Pub Date : 2024-02-15DOI: 10.3103/s1068373923120014
Yu. A. Simonov, S. V. Borsch, N. K. Semenova, A. V. Khristoforov
Abstract
A method for short-range forecasting of average daily streamflow is proposed. The method uses the HBV-96 conceptual model of river runoff formation and the COSMO-Ru operational numerical weather prediction system. The method has been implemented for 546 river basins located throughout Russia. An archive of the required hydrometeorological information for the period from 2010 to 2019 has been formed. The method has been developed using the data for the first seven years and verified on independent material with the ones for the last three years. The verification results have shown that the method allows obtaining satisfactory forecasts for a quite large number of river basins. The results make it possible to use the proposed method within the framework of an automated system for preparing and issuing short-range forecasts for the Russian river streamflow.
{"title":"Short-range Streamflow Forecasting for Russian Rivers Using the HBV-96 Model and the COSMO-Ru System","authors":"Yu. A. Simonov, S. V. Borsch, N. K. Semenova, A. V. Khristoforov","doi":"10.3103/s1068373923120014","DOIUrl":"https://doi.org/10.3103/s1068373923120014","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>A method for short-range forecasting of average daily streamflow is proposed. The method uses the HBV-96 conceptual model of river runoff formation and the COSMO-Ru operational numerical weather prediction system. The method has been implemented for 546 river basins located throughout Russia. An archive of the required hydrometeorological information for the period from 2010 to 2019 has been formed. The method has been developed using the data for the first seven years and verified on independent material with the ones for the last three years. The verification results have shown that the method allows obtaining satisfactory forecasts for a quite large number of river basins. The results make it possible to use the proposed method within the framework of an automated system for preparing and issuing short-range forecasts for the Russian river streamflow.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3103/s1068373923120117
N. S. Ivanova, I. N. Kuznetsova, E. A. Lezina
Abstract
The review is compiled according to the results of exploiting the system of monitoring total ozone (TO) over Russia and adjoining territories, which is functioning in operational mode at the Central Aerological Observatory (CAO). The monitoring system uses the data from the national network equipped with M-124 filter ozonometers under the methodological supervision of the Main Geophysical Observatory. The quality of the functioning of the entire system is operationally controlled based on the OMI satellite equipment observations (NASA, USA). Basic TO observation data are generalized for each month of the third quarter of 2023 and for the third quarter. The data of routine observations of ground-level ozone in the Moscow region are also presented.
摘要 本综述是根据对俄罗斯及邻近地区总臭氧监测系统的利用结果编写的，该系统在中央空 气观测站（CAO）以运行模式运行。该监测系统在主要地球物理观测站的方法监督下，使用配备 M-124 过滤臭氧测量仪的国家网络提供的数据。整个系统的运行质量是在 OMI 卫星设备观测（美国宇航局）的基础上进行控制的。基础 TO 观测数据是 2023 年第三季度每个月和第三季度的通用数据。还介绍了莫斯科地区地面臭氧的常规观测数据。
{"title":"Ozone Content over the Russian Federation in the Third Quarter of 2023","authors":"N. S. Ivanova, I. N. Kuznetsova, E. A. Lezina","doi":"10.3103/s1068373923120117","DOIUrl":"https://doi.org/10.3103/s1068373923120117","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The review is compiled according to the results of exploiting the system of monitoring total ozone (TO) over Russia and adjoining territories, which is functioning in operational mode at the Central Aerological Observatory (CAO). The monitoring system uses the data from the national network equipped with M-124 filter ozonometers under the methodological supervision of the Main Geophysical Observatory. The quality of the functioning of the entire system is operationally controlled based on the OMI satellite equipment observations (NASA, USA). Basic TO observation data are generalized for each month of the third quarter of 2023 and for the third quarter. The data of routine observations of ground-level ozone in the Moscow region are also presented.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3103/s1068373923120099
H. Allali, Y. Elmeddahi, N. Badni, M. El-nesr
Abstract
Rainfall-runoff modeling plays a crucial role in determining the regular water balance. Modifications in land use and land cover (LULC) significantly impact on the hydrological response of watersheds. The study aims to analyze the effect of land use change on river runoff with the use of hydrological modeling in the Wadi Ouahrane watershed in northwestern Algeria. The study was conducted for the period from 1987 to 2017. According to the LULC change study, cultivated land and built-up areas have increased, whereas forest and grassland areas have decreased. Sensitivity evaluation has shown that the CN (curve number) is the most important factor affecting the watershed hydrology. The Nash–Sutcliffe (NSE) and (R^{2}) efficiency values for the Wadi Ouahrane watershed were 0.76–0.82 and 0.86–0.91 for the calibration period and 0.72–0.74 and 0.81–0.83 for the validation one, respectively. The assessment of the HEC-HMS response to the LULC change showed that the peak discharge for 2017 increased by 68% relative to the 1987 peak discharge. This research has improved the knowledge of the relationship between land use change and hydrological regimes in the Wadi Ouahrane watershed.
{"title":"Assessment of the Hydrological Responces to Land Use Changes in Wadi Ouahrane Watershed, Algeria","authors":"H. Allali, Y. Elmeddahi, N. Badni, M. El-nesr","doi":"10.3103/s1068373923120099","DOIUrl":"https://doi.org/10.3103/s1068373923120099","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Rainfall-runoff modeling plays a crucial role in determining the regular water balance. Modifications in land use and land cover (LULC) significantly impact on the hydrological response of watersheds. The study aims to analyze the effect of land use change on river runoff with the use of hydrological modeling in the Wadi Ouahrane watershed in northwestern Algeria. The study was conducted for the period from 1987 to 2017. According to the LULC change study, cultivated land and built-up areas have increased, whereas forest and grassland areas have decreased. Sensitivity evaluation has shown that the CN (curve number) is the most important factor affecting the watershed hydrology. The Nash–Sutcliffe (NSE) and <span>(R^{2})</span> efficiency values for the Wadi Ouahrane watershed were 0.76–0.82 and 0.86–0.91 for the calibration period and 0.72–0.74 and 0.81–0.83 for the validation one, respectively. The assessment of the HEC-HMS response to the LULC change showed that the peak discharge for 2017 increased by 68% relative to the 1987 peak discharge. This research has improved the knowledge of the relationship between land use change and hydrological regimes in the Wadi Ouahrane watershed.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3103/s1068373923120105
R. Buragohain, H. Medhi, B. Kh. Narzary, K. U. Ahamad
Abstract
In time-series analysis, several non-parametric and parametric techniques are available to identify a trend. However, due to the lesser sensitivity of the non-parametric methods towards the outliers, they are often given priority over parametric methods for analysing the trend. In this study, the significance of the trend in the rainfall data of the four cities: Guwahati, Tezpur, North Lakhimpur, and Dibrugarh in Assam is examined using the non-parametric Mann–Kendall method. The non-parametric Sen’s estimator method is used to estimate the magnitude of the significant trends for the four cities. The rainfall trend has been studied based on monthly, yearly, and seasonal observations. The results clearly show that there is no trend in the cities except for Dibrugarh, where an increasing rainfall trend is observed within 5% significance level. Based on the seasonal rainfall analysis, it is noted that the pre- and post-monsoon precipitation has a significant increasing trend, while no trend is seen during the monsoon period, which indicates an absence of significant change in the rainfall magnitude during the monsoon for the study period. The analysis of the monthly rainfall data has reveal a significant trend for July in the cities of Guwahati and Tezpur, which are closely located, while the significant trend for May is seen in the city of North Lakhimpur. However, for Dibrugarh, all months have shown significant trends at 5% except for September, November, and December. The analysis has shown that there is a significant change in the rainfall trend for the non-monsoon period, indicating the change in the rainfall pattern, while the overall trend for the monsoon period remains the same. This change of rainfall pattern during the non-monsoon period may be an impact of the climate change, which requires detailed studies. The overall analysis for the four sites over the period under review has shown a significant trend in rainfall only for Dibrugarh.
{"title":"Identification of Rainfall Trends over Four Cities of Assam, India","authors":"R. Buragohain, H. Medhi, B. Kh. Narzary, K. U. Ahamad","doi":"10.3103/s1068373923120105","DOIUrl":"https://doi.org/10.3103/s1068373923120105","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>In time-series analysis, several non-parametric and parametric techniques are available to identify a trend. However, due to the lesser sensitivity of the non-parametric methods towards the outliers, they are often given priority over parametric methods for analysing the trend. In this study, the significance of the trend in the rainfall data of the four cities: Guwahati, Tezpur, North Lakhimpur, and Dibrugarh in Assam is examined using the non-parametric Mann–Kendall method. The non-parametric Sen’s estimator method is used to estimate the magnitude of the significant trends for the four cities. The rainfall trend has been studied based on monthly, yearly, and seasonal observations. The results clearly show that there is no trend in the cities except for Dibrugarh, where an increasing rainfall trend is observed within 5% significance level. Based on the seasonal rainfall analysis, it is noted that the pre- and post-monsoon precipitation has a significant increasing trend, while no trend is seen during the monsoon period, which indicates an absence of significant change in the rainfall magnitude during the monsoon for the study period. The analysis of the monthly rainfall data has reveal a significant trend for July in the cities of Guwahati and Tezpur, which are closely located, while the significant trend for May is seen in the city of North Lakhimpur. However, for Dibrugarh, all months have shown significant trends at 5% except for September, November, and December. The analysis has shown that there is a significant change in the rainfall trend for the non-monsoon period, indicating the change in the rainfall pattern, while the overall trend for the monsoon period remains the same. This change of rainfall pattern during the non-monsoon period may be an impact of the climate change, which requires detailed studies. The overall analysis for the four sites over the period under review has shown a significant trend in rainfall only for Dibrugarh.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3103/s1068373923120075
A. G. Georgiadi, I. P. Milyukova
Abstract
The results of studying long-term (lasting 10–15 years or more) phases of decreased and increased conditionally natural annual and seasonal runoff of the Don River near the village of Razdorskaya and the Lena River near the village of Kyusyur are considered. The retrieval of long-term water flow time series (excluding the changes that are caused by anthropogenic impacts from the observed water flow) is based on the transformation of the annual hydrograph of average daily water flow using the Kalinin–Milyukov method. The long-term phases of annual and seasonal runoff have been identified on the basis of cumulative deviation curves and criteria for statistical homogeneity of time series by their averages. For the entire period of observations on the Don (1891–2019) and the Lena (1936–2019), two cardinally different types of long-term dynamics for contrasting phases of annual and seasonal runoff that are characteristic of these rivers and common in most of Russia have been revealed. On the Lena, the phases of decreased and increased values of annual and seasonal runoff have changed quasisynchronously, whereas on the Don, the phases of annual runoff and snow melt flood runoff on the one hand and summer-autumn and winter runoff on the other hand have changed asynchronously. The main characteristics of the contrast phases have been determined.
{"title":"Peculiarities of Long-term Phases of the Increased and Decreased Don and Lena Runoff in the 19th–21st Centuries","authors":"A. G. Georgiadi, I. P. Milyukova","doi":"10.3103/s1068373923120075","DOIUrl":"https://doi.org/10.3103/s1068373923120075","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The results of studying long-term (lasting 10–15 years or more) phases of decreased and increased conditionally natural annual and seasonal runoff of the Don River near the village of Razdorskaya and the Lena River near the village of Kyusyur are considered. The retrieval of long-term water flow time series (excluding the changes that are caused by anthropogenic impacts from the observed water flow) is based on the transformation of the annual hydrograph of average daily water flow using the Kalinin–Milyukov method. The long-term phases of annual and seasonal runoff have been identified on the basis of cumulative deviation curves and criteria for statistical homogeneity of time series by their averages. For the entire period of observations on the Don (1891–2019) and the Lena (1936–2019), two cardinally different types of long-term dynamics for contrasting phases of annual and seasonal runoff that are characteristic of these rivers and common in most of Russia have been revealed. On the Lena, the phases of decreased and increased values of annual and seasonal runoff have changed quasisynchronously, whereas on the Don, the phases of annual runoff and snow melt flood runoff on the one hand and summer-autumn and winter runoff on the other hand have changed asynchronously. The main characteristics of the contrast phases have been determined.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3103/s1068373923120051
A. N. Bugaets, S. Yu. Lupakov, L. V. Gonchukov, O. V. Sokolov, N. Yu. Sidorenko
Abstract
Experience of using meteorological observations and the ERA5 reanalysis for runoff modeling using the GR4J conceptual model is outlined. The study objects are catchments within the Ussuri River basin (Kirovskii, the Russian Far East). The results of the comparison of ground-based observations and reanalysis data are presented. The hydrological model has been calibrated and verified on the basis of various data sources. The traditional scores NSE, logNSE, and BIAS have been used to evaluate the modeling efficiency. According to the scores, the modeling efficiency is generally "satisfactory" and better. It is shown that for simulations, it is better to use observation network data in case of floods and the reanalysis data in case of spring high water and low flow periods. It is concluded that the effective resolution of the ERA5 data for daily precipitation and air temperature for hydrological modeling in the study area is (0.75^circ{-}1.0^circ) ((sim)90–120 km).
{"title":"Runoff Modeling Efficiency for the Upper Ussuri Basin Using Observational Data and the ERA5 Reanalysis","authors":"A. N. Bugaets, S. Yu. Lupakov, L. V. Gonchukov, O. V. Sokolov, N. Yu. Sidorenko","doi":"10.3103/s1068373923120051","DOIUrl":"https://doi.org/10.3103/s1068373923120051","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Experience of using meteorological observations and the ERA5 reanalysis for runoff modeling using the GR4J conceptual model is outlined. The study objects are catchments within the Ussuri River basin (Kirovskii, the Russian Far East). The results of the comparison of ground-based observations and reanalysis data are presented. The hydrological model has been calibrated and verified on the basis of various data sources. The traditional scores NSE, logNSE, and BIAS have been used to evaluate the modeling efficiency. According to the scores, the modeling efficiency is generally \"satisfactory\" and better. It is shown that for simulations, it is better to use observation network data in case of floods and the reanalysis data in case of spring high water and low flow periods. It is concluded that the effective resolution of the ERA5 data for daily precipitation and air temperature for hydrological modeling in the study area is <span>(0.75^circ{-}1.0^circ)</span> (<span>(sim)</span>90–120 km).</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3103/s106837392312004x
D. A. Migunov, P. N. Terskii, O. V. Gorelits, E. L. Ratkovich
Abstract
The Volga delta is a large, dynamically changing water object. Its regime is determined by both natural water balance components and artificial streamflow regulation by the Volga hydroelectric power plant. The paper provides a brief overview of the studies of the Volga delta delta water regime and runoff distribution among the Volga delta branches, including those dealing with the runoff parametrization and computation. It also discusses the works on modeling the runoff distribution. The HEC-RAS software has been used to develop a one-dimensional hydrodynamic model of the Volga delta from its top (the Volga/Verkhnelebyazh’e gauging station) to the Astrakhan–Krasnyi Yar gauge line. The model calibration has been performed using in situ measurements in the delta in 2019 and network gauging data, the validation has been carried out based on the network gauging data for 2015, 2017, and 2018. Modeling results have shown that the contribution of runoff flowing to the Buzan branch source has slightly increased as compared to the period of 2001–2012.
{"title":"Current River Runoff Distribution in the Volga Delta: Analysis and Modeling","authors":"D. A. Migunov, P. N. Terskii, O. V. Gorelits, E. L. Ratkovich","doi":"10.3103/s106837392312004x","DOIUrl":"https://doi.org/10.3103/s106837392312004x","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The Volga delta is a large, dynamically changing water object. Its regime is determined by both natural water balance components and artificial streamflow regulation by the Volga hydroelectric power plant. The paper provides a brief overview of the studies of the Volga delta delta water regime and runoff distribution among the Volga delta branches, including those dealing with the runoff parametrization and computation. It also discusses the works on modeling the runoff distribution. The HEC-RAS software has been used to develop a one-dimensional hydrodynamic model of the Volga delta from its top (the Volga/Verkhnelebyazh’e gauging station) to the Astrakhan–Krasnyi Yar gauge line. The model calibration has been performed using in situ measurements in the delta in 2019 and network gauging data, the validation has been carried out based on the network gauging data for 2015, 2017, and 2018. Modeling results have shown that the contribution of runoff flowing to the Buzan branch source has slightly increased as compared to the period of 2001–2012.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3103/s1068373923120026
N. K. Semenova, Yu. A. Simonov, A. V. Khristoforov
Abstract
The possibility of extended predictions of the Russian river streamflow is considered based on dynamic approach, in which the HBV-96 water-balance runoff formation model is used jointly with the extended ensemble meteorological forecast obtained with the INM5 model. Twelve river basins located in different climatic and physiographic zones of Russia were selected for analysis. The average annual and average monthly discharges, as well as the annual maximum streamflow, were predicted with a lead time of 1–5 years. The test on the reanalysis data for the period from 1980 to 2020 has shown that the applied dynamic approach makes it possible to adequately assess possible interannual fluctuations in the streamflow and its intraannual distribution. The ensemble of forecasts of the annual and maximum streamflow for the period 2023–2026 obtained using the HBV-96 and INM5 models is consistent with the data on the water regime of the analyzed rivers.
{"title":"Extended Streamflow Prediction for Russian Rivers","authors":"N. K. Semenova, Yu. A. Simonov, A. V. Khristoforov","doi":"10.3103/s1068373923120026","DOIUrl":"https://doi.org/10.3103/s1068373923120026","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The possibility of extended predictions of the Russian river streamflow is considered based on dynamic approach, in which the HBV-96 water-balance runoff formation model is used jointly with the extended ensemble meteorological forecast obtained with the INM5 model. Twelve river basins located in different climatic and physiographic zones of Russia were selected for analysis. The average annual and average monthly discharges, as well as the annual maximum streamflow, were predicted with a lead time of 1–5 years. The test on the reanalysis data for the period from 1980 to 2020 has shown that the applied dynamic approach makes it possible to adequately assess possible interannual fluctuations in the streamflow and its intraannual distribution. The ensemble of forecasts of the annual and maximum streamflow for the period 2023–2026 obtained using the HBV-96 and INM5 models is consistent with the data on the water regime of the analyzed rivers.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3103/s1068373923120063
M. V. Georgievskii, A. V. Babkin, N. I. Goroshkova, A. V. Strizhenok, D. A. Semenova
Abstract
The paper presents the analysis, modeling, and forecasting of the time series of the ice jam peak water level of the Sukhona River near Veliky Ustyug, taking into account the predictors selected by the multiple regression technique. A methodology based on the multiple regression that uses the results of modeling by the method developed by V.A. Buzin as a separate predictor is proposed. This approach has improved the forecast skill and forecast results. The observed and predicted values are significantly correlated.
{"title":"Forecasting Ice Jam Peak Levels of the Sukhona River near Veliky Ustyug","authors":"M. V. Georgievskii, A. V. Babkin, N. I. Goroshkova, A. V. Strizhenok, D. A. Semenova","doi":"10.3103/s1068373923120063","DOIUrl":"https://doi.org/10.3103/s1068373923120063","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper presents the analysis, modeling, and forecasting of the time series of the ice jam peak water level of the Sukhona River near Veliky Ustyug, taking into account the predictors selected by the multiple regression technique. A methodology based on the multiple regression that uses the results of modeling by the method developed by V.A. Buzin as a separate predictor is proposed. This approach has improved the forecast skill and forecast results. The observed and predicted values are significantly correlated.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3103/s1068373923120038
S. A. Lavrov
Abstract
The paper presents a physically based mathematical model of the key hydrophysical processes of runoff formation at a catchment point over a long-term period. The model describes the freezing and thawing of soil, the formation and melting of the snow cover, the migration of moisture to the freezing front and the infiltration of rain and melt moisture, evaporation from snow, soil cover, vegetation, and water surface. Average daily values of meteorological parameters are used as initial information for mathematical modeling. The relevance of the study is caused by a need to reveal the main links between the processes of vertical heat and moisture exchange in soil and the environmental factors that determine their climate-driven nature. Using observational data from water balance stations, numerical experiments and an analysis of the influence of long-term variability of the key meteorological factors on evaporation from the land and water surface and on vertical moisture flows in soil were carried out.
{"title":"A Physically Based Mathematical Model of Hydrophysical Processes of Runoff Formation during a Climatic Year: The GGI-Gidrofizika Model","authors":"S. A. Lavrov","doi":"10.3103/s1068373923120038","DOIUrl":"https://doi.org/10.3103/s1068373923120038","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper presents a physically based mathematical model of the key hydrophysical processes of runoff formation at a catchment point over a long-term period. The model describes the freezing and thawing of soil, the formation and melting of the snow cover, the migration of moisture to the freezing front and the infiltration of rain and melt moisture, evaporation from snow, soil cover, vegetation, and water surface. Average daily values of meteorological parameters are used as initial information for mathematical modeling. The relevance of the study is caused by a need to reveal the main links between the processes of vertical heat and moisture exchange in soil and the environmental factors that determine their climate-driven nature. Using observational data from water balance stations, numerical experiments and an analysis of the influence of long-term variability of the key meteorological factors on evaporation from the land and water surface and on vertical moisture flows in soil were carried out.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139755533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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