alpine watersheds
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Author(s):  
Xiaohua Chen ◽  
Guoping Tang ◽  
Tao Chen ◽  
Xiangyu Niu

In semiarid to arid regions of the western U. S., the availability and variability of river flow are highly subject to shifts in snow accumulation and ablation in alpine watersheds. This study aims to examine how shifts in snowmelt rate (SMR) and snow continuity, an indicator of the consistent existence of snow on the ground, affect snow-driven streamflow dynamics in three alpine watersheds in the U.S. Great Basin. To achieve this end, the coupled hydro-ecological simulation system (CHESS) is used to simulate river flow dynamics and multiple snow metrics are calculated to quantify the variation of snowmelt rate and snow continuity, the latter of which is measured, respectively, by snow persistence (SP), snow residence time (SRT) and snow season length (SSL). Then, a new approach is proposed to partition streamflow into snow-driven and rain-driven streamflow. The statistical analyses indicate that the three alpine watersheds experienced a downward trend in SP, SRT, SSL and SMR during the study period of 1990-2016 due to regional warming. As a result, the decrease in SMR and the decline in snow continuity shifted the day of 25% and 50% of the snow-driven cumulative discharge as well as peak discharge toward an earlier occurrence. Besides, the magnitudes of snow-driven annual streamflow, summer baseflow and peak discharge also decreased due to the declined snow continuity and the reduced snowmelt rate. Overall, by using multiple snow and flow metrics as well as by partitioning streamflow into snow-driven and rain-driven flow via the newly proposed approach, we found that snowmelt rate and snow continuity determine the streamflow hydrographs and magnitudes in the three alpine watersheds. This has important implications for water resource management in the snow-dominated region facing future climate warming given that warming can significantly affect snow dynamics in alpine watersheds in semiarid to arid regions.


2021 ◽  
pp. 127125
Author(s):  
Andrea Galletti ◽  
Diego Avesani ◽  
Alberto Bellin ◽  
Bruno Majone

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1199
Author(s):  
Kyle Siemens ◽  
Yonas Dibike ◽  
Rajesh R Shrestha ◽  
Terry Prowse

The rising global temperature is shifting the runoff patterns of snowmelt-dominated alpine watersheds, resulting in increased cold season flows, earlier spring peak flows, and reduced summer runoff. Projections of future runoff are beneficial in preparing for the anticipated changes in streamflow regimes. This study applied the degree–day Snowmelt Runoff Model (SRM) in combination with the MODIS to remotely sense snow cover observations for modeling the snowmelt runoff response of the Upper Athabasca River Basin in western Canada. After assessing its ability to simulate the observed historical flows, the SRM was applied for projecting future runoff in the basin. The inclusion of a spatial and temporal variation in the degree–day factor (DDF) and separation of the DDF for glaciated and non-glaciated areas were found to be important for improved simulation of varying snow conditions over multiple years. The SRM simulations, driven by an ensemble of six statistically downscaled GCM runs under the RCP8.5 scenario for the future period (2070–2080), show a consistent pattern in projected runoff change, with substantial increases in May runoff, smaller increases over the winter months, and decreased runoff in the summer months (June–August). Despite the SRM’s relative simplicity and requirement of only a few input variables, the model performed well in simulating historical flows, and provides runoff projections consistent with historical trends and previous modeling studies.


2020 ◽  
Vol 32 ◽  
pp. 100759
Author(s):  
Yuheng Yang ◽  
Baisha Weng ◽  
Denghua Yan ◽  
Yongzhen Niu ◽  
Xiaoyan Gong ◽  
...  
Keyword(s):  

2020 ◽  
Author(s):  
Bob de Graffenried ◽  
Ivan Pascal ◽  
Tomas Trewhela ◽  
Valentina Martinez ◽  
Christophe Ancey

<p>Characterising morphological changes in mountain areas is of fundamental importance for science<br>and engineering. Intense floods usually involve massive sediment transport, which may significantly<br>alter basin and river characteristics. Sediment erosion and deposition control the dynamics<br>of morphological structures such as alternate bars and meanders. By using unmanned aerial vehicles<br>(UAV), it has been possible to obtain high-precision bed elevation data at the sediment scale.<br>Our project aims to develop a consistent and optimised methodology for monitoring morphological<br>changes in an Alpine watershed using an UAV. Since 2017, we have been monitoring the Plat de la<br>Lé area drained by the River Navisence (Zinal, canton Valais, Switzerland). In mountainous regions,<br>poor accessibility and light conditions make it difficult to set control points on the ground. We first<br>analysed the relevance and influence of certain ground control points (GCP) on the the accuracy of<br>the digital elevation model (DEM) obtained from the UAV’s images. Errors in the GCP localisation<br>were much larger than the DEM resolution. Not only did the GCP number and flight height affect<br>these errors, as expected, but their positions and orientations also played a part. We then carried<br>out an additional monitoring campaign to understand the influence of these parameters on the DEM<br>accuracy. This campaign was ran on two areas: a steep-slope area with irregular topography and<br>a low-slope area that comprises the river channel and its floodplain. We built DEMs for each area<br>considering different GCP numbers (in the 3–18 range with 14 additional checkpoints) and flight<br>heights (in the 40–140-m range). The present study provides guidelines, including an optimal combination<br>of parameters that significantly reduce errors in the DEM, and a methodology that can be<br>used for monitoring Alpine watersheds on a regular basis.</p>


2018 ◽  
Vol 54 (3) ◽  
pp. 1599-1615 ◽  
Author(s):  
Sarah G. Evans ◽  
Shemin Ge ◽  
Clifford I. Voss ◽  
Noah P. Molotch

2017 ◽  
Vol 13 (1) ◽  
pp. 235-248
Author(s):  
Zoltán Árpád LIPTAY ◽  
◽  
Szabolcs CZIGÁNY ◽  
Ervin PIRKHOFFER ◽  
Hermann KLUG

2012 ◽  
Vol 48 (5) ◽  
Author(s):  
Steven M. Jepsen ◽  
Noah P. Molotch ◽  
Mark W. Williams ◽  
Karl E. Rittger ◽  
James O. Sickman

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