Hydrological Research Letters最新文献

Evaluation of the temporal behavior of fulvic acid iron in Asahi River, Okayama, Japan 日本冈山朝日河中黄腐酸铁的时间行为评价

Hydrological Research Letters Pub Date : 2025-01-01 DOI: 10.3178/hrl.24-00012

Rohdof Lactem Yengeh, Hiroaki Somura, Toshitsugu Moroizumi, Yasushi Mori, Morihiro Maeda

{"title":"Evaluation of the temporal behavior of fulvic acid iron in Asahi River, Okayama, Japan","authors":"Rohdof Lactem Yengeh, Hiroaki Somura, Toshitsugu Moroizumi, Yasushi Mori, Morihiro Maeda","doi":"10.3178/hrl.24-00012","DOIUrl":"https://doi.org/10.3178/hrl.24-00012","url":null,"abstract":"Iron is essential for biogeochemical processes in aquatic ecosystems, but its riverine concentration can be affected by environmental conditions. This study assessed weekly fulvic acid iron (FAFe) concentration at a single sampling site in Asahi River from 2022–2023 to explore the differences in the temporal scales. The objectives of this study were to evaluate the effects of physicochemical properties of the river on the concentration of FAFe, analyze the concentration of FAFe in spring, summer, autumn and winter, and assess the relationship between FAFe concentration and land use types of the watershed. The results indicated that physicochemical parameters, such as pH and surface water temperature (SWT) seemed to influence FAFe concentration (p < 0.05). Hydrological dynamics influenced FAFe concentration and transport, revealing an increasing trend during spring (p < 0.001) and summer (p = 0.05), with non-significant trends during autumn and winter (p > 0.05). FAFe exhibited a strong positive correlation with total organic carbon (TOC) (p < 0.001). Upland fields significantly influenced FAFe concentration (p < 0.01) through runoff with abundant NO3– and PO43– into the river. Thus, FAFe concentration in Asahi River was influenced by pH, SWT, TOC, hydrological regime, and agricultural runoff.","PeriodicalId":13111,"journal":{"name":"Hydrological Research Letters","volume":"19 1","pages":"36-43"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.jstage.jst.go.jp/article/hrl/19/1/19_36/_pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147888727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stormwater management modeling and machine learning for flash flood susceptibility prediction in Wadi Qows, Saudi Arabia 沙特阿拉伯Wadi Qows洪水易感性预测的雨水管理模型和机器学习

Hydrological Research Letters Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.62

Fahad Alamoudi, Mohamed Saber, Sameh A. Kantoush, Tayeb Boulmaiz, Karim I. Abdrabo, Hadir Abdelmoneim, Tetsuya Sumi

{"title":"Stormwater management modeling and machine learning for flash flood susceptibility prediction in Wadi Qows, Saudi Arabia","authors":"Fahad Alamoudi, Mohamed Saber, Sameh A. Kantoush, Tayeb Boulmaiz, Karim I. Abdrabo, Hadir Abdelmoneim, Tetsuya Sumi","doi":"10.3178/hrl.17.62","DOIUrl":"https://doi.org/10.3178/hrl.17.62","url":null,"abstract":"Predicting flash flood-prone areas is essential for proactive disaster management. ‎However, such predictions are challenging to obtain accurately with physical hydrological models owing to the scarcity of flood observation stations and the lack of monitoring systems. This study aims ‎to compare machine learning (ML) models (Random Forest, ‎Light, and CatBoost) and the Personal ‎Computer Storm Water Management Model ‎‎(PCSWMM) hydrological ‎model to predict flash flood susceptibility ‎‎maps (FFSMs) in an arid region (Wadi Qows in ‎Saudi Arabia). Nine independent factors ‎that influence FFSMs in the study area were ‎assessed. ‎Approximately 300 flash flood sites were identified through a post-flood survey after the ‎‎extreme flash floods of 2009 in Jeddah city. The dataset was randomly split into 70 percent for training and 30 percent for testing. The results ‎show that the area ‎under the receiver operating curve (ROC) values were ‎above 95% for all tested ‎models, indicating evident accuracy. The FFSMs developed by the ML ‎‎methods show acceptable agreement with the flood inundation map created using the ‎PCSWMM in terms of flood extension. Planners and officials can use the outcomes of this study to improve the mitigation measures for flood-prone regions in Saudi Arabia.","PeriodicalId":13111,"journal":{"name":"Hydrological Research Letters","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135446088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimation of groundwater potential and aquifer hydraulic characteristics using resistivity and pumping test techniques in Makassar Indonesia 在印度尼西亚望加锡利用电阻率和抽水试验技术估计地下水潜力和含水层水力特征

IF 1.1

Hydrological Research Letters Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.42

S. Badaruddin, Hasdaryatmin Djufri, Zulvyah Faisal, Rakhmat Adi Cipta, Vita Fajriani Ridwan, A. Nabi, Andi Muhammad Subhan Saiby, M. Suradi, Z. Saing

引用次数: 0

Uncertainty of internal climate variability in probabilistic flood simulations using d4PDF 使用d4PDF的概率洪水模拟中内部气候变率的不确定性

IF 1.1

Hydrological Research Letters Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.15

Y. Kita, Dai Yamazaki

引用次数: 1

Developing a vertical quasi-two-dimensional surface-subsurface flow model using an approximation for hydraulic gradient 利用水力梯度近似建立垂直准二维地表-地下流动模型