Topography significantly influencing low flows in snow-dominated watersheds

Li, Qiang; Wei, Xiaohua; Yang, Xin; Giles-Hansen, Krysta; Zhang, Mingfang; Liu, Wenfei

doi:10.5194/hess-2017-560

Cited by 3 publications

(9 citation statements)

References 31 publications

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“…The difference in the drought progression processes between areas with different landscapes was also found by Sadri et al (2016) in the eastern United States. This confirms the findings of Laaha et al (2017), Bormann and Pinter (2017) and Li et al (2018) that the importance of local environmental elements on the process of formation of streamflow droughts is of greater importance than general global factors.…”

Section: Summary and Discussionsupporting

confidence: 91%

Simulating low flows over a heterogeneous landscape in southeastern Poland

Raczyński

Dyer

2021

Hydrological Processes

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This paper presents a scheme describing low flow formation processes in areas with different environmental conditions, including the impact of the selection and explanatory power of predictors for a probabilistic model based on the Logit model. The research was carried out using 29 daily streamflow gauges located in the Lublin region of southeastern Poland for the hydrological period 1976-2018. Analysis resulted in two distinct low flow schemes. In the lowland rivers, low flows occur during the warm season and are related to evaporation exceeding precipitation. In the upland rivers, hydrogeological factors related to water levels in the local Cretaceous aquifers determine the occurrence of low flows. This differentiation affects the quality of the predictive models. For lowland rivers, models based on the climatic water balance with a monthly shift have a better fit, while these models used for upland rivers are characterized by an approximately 10% decrease in accuracy. For upland rivers, the combined C t H t models without shifts produce the best model fit. The generalized precision of the Logit models is around 80%-90%.

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Section: Summary and Discussionsupporting

confidence: 91%

Simulating low flows over a heterogeneous landscape in southeastern Poland

Raczyński

Dyer

2021

Hydrological Processes

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“…Indeed, catchment average elevation and slope were correlated to the low-flow metrics (q min , q 95 and C) (Figures 4, 5; Table 4), as reported also in previous studies (e.g. Kroll et al, 2004;Li et al, 2018;Staudinger et al, 2015).…”

Section: Relevant Catchment Characteristics For Lowflow Assessment and Predictionsupporting

confidence: 85%

“…We obtained the main catchment characteristics (climate, topography, land cover and geology) for each catchment from available data from the Federal Office of Meteorology and Climatology (MeteoSwiss) and the Federal Office of Topography (Swisstopo; Table 1). Daily gridded datasets of The 2m resolution DEM was used to calculate several topographic catchment descriptors: upslope area, exposition, slope (average slope, and fraction of area for different slope classes), average terrain roughness (1/cos(β), where β is the pixel slope; Li et al, 2018), average topographic wetness index (TWI; ln(a/tan(β), where a is the accumulated area for every pixel; Beven & Kirkby, 1979), and the drainage density (L t /A, where L t is total channel length derived from the Swiss Vector dataset-Swisstopo, and A is catchment size; Tarboton et al, 1992).…”

Section: Catchment Characteristicsmentioning

confidence: 99%

“…Low flows are caused by climatic variations, mainly low precipitation, high evapotranspiration, or freezing conditions (e.g. Dierauer et al, 2018;Floriancic et al, 2020;Floriancic et al, 2021;Kormos et al, 2016;Teuling et al, 2013), but their magnitude also depends on catchment characteristics, like geology, soil properties, or topography (Floriancic et al, 2019;Li et al, 2018;Price et al, 2011;Staudinger et al, 2017). Thus, the expectation is that lowflow metrics can to some degree be predicted from the spatial distribution of these catchment characteristics and climate (e.g.…”

Section: Introductionmentioning

confidence: 99%

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A multi‐scale study of the dominant catchment characteristics impacting low‐flow metrics

Floriancic

Spies

Meerveld

et al. 2022

Hydrological Processes

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Low flows can impact water use and instream ecology. Therefore, reliable predictions of low-flow metrics are crucial. In this study, we assess which catchment characteristics (climate, topography, geology and landcover) can explain the spatial variability of lowflow metrics at two different scales: the regional scale and the small headwater catchment scale. For the regional-scale analysis, we calculated the mean 7-day annual minimum flow (q min ), the mean of the flow that is exceeded 95% of the year (q 95 ), and the master recession constant (C) for 280 independent gauging stations across the Swiss Plateau and the Swiss Alps for the 2000-2018 period. We assessed the relation between 44 catchment characteristics and the three low-flow metrics based on correlation analysis and a random forest model. Low-flow magnitudes across the Swiss Plateau were positively correlated with the fraction of the area covered by sandstone bedrock or alluvium, and with the area that has a slope between 10 and 30 . Across the Swiss Alps, low-flow magnitudes were positively correlated with the fraction of area with slopes between 30 and 60 , and the area with glacial deposits and debris cover. There was good agreement between observations and predictions by the random forest regression model with the top 11 catchment characteristics for both regions: for 80% of the Swiss Plateau catchments and 60% of the Swiss Alpine catchments, we could predict the three low-flow metrics within an error of 30%. The residuals of the regression model, however, varied across short distances, suggesting that local catchment characteristics affect the variability of low-flow metrics. For the local-scale headwater catchments, we conducted 1-day snapshot field campaigns in 16 catchments during low-flow periods in 2015 and 2016. The measurements in these sub-catchments also showed that areas with sandstone bedrock and a good storage-to-river connectivity had above average low-flow magnitudes. Including knowledge on local catchment characteristics may help to improve regional low-flow predictions, however, not all local catchment characteristics were useful descriptors at larger scales.

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“…Payn et al (2012) found that the impact of topographical contributing area on baseflow decreases during recession, indicating that catchment subsurface properties then gain in importance. Li et al (2017) showed that summer low flows are significantly influenced by topography in snow-dominated catchments, while Godsey et al (2014) concluded that summer low flows are strongly dependent on annual peak snow water equivalent (SWE), with a decrease leading to decreased summer low flows. Moreover, Jenicek et al (2016) showed that during high SWE years, summer low flows occur later and precipitation after maximum SWE has a significant impact on summer low flows.…”

Section: Citationmentioning

confidence: 99%

Snow to Precipitation Ratio Controls Catchment Storage and Summer Flows in Boreal Headwater Catchments

Meriö

Ala‐aho

Linjama

et al. 2019

Water Resources Research

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Catchment storage sustains ecologically important low flows in headwater systems. Understanding the factors controlling storage is essential in analysis of catchment vulnerability to global change. We calculated catchment storage and storage sensitivity of streamflow for 61 boreal headwater catchments in Finland. We also explored the connection between computed storage indices and low flow conditions. The relationships between selected climate, snow, and catchment characteristics and calculated storage properties and low flows were investigated, in order to assess the importance of different factors that render catchments vulnerable to climate and environmental change. We found that the most sensitive areas to climate change were located in the southern boreal coastal zone, with fine‐grained soils and agricultural areas. In contrast, catchments in the middle and northern boreal zone, with till and peatland soils and higher snow water equivalent values, were less sensitive under current conditions. In addition, we found a threshold at a snow to precipitation ratio of 0.35. Above that threshold, summer low flows were generally sensitive to changes in snow conditions, whereas below that threshold catchment characteristics gained importance and the sensitivity was more directly related to changes in temperature and timing of rainfall. These findings suggest that a warming climate will have pronounced impacts on hydrology and catchment sensitivity related to snow quantity and snow cover duration in certain snow to precipitation ratio zones. Moreover, land use activities had an impact on storage properties in agricultural and drained peatland areas, resulting in a negative effect on low flows.

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Topography significantly influencing low flows in snow-dominated watersheds

Cited by 3 publications

References 31 publications

Simulating low flows over a heterogeneous landscape in southeastern Poland

Simulating low flows over a heterogeneous landscape in southeastern Poland

A multi‐scale study of the dominant catchment characteristics impacting low‐flow metrics

Snow to Precipitation Ratio Controls Catchment Storage and Summer Flows in Boreal Headwater Catchments

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