Hydrology Research最新文献

Video velocity measurement: A two-stage flow velocity prediction method based on deep learning 视频流速测量：基于深度学习的两阶段流速预测方法

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2024-05-01 DOI: 10.2166/nh.2024.128

Xiaolong Wang, Qiang Ma, Genyi Wang, Guocheng An

{"title":"Video velocity measurement: A two-stage flow velocity prediction method based on deep learning","authors":"Xiaolong Wang, Qiang Ma, Genyi Wang, Guocheng An","doi":"10.2166/nh.2024.128","DOIUrl":"https://doi.org/10.2166/nh.2024.128","url":null,"abstract":"Due to the uncertainty in output caused by environmental changes, significant discrepancies are expected between the surface flow velocities predicted using deep learning methods and the instantaneous flow velocities. In this paper, a two-stage deep learning flow velocity measurement algorithm is proposed. During the external calibration process, the upper and lower frames of the recorded water flow video are cyclically traversed to acquire predicted flow velocity values using the deep learning velocity measurement algorithm. Meanwhile, the pixel displacement is obtained using the sparse optical flow tracking method and then post-processed to derive the velocity calibration value and pixel calibration value. During the detection process, the deep learning-predicted flow velocity is internally calibrated using the velocity calibration value and the pixel calibration value to adapt to changes in water flows. Compared with the pre-improved algorithm, the method achieves the minimum root mean square error in five different flow velocity videos and maintains high accuracy when the flow velocity changes rapidly. The obtained results are very promising and can help improve the reliability of video flow rate assessment algorithms.","PeriodicalId":13096,"journal":{"name":"Hydrology Research","volume":"47 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141191550","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}

引用次数: 0

Evaluation of water shortage and instream flows of shared rivers in South Korea according to the dam operations in North Korea 根据北朝鲜大坝运行情况评估南朝鲜共有河流的缺水情况和内流流量

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2024-05-01 DOI: 10.2166/nh.2024.145

Jae-Kyoung Lee, Suk Hwan Jang

引用次数: 0

An approach for flood flow prediction utilizing new hybrids of ANFIS with several optimization techniques: a case study 利用 ANFIS 与若干优化技术的新混合体进行洪水流量预测的方法：案例研究

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2024-05-01 DOI: 10.2166/nh.2024.191

Negin Ahmadi, Sina Fard Moradinia

{"title":"An approach for flood flow prediction utilizing new hybrids of ANFIS with several optimization techniques: a case study","authors":"Negin Ahmadi, Sina Fard Moradinia","doi":"10.2166/nh.2024.191","DOIUrl":"https://doi.org/10.2166/nh.2024.191","url":null,"abstract":"Using machine learning methods is efficient in predicting floods in areas where complete data is not available. Therefore, this study considers the Adaptive Neuro-Fuzzy Inference System (ANFIS) model combined with evolutionary algorithms, namely Harris Hawks Optimization (HHO) and Arithmetic Optimization Algorithm (AOA), to predict the flood of Shahrchay River in the northwest of Iran. The data used included the daily data of precipitation, evaporation, and runoff in the years 2016 and 2017, where 70% of the data were used for model training and the rest for testing the models. The results showed that although the ANFIS model provided values with high errors in several steps, especially in steps with maximum or minimum values, the use of HHO and AOA optimization algorithms resulted in a significant reduction in the error values. The ANFIS-AOA model utilizing an input scenario including the flow in the previous one to three days exerted the most promising results in the test data, with Nash Sutcliffe Efficiency (NSE) Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) of 0.93, 1.34, and 0.69, respectively. According to Taylor's diagram, the ANFIS-AOA hybrid algorithm predicts flood values with greater performance than the other models.","PeriodicalId":13096,"journal":{"name":"Hydrology Research","volume":"84 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141191926","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}

引用次数: 0

Attribution discernment of climate change and human interventions to runoff decline in Huangshui River Basin, China 气候变化和人为干预对中国湟水流域径流减少的归因分析

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2024-03-01 DOI: 10.2166/nh.2024.130

Pengquan Wang, Runjie Li, Shengkui Cao

引用次数: 0

Identification of hydrologically homogenous watersheds and climate-vegetation dynamics in the Blue Nile Basin of Ethiopia 埃塞俄比亚青尼罗河流域水文同源流域的确定和气候-植被动态变化

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2024-03-01 DOI: 10.2166/nh.2024.098

Temesgen Tsehayeneh Mihret, Fasikaw A. Zemale, Abeyou W. Worqlul, Ayenew D. Ayalew, Nicola Fohrer

引用次数: 0

Analysis of scaling relationships for flood parameters and peak discharge estimation in a tropical region 热带地区洪水参数的比例关系分析和洪峰流量估算

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2024-02-01 DOI: 10.2166/nh.2024.111

Charles Mazivanhanga, Robert C. Grabowski, Eunice Pérez-Sánchez, Victor R. Carballo-Cruz

{"title":"Analysis of scaling relationships for flood parameters and peak discharge estimation in a tropical region","authors":"Charles Mazivanhanga, Robert C. Grabowski, Eunice Pérez-Sánchez, Victor R. Carballo-Cruz","doi":"10.2166/nh.2024.111","DOIUrl":"https://doi.org/10.2166/nh.2024.111","url":null,"abstract":"Relationships between peak discharges and catchment size (e.g., flood scaling) in a catchment have the potential to support new river flood forecasting approaches but have not been tested in tropical regions. This study determined flood scaling relationships between peak discharge and nested drainage areas in the La Sierra catchment (Mexico). A statistical power law equation was applied to selected rainfall–runoff events that occurred between 2012 and 2015. Variations in flood scaling parameters were determined in relation to catchment descriptors and processes for peak downstream discharge estimation. Similar to studies in humid temperate regions, the results reveal the existence of log-linear relationships between the intercept (α) and exponent (θ) parameter values and the log–log power–law relationships between (α) and the peak discharge observed from the smallest headwater catchments. The flood parameter values obtained were then factored into the scaling equation (QP = αAθ) and successfully predicted downstream flood peaks, especially highly recurrent flood events. The findings contribute to a better understanding of the nature of flood wave generation and support the development of new flood forecasting approaches in unregulated catchments suitable for non-stationarity in hydrological processes with climate change.","PeriodicalId":13096,"journal":{"name":"Hydrology Research","volume":"170 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140002263","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}

引用次数: 0

Effect of mountainous rainfall on uncertainty in flood model parameter estimation 山区降雨对洪水模型参数估计不确定性的影响

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2024-02-01 DOI: 10.2166/nh.2024.144

Jeonghoon Lee, Jeonghyeon Choi, Suhyung Jang, Sangdan Kim

引用次数: 0

Corrigendum: Hydrology Research 52 (6), 1357–1371: Sampling uncertainty of UK design flood estimation, Anthony Hammond, https://dx.doi.org/10.2166/nh.2021.059 更正：水文学研究 52 (6)，1357-1371：英国设计洪水估算的取样不确定性，Anthony Hammond，https://dx.doi.org/10.2166/nh.2021.059

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2024-02-01 DOI: 10.2166/nh.2024.001

引用次数: 0

A review on sources of uncertainties for groundwater recharge estimates; insight to data Scares Tropical, Arid, and Semiarid regions 关于地下水补给估算不确定性来源的综述；对热带、干旱和半干旱地区数据的见解

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2023-12-26 DOI: 10.2166/nh.2023.221

T. D. Beyene, F. A. Zimale, S. Gebrekristos

{"title":"A review on sources of uncertainties for groundwater recharge estimates; insight to data Scares Tropical, Arid, and Semiarid regions","authors":"T. D. Beyene, F. A. Zimale, S. Gebrekristos","doi":"10.2166/nh.2023.221","DOIUrl":"https://doi.org/10.2166/nh.2023.221","url":null,"abstract":"Successful sustainable groundwater management requires accurate information on recharge for a given aquifer system. However, recharge estimates are usually used in a relative term rather than an absolute sense. A review of available studies on groundwater recharge estimate uncertainty as well as tools for uncertainty analysis was conducted. Nonetheless, except for the handful research that have conducted proper uncertainty analysis, most studies inclined to implement multiple methods as an indication of the range of uncertainty. The global trend indicates that considering the significant number of methods for recharge estimation, very little has been done to assess the uncertainty of each method. Therefore, more focus should be given to the individual uncertainty analysis of selected methods as much as using multiple methods recommended for investigating uncertainty. Insight of the review indicates, when used carefully, that tracer-based analysis can be effective and coupling is required for uncertainty analysis. Furthermore, spatial uncertainty due to input data could be potentially minimized by using input data from multiple sources. Better conceptualization of the hydrogeological process can reduce the uncertainty of numerical modelling. This review is limited to widely used methods and excludes uncertainty due to inappropriate method implementation as well as controlled experimental uncertainties.","PeriodicalId":13096,"journal":{"name":"Hydrology Research","volume":"29 4","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139157007","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}

引用次数: 0

Assessment of ecological flow alterations induced by hydraulic engineering projects in the Han River, China 中国汉江水利工程引起的生态流量变化评估

IF 2.7 4区环境科学与生态学

Hydrology Research Pub Date : 2023-12-22 DOI: 10.2166/nh.2023.220

Lele Deng, Shenglian Guo, Jinghan Tian, Heyu Wang

{"title":"Assessment of ecological flow alterations induced by hydraulic engineering projects in the Han River, China","authors":"Lele Deng, Shenglian Guo, Jinghan Tian, Heyu Wang","doi":"10.2166/nh.2023.220","DOIUrl":"https://doi.org/10.2166/nh.2023.220","url":null,"abstract":"\u0000 \u0000 A thorough understanding of the ecological impacts behind the hydrologic alteration is still insufficient and hinders the watershed management. Here, we used eco-flow indicators, multiple hydrological indicators, and fluvial biodiversity to investigate the ecological flow in different temporal scales. The case study in the Han River shows a decrease in high flows contributed to the decrease in eco-surplus and increase in eco-deficit in summer and autumn, while the decrease in eco-deficit can be attributed to the change of low flow in spring. An integrated hydrologic alteration was over 48% degree and was under moderate ecological risk degree in impact period I, while DHRAM scores showed the Huangzhuang station faced a high ecological risk degree in impact period II. The decrease (increase) in total seasonal eco-surplus (eco-deficit) was identified after alteration with the change in seasonal eco-flow indicators contributions. Shannon index showed a decreasing trend, indicating the degradation of fluvial biodiversity in the Han River basin. Eco-flow indicators such as eco-surplus and eco-deficit are in strong relationships with 32 hydrological indicators and can be accepted for ecohydrological alterations at multiple temporal scales. This study deepens the understanding of ecological responses to hydrologic alteration, which may provide references for water resources management and ecological security maintenance.","PeriodicalId":13096,"journal":{"name":"Hydrology Research","volume":"38 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138946015","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}

引用次数: 0