0.77), respectively, when a semi-distributed HBV-light model was used. For all objective functions, we found that the average annual recharge rate of the study catchment ranges from 185.9 to 280.5 mm when the HBV-light model was considered as a semi-distributed model. In contrast, the average annual recharge rate ranges from 185.3 to 321.7 mm when applying the HBV-light model as a lumped model.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"23 4","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139889354","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}
Kielo Isomäki, Aleksi Salla, H. Salo, H. Koivusalo
Controlled drainage (CRD) is an agricultural water management practice designed to adjust the capacity of a drainage system under varying hydrological conditions. This simulation study aimed to quantify the potential of combining a controlled subsurface drainage (CS) with open ditch damming (CD) to manage the water table depth (WTD) and field water balance in Nordic conditions. Simulations with and without controlled drainage were run using a hydrological model that had been set up for a flat loamy field in Northern Ostrobothnia, Finland, for the period 2010–2021. All CRD scenarios reduced the probability of deep WTDs during growing seasons (May–Sep). The impact of CS on WTDs was greater and more uniform than CD. The CRD effects on water balance were seen in water outflow pathways, as CS reduced drain discharge while CD had the opposite effect. When both methods were applied simultaneously, annual evapotranspiration increased 5–12% compared with the free drainage scenario. The effects of CRD on evapotranspiration were greatest during the dry years indicating that CRD has potential to reduce drought in food production areas. None of the CRD scenarios could maintain optimal WTDs during the entire growing season, highlighting the complexity of optimizing field water management using CRD alone.
{"title":"Hydrological effects of open ditch damming and controlled subsurface drainage in a Nordic agricultural field","authors":"Kielo Isomäki, Aleksi Salla, H. Salo, H. Koivusalo","doi":"10.2166/nh.2024.053","DOIUrl":"https://doi.org/10.2166/nh.2024.053","url":null,"abstract":"\u0000 Controlled drainage (CRD) is an agricultural water management practice designed to adjust the capacity of a drainage system under varying hydrological conditions. This simulation study aimed to quantify the potential of combining a controlled subsurface drainage (CS) with open ditch damming (CD) to manage the water table depth (WTD) and field water balance in Nordic conditions. Simulations with and without controlled drainage were run using a hydrological model that had been set up for a flat loamy field in Northern Ostrobothnia, Finland, for the period 2010–2021. All CRD scenarios reduced the probability of deep WTDs during growing seasons (May–Sep). The impact of CS on WTDs was greater and more uniform than CD. The CRD effects on water balance were seen in water outflow pathways, as CS reduced drain discharge while CD had the opposite effect. When both methods were applied simultaneously, annual evapotranspiration increased 5–12% compared with the free drainage scenario. The effects of CRD on evapotranspiration were greatest during the dry years indicating that CRD has potential to reduce drought in food production areas. None of the CRD scenarios could maintain optimal WTDs during the entire growing season, highlighting the complexity of optimizing field water management using CRD alone.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"53 ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139830207","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}
Kielo Isomäki, Aleksi Salla, H. Salo, H. Koivusalo
Controlled drainage (CRD) is an agricultural water management practice designed to adjust the capacity of a drainage system under varying hydrological conditions. This simulation study aimed to quantify the potential of combining a controlled subsurface drainage (CS) with open ditch damming (CD) to manage the water table depth (WTD) and field water balance in Nordic conditions. Simulations with and without controlled drainage were run using a hydrological model that had been set up for a flat loamy field in Northern Ostrobothnia, Finland, for the period 2010–2021. All CRD scenarios reduced the probability of deep WTDs during growing seasons (May–Sep). The impact of CS on WTDs was greater and more uniform than CD. The CRD effects on water balance were seen in water outflow pathways, as CS reduced drain discharge while CD had the opposite effect. When both methods were applied simultaneously, annual evapotranspiration increased 5–12% compared with the free drainage scenario. The effects of CRD on evapotranspiration were greatest during the dry years indicating that CRD has potential to reduce drought in food production areas. None of the CRD scenarios could maintain optimal WTDs during the entire growing season, highlighting the complexity of optimizing field water management using CRD alone.
{"title":"Hydrological effects of open ditch damming and controlled subsurface drainage in a Nordic agricultural field","authors":"Kielo Isomäki, Aleksi Salla, H. Salo, H. Koivusalo","doi":"10.2166/nh.2024.053","DOIUrl":"https://doi.org/10.2166/nh.2024.053","url":null,"abstract":"\u0000 Controlled drainage (CRD) is an agricultural water management practice designed to adjust the capacity of a drainage system under varying hydrological conditions. This simulation study aimed to quantify the potential of combining a controlled subsurface drainage (CS) with open ditch damming (CD) to manage the water table depth (WTD) and field water balance in Nordic conditions. Simulations with and without controlled drainage were run using a hydrological model that had been set up for a flat loamy field in Northern Ostrobothnia, Finland, for the period 2010–2021. All CRD scenarios reduced the probability of deep WTDs during growing seasons (May–Sep). The impact of CS on WTDs was greater and more uniform than CD. The CRD effects on water balance were seen in water outflow pathways, as CS reduced drain discharge while CD had the opposite effect. When both methods were applied simultaneously, annual evapotranspiration increased 5–12% compared with the free drainage scenario. The effects of CRD on evapotranspiration were greatest during the dry years indicating that CRD has potential to reduce drought in food production areas. None of the CRD scenarios could maintain optimal WTDs during the entire growing season, highlighting the complexity of optimizing field water management using CRD alone.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"26 4","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139890129","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}
Hanie Pashaie, S. S. M. Nadoushani, Ali Moridi, Ali Ahani
Bivariate approaches in Regional Frequency Analysis (RFA) address two issues: first, to evaluate the homogeneity of regions, and second, to estimate the joint return periods. This study was conducted to investigate the joint return period of a severe historical drought in southwestern Iran. Fifty-nine rain gauges were first clustered into three, four, and five regions using the fuzzy c-means clustering (FCM) algorithm. Then bivariate discordancy and homogeneity tests were applied to adjust the initial clusters. The results showed that only in the case of three clusters all the regions were homogeneous. Therefore, it can be inferred that combining clustering analysis and discordancy test is insufficient to form homogeneous regions. Finally, the joint return period, by choosing Generalized Logistic and Wakeby as marginal distributions and Clayton as a copula, was estimated for all the sites in the three regions. Since no three-parameter distribution function fitted well to the variable severity, the bivariate homogeneity index does not necessarily attest to region homogeneity regarding the marginal distribution functions. it is also deduced that sites with higher mean annual precipiataion (MAP) and, correspondingly, higher elevation are more likely to experience shorter return periods of same drought events, in contrast to sites with lower MAP or lower elevation.
{"title":"Bivariate regional drought frequency analysis using multivariate approaches: a case study in southwestern Iran","authors":"Hanie Pashaie, S. S. M. Nadoushani, Ali Moridi, Ali Ahani","doi":"10.2166/nh.2024.160","DOIUrl":"https://doi.org/10.2166/nh.2024.160","url":null,"abstract":"\u0000 Bivariate approaches in Regional Frequency Analysis (RFA) address two issues: first, to evaluate the homogeneity of regions, and second, to estimate the joint return periods. This study was conducted to investigate the joint return period of a severe historical drought in southwestern Iran. Fifty-nine rain gauges were first clustered into three, four, and five regions using the fuzzy c-means clustering (FCM) algorithm. Then bivariate discordancy and homogeneity tests were applied to adjust the initial clusters. The results showed that only in the case of three clusters all the regions were homogeneous. Therefore, it can be inferred that combining clustering analysis and discordancy test is insufficient to form homogeneous regions. Finally, the joint return period, by choosing Generalized Logistic and Wakeby as marginal distributions and Clayton as a copula, was estimated for all the sites in the three regions. Since no three-parameter distribution function fitted well to the variable severity, the bivariate homogeneity index does not necessarily attest to region homogeneity regarding the marginal distribution functions. it is also deduced that sites with higher mean annual precipiataion (MAP) and, correspondingly, higher elevation are more likely to experience shorter return periods of same drought events, in contrast to sites with lower MAP or lower elevation.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"52 5-6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139890983","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}
Reliable quantification of groundwater recharge rate is crucial for the sustainable utilization of groundwater resources. However, little information is documented about the uncertainty associated with recharge rate estimation from the different combinations of model complexity and objective function perspectives. Therefore, this study aims to (i) analyze the sensitivity of the model parameters under different combinations of model complexities and objective functions and (ii) estimate the groundwater recharge rate in the Hombele catchment, Upper Awash Basin, Ethiopia, for different combinations of objective functions and model complexities. The effect of these model complexities in estimating groundwater recharge rate and parametrizing model parameters was quantified for the period 1986–2013. A total of 10 combinations of model complexities and objective functions were used for the analysis. The Kling–Gupta efficiency (Nash–Sutcliffe efficiency) values for calibration, validation, and the whole period are 0.89 (0.80), 0.80 (0.73), and 0.87 (0.77), respectively, when a semi-distributed HBV-light model was used. For all objective functions, we found that the average annual recharge rate of the study catchment ranges from 185.9 to 280.5 mm when the HBV-light model was considered as a semi-distributed model. In contrast, the average annual recharge rate ranges from 185.3 to 321.7 mm when applying the HBV-light model as a lumped model.
{"title":"Estimating groundwater recharge rates in the Upper Awash Basin, Ethiopia under different combinations of model complexity and objective functions","authors":"Muauz Amare Redda, Behailu Birhanu, Bediru Hussien","doi":"10.2166/nh.2024.059","DOIUrl":"https://doi.org/10.2166/nh.2024.059","url":null,"abstract":"\u0000 Reliable quantification of groundwater recharge rate is crucial for the sustainable utilization of groundwater resources. However, little information is documented about the uncertainty associated with recharge rate estimation from the different combinations of model complexity and objective function perspectives. Therefore, this study aims to (i) analyze the sensitivity of the model parameters under different combinations of model complexities and objective functions and (ii) estimate the groundwater recharge rate in the Hombele catchment, Upper Awash Basin, Ethiopia, for different combinations of objective functions and model complexities. The effect of these model complexities in estimating groundwater recharge rate and parametrizing model parameters was quantified for the period 1986–2013. A total of 10 combinations of model complexities and objective functions were used for the analysis. The Kling–Gupta efficiency (Nash–Sutcliffe efficiency) values for calibration, validation, and the whole period are 0.89 (0.80), 0.80 (0.73), and 0.87 (0.77), respectively, when a semi-distributed HBV-light model was used. For all objective functions, we found that the average annual recharge rate of the study catchment ranges from 185.9 to 280.5 mm when the HBV-light model was considered as a semi-distributed model. In contrast, the average annual recharge rate ranges from 185.3 to 321.7 mm when applying the HBV-light model as a lumped model.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"81 ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139829503","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}
J. J. Fang, Linshan Yang, Xiaohu Wen, Weide Li, Haijiao Yu, Ting Zhou
Accurate streamflow prediction is crucial for effective water resource management. However, reliable prediction remains a considerable challenge because of the highly complex, non-stationary, and non-linear processes that contribute to streamflow at various spatial and temporal scales. In this study, we utilized a convolutional neural network (CNN)–Transformer–Long short-term memory (LSTM) (CTL) model for streamflow prediction, which replaced the embedding layer with a CNN layer to extract partial hidden features, and added a LSTM layer to extract correlations on a temporal scale. The CTL model incorporated Transformer's ability to extract global information, CNN's ability to extract hidden features, and LSTM's ability to capture temporal correlations. To validate its effectiveness, we applied it for streamflow prediction in the Shule River basin in northwest China across 1-, 3-, and 6-month horizons and compared its performance with Transformer, CNN, LSTM, CNN–Transformer, and Transformer–LSTM. The results demonstrated that CTL outperformed all other models in terms of predictive accuracy with Nash–Sutcliffe coefficient (NSE) values of 0.964, 0.912, and 0.856 for 1-, 3-, 6-month ahead prediction. The best results among the five comparative models were 0.908, 0.824, and 0.778, respectively. This indicated that CTL is an outstanding alternative technique for streamflow prediction where surface data are limited.
{"title":"A deep learning-based hybrid approach for multi-time-ahead streamflow prediction in an arid region of Northwest China","authors":"J. J. Fang, Linshan Yang, Xiaohu Wen, Weide Li, Haijiao Yu, Ting Zhou","doi":"10.2166/nh.2024.124","DOIUrl":"https://doi.org/10.2166/nh.2024.124","url":null,"abstract":"\u0000 \u0000 Accurate streamflow prediction is crucial for effective water resource management. However, reliable prediction remains a considerable challenge because of the highly complex, non-stationary, and non-linear processes that contribute to streamflow at various spatial and temporal scales. In this study, we utilized a convolutional neural network (CNN)–Transformer–Long short-term memory (LSTM) (CTL) model for streamflow prediction, which replaced the embedding layer with a CNN layer to extract partial hidden features, and added a LSTM layer to extract correlations on a temporal scale. The CTL model incorporated Transformer's ability to extract global information, CNN's ability to extract hidden features, and LSTM's ability to capture temporal correlations. To validate its effectiveness, we applied it for streamflow prediction in the Shule River basin in northwest China across 1-, 3-, and 6-month horizons and compared its performance with Transformer, CNN, LSTM, CNN–Transformer, and Transformer–LSTM. The results demonstrated that CTL outperformed all other models in terms of predictive accuracy with Nash–Sutcliffe coefficient (NSE) values of 0.964, 0.912, and 0.856 for 1-, 3-, 6-month ahead prediction. The best results among the five comparative models were 0.908, 0.824, and 0.778, respectively. This indicated that CTL is an outstanding alternative technique for streamflow prediction where surface data are limited.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"92 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139440233","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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