scholarly journals Supplementary material to "Partitioning snowmelt and rainfall in the critical zone: effects of climate type and soil properties"

Author(s):  
John C. Hammond ◽  
Adrian A. Harpold ◽  
Sydney Weiss ◽  
Stephanie K. Kampf
2019 ◽  
Vol 23 (9) ◽  
pp. 3553-3570 ◽  
Author(s):  
John C. Hammond ◽  
Adrian A. Harpold ◽  
Sydney Weiss ◽  
Stephanie K. Kampf

Abstract. Streamflow generation and deep groundwater recharge may be vulnerable to loss of snow, making it important to quantify how snowmelt is partitioned between soil storage, deep drainage, evapotranspiration, and runoff. Based on previous findings, we hypothesize that snowmelt produces greater streamflow and deep drainage than rainfall and that this effect is greatest in dry climates. To test this hypothesis we examine how snowmelt and rainfall partitioning vary with climate and soil properties using a physically based variably saturated subsurface flow model, HYDRUS-1D. We developed model experiments using observed climate from mountain regions and artificial climate inputs that convert all precipitation to rain, and then evaluated how climate variability affects partitioning in soils with different hydraulic properties and depths. Results indicate that event-scale runoff is higher for snowmelt than for rainfall due to higher antecedent moisture and input rates in both wet and dry climates. Annual runoff also increases with snowmelt fraction, whereas deep drainage is not correlated with snowmelt fraction. Deep drainage is less affected by changes from snowmelt to rainfall because it is controlled by deep soil moisture changes over longer timescales. Soil texture modifies daily wetting and drying patterns but has limited effect on annual water budget partitioning, whereas increases in soil depth lead to lower runoff and greater deep drainage. Overall these results indicate that runoff may be substantially reduced with seasonal snowpack decline in all climates, whereas the effects of snowpack decline on deep drainage are less consistent. These mechanisms help explain recent observations of streamflow sensitivity to changing snowpack and highlight the importance of developing strategies to plan for changes in water budgets in areas most at risk for shifts from snow to rain.


Author(s):  
Juan C. Viviescas ◽  
Juan P. Osorio ◽  
Cesar Pastén

Soil properties variability in geotechnical engineering is one of the most important tasks in reliability-based designs (RBDs). However, these analyses have been carried without taking into account the influence of the geological origin in the different aspects that alter the soil properties variability. Therefore, two types of geological formations are analysed: residual soils (stationary origin) and mudflows (dynamic origin). First, the index properties variability was evaluated for each geology, where mudflows are less variable in comparison with the residual soils. It was confirmed that the correlations of the effective friction angle should not be used for high plasticity and fine-grained soils; however, the shape characteristics of the Probability Density Functions (PDF) of both effective and total parameters depends on the geological origin. The undrained compressive strength (qu) analyses show that geology influences the shape characteristics of the PDF and is directly proportional to the (N1)60 PDF. From the results, mudflows present a qu PDF with a lognormal tendency, which is inferred to be due to the possible presence of rock fragments and randomness related to the soil's formation. However, the residual soils, under the same state of weathering tend to have a normal qu PDF, possibly due to the stationary origin of these soils.Supplementary material:https://doi.org/10.6084/m9.figshare.c.5420240


2007 ◽  
Vol 11 (5) ◽  
pp. 1633-1644 ◽  
Author(s):  
M. C. Peel ◽  
B. L. Finlayson ◽  
T. A. McMahon

Abstract. Although now over 100 years old, the classification of climate originally formulated by Wladimir Köppen and modified by his collaborators and successors, is still in widespread use. It is widely used in teaching school and undergraduate courses on climate. It is also still in regular use by researchers across a range of disciplines as a basis for climatic regionalisation of variables and for assessing the output of global climate models. Here we have produced a new global map of climate using the Köppen-Geiger system based on a large global data set of long-term monthly precipitation and temperature station time series. Climatic variables used in the Köppen-Geiger system were calculated at each station and interpolated between stations using a two-dimensional (latitude and longitude) thin-plate spline with tension onto a 0.1°×0.1° grid for each continent. We discuss some problems in dealing with sites that are not uniquely classified into one climate type by the Köppen-Geiger system and assess the outcomes on a continent by continent basis. Globally the most common climate type by land area is BWh (14.2%, Hot desert) followed by Aw (11.5%, Tropical savannah). The updated world Köppen-Geiger climate map is freely available electronically in the Supplementary Material Section.


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