Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations in the Western United States

This study used long-term in situ rainfall, snow, and streamflow data to explore the predictive contributions of snowmelt and rainfall to streamflow in six watersheds over the Western United States. Analysis showed that peak snow accumulation, snow-free day, and snowmelt slope all had strong correla...

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Main Authors: Xiaohui Zheng, Qiguang Wang, Lihua Zhou, Qing Sun, Qi Li
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Advances in Meteorology
Online Access:http://dx.doi.org/10.1155/2018/3765098
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author Xiaohui Zheng
Qiguang Wang
Lihua Zhou
Qing Sun
Qi Li
author_facet Xiaohui Zheng
Qiguang Wang
Lihua Zhou
Qing Sun
Qi Li
author_sort Xiaohui Zheng
collection DOAJ
description This study used long-term in situ rainfall, snow, and streamflow data to explore the predictive contributions of snowmelt and rainfall to streamflow in six watersheds over the Western United States. Analysis showed that peak snow accumulation, snow-free day, and snowmelt slope all had strong correlation with peak streamflow, particularly in inland basins. Further analysis revealed that the variation of snow accumulation anomaly had strong lead correlation with the variation of streamflow anomaly. Over the entire Western United States, inner mountain areas had lead times of 4–10 pentads. However, in coastal areas, nearly all sites had lead times of less than one pentad. The relative contributions of rainfall and snowmelt to streamflow in different watersheds were calculated based on the snow lead time. The geographic distribution of annual relative contributions revealed that interior areas were dominated by snowmelt contribution, whereas the rainfall contribution dominated coastal areas. In the wet season, the snowmelt contribution increased in the western Pacific Northwest, whereas the rainfall contribution increased in the southeastern Pacific Northwest, southern Upper Colorado, and northern Rio Grande regions. The derived results demonstrated the predictive contributions of snowmelt and rainfall to streamflow. These findings could be considered a reference both for seasonal predictions of streamflow and for prevention of hydrological disasters. Furthermore, they will be helpful in the evaluation and improvement of hydrological and climate models.
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language English
publishDate 2018-01-01
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series Advances in Meteorology
spelling doaj-art-a85fd165c8714c519d93b7e16a75db562025-02-03T05:59:45ZengWileyAdvances in Meteorology1687-93091687-93172018-01-01201810.1155/2018/37650983765098Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations in the Western United StatesXiaohui Zheng0Qiguang Wang1Lihua Zhou2Qing Sun3Qi Li4College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaChina Meteorological Administration Training Center (CMA), Beijing 100081, ChinaCollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaCollege of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Atmospheric Physics and Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaThis study used long-term in situ rainfall, snow, and streamflow data to explore the predictive contributions of snowmelt and rainfall to streamflow in six watersheds over the Western United States. Analysis showed that peak snow accumulation, snow-free day, and snowmelt slope all had strong correlation with peak streamflow, particularly in inland basins. Further analysis revealed that the variation of snow accumulation anomaly had strong lead correlation with the variation of streamflow anomaly. Over the entire Western United States, inner mountain areas had lead times of 4–10 pentads. However, in coastal areas, nearly all sites had lead times of less than one pentad. The relative contributions of rainfall and snowmelt to streamflow in different watersheds were calculated based on the snow lead time. The geographic distribution of annual relative contributions revealed that interior areas were dominated by snowmelt contribution, whereas the rainfall contribution dominated coastal areas. In the wet season, the snowmelt contribution increased in the western Pacific Northwest, whereas the rainfall contribution increased in the southeastern Pacific Northwest, southern Upper Colorado, and northern Rio Grande regions. The derived results demonstrated the predictive contributions of snowmelt and rainfall to streamflow. These findings could be considered a reference both for seasonal predictions of streamflow and for prevention of hydrological disasters. Furthermore, they will be helpful in the evaluation and improvement of hydrological and climate models.http://dx.doi.org/10.1155/2018/3765098
spellingShingle Xiaohui Zheng
Qiguang Wang
Lihua Zhou
Qing Sun
Qi Li
Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations in the Western United States
Advances in Meteorology
title Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations in the Western United States
title_full Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations in the Western United States
title_fullStr Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations in the Western United States
title_full_unstemmed Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations in the Western United States
title_short Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations in the Western United States
title_sort predictive contributions of snowmelt and rainfall to streamflow variations in the western united states
url http://dx.doi.org/10.1155/2018/3765098
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AT lihuazhou predictivecontributionsofsnowmeltandrainfalltostreamflowvariationsinthewesternunitedstates
AT qingsun predictivecontributionsofsnowmeltandrainfalltostreamflowvariationsinthewesternunitedstates
AT qili predictivecontributionsofsnowmeltandrainfalltostreamflowvariationsinthewesternunitedstates