Yongqiang Yin, Xiaoxiang Zhang, Zheng Guan, Yuehong Chen, Changjun Liu, Tao Yang
Flash floods are a frequent and highly destructive natural hazard in China. In order to prevent and manage these disasters, it is crucial for decision-makers to create GIS-based flash flood susceptibility maps. In this study, we present an improved Blending approach, RF-Blending (Reserve Feature Blending), which differs from the Blending approach in that it preserves the original feature dataset during meta-learner training. Our objectives were to demonstrate the performance improvement of the RF-Blending approach and to produce flash flood susceptibility maps for all catchments in Jiangxi Province using the RF-Blending approach. The Blending approach employs a double-layer structure consisting of support vector machine (SVM), K-nearest neighbor (KNN), and random forest (RF) as base learners for level-0, and the output of level-0 is utilized as the meta-feature dataset for the meta-learner in level-1, which is logistic regression (LR). RF-Blending employs the output of level-0 along with the original feature dataset for meta-learner training. To develop flood susceptibility maps, we utilized these approaches in conjunction with historical flash flood points and catchment-based factors. Our results indicate that the RF-Blending approach outperformed the other approaches. These can significantly aid catchment-based flash flood susceptibility mapping and assist managers in controlling and remediating induced damages.
{"title":"Flash flood susceptibility mapping based on catchments using an improved Blending machine learning approach","authors":"Yongqiang Yin, Xiaoxiang Zhang, Zheng Guan, Yuehong Chen, Changjun Liu, Tao Yang","doi":"10.2166/nh.2023.139","DOIUrl":"https://doi.org/10.2166/nh.2023.139","url":null,"abstract":"\u0000 Flash floods are a frequent and highly destructive natural hazard in China. In order to prevent and manage these disasters, it is crucial for decision-makers to create GIS-based flash flood susceptibility maps. In this study, we present an improved Blending approach, RF-Blending (Reserve Feature Blending), which differs from the Blending approach in that it preserves the original feature dataset during meta-learner training. Our objectives were to demonstrate the performance improvement of the RF-Blending approach and to produce flash flood susceptibility maps for all catchments in Jiangxi Province using the RF-Blending approach. The Blending approach employs a double-layer structure consisting of support vector machine (SVM), K-nearest neighbor (KNN), and random forest (RF) as base learners for level-0, and the output of level-0 is utilized as the meta-feature dataset for the meta-learner in level-1, which is logistic regression (LR). RF-Blending employs the output of level-0 along with the original feature dataset for meta-learner training. To develop flood susceptibility maps, we utilized these approaches in conjunction with historical flash flood points and catchment-based factors. Our results indicate that the RF-Blending approach outperformed the other approaches. These can significantly aid catchment-based flash flood susceptibility mapping and assist managers in controlling and remediating induced damages.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45044901","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}
Tess O'Hara, F. McClean, Roberto Villalobos Herrera, E. Lewis, H. Fowler
This paper demonstrates the potential for crowdsourced rainfall data to infill gaps in the official rain gauge network and to provide new datasets for use in research. We use data from the Met Office Weather Observation Website (WOW) over 10 years (2011–2020) to generate two open-source datasets for Britain; multi-parameter raw data in an easy-to-use format; and an hourly rainfall dataset. We have compiled and prepared the data and detail here station selection, rain depth calculation, and data resampling to hourly intervals to create a consistent dataset for further processing (including statistical quality control) and application. Mapping the new rainfall dataset establishes that WOW observations fill spatial gaps in the official ground-based rain gauge network over Britain, particularly in urban areas. This could be particularly useful for post-event analysis of rainfall that results in pluvial flash flooding. Here, we focus on Britain but due to agreements with meteorological services in Belgium, the Netherlands, Australia, New Zealand, Sweden, and the Republic of Ireland, plus many citizen scientists globally opting to share data via WOW there is potential for the development of similar datasets using these methods around the world.
{"title":"Filling observational gaps with crowdsourced citizen science rainfall data from the Met Office Weather Observation Website","authors":"Tess O'Hara, F. McClean, Roberto Villalobos Herrera, E. Lewis, H. Fowler","doi":"10.2166/nh.2023.136","DOIUrl":"https://doi.org/10.2166/nh.2023.136","url":null,"abstract":"\u0000 This paper demonstrates the potential for crowdsourced rainfall data to infill gaps in the official rain gauge network and to provide new datasets for use in research. We use data from the Met Office Weather Observation Website (WOW) over 10 years (2011–2020) to generate two open-source datasets for Britain; multi-parameter raw data in an easy-to-use format; and an hourly rainfall dataset. We have compiled and prepared the data and detail here station selection, rain depth calculation, and data resampling to hourly intervals to create a consistent dataset for further processing (including statistical quality control) and application. Mapping the new rainfall dataset establishes that WOW observations fill spatial gaps in the official ground-based rain gauge network over Britain, particularly in urban areas. This could be particularly useful for post-event analysis of rainfall that results in pluvial flash flooding. Here, we focus on Britain but due to agreements with meteorological services in Belgium, the Netherlands, Australia, New Zealand, Sweden, and the Republic of Ireland, plus many citizen scientists globally opting to share data via WOW there is potential for the development of similar datasets using these methods around the world.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":"1 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67905885","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}
Li-Yu Daisy Liu, D. Wan, Yufeng Yu, Yangming Zhang
The grid-based Xin'anjiang model (GXM) has been widely applied to flood forecasting. However, when the model warm-up period is long and the amount of input data is large, the computational efficiency of the GXM is obviously low. Therefore, a GXM parallel algorithm based on grid flow direction division is proposed from the perspective of spatial parallelism, which realizes the parallel computing of the GXM by extracting the parallel routing sequence of the watershed grids. To solve data skew, a DAG scheduling algorithm based on dynamic priority is proposed for task scheduling. The proposed GXM parallel algorithm is verified in the Qianhe River watershed of Shaanxi Province and the Tunxi watershed of Anhui Province. The results show that the GXM parallel algorithm based on grid flow direction division has good flood forecasting accuracy and higher computational efficiency than the traditional serial computing method. In addition, the DAG scheduling algorithm can effectively improve the parallel efficiency of the GXM.
{"title":"Research and application of the parallel computing method for the grid-based Xin'anjiang model","authors":"Li-Yu Daisy Liu, D. Wan, Yufeng Yu, Yangming Zhang","doi":"10.2166/nh.2023.002","DOIUrl":"https://doi.org/10.2166/nh.2023.002","url":null,"abstract":"The grid-based Xin'anjiang model (GXM) has been widely applied to flood forecasting. However, when the model warm-up period is long and the amount of input data is large, the computational efficiency of the GXM is obviously low. Therefore, a GXM parallel algorithm based on grid flow direction division is proposed from the perspective of spatial parallelism, which realizes the parallel computing of the GXM by extracting the parallel routing sequence of the watershed grids. To solve data skew, a DAG scheduling algorithm based on dynamic priority is proposed for task scheduling. The proposed GXM parallel algorithm is verified in the Qianhe River watershed of Shaanxi Province and the Tunxi watershed of Anhui Province. The results show that the GXM parallel algorithm based on grid flow direction division has good flood forecasting accuracy and higher computational efficiency than the traditional serial computing method. In addition, the DAG scheduling algorithm can effectively improve the parallel efficiency of the GXM.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43497005","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}
Yanyu Dai, Fan Lu, B. Ruan, Xinyi Song, Yu Du, Yiran Xu
Quantitative differentiation of climate and human activities on runoff is important for water resources management and future water resources trend prediction. In recent years, runoff in the middle reaches of the Yellow River (MRYR) has decreased dramatically. Many studies have analyzed the causes of runoff reduction, but there is still a lack of understanding of the spatial differences in runoff contributions and their causes. Therefore, this study quantitatively distinguishes the contributions of climate and human activities to runoff changes in nine sub-basins of the MRYR based on the Budyko framework and analyses the differences in the contributions of different basins and their causes. The results show that the runoff in the nine sub-basins decreases significantly and the precipitation increases from northwest to southeast. The contribution of human activities to runoff is greater than that of climate change, especially in the Huangfuchuan (HF) River and Kuye (KY) River basins, where the contribution of human activities to runoff exceeds 90%. The greater impact of human activities in HF River and KY River is due to the significantly higher water use growth rate and normalized vegetation index trends than in other areas.
{"title":"Decomposition of contribution to runoff changes and spatial differences of major tributaries in the middle reaches of the Yellow River based on the Budyko framework","authors":"Yanyu Dai, Fan Lu, B. Ruan, Xinyi Song, Yu Du, Yiran Xu","doi":"10.2166/nh.2023.061","DOIUrl":"https://doi.org/10.2166/nh.2023.061","url":null,"abstract":"\u0000 Quantitative differentiation of climate and human activities on runoff is important for water resources management and future water resources trend prediction. In recent years, runoff in the middle reaches of the Yellow River (MRYR) has decreased dramatically. Many studies have analyzed the causes of runoff reduction, but there is still a lack of understanding of the spatial differences in runoff contributions and their causes. Therefore, this study quantitatively distinguishes the contributions of climate and human activities to runoff changes in nine sub-basins of the MRYR based on the Budyko framework and analyses the differences in the contributions of different basins and their causes. The results show that the runoff in the nine sub-basins decreases significantly and the precipitation increases from northwest to southeast. The contribution of human activities to runoff is greater than that of climate change, especially in the Huangfuchuan (HF) River and Kuye (KY) River basins, where the contribution of human activities to runoff exceeds 90%. The greater impact of human activities in HF River and KY River is due to the significantly higher water use growth rate and normalized vegetation index trends than in other areas.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45229611","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}
Yishuang Zhou, Xiaoxia Tong, R. Gan, Panfeng Liu, Lin Guo, Shan-shan Zhao
A clear understanding of the spatial and temporal distribution characteristics of water resources is essential for the optimal allocation and sustainable utilization of water resources. In this paper, the spatial and temporal distribution characteristics of water resources in Henan Province were studied based on GIS, combining the Mann-Kendall (M-K) nonparametric test and rescaled range (R/S) analysis. In addition, SPSS software was used to analyze the influence of climate and land use type on water resources. The results indicated that (1) the hot spots of water resources were concentrated in the southwest, while the low values were concentrated in the northeast, and the distribution of water resources decreased from southwest to northeast. (2) In the past 21 years, spatiotemporal mutations in the water resource sequence occurred between 2010 and 2014. The Z-values of the M-K trend test were all less than 0, the H-values of groundwater resources (GWRs) were mostly greater than 0.5, and the h-values of surface water resources (SWRs) and total water resources (TWRs) were less than 0.5, showing an overall declining trend. However, this trend may change in the future. (3) From the correlation analysis, climate change had a greater impact on water resources than land use changes did.
{"title":"Distribution characteristics and influencing factors of water resources in Henan Province","authors":"Yishuang Zhou, Xiaoxia Tong, R. Gan, Panfeng Liu, Lin Guo, Shan-shan Zhao","doi":"10.2166/nh.2023.096","DOIUrl":"https://doi.org/10.2166/nh.2023.096","url":null,"abstract":"\u0000 A clear understanding of the spatial and temporal distribution characteristics of water resources is essential for the optimal allocation and sustainable utilization of water resources. In this paper, the spatial and temporal distribution characteristics of water resources in Henan Province were studied based on GIS, combining the Mann-Kendall (M-K) nonparametric test and rescaled range (R/S) analysis. In addition, SPSS software was used to analyze the influence of climate and land use type on water resources. The results indicated that (1) the hot spots of water resources were concentrated in the southwest, while the low values were concentrated in the northeast, and the distribution of water resources decreased from southwest to northeast. (2) In the past 21 years, spatiotemporal mutations in the water resource sequence occurred between 2010 and 2014. The Z-values of the M-K trend test were all less than 0, the H-values of groundwater resources (GWRs) were mostly greater than 0.5, and the h-values of surface water resources (SWRs) and total water resources (TWRs) were less than 0.5, showing an overall declining trend. However, this trend may change in the future. (3) From the correlation analysis, climate change had a greater impact on water resources than land use changes did.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47237525","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}
Xuyang Qi, Shuni Qian, Kebing Chen, Jun Li, Xushu Wu, Zhaoli Wang, Zi‐Wang Deng, Jie Jiang
Rainfall and wind speed are two important meteorological variables that have a significant impact on agriculture, human health, and socio-economic development. While individual rainfall or wind events have been widely studied, little attention has been devoted to study the lead–lag relationship between rainfall and wind speed, particularly in coastal regions where strong dependence between rainfall and wind speed is expected. Taking China's coastline as the case study, this paper aims to explore the variation trends of wind speed and rainfall and reveal the relationships between rainfall events and wind speeds on days before and after rainfall occurrence, by using meteorological station data from 1960 to 2018. The results show that wind speed trended to decrease while rainfall showed a slight increase for most stations. The daily wind speed increased 2 days before rainfall occurrence and decreased after then, with the highest wind speed observed during rainfall onset regardless of rainfall amount. Moreover, heavier rainfall events are more likely to occur with higher wind speeds. The findings of this study potentially improve the understanding of the dependence of rainfall and wind speed, which could help rainfall or wind-related disaster mitigation.
{"title":"Dependence of daily precipitation and wind speed over coastal areas: evidence from China's coastline","authors":"Xuyang Qi, Shuni Qian, Kebing Chen, Jun Li, Xushu Wu, Zhaoli Wang, Zi‐Wang Deng, Jie Jiang","doi":"10.2166/nh.2023.093","DOIUrl":"https://doi.org/10.2166/nh.2023.093","url":null,"abstract":"\u0000 Rainfall and wind speed are two important meteorological variables that have a significant impact on agriculture, human health, and socio-economic development. While individual rainfall or wind events have been widely studied, little attention has been devoted to study the lead–lag relationship between rainfall and wind speed, particularly in coastal regions where strong dependence between rainfall and wind speed is expected. Taking China's coastline as the case study, this paper aims to explore the variation trends of wind speed and rainfall and reveal the relationships between rainfall events and wind speeds on days before and after rainfall occurrence, by using meteorological station data from 1960 to 2018. The results show that wind speed trended to decrease while rainfall showed a slight increase for most stations. The daily wind speed increased 2 days before rainfall occurrence and decreased after then, with the highest wind speed observed during rainfall onset regardless of rainfall amount. Moreover, heavier rainfall events are more likely to occur with higher wind speeds. The findings of this study potentially improve the understanding of the dependence of rainfall and wind speed, which could help rainfall or wind-related disaster mitigation.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41905263","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}
Haijie Wang, P. Jiang, Rongrong Zhang, Jiahui Zhao, W. Si, Yong Fang, Nana Zhang
Changes in precipitation storm characteristics especially extreme precipitation events have been frequently reported during recent years, which poses great challenges for flood controls of reservoir basins. In this study, we present a comprehensive examination on the evolution of storm properties during two distinct rainy seasons in Changtan Reservoir Basin located on the southeastern coast of China. We compare the differences in storm duration, inter-storm period, the average storm intensity, and with-in storm pattern between the Meiyu flood season (MFS) and typhoon flood season (TFS). We also explore the future projections of these storm properties based on Coupled Model Inter-comparison Project 6 (CMIP6) precipitation outputs. Our results indicate that precipitation storms in TFS exhibit shorter duration and higher average storm intensity than those of MFS, the flood risk in June is mainly due to accumulative precipitation (longer duration), while in July to September, is mainly due to the storms with high intensity. The projected precipitation shows uncertainties for different emission scenarios, especially during TFS. However, the increasing trend of the average storm intensity is relatively consistent, which is supposed to bring more pressure on flood control in the study area. The results can provide a beneficial reference to water resources management.
{"title":"The changing precipitation storm properties under future climate change","authors":"Haijie Wang, P. Jiang, Rongrong Zhang, Jiahui Zhao, W. Si, Yong Fang, Nana Zhang","doi":"10.2166/nh.2023.142","DOIUrl":"https://doi.org/10.2166/nh.2023.142","url":null,"abstract":"\u0000 Changes in precipitation storm characteristics especially extreme precipitation events have been frequently reported during recent years, which poses great challenges for flood controls of reservoir basins. In this study, we present a comprehensive examination on the evolution of storm properties during two distinct rainy seasons in Changtan Reservoir Basin located on the southeastern coast of China. We compare the differences in storm duration, inter-storm period, the average storm intensity, and with-in storm pattern between the Meiyu flood season (MFS) and typhoon flood season (TFS). We also explore the future projections of these storm properties based on Coupled Model Inter-comparison Project 6 (CMIP6) precipitation outputs. Our results indicate that precipitation storms in TFS exhibit shorter duration and higher average storm intensity than those of MFS, the flood risk in June is mainly due to accumulative precipitation (longer duration), while in July to September, is mainly due to the storms with high intensity. The projected precipitation shows uncertainties for different emission scenarios, especially during TFS. However, the increasing trend of the average storm intensity is relatively consistent, which is supposed to bring more pressure on flood control in the study area. The results can provide a beneficial reference to water resources management.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41965032","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 relationship between water resources and the social economy has become a restricting factor for the sustainable development of cities around the world. Based on the urban development demand and water resources condition of Linhai City in eastern China, which has the fastest economic growth and population boom, the system dynamics model of water resources carrying capacity was established to analyze the interaction between society, economy and water resources. According to the different development emphases, six different modes of water resource utilization were designed. Taking total population, GDP, industrial output value, tertiary industry output value, water consumption, water supply and sewage discharge as the measurement indexes, the research predicted the development status of water resources carrying capacity of Linhai City from 2015 to 2030 under different development modes. Through the simulation results, it is found that the water-saving measures can reduce the gap between water supply and demand only in a short term. In the long run, the adjustment of industrial structure can improve the water resources carrying capacity and simultaneously promote the economy. In addition, increasing the water income sources as well as strengthening sewage treatment are also necessary to balance the water supply and demand.
{"title":"Research on the urban water resources carrying capacity by using system dynamics simulation","authors":"Xing Chen, Qin Xu, Jing Cai","doi":"10.2166/nh.2023.101","DOIUrl":"https://doi.org/10.2166/nh.2023.101","url":null,"abstract":"\u0000 The relationship between water resources and the social economy has become a restricting factor for the sustainable development of cities around the world. Based on the urban development demand and water resources condition of Linhai City in eastern China, which has the fastest economic growth and population boom, the system dynamics model of water resources carrying capacity was established to analyze the interaction between society, economy and water resources. According to the different development emphases, six different modes of water resource utilization were designed. Taking total population, GDP, industrial output value, tertiary industry output value, water consumption, water supply and sewage discharge as the measurement indexes, the research predicted the development status of water resources carrying capacity of Linhai City from 2015 to 2030 under different development modes. Through the simulation results, it is found that the water-saving measures can reduce the gap between water supply and demand only in a short term. In the long run, the adjustment of industrial structure can improve the water resources carrying capacity and simultaneously promote the economy. In addition, increasing the water income sources as well as strengthening sewage treatment are also necessary to balance the water supply and demand.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46320890","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}
Data scarcity in many areas around the world represents a major problem for hydrological model calibrations. Global parameter estimates and global forcing can provide possibilities to access hydrological responses in ungauged regions. In this study, we applied HBV global parameter estimates considering uncertainty in the Upper Neckar and Upper Danube catchments, Germany to answer what are the influencing factors and how good are their local applications. We tested simulations with precipitation in spatial resolutions from 0.05° to 0.2° and with local/global sources. Results show that the general performance is acceptable to good (Kling-Gupta efficiency, KGE: 0.51–0.79) in both catchments using local or global precipitation. The influence of spatial resolutions is insignificant while using local precipitation slightly increases performance in both catchments. Catchment properties such as complex topography and special karst subsurface may lead to a deterioration of performance by 0.2 of median KGE in the Upper Danube compared with the Upper Neckar catchment. The median correlation coefficient, runoff ratio and relative error suggest that using global parameter estimates can reproduce seasonality and long-term water balance in our studied region. Our study highlights the potential of using global parameter estimates and global forcing in ungauged areas.
{"title":"Global hydrological parameter estimates to local applications: influence of forcing and catchment properties","authors":"Jasper Schalla, A. Hartmann, T. Abraham, Y. Liu","doi":"10.2166/nh.2023.086","DOIUrl":"https://doi.org/10.2166/nh.2023.086","url":null,"abstract":"\u0000 Data scarcity in many areas around the world represents a major problem for hydrological model calibrations. Global parameter estimates and global forcing can provide possibilities to access hydrological responses in ungauged regions. In this study, we applied HBV global parameter estimates considering uncertainty in the Upper Neckar and Upper Danube catchments, Germany to answer what are the influencing factors and how good are their local applications. We tested simulations with precipitation in spatial resolutions from 0.05° to 0.2° and with local/global sources. Results show that the general performance is acceptable to good (Kling-Gupta efficiency, KGE: 0.51–0.79) in both catchments using local or global precipitation. The influence of spatial resolutions is insignificant while using local precipitation slightly increases performance in both catchments. Catchment properties such as complex topography and special karst subsurface may lead to a deterioration of performance by 0.2 of median KGE in the Upper Danube compared with the Upper Neckar catchment. The median correlation coefficient, runoff ratio and relative error suggest that using global parameter estimates can reproduce seasonality and long-term water balance in our studied region. Our study highlights the potential of using global parameter estimates and global forcing in ungauged areas.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46638132","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}
This work presents a novel, spatially distributed, GIS-based application of Benfratello's conceptual method to estimate the climatic water deficit and the irrigation deficit at the field and basin scales. Explicit analytical relationships are obtained to define the deficit uncertainty on the basis of the interannual variability of temperature and precipitation. With this model, we aim at proposing a rather simple and effective tool to deal with the complicated issues of assessing the soil water balance, determining the irrigation deficit and managing the water resources in semiarid agricultural environments, in the context of climatic, land-use and anthropogenic changes. In order to test this new application, the model was applied to estimate the irrigation deficit of the Bonifica della Capitanata consortium in the Apulia region, one of the most important agricultural districts in Southern Italy and in the whole Mediterranean area, in four different historical land-use scenarios. The first results of the application seem encouraging, as by using a limited amount of parameters we estimated an irrigation demand which is in agreement with the irrigation volumes erogated by the consortium. The different land-use cases are discussed in the light of an application of the Budyko curve.
这项工作提出了一种新颖的、空间分布的、基于GIS的Benfratello概念方法应用，以估计农田和流域尺度的气候缺水和灌溉缺水。在温度和降水年际变化的基础上，得到了明确的分析关系来定义赤字的不确定性。利用该模型，我们旨在提出一种相当简单有效的工具，在气候、土地利用和人为变化的背景下，处理半干旱农业环境中评估土壤水分平衡、确定灌溉赤字和管理水资源的复杂问题。为了测试这一新应用，该模型被应用于评估阿普利亚地区Bonifica della Capitanata财团的灌溉赤字，阿普利亚是意大利南部和整个地中海地区最重要的农业区之一，在四种不同的历史土地利用情景中。该应用程序的第一个结果似乎令人鼓舞，因为通过使用有限的参数，我们估计了灌溉需求，该灌溉需求与财团批准的灌溉量一致。根据Budyko曲线的应用，讨论了不同的土地利用情况。
{"title":"Application of Benfratello's method to estimate the spatio-temporal variability of the irrigation deficit in a Mediterranean semiarid climate","authors":"M. Peli, Cesare Rapuzzi, S. Barontini, R. Ranzi","doi":"10.2166/nh.2023.081","DOIUrl":"https://doi.org/10.2166/nh.2023.081","url":null,"abstract":"\u0000 This work presents a novel, spatially distributed, GIS-based application of Benfratello's conceptual method to estimate the climatic water deficit and the irrigation deficit at the field and basin scales. Explicit analytical relationships are obtained to define the deficit uncertainty on the basis of the interannual variability of temperature and precipitation. With this model, we aim at proposing a rather simple and effective tool to deal with the complicated issues of assessing the soil water balance, determining the irrigation deficit and managing the water resources in semiarid agricultural environments, in the context of climatic, land-use and anthropogenic changes. In order to test this new application, the model was applied to estimate the irrigation deficit of the Bonifica della Capitanata consortium in the Apulia region, one of the most important agricultural districts in Southern Italy and in the whole Mediterranean area, in four different historical land-use scenarios. The first results of the application seem encouraging, as by using a limited amount of parameters we estimated an irrigation demand which is in agreement with the irrigation volumes erogated by the consortium. The different land-use cases are discussed in the light of an application of the Budyko curve.","PeriodicalId":55040,"journal":{"name":"Hydrology Research","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47235968","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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