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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 Q3 Earth and Planetary Sciences 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
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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
Q3 Earth and Planetary Sciences 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
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.
预测易发山洪的地区对于积极主动的灾害管理至关重要。然而,由于洪水观测站的缺乏和监测系统的缺乏,这种预测很难用物理水文模型准确地获得。本研究旨在比较机器学习(ML)模型(Random Forest、Light和CatBoost)和个人计算机雨水管理模型(PCSWMM)水文模型,以预测干旱地区(沙特阿拉伯的Wadi Qows)的山洪易发性地图(FFSMs)。评估了影响研究区域FFSMs的9个独立因素。2009年吉达市极端山洪暴发后,通过灾后调查确定了大约300个山洪暴发点。数据集被随机分成70%用于训练,30%用于测试。结果表明,所有测试模型的受试者工作曲线(ROC)值下面积均在95%以上,具有较好的准确性。在洪水扩展方面,ML方法开发的FFSMs与使用PCSWMM绘制的洪水淹没图具有良好的一致性。规划者和官员可以利用这项研究的结果来改进沙特阿拉伯洪水易发地区的减灾措施。
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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 Q3 Earth and Planetary Sciences Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.15
Y. Kita, Dai Yamazaki
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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
IF 1.1 Q3 Earth and Planetary Sciences Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.36
Sora Fugami, Y. Ichikawa, K. Yorozu, H. An, Y. Tachikawa
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引用次数: 0
Assessing characteristics and long-term trends in runoff and baseflow index in eastern Japan 评估日本东部径流和基流指数的特征和长期趋势
IF 1.1 Q3 Earth and Planetary Sciences Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.1
Stanley N. Chapasa, A. Whitaker
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引用次数: 0
Impact of flood experiences and anxiety on subjective well-being 洪水经历和焦虑对主观幸福感的影响
IF 1.1 Q3 Earth and Planetary Sciences Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.56
Ryo Murata, Daisuke Tokuda, Masashi Kiguchi, Keigo Noda, T. Oki
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引用次数: 0
Assessment of extreme local topographic winds and their future changes from a massive high-resolution ensemble climate dataset 从大规模高分辨率集合气候数据集评估极端局部地形风及其未来变化
Q3 Earth and Planetary Sciences Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.69
Yoshikazu Kitano, Masamichi Ohba, Naohiro Soda, Yasuo Hattori, Tsuyoshi Hoshino, Tomohito J. Yamada
The estimation of extreme wind speeds, their directional variation, and potential future changes is essential for wind-resistant design and is possible using climate models. Accurate evaluations of local topographic winds such as downslope windstorms and gap winds require high-resolution calculation and many ensemble years. However, few climate databases satisfy both requirements and none have been validated for extreme wind speeds.
极端风速及其方向变化和未来潜在变化的估计对于抗风设计至关重要,并且可以使用气候模型。准确评估当地地形风,如下坡风和间隙风,需要高分辨率的计算和许多年的集合。然而,很少有气候数据库同时满足这两个要求,而且没有一个数据库对极端风速进行了验证。
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引用次数: 0
Automatic levee detection using a high-resolution DEM − Case study in Kinu river basin, Japan 基于高分辨率DEM的堤防自动检测——以日本基努河流域为例
IF 1.1 Q3 Earth and Planetary Sciences Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.9
O. Sasaki, Yugo Tsumura, Masafumi Yamada, Y. Hirabayashi
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引用次数: 0
Seasonal variation of physico-chemical characteristics in water of meromictic Lake Oigon 奥贡分生湖水体理化特征的季节变化
IF 1.1 Q3 Earth and Planetary Sciences Pub Date : 2023-01-01 DOI: 10.3178/hrl.17.49
Byambadulam Enkhee, B. Chuluun, Bayanmunkh Baatar, S. Nyamdorj, Sen-Lin Tang, B. Oyuntsetseg
{"title":"Seasonal variation of physico-chemical characteristics in water of meromictic Lake Oigon","authors":"Byambadulam Enkhee, B. Chuluun, Bayanmunkh Baatar, S. Nyamdorj, Sen-Lin Tang, B. Oyuntsetseg","doi":"10.3178/hrl.17.49","DOIUrl":"https://doi.org/10.3178/hrl.17.49","url":null,"abstract":"","PeriodicalId":13111,"journal":{"name":"Hydrological Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69395168","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
Improvement of socio-hydrological model to capture the dynamics of combined river and urban floods: a case study in Lower Kelani River Basin, Sri Lanka 社会水文模型的改进,以捕捉河流和城市洪水的动态:斯里兰卡下克拉尼河流域的案例研究
IF 1.1 Q3 Earth and Planetary Sciences Pub Date : 2022-01-01 DOI: 10.3178/hrl.16.40
C. Perera, Shinichiro Nakamura
: Identifying the complex patterns of human-flood interac‐ tions over longer periods of time is very important in flood‐ plain management activities. The recently introduced socio-hydrology (SH) model contributes to capture these long-term behaviors of human-flood systems. This model can be utilized to explain the long-term dynamics of human-water interaction in floodplains. The current SH model exclu‐ sively illustrates the impact of river floods on floodplain communities. However, in some river basins, urban floods (due to high intensity rainfall) are dominant, whereas in other river basins, both river floods and urban floods influ‐ ence the dynamics of the system. It is often difficult to dis‐ tinguish the type of flood from actual local disaster data sets. In this study, we proposed an improvement to the existing SH model to capture the dynamics of both river floods and urban floods based on a case study from the Lower Kelani Basin, Sri Lanka, using simulated historical flood damages. The improved model was applied to capture flood damages in the target watershed, and the results fur‐ ther emphasize the importance of flood risk perception in flood damage reduction.
在洪泛平原管理活动中,识别人类与洪水长期相互作用的复杂模式是非常重要的。最近引入的社会水文学(SH)模型有助于捕捉人类洪水系统的这些长期行为。该模型可用于解释洪泛区人-水相互作用的长期动态。目前的SH模型仅说明了河流洪水对洪泛区社区的影响。然而,在一些河流流域,城市洪水(由于高强度降雨)占主导地位,而在其他河流流域,河流洪水和城市洪水都影响系统的动态。通常很难从实际的当地灾害数据集中区分洪水的类型。本研究以斯里兰卡下克拉尼盆地为例,利用模拟历史洪水灾害,对现有SH模型进行了改进,以捕捉河流洪水和城市洪水的动态变化。将改进的模型应用于目标流域的洪水灾害,结果强调了洪水风险感知在减少洪水灾害中的重要性。
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引用次数: 3
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Hydrological Research Letters
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