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TSWS: An observation-based streamflow dataset of Tianshan Mountains watersheds (1901–2019) [PDF]
Scientific DataDue to scarcity of data and complex hydrological conditions in the Tianshan region, long-term and complete streamflow data are lacking. This study produced a multi-basin streamflow dataset, named Tianshan watershed streamflow (TSWS) dataset, by comparing
Shuai Li +4 more
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Relationship between Ocean-Atmospheric Climate Variables and Regional Streamflow of the Conterminous United States [PDF]
Hydrology, 2018 Understanding the interconnections between oceanic-atmospheric climate variables and regional streamflow of the conterminous United States may aid in improving regional long lead-time streamflow forecasting. The current research evaluates the time-lagged
Swastik Bhandari +3 more
doaj +3 more sources
High-resolution gridded streamflow data for Ganges-Brahmaputra-Meghna River Basins in Bangladesh (1951–2023) [PDF]
Scientific DataA 9-km daily gridded streamflow dataset is generated using the Variable Infiltration Capacity-River Routing Model (VIC-RRM) across the Ganges-Brahmaputra-Meghna River basins over 1951–2023, forced by the ERA5-Land reanalysis data for naturalized ...
Byeong-Hee Kim +2 more
doaj +2 more sources
Direct vegetation response to recent CO2 rise shows limited effect on global streamflow [PDF]
Nature CommunicationsGlobal streamflow, crucial for ecology, agriculture, and human activities, can be influenced by elevated atmospheric CO2 (eCO2) though direct regulation of vegetation physiology and structure, which can either decrease or increase streamflow.
Haoshan Wei +6 more
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A global algorithm for identifying changing streamflow regimes: application to Canadian natural streams (1966–2010) [PDF]
Hydrology and Earth System Sciences, 2021 Climate change affects natural streamflow regimes globally. To assess alterations in streamflow regimes, typically temporal variations in one or a few streamflow characteristics are taken into account.
M. Zaerpour +3 more
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Frontiers in Water, 2022 The interpretation of deep learning (DL) hydrological models is a key challenge in data-driven modeling of streamflow, as the DL models are often seen as “black box” models despite often outperforming process-based models in streamflow prediction.
Sam Anderson, Valentina Radić
doaj +1 more source
A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022) [PDF]
Earth System Science Data, 2023 With the booming big data techniques, large-sample hydrological analysis on streamflow regime is becoming feasible, which could derive robust conclusions on hydrological processes from a big-picture perspective.
X. Chen +4 more
doaj +1 more source
Hydrology Research, 2021 Natural streamflow reconstruction is highly significant to assess long-term trends, variability, and pattern of streamflow, and is critical for addressing implications of climate change for adaptive water resources management.
Chiheng Dang +5 more
doaj +1 more source
Hydrology, 2020 The spatiotemporal hydrologic variability over different regions of the contiguous United States poses the risk of droughts and floods. Understanding the historic variations in streamflow can help in accessing future hydrologic conditions.
Balbhadra Thakur +4 more
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Hydrologic homogeneous regions using monthly Streamflow in Turkey [PDF]
, 2008 Cluster analysis of gauged streamflow records into homogeneous and robust regions is an important tool for the characterization of hydrologic systems.
Beg, Osman A. +2 more
core +11 more sources