Hydrological Sciences Journal-Journal Des Sciences Hydrologiques最新文献_第2页

Low-impact development (LID) control feasibility in a small-scale urban catchment for altered climate change scenarios 气候变化情景下小型城市集水区低影响发展(LID)控制的可行性

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-08-21 DOI: 10.1080/02626667.2023.2239797

Abhinav Wadhwa, Venkatesh Budamala, Pavan Kumar Kummamuru, K. Kasiviswanathan, Srimuruganandam B

{"title":"Low-impact development (LID) control feasibility in a small-scale urban catchment for altered climate change scenarios","authors":"Abhinav Wadhwa, Venkatesh Budamala, Pavan Kumar Kummamuru, K. Kasiviswanathan, Srimuruganandam B","doi":"10.1080/02626667.2023.2239797","DOIUrl":"https://doi.org/10.1080/02626667.2023.2239797","url":null,"abstract":"ABSTRACT Rainfall is considered a major input in designing stormwater management measures, especially for any low-impact development (LID) control design. With the impact of climate change, rainfall frequency and its patterns are changing continuously. Quantification of these changes and their impact on the performance of LID design becomes crucial. This paper presents a methodology to quantify the change in rainfall patterns using the Coupled Model Intercomparison Project 5 (CMIP5) climate model and to select the most feasible LID for a catchment with haphazard development. Interconnected decentralization-based LID controls are evaluated with the objective of emulating a pre-urbanized scenario. The overall analyses indicated that green roof (GR) followed by infiltration trenches (IT), rooftop disconnection (RTD), and permeable pavement (PP) showed better performance. Furthermore, a combination of IT, PP, and RTD accomplishes better efficiency for extreme rainfall events. Implementation of the most feasible combination will provide the additional benefit of water recycle and reuse.","PeriodicalId":55042,"journal":{"name":"Hydrological Sciences Journal-Journal Des Sciences Hydrologiques","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44431312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

The uncertainty associated with the use of copulas in multivariate analysis 多元分析中使用copula的不确定性

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-08-18 DOI: 10.1080/02626667.2023.2249459

Changrang Zhou, Ronald van Nooijen, A. Kolechkina, Emna Gargouri, F. Slama, N. C. van de Giesen

引用次数: 0

Evaluation of CHIRPS in dry and wet spell assessment utilizing copula-based severity–duration–frequency curves 利用基于copula的严重程度-持续时间-频率曲线评估干旱和潮湿期评估中的CHIRPS

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-08-17 DOI: 10.1080/02626667.2023.2248971

Mohammadali Alijanian, Fatemeh Dehghani

引用次数: 0

A graphical non-parametric hydrologic alteration test using flow duration curves 使用流量历时曲线的图形非参数水文变化试验

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-08-16 DOI: 10.1080/02626667.2023.2248109

Mohamed H. Mowafy, C. Kroll, R. Vogel

引用次数: 0

A hydraulic model of the Amur River informed by ICESat-2 elevation 由ICESat-2高程提供的阿穆尔河水力模型

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-08-14 DOI: 10.1080/02626667.2023.2245811

P. Bauer‐Gottwein, Elena Zakharova, Monica Coppo Frias, H. Ranndal, K. Nielsen, Linda Christoffersen, J. Liu, Liguang Jiang

{"title":"A hydraulic model of the Amur River informed by ICESat-2 elevation","authors":"P. Bauer‐Gottwein, Elena Zakharova, Monica Coppo Frias, H. Ranndal, K. Nielsen, Linda Christoffersen, J. Liu, Liguang Jiang","doi":"10.1080/02626667.2023.2245811","DOIUrl":"https://doi.org/10.1080/02626667.2023.2245811","url":null,"abstract":"ABSTRACT Accurate predictions of water surface elevation (WSE) in rivers at high spatial and temporal resolution are important for flood/drought risk assessment and flood/drought forecasting and management. WSE in a river is controlled by three main factors: discharge, riverbed geometry, and hydraulic roughness. In remote and poorly instrumented rivers, discharge and riverbed geometry are highly uncertain and WSE is therefore hard to predict. ICESat-2 laser altimetry provides accurate elevation transects across the river at very high spatial resolution (70 cm along track). This paper demonstrates how ICESat-2 elevation transects can be used to parameterize a basin-scale hydraulic model of a continental-scale river. The workflow is demonstrated for the transboundary Amur River in North-East Asia. Simulated WSE is subsequently validated against a large dataset of in situ and satellite altimetry observations, and we demonstrate that the model can reproduce available WSE observations throughout the basin with an accuracy of 1–2 m.","PeriodicalId":55042,"journal":{"name":"Hydrological Sciences Journal-Journal Des Sciences Hydrologiques","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44992353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Quantifying climate change impacts on hydropower production under CMIP6 multi-model ensemble projections using SWAT model 基于SWAT模型的CMIP6多模式集合预估下气候变化对水电生产的影响

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-08-08 DOI: 10.1080/02626667.2023.2245815

Emrah Yalcin

引用次数: 0

Improving the accuracy of multimodel short-to-medium-range precipitation and streamflow forecasts over the Upper Bhima river basin, India 提高印度比马河上游流域多模式中短期降水和流量预测的准确性

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-08-01 DOI: 10.1080/02626667.2023.2243257

S. Nandi, M. Janga Reddy

{"title":"Improving the accuracy of multimodel short-to-medium-range precipitation and streamflow forecasts over the Upper Bhima river basin, India","authors":"S. Nandi, M. Janga Reddy","doi":"10.1080/02626667.2023.2243257","DOIUrl":"https://doi.org/10.1080/02626667.2023.2243257","url":null,"abstract":"ABSTRACT Accurate precipitation forecasting with sufficient lead time is a prerequisite for developing a robust flood warning system (FWS), which is very challenging, particularly in developing countries like India. This study evaluates the utility of the TIGGE multimodel ensemble meteorological forecasts over the Upper Bhima River basin and investigated the hydrological utility of the TIGGE forecasts through a calibrated hydrological (VIC-RAPID) model followed by the post-processing of streamflow through Bayesian model average (BMA) approach. Results show that the quality of the meteorological forecasts of precipitation, and of the simulated streamflow, deteriorated with increasing lead time, which can be ameliorated with a suitable bias-correction technique. The BMA-based post-processing further improved the streamflow simulations, especially in case of extreme events, which highlighted its efficacy in flood forecasting. From the results of the study, it is recommended that a compound system of improved precipitation prediction, calibrated VIC-RAPID model and post-processing of streamflows in an integrated manner would facilitate a reliable FWS for operational purposes.","PeriodicalId":55042,"journal":{"name":"Hydrological Sciences Journal-Journal Des Sciences Hydrologiques","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43979627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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: 1

Estimation of least ecological streamflow through long-term habitat evaluation using stream hydrodynamics and water quality factors 利用河流流体力学和水质因素通过长期栖息地评估估算最小生态流量

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-07-27 DOI: 10.1080/02626667.2023.2241582

Jinseok Park, Seongju Jang, Rokgi Hong, I. Song

引用次数: 0

Automatic water-level class estimation from repeated crowd-based photos of streams 根据重复的基于人群的溪流照片自动估计水位等级

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-07-27 DOI: 10.1080/02626667.2023.2240312

Zeming Wang, J. Seibert, Ilja van Meerveld, H. Lyu, Chi Zhang

引用次数: 0

Physical and artificial intelligence-based hybrid models for rainfall–runoff–sediment process modelling 基于物理和人工智能的降雨-径流-泥沙过程建模混合模型

IF 3.5 3区环境科学与生态学

Hydrological Sciences Journal-Journal Des Sciences Hydrologiques Pub Date : 2023-07-27 DOI: 10.1080/02626667.2023.2241850

G. Gelete, Vahid Nourani, H. Gokçekuş, Tagesse Gichamo

{"title":"Physical and artificial intelligence-based hybrid models for rainfall–runoff–sediment process modelling","authors":"G. Gelete, Vahid Nourani, H. Gokçekuş, Tagesse Gichamo","doi":"10.1080/02626667.2023.2241850","DOIUrl":"https://doi.org/10.1080/02626667.2023.2241850","url":null,"abstract":"ABSTRACT This study evaluates the performance of the Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS), Hydrologiska Byråns Vattenbalansavdelning (HBV), Soil and Water Assessment Tool (SWAT), feedforward neural network (FFNN), adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR) and multilinear regression (MLR) for modelling the rainfall–runoff–sediment process in Katar catchment, Ethiopia. Afterward, neural network ensemble (NE), weighted average ensemble (WE) and simple average ensemble (SE) techniques were developed to improve the performance of single models. The performance of the models was evaluated using Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE) and mean absolute error (MAE). The results show that the ANFIS model outperformed the other single models for rainfall–runoff–sediment modelling. Moreover, the integration of artificial intelligence and physically-based models resulted in improved performance, with the NE technique demonstrating better accuracy by improving individual models by 5.8–27.6% for rainfall–runoff and 3.59–37.9% for suspended sediment load modelling in the validation phase.","PeriodicalId":55042,"journal":{"name":"Hydrological Sciences Journal-Journal Des Sciences Hydrologiques","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44156665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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: 1