Processes of runoff generation operating during the spring and autumn seasons in a permafrost catchment on semi-arid plateaus

Accepted Manuscript Research papers Processes of runoff generation operating during the spring and autumn seasons in a permafrost catchment on semi-arid plateaus Wang Genxu, Mao Tianxu, Chang Juan, Song Chunlin, Huang Kewei PII: DOI: Reference:

S0022-1694(17)30309-8 http://dx.doi.org/10.1016/j.jhydrol.2017.05.020 HYDROL 22011

To appear in:

Journal of Hydrology

Received Date: Revised Date: Accepted Date:

9 January 2017 10 May 2017 11 May 2017

Please cite this article as: Genxu, W., Tianxu, M., Juan, C., Chunlin, S., Kewei, H., Processes of runoff generation operating during the spring and autumn seasons in a permafrost catchment on semi-arid plateaus, Journal of Hydrology (2017), doi: http://dx.doi.org/10.1016/j.jhydrol.2017.05.020

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Processes of runoff generation operating during the spring and autumn seasons in a permafrost catchment on semi-arid plateaus

Wang Genxu, Mao Tianxu, Song Chunlin, Huang Kewei Key Laboratory of Mountain Environment Evolvement and Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, P. R. China Email: Wang Genxu, [email protected]; Mao Tianxu, [email protected]; Huang Kewei, [email protected] Tel. +86-02885233420, +8613540813939

Chang Juan College of Earth and Environment Science, Lanzhou University, Lanzhou 730000, P. R. China Email: [email protected] Tel. +8618009402278

Corresponding author: Wang Genxu, Key Laboratory of Mountain Environment Evolvement and Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, P. R. China Email: [email protected]; Tel. +86-02885233420, +8613540813939

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Highlights: 1. A new approach based on soil temperature threshold is presented to simulate runoff generation in semi-arid plateau. 2. Bidirectional freezing of the active layer controls the autumn runoff recession processes and runoff composition. 3. Soil temperature plays a crucial role in the spring runoff processes with the enlargement of the active layer 4. The effects of soil freeze-thaw cycle on spring and autumn runoff processes and the mechanism are identified

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Processes of runoff generation operating during the spring and autumn seasons in a permafrost catchment on semi-arid plateaus Wang Genxu1, Mao Tianxu1, Chang Juan2, Song chunlin1 Huang Kewei1 1

Key Laboratory of Mountain Environment Evolvement and Regulation, Institute of

Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, P. R. China 2

College of Earth and Environment Science, Lanzhou University, Lanzhou 730000, P. R.

China

Abstract There is a lack of knowledge about how to quantify runoff generation and the hydrological

processes operating in permafrost catchments on semi-arid plateaus. To understand how freeze-thaw cycles affect runoff generation processes in permafrost catchments, a typical headwater catchment with continuous permafrost on the Tibetan Plateau was measured. A new approach is presented in this study to account for runoff processes on the spring thawing period and autumn freezing period, when runoff generation clearly differs from that of non-permafrost catchments. This approach introduces a soil temperature-based water saturation function and modifies the soil water storage curve with a soil temperature threshold. The results show that surface soil thawing induced saturation excess runoff and subsurface interflow account for approximately 66-86% and 14-34% of total spring runoff, respectively, and the soil temperature significantly affects the runoff generation pattern, the runoff composition and the runoff coefficient with the enlargement of the active layer. The 3 / 46

suprapermafrost groundwater discharge decreases exponentially with active layer frozen processes during autumn runoff recession, whereas the ratio of groundwater discharge to total runoff and the direct surface runoff coefficient simultaneously increase. The bidirectional freezing of the active layer controls and changes the autumn runoff processes and runoff composition. The new approach could be used to further develop hydrological models of cold regions dominated by permafrost. Key words: Runoff generation, soil temperature threshold, quantitative approach, seasonal dynamics, permafrost headwater catchment

INTRODUCTION In cold terrain underlain by permafrost, precipitation-runoff relationships and runoff

processes differ from those of temperate environments. Generally, permafrost acts as an impermeable layer to obstruct soil liquid water from leakage to deeper layers and forms an aquifer floor of suprapermafrost groundwater or aquifer roof of subpermafrost groundwater (Zhou et al., 2000; Woo and Winter, 1993).Meanwhile, the soil temperature gradient generated by active soil thawing and freezing cycle redistributes water in the soil profile, which also changes the soil water storage capacity and the soil water conductivity (Cheng, 1983; Quinton and Mash, 1999; Wright et al., 2009). Therefore, runoff connectivity, interflow and groundwater flow in the active layer and their discharge to surface waters substantially controlled by variations in the freezing and thawing of the active layer. The precipitation-runoff relationships that are based on the concept of slope runoff generation 4 / 46

and are used in runoff generation theories designed for temperate environment couldn’t be applied to permafrost slopes (Spence and Woo, 2006; Careyand Pomeroy, 2009; Woo, 2012). Some classical physical methods, such as that of de Saint-Venant or the kinematic-wave equation, which are commonly used to simulate processes of surface flow or subsurface flow at scales from individual slope to small watershed, are difficult to apply in permafrost landscapes because the required information on inclination, morphology, and roughness of slopes cannot be supplied (Vinogradov et al. 2011; Semenova et al., 2012). In recent 15 years, some complex physical process-based methods have been developed to represent water dynamics in variably saturated, alternately thawed and frozen soil profiles and hillslope runoff (Kuchment et al., 2000; Pomeroy et al., 2007; Rigon et al. 2006; Zhang et al., 2012). However, in cold environments such as TP, where forcing data and parameter information is typically lacking or poorly approximated, the sophisticated models are prohibited to successfully employ. It is inappropriate and physically unrealistic to run detailed distributed models for simulating and predicting streamflow processes of ungauged or poorly gauged basins in permafrost regions (Kuchment et al., 2000; Zhou et al., 2014). Thus, conceptual modelling of flow transformation processes seems to be quite reasonable and valid, especially for vast ungauged permafrost domains. Examples include the ‘element threshold concept’ of Connon et al. (2015) for interconnected bog complexes in discontinuous permafrost terrains or the ‘fill-and-spill’ approach of Spence and Woo (2006) for the semi-arid Canadian Shield region that explains streamflow generation along chains of lakes. However, in semi-arid

plateaus and moderate mountains in permafrost regions (widely distributed over Alaska, eastern Siberia and the Tibetan Plateau), most recent studies have focused on vertical rather 5 / 46

than horizontal processes, leaving precipitation, evaporation, infiltration and percolation as the mechanisms that affect storage in soil columns (Woo et al., 2008; Spence et al., 2010; Semenova et al., 2012). Therefore, there is a lack of knowledge about how to determine the mechanisms responsible for and to quantify runoff generation and hydrological processes (Wright et al., 2009; Spence et al., 2010). Coupling of the seasonal freeze-thaw cycles with the precipitation rhythm is suggested as a possible principal control on hydrologic processes for developing numerical or conceptual models in this terrain type (Yamazaki et al., 2006; Pomeroy et al., 2007). Runoff generation is the most crucial part of slope hydrological processes. The mechanism and quantitatively simulating approach within different environments remain unresolved (Güntner et al., 2004; Yamazaki et al., 2006; Penna et al., 2011), which is specially one of the most challenging obstructions to deeply understand the hydrological processes in cold regions. In the last two decades, a concept of variable contribution area has been developed and employed to clarify the processes, drives and mechanisms of the runoff generation (Güntner et al., 2004; Latron and Gallart, 2007; Penna et al., 2011). In permafrost regions, previous conceptual approaches, such as the “element threshold concept” and the “fill-and-spill” approach, could be regarded as applications of the variable contributing area

concept to permafrost environments (Spence et al., 2010). However, soil moisture, ground water, surface flow and the correlations of surface and subsurface hydrological responses to active freezing and thawing are not yet well integrated through detailed process studies in permafrost, which restricts the development of hydrological models in permafrost regions (Kuchment et al., 2000; Wright et al., 2009; Semenova et al., 2012). Consequently, the first 6 / 46

goal of the present study is to develop an approach based on the variable contributing area concept that integrates soil water storage (soil saturation) and the associated active-layer (soil temperature) dynamics with surface and subsurface runoff processes to precisely simulate runoff generation and variability. In permafrost watershed, the position of the frozen frontier within the active layer is the dominant factor controlling the distribution of the soil liquid water content, water-saturated zone as well as the positions of suprapermafrost groundwater flow on permafrost hillslopes (Wright et al., 2009; Woo, 2012), which then controlled the threshold relations between soil water content and surface runoff generation (Leavesley et al., 1983, Zehe et al., 2010). Thus, the distribution and dynamics of frost table depths controls the generation and composition of runoff from permafrost watershed (Quinton and Marsh, 1999; Wright et al., 2009; Spence et al., 2010). The seasonal variation of active layer is also the critical factor in determining the flow of suprapermafrost groundwater and the processes by which watershed flow is concentrated. Consequently, the second goal of the present study is to determine the seasonal dynamics of runoff composition in a headwater catchment of a semi-arid plateau with continuous permafrost and to estimate the effects of the freezing and thawing of the active layer on the runoff generation processes.

STUDY AREA AND METHODOLOGY Study area description and data collection This study was conducted in the Fenghuoshan watershed in the central regions of the Qinghai-Tibet Plateau (93◦3–92◦50E and 34◦40–34◦48N)with continuous permafrost (Fig. 1, Wang et al., 2015). One of the primary tributaries with a total catchment area of 1.62 km2, 7 / 46

which ranges in elevation from 4780 to 5143 m a.s.l., was selected for this study and observation systems were implemented. Precipitation observed in the region ranges from 248.5 to 467.4 mm, with more than 85% falling during the warmer season (June to September). The mean annual air temperature from the years 2005 to 2015 was of -5.2°C. Due to the snowfall was less than 21 mm (i.e., less than 5%) during the freezing season (November to April), the snow cover was irregular, filmy and discontinuously distributed over the ground surface, even during full winter season (Sato, 2001; Wang et al., 2015). The mean daily soil temperature and moisture at different elevations are shown in Figures 2a and 2b. The surface soil (up to 10 cm in depth) started to thaw at the end of April or early May in relatively low parts of the catchment with an elevation below 4850 m a.s.l. and was delayed approximately 8-10 days in relatively high parts of the catchment with an elevation over 4930 m a.s.l. At the end of September, the surface soil in the high parts of the catchment started to freeze, which was 12-15 days ahead of that in the low parts of the catchment. At the same site, the time of thawing in the surface soil layer was 40-43 days ahead of that in the layer at a depth of 90 cm, but the difference in freezing time between the surface and deep soil layers was only 25-27 days (Fig. 2a). The permafrost catchment is dominated by alpine meadows and swamps with an average coverage of 60 to 93% and 67 to 97%, respectively (Wang et al., 2010). The thickness of the active layer ranged from 2.1 m in the valley to 0.8 m on the mountain ridge (Zhou et al., 2000; Wu and Zhang, 2008). Figure 1 shows the field observation sites distributed in the study catchment, where 19 sites were located at different elevations from the river valley to the mountain ridge on two side slopes (Wang et al., 2015). The soil temperatures at depths of 0.05, 0.20, 0.40, 0.80, 1.0, 8 / 46

1.20, and 1.60 m were measured by a thermal resistance sensor (HMP45AC, Vaisala, Finland), and the soil moistures at the same depths were measured by a frequency domain reflectometer (CS616, Campbell, USA) with Data logger (CR1000, Campbell, USA). One micro-meteorological station was established in the experimental catchment to monitor air temperature (HMP155-L15, Vaisala, Finland) and precipitation (52202-L30, R. M. Yong, USA). Two snow-monitoring sensors were established in the valley and on the mountain ridge. In the study catchment, three observation holes were constructed at a depth of 300 cm, of which one was located on the upper section of the slope at an elevation of 4920 m, the second one was located on the middle slope with the elevation of 4870 m, and the last one was on the lower section of the slope at 4820 m a.s.l., with a distance of 120-150 m between them. HOBO U20-001-04 water level data loggers (ONSET Co., USA) were installed to monitor the suprapermafrost groundwater level. Daily stream flows were monitored by a V-notch weir at the outlet of the catchment from July 2012 to July 2015. The characteristics, production companies, accuracies and resolutions of all the devices are listed in Table 1.

Analysis Approach Water storage capacity curve based runoff generation theory. The saturation excess runoff and infiltration excess runoff are the two dominant types of runoff and have often been used to indicate runoff contribution area (Ward and Robinson, 1990; Rui, 2004). Usually, the nonlinear variation curves of the soil water storage capacity and water-saturation capacity are used as indices to indicate the processes responsible for generating saturation excess runoff; whereas the nonlinear curve describing soil infiltration 9 / 46

capacity is used to indicate the processes responsible for generating infiltration excess runoff in non-permafrost regions (Rui, 2004; Brutsaert, 2005). The water storage capacity-based contribution to saturation excess runoff in non-permafrost catchment can be estimated from the water balance equation as follows (Rui, 2004; Brutsaert, 2005):
 = P − E − 



1 − β    ′

′

(1)

where
 is runoff production in the catchment (mm), P is daily precipitation (mm), and E is the actual daily evapotranspiration (mm).  is the soil water content at field water ′

capacity, and β   = τ is the water storage capacity curve, which refers to the ratio of ′

areas with soil water content≤ to the total catchment area (Rui, 2004). The infiltration ′

excess runoff production
 can also be estimated with the infiltration capacity curve  and the rainfall intensity  using following simple equation [Rui, 2004; Brutsaert, 2005]:
 = ∑

!" 

−  ∆

(2)

However, all these approaches of runoff generation are closely linked to the relationships between the soil water regime and precipitation, which are obviously not applicable in permafrost catchments where the variations of frozen frontiers within the active layer have important effects on the soil hydraulic properties and then the runoff generating processes. Therefore, it is essential to develop new approaches to identify the unique runoff generation processes in permafrost catchment. In both the saturation excess and infiltration excess surface runoff production equations (equations (1) and (2)), the previous soil water content W0 is the main force driving β   = τ and the infiltration ′

capacity curve  . Because thawing and freezing of the active layer changes the soil water

storage and soil water infiltration capacity, which results in variations in W0 and  , the 10 / 46

functions of β  and  in equations (1) and (2) need to be revised for use in ′

permafrost environments. Hypothesis and numerical implementation. In general, the functions β   and  ′

depend on the degree of saturation of surface soil because permeability decreases with decreasing liquid water saturation. Under conditions with active freeze-thaw cycles, the effective water saturation, Se, can be computed using an empirical exponential relationship as follows [Koopmans and Miller,1966; Ge et al., 2011]: #$ = 1 − #% &

'(') +  *



+ #%

(3)

where Sr is the residual water saturation, T is soil temperature (°C), Tf is the temperature corresponding to the soil freezing point, and - is a fitting parameter. Given Se, the

permeability can be computed by . = . 100123  , where ks is the saturated permeability (m2) and 4 is an empirical impedance factor [Hansson et al., 2004]. While different functions

for the unsaturated soil hydraulic properties may be used, the Se can also be computed using the expressions presented by van Genuchten [1980] and van Genuchten et al. [1991], in which #$ =

56 57 

58 57 

. Here, 9% and 9 denote the residual and saturated water contents (m3/m3),

respectively, and 9 is the soil water content of the study site during the study. There is a linear relationship between permeability and hydraulic conductivity, K (m/s), . = : <= , ;

where > is the dynamic viscosity of water (kg/m·s), ? is the density of water (kg/m3 ), and @ is the gravitational acceleration (m/s2). Therefore, the hydraulic conductivity of surface soil

can also be computed using the water saturation, Se. Thus, the degree of soil water saturation (or soil liquid water content) and water infiltration capacity can be expressed in terms of the soil temperature in the thawing period and the freezing point. 11 / 46

In the study headwater catchment of the permafrost region on Tibetan Plateau (TP), runoff generation varies from saturation excess (or infiltration excess where the surface soil is frozen) in spring to saturation excess mixed with subsurface interflow in early summer, along with surface soil thawing and maintaining higher degrees of water saturation. Then, runoff generation is dominated by infiltration excess when the water saturation of the thawed surface layer is less than the field capacity (Yang et al., 2000; Wang et al., 2012). It is hypothesized that a threshold of water saturation in surface layer controls the partitioning of runoff among saturation excess, saturation excess mixed with subsurface interflow and infiltration excess (Rui, 2004). A common assumption is that the water saturation threshold equals the field capacity, 9A , when #$A = 9A  =

5B 57  58 57 

. Corresponding the water saturation threshold, the

soil temperature regime, (CA − C! , is defined as the soil temperature threshold for surface soil water saturation in spring thawing processes. After surface soil temperature being over the threshold and soil water content below 9A , infiltration excess becomes the dominant runoff generation process and the river runoff regime transformed from spring flood period into summer dry period when the runoff generation processes are similar as that in non-permafrost regions (Yang et al., 2000). Then, we develop a new approach to simulate the spring runoff generation processes of permafrost catchment based on those hypotheses. In the study watershed, the precipitation in winter and early spring season from the end of November to February is generally less than 21 mm. Most snowfall occurs during the spring season from April to May, when the frozen ground begins to thaw and the snow melts and evaporates quickly (Sato, 2001; Wang et al., 2010). Thus, no surface runoff occurred before 20 April or after 10 November in the studied watershed (Wang et al., 2009), and the 12 / 46

infiltration excess runoff generated from snowmelt before the frozen ground has begun to thaw is too small to be considered in this study. In the spring and early summer seasons, the surface soil water content increases quickly and reaches its peak value along with the thawing of the active layer (Yi et al., 2009; Wang et al., 2012), which means that rainfall and snowmelt can saturate the thin layer of thawed soil (that is, the soil water content exceeds the field water capacity) when (C − C!  ≤ CA − C! , where C and CA are the actual and saturated soil

temperatures at site E in the study watershed, respectively. Then, saturation excess runoff and saturation excess mixed with subsurface interflow generating processes can occur, forming the spring flood runoff. During this period, there are no significant relationships between soil moisture and precipitation or between precipitation and runoff due to the water comes from precipitation, snowmelt and the melt of soil ice in the thawed active layer (Wang et al., 2009). Because C , CA and C! differ among sites, the runoff-contributing areas and active layer thawing processes vary within the study watershed. During the spring, when flood runoff processes operate within headwater catchments within the region of permafrost, it is difficult to divide runoff generation into saturation excess and saturation excess mixed with subsurface interflow. Thus, the two types of surface runoff generated during spring thawing are combined together and considered “saturation excess runoff”. The area of saturation excess runoff generation (SERG) induced by soil temperature varies with (C − C!  at different elevations and slope aspects due to variations in the surface energy balance. The degree of water saturation in soil that is at field water capacity, #$A , can be used to replace  in equation (1). In this case, β#$A  = τ, which is ′

the water saturation curve and refers to the ratio of areas with ≤#$A to the total catchment 13 / 46

area. If the soil temperature is within the range of 0 ≤ C ≤CA when SERG is the dominant surface runoff, equation (1) can be expressed in terms of the soil thawing processes as follows:
= F + G − H  + 2 B I

1 56 5B  3

R = F + G − H  − 2 3 2B 7

∅

K 1 − β#$A #$ 0 ≤ C ≤CA , #$ ≥ #$A

(4)

1 − β#$A #$ 0 ≤ C ≤CA , #$ < #$A (5)

where the second term on the right-hand side of equation (4),
P = 2B I

1 56 5B  3

∅

K 1 −

β#$A #$ , is defined as the subsurface runoff (interflow) curve within the thawing active layer. ∅ is the average soil porosity (%), and G is the snowmelt water (mm). The factor

1 − β#$A  that appears in equations (4) and (5) refers to the catchment area with soil water content less than the soil’s field capacity or water-saturated condition. At temperatures that are less than the soil temperature threshold, meltwater from snow G is an important factor in the water balance of the area contributing to runoff (DeBeer and Pomeroy, 2010). The meltwater from snow G was calculated using the degree-day factor method (equation (6))when there was continuous snow cover for at least two days based on the sensor data, or using the air temperature threshold method directly when there was discontinuous snow accumulation and mixed snow and rain occurred (equation (7), Chen et al., 2014). G = QCR − CR S

FCRV − CR  WC − C  CR < CR < CRV RV R X Q = U F CR ≤ CR

(6)

(7)

where P is the precipitation as snow (mm) in study area. CR , CR , CRV is the air temperature, lowest threshold temperature below which the precipitation is snow (oC), and the highest threshold temperature above which the precipitation is rain (oC), respectively. CR is the 14 / 46

initial air temperature of snowmelt. a, b are the degree-day factor that are obtained from

Yang et al (2000). E is the actual daily evapotranspiration estimated by field observations, as explained in section 2.3 below. When the surface soil temperature increases from less than 0℃ to 0℃, the frozen soil begins to thaw, and till to reaching T\ , the liquid water content within the thawed surface layer reaches the field capacity or water-saturated condition, in the equation (4) was applied to calculate the saturation excess runoff generation. Otherwise, the saturation excess runoff was calculated using equation (5) when #$ < #$A and 0 ≤ C ≤CA . Although the runoff calculated from equations (4) and (5) belong to the same type of saturation excess runoff, SERG, there is an essential difference. R in equation (4) indicates saturation due to earlier thawing episodes, where meltwater stored in the soil and snow meltwater infiltration saturated the surface thawed soil layer, as happens in wetlands. On the other hand, the R in equation (5) is related to excess storage runoff generation where previous soil water content was small and demanded relatively large amounts of infiltration from precipitation and snowmelt to reach the field capacity of the surface soil layer. Along with the deeper active layer thawing, the fundamental assumption is that the surface infiltration excess runoff occurred in places where saturation excess runoff generation stopped after #$ < #$A and T ≥CA . The runoff generation during autumn freezing period is another attentional process focussed in this study. There are two directions of freezing processes, i.e., from surface downward and from active layer bottom upward. Downward ground freezing controls surface runoff generation and the recharge of suprapermafrost groundwater, whereas upward 15 / 46

ground freezing affects the discharge of groundwater (especially suprapermafrost groundwater). In the study catchment, the depth at which the downward and upward ground freezing fronts meet is at 50-60 cm, and the depth of the active layer in most slope areas is approximately 120-180 cm (Chang et al., 2015; Wang et al., 2010). Considering that the effects of downward ground freezing could directly cause the groundwater level to drop and that the relatively quicker upward freezing process directly transforms the groundwater in the aquifer into ice, the upward freezing process is the dominant driving force that reduces the groundwater discharge. In some headwater catchments of the permafrost region on the QTP, a few studies have found that ice accumulated quickly at the bottom of the active soil layer from autumn to winter in the lower parts of slopes, while the suprapermafrost groundwater could be completely evacuated during late autumn and winter in the upper parts of slopes (Yang et al., 2000; Chang et al., 2015). Generally, groundwater flow starts to decrease in middle September, as temperatures decline, and stops from the end of October to the following April (Ge et al., 2011; Chang et al., 2015). Along with the freezing of the active soil layer, the discharge of suprapermafrost groundwater accounts for approximately 60-80% of total recession runoff during autumn season (Liu et al., 2012; Wang et al., 2009). Lyon et al. (2009) and Lyon and Destouni (2010) proposed an approach of using the relationship between the recession rate and the active soil depth to simulate the variation of active soil depth during freezing period. Using this approach, an equation was developed in this study that relates groundwater discharge to the soil temperature (C2] ) at or near the

lower boundary of the active layer zC2] . As with the freezing fronts rising during freezing period, the saturation excess runoff generation would be occurred and became the dominant 16 / 46

type of surface runoff generation in some upper parts of the catchment. After the surface soil is frozen, the surface infiltration excess runoff generated from snowmelt is also neglected because of the small amount of autumn snow cover in the study catchment. Thus, runoff production during the autumn freezing period is primarily composed of surface saturation excess runoff and groundwater discharge. Equation (1) can be changed as follows:
= F + G − H  − 2 3 2B 7

1 − β#$A #$ + zC2]  (8)

where C2] is defined as the soil temperature at or near the bottom of the suprapermafrost groundwater aquifer (approximately is equal to the soil temperature at or near the lower boundary of the active layer during the active layer entirely thawed period). zC2]  is defined as the suprapermafrost groundwater discharge function that varies

with C2] and is determined using the regression relationship between the autumn runoff

recession rate and C2] (Lyon et al., 2009; Lyon and Destouni, 2010). The groundwater discharge mainly related the suprapermafrost aquifer because there is no discharge of subpermafrost groundwater in the studied headwater catchment. Although zC2]  is mainly developed by using the correlation between groundwater discharge and the soil temperature at or near the bottom of the suprapermafrost groundwater aquifer, variations in groundwater discharge actually include the effects of both downward and upward ground freezing. Parameter determination. All the parameters used in this study are listed in Table 2. The saturated soil temperature at field water capacity, T\ , is a special parameter that varies with climate, vegetation cover and topographic conditions and can be determined using high-precision land surface models and field observations. In the study catchment, we obtained a value for T\ and its dynamics corresponding to the soil water content at field 17 / 46

capacity through field observation. According to the observation data, the surface soil moisture (top 20 cm) was found to be at its spring peak volume of 40 to 60% (volumetric soil moisture) with the soil field water capacity of 23-37% (Table 2), when the zero isotherm during thawing was above a depth of 40 cm (Wang et al. 2009, 2012). It was also found that runoff processes was closely correlated with the surface soil temperature (at top 20 cm depth) rather than precipitation from April to June when the depth of the thawed active layer was less than 50 cm (Wang et al., 2009). Thus, the surface soil temperature threshold, (CA − C! , was determined as the point where the zero isotherm reached a depth of 40 cm during the spring thawing period. It is assumed that the S`\ in the top 20 cm determined the suitability of equation (4) to simulate surface runoff generation from surface saturation excess and that S`\ at a depth of 40 cm determined the suitability of equation (5). The freezing point temperature, C! , soil field water capacity, 9A , and the surface soil infiltration rate, a , were all

obtained from field observation and are listed in Table 2. There are two ways to determine the C2] , one is the spatialization of C2] using spatializing models based on adequately spatial observation data within catchment area, and another is approximate estimation of C2] using spatial mean algorithm for limited spatial observation data. The second approach is the suitable way in most permafrost catchment due to the limitation of field observation. From the data of the three suprapermafrost groundwater level monitoring sites at different elevation in the study catchment, the thickness of the suprapermafrost groundwater aquifer was found to range from 140 cm on lower section to 70 cm on upper section during 2012 to 2015. Using spatial mean algorithm, the thickness of active layer and the suprapermafrost groundwater aquifer at the mid-slope 18 / 46

point is approximately determined as the mean thickness of the whole catchment. Thus, the soil temperature at a depth corresponding to two-thirds of the thickness of the suprapermafrost aquifer at the mid-slope point was used to identify C2] . Of the field monitoring data collected from September 2012 to July 2015 in the study catchment, the observations of mean daily soil temperature C2] and the groundwater discharge during the autumn runoff recession period from 1 September to 20 October 2012 were used to determine zC2] . Moreover, the observations of spring runoff processes during the thawing period from 1 June to 20 July 2013 were integrated with observations collected during the freezing period from September to 20 October 2012 to determine the freezing point temperature, C! , and the fitting parameter, -. Normally, the residual water saturation is

obtained from the soil–water characteristic curve (SWCC), or from freezing function curve (McKenzie et al., 2007). In this study, the initial values of - and Sr were obtained from Ge et al. (2011) due to the same study area. Then, the data from the two spring thawing seasons in 2014 and 2015, as well as the data from the two autumn freezing seasons in 2013 and 2014, were used to test and verify the approach described by equations (4) - (5) and (8). Because more than 87% total area of the study catchment covered with vegetation coverage of 60-95%, the actual average daily evapotranspiration, E, is approximately estimated using area weighted average (AWA) approach with the field-observed daily E values of 93% and 67% vegetation coverage using weighing lysimeters method from 2012 to 2014. In the spring season, precipitation increased, accompanied by snow and mixtures of snow and rain. Thus, we determine snow with the snow monitoring sensor data (snow accumulated and lasted over two days) combing with division method of threshold air 19 / 46

temperature from daily precipitation (Chen et al., 2014).The major flowcharts of the new approach development and practice of the study permafrost watershed in semi-arid Tibetan plateau are schematically shown in Fig. 3.

RESULTS AND DISCUSSION Runoff generation processes during the thawing period Using the new approach of equations (4) and (5), the daily runoff of the study catchment was simulated for the spring thawing period and the results are shown in Figure 4a. It was found that the new approach of equation (4) yielded excellent simulation accuracy with the correlation coefficient (R2 ) of 0.971 between the simulated and observation runoff and the NSEC (Nash–Sutcliffe model efficiency coefficient) more than 0.94 (Fig. 4b). In previous study, the Cold Regions Hydrological Model platform (CRHM) was conducted in this watershed with intensive observation of 64 parameters (Zhou et al., 2014). By replacing the soil infiltration algorithm describing frozen soil infiltration (using Gray’s expression for frozen soil infiltration) in the CRHM during the spring period, the coefficient of determination for the linear regressions R2 and NSE values between simulated and observed streamflows are improved from 0.58 and 0.55 to 0.87 and 0.79, respectively (zhou et al., 2014). Comparison of this study with the previous study shows that the new approach has a significant improvement in the simulation of spring runoff generation. The results also mean the saturation excess runoff generation controlled by thawing processes of surface active layer could be used to entirely explain the spring runoff generation in permafrost catchment.

Figure 4a shows a comparison of simulated and observed variations in runoff with 20 / 46

increasing thawing depth over the thawing period. Before the end of June, the simulated discharge agrees well with the observations, with relative errors below 6.6% in both 2014 and 2015. However, the relative error increased to 13.4% and 15.4% in July 2015 and 2014, respectively. Considering the spatial variations in 9A and ∅ and the systematic errors involved in the lumped model, these relative errors are acceptable. In fact, the suprapermafrost groundwater aquifer in the lower parts of the catchment would be partly thawed and provide discharge to the total runoff after the end of July in this study catchment, but this discharge is not represented by equation (4) due to the assumptions mentioned above, which is also one of the causes of the increase in simulation error in July. The greater amounts of precipitation that occurred in June and July of 2015 resulted in larger spring runoff than in 2014. From the end of June to the first ten days of July 2015, the precipitation was larger than that in 2014 by 96%, which resulted in the much larger surface runoff that occurred in July 2015. Thus, the thawing processes of the surface part of the active soil layer control the pattern of saturation excess runoff generation during the spring season, but precipitation affects the runoff volume and the associated diagram in June and early in July (Fig. 4a). During the spring season, subsurface runoff (interflow) within the thawing active layer,
P , which is formed from ice melt within active soil and snow meltwater and rainfall

infiltration, commonly shows a single peak (Fig. 5).
P increased quickly with the surface active soil temperature and then reached its peak flow at a certain soil temperature threshold (CA − C! . After that point, the interflow decreased quickly with increasing soil temperature.

The
P accounted for approximately 14.4% of total runoff in 2015 and 34.1% of total 21 / 46

runoff in 2014. The ratio of
P /R has an inverse relationship with spring precipitation, i.e., the larger the spring precipitation is, the lower the
P /R ratio will be. However,
P varied significantly with soil temperature (coefficient of determination R2≥0.45, p<0.001 using a standard t test), and there is no statistically significant relationship between precipitation and interflow (R2≤0.15, p≥0.17). This result indicates that the soil temperature determines the interflow pattern but that spring precipitation controls the volume of
P and the ratio
P /R. The generation and dynamics of
P shaped the spatial and temporal pattern of the runoff coefficient in the permafrost catchment. In the headwater catchment studied, the 10-day average runoff coefficient reached its peak of 0.43 at the end of June and decreased to only 0.13 in the middle of July. When the water content of the soil above a depth of 20 cm was below the soil water field capacity, the thawed soil depth extended to 40-60 cm with the surface soil temperature was above the threshold in the study catchment. Along with the developing of thawed depth and gradual drying of the surface soil layer, a large portion of the precipitation infiltrated into the active soil layer to replenish the soil moisture, which reduced the runoff coefficient and the contributing area of saturation excess runoff generation. In the study headwater catchment, the monthly mean runoff coefficient decreased from 0.39 in June to 0.06 in August. In the Fenghuoshan watershed with area of 117 km2 , where the study headwater catchment located in as one of the primary tributaries, the monthly mean runoff coefficient was also found to decrease from 0.60 in June to 0.24 in August. Thus, the initial thawing, including thawing of the surface active soil layer and melting of snow, formed the spring flood flow by saturation excess runoff generation that enhanced the increase in the runoff 22 / 46

coefficient. After the active thawing depth reached the threshold point during the late of spring season, the surface runoff generation was significantly restricted and the recession process was formed by infiltration excess runoff generation under drying surface soil layer. In permafrost catchment, the surface soil temperature dynamics controlled the spring runoff processes by changing the saturation excess runoff generation area.

Runoff generation processes during the freezing period After using the Levenberg-Marquardt and Universal Global Optimization methods (Price et al., 2005; Nocedal and Wright, 1999) and the field monitoring observations of mean daily soil temperature C2] and groundwater discharge during the autumn runoff recession period, the following function for zC2]  was obtained: zC2]  = 0.72& .efghi

(Fig. 6). Equation (8) was then parameterized and used to simulate the runoff recession processes during the freezing period of two autumn seasons in 2013 and 2014, respectively (Fig. 7). The new approach, which treated mixtures of surface runoff generation and suprapermafrost groundwater discharge, represent subtle features of the runoff recession processes in autumn season. Although the modelling results of the new approach (equation (8)) slightly underestimated the actual discharge, the simulated runoff curve was in well agreement with the actual fluctuation of the autumn runoff recession (Fig. 7a). In general, the new approach has a high simulating precision with the correlation coefficient (R2=0.836, p=0.0001; Fig. 7b) that exhibited satisfactory precision. The fitting RMSE (root mean square error) and the RE (relative error) between the measured and the estimated runoff values are 0.66 mm and 8.7%, respectively. Thus, the new approach of equation (8), which 23 / 46

integrates the variations in the surface runoff generation and suprapermafrost groundwater discharge, has a high validity in clarifying the effects of soil freezing processes on runoff recession processes in permafrost catchments. The runoff processes clearly differed between 2013 and 2014 (Fig. 7a). In 2013, the precipitation during the summer season (from July to August) was only 56.7% of that in 2014. Moreover, the mean surface soil temperatures during the autumn freezing period, including September and October, in 2013 were 1.41℃ and 0.4℃ lower, respectively, than the values for the same months in 2014. These values indicate clear differences in climate conditions between the autumn seasons of 2013 and 2014. That is, the autumn of 2013 was drier and colder, and the autumn of 2014 was wetter and warmer. The plentiful rainfall during the summer could increase the recharge of suprapermafrost groundwater, which would increase the discharge of groundwater to surface river flow. Meanwhile, the warmer soil temperature in autumn could have postponed the time of freezing of the surface soil and the suprapermafrost aquifer, which favours increased surface runoff generation and suprapermafrost groundwater discharge and postpones the runoff recession time. Thus, the recession discharge during the autumn freezing period in 2014 was larger and persisted longer than that in 2013 (Fig. 7a). In headwater watersheds in permafrost regions, differences in summer precipitation and autumn soil temperature control the interannual variability of runoff recession patterns during the autumn freezing period. In permafrost region, approximately all of river base-flow and most of total river flow in autumn and winter season are contributed by groundwater discharge (Liu et al., 2012; Boucher and Carey, 2010), and it was recently inferred increases in groundwater discharge 24 / 46

of several (sub-)Arctic rivers with permafrost warming [Smith et al., 2007; Lapp, 2015]. Because the function zC2]  in equation (8) presented as a proxy for variations in groundwater discharge in this study, we used it to approximately separate the groundwater discharge from the total surface runoff. The results show that the contribution from groundwater discharge ranges from approximately 83.0% of the total river runoff in September to 90.8% in October during the autumn recession period in 2014 (Fig. 8a). The results for 2013 are similar; the groundwater discharge contribution increased from 74.3% in September to 100% in October. This result is consistent with the results of earlier studies using stable isotope measurements, such as Liu (2012), who investigated the same watershed, and Lapp (2015), who investigated Arctic rivers. The direct runoff, which is formed by fast-moving interflow and surface runoff fed directly by rainfall, accounted for an average of 25.2% and 17.2% of the total runoff in autumn recession of 2013 and 2014, respectively.. Figure 8b shows that the direct runoff (rather than total runoff) has a highly significant relationship with precipitation (R2=0.839, p<0.001) during the autumn freezing period. This result implies that precipitation only plays a small role in terms of direct runoff (accounted less than 25% of total runoff), but the deep soil temperature controls the total runoff by through changing the groundwater discharge during the autumn recession processes. From 8 September to 10 October, the total runoff decreases exponentially in response to the variation of soil temperature in the deep soil layer (90 cm depth) with a ratio of 1.38 mm per 1℃, while the suprapermafrost groundwater discharge decreased by 1.35 mm per 1℃. Therefore, the impacts of soil freezing on runoff processes are mostly contributed by variations in suprapermafrost groundwater discharge. However, the direct runoff coefficient 25 / 46

increased from 0.44 to 0.89 in 2013 and 0.21 to 0.73 in 2014 (Fig. 8a), meaning that the freezing of the surface soil enhanced the efficiency of surface runoff production from rainfall. Under the effects of bidirectional freezing of the active layer (i.e., downward freezing from the surface and upward freezing from the bottom of the active layer), most of the decrease in suprapermafrost groundwater discharge (approximately 92%) occurred before the soil temperature at a depth of 90 cm decreased to 0.5℃. Consequently, autumn freezing of the active layer resulted directly in the rapid end of the runoff recession process before November in this permafrost headwater catchment. Those results imply that the soil temperature increase caused by climate warming would enhance groundwater discharge and lengthen recession processes of autumn and winter season, which are in qualitative agreement with the recently inferred increases in groundwater discharges of several Arctic rivers during winter season (Walvoord et al., 2007).

CONCLUSIONS The contributing-area concept is defined by this study as a nonlinear relationship with soil temperature rather than soil moisture during spring and autumn season in a permafrost catchment.

By modifying the soil water storage capacity curve with the effects of active

soil freeze-thaw cycle, we develop a new quantitative approach to simulate the spring and autumn runoff processes in permafrost headwater catchments. The new approach successfully fills the gap in quantitative approaches in modelling of runoff generation processes in permafrost catchments of the semi-arid plateaus where the saturation excess runoff generation and the infiltration excess runoff generation alternately occurred from spring to autumn season. 26 / 46

During the initial spring thawing period, saturation excess runoff and subsurface interflow within the thawed active layer are the dominant runoff components supported by the shallow freeze front. In a permafrost headwater catchment on the semi-arid TP, the subsurface interflow may account for approximately 14-34% of total spring runoff. It increases linearly before the threshold point when the thawed soil layer reaches a depth of 40 cm, and then exponentially decreases with the enlargement of the active layer. This process results in a linear decrease in the runoff coefficient from initial period of early spring to summer. Although there is no statistically significant relationship between runoff and precipitation during the spring season, larger amounts of spring precipitation resulted in larger interflow and lower ratios of interflow to total runoff. During the autumn freezing period, the groundwater discharge is the dominant source of runoff generation, contributing more than 75% of the total river runoff in the permafrost headwater catchment of the semi-arid TP. From early September to the end of October, the suprapermafrost groundwater

discharge decreases exponentially with active layer frozen processes, whereas the ratio of contributions from groundwater discharge to total runoff lineally increases. Meanwhile, the direct surface runoff coefficient increased by more than three times although the contribution of surface runoff to total runoff decreased by more than 80%. The bidirectional freezing of the active layer controls the autumn runoff recession processes and runoff composition, while the variations of summer precipitation and autumn air temperature could shift the interannual pattern of autumn runoff recession. The soil temperature variation of the active layer under seasonal cycles of freezing and thawing is the crucial variable that shapes the runoff generation pattern in spring and autumn. 27 / 46

In the future, with increased warming, the spring runoff period will occur sooner and be shorter with more variation interannual spring runoff value affected by shifts of spring precipitation. Meanwhile, the autumn runoff period will appear more delay and more extension of recession with more groundwater discharge into rivers in the freezing season. We anticipate that the approach and insights provided here will begin to aid in establishing process-based hydrological models allowing the coupling of groundwater flow and surface hydrological and climate models in permafrost regions on the semi-arid and arid TP.

Acknowledgements: This study was funded by the Natural Science Foundation of China (No.

91547203 ) and the National Basic Research Program of China (No. 2013CBA01807). The majority of data used in this analysis are freely available from the authors, Dr. Wang Genxu by email: [email protected], or from Dr. Mao, [email protected]. We are grateful to the anonymous reviewers for their valuable comments on this manuscript

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Captions of Figures Figure 1 Study catchment in the experimental Fenghuo Mountains located in centre permafrost region of Qinghai-Tibet plateau, China. The soil temperature and moisture monitoring sites in the headwater catchment are used in this study. At each site, there was a 1.6-m-deep borehole for soil temperature and moisture monitoring. Figure 2. Background of soil temperature and humidity in the study catchment, (a) spatio-temporal differences of soil temperature at a 10-cm and 90-cm depth with different elevations of 4920 m and 4870 m a.s.l., respectively; (b) spatio-temporal differences of soil moisture dynamics at a 10-cm and 90-cm depth with different elevation of 4920 m and 4870 m a.s.l., respectively. Figure 3. The flowchart diagram illustrating the major steps of the approach development and practice in the study permafrost watershed. Figure 4 Comparison of simulating hydrograph with field-observed runoff processes during the spring thawing period, (a) Fitting hydrograph of simulation using equation (4) and (5) with observation in 2014 and 2015, respectively, the inset chart shows the precipitation differences in June and July of 2014 and 2015; (b) Correlation between simulation runoff and observation runoff with two spring seasons’ data of 2014 and 2015 for fitting analysis that exhibited highly precision. The dotted line is 1:1 line while the solid line is the fitting trend with R2=0.971. Figure 5. The variation of the interflow
P from the infiltration of ice melt and meltwater from snow during earlier thawing processes that saturated the surface thawed soil layer 34 / 46

in the permafrost catchment. Figure 6 Based on field monitoring of mean daily soil temperature C2] at a depth of 90 cm depth on the mid-slope point (4870 m a.s.l.) and the runoff during the autumn runoff recession period, the relationship between suprapermafrost groundwater discharges and C2] is approximately determined using the statistical regression method.

Figure 7 Comparison of simulated hydrograph with observed runoff during the autumn recession processes in two years of 2013 and 2014. (a) Fitting runoff hydrographs of simulation using equation (6) with observation during autumn season in 2013 and 2014, respectively. The inset charts shows the differences of soil temperature at top 20 cm depth in September (Ts-9) and October (Ts-10), and the differences of precipitation during summer season in 2013 and 2014, respectively. (b) Correlation between simulation runoff and observation runoff with two autumn seasons’ data of 2013 and 2014 for fitting analysis; Solid line indicated the fitting trend, and dotted line indicated the 1:1 trend. Figure 8. The mean half month ratio of groundwater discharge to total runoff (denoted by bar graph), direct runoff coefficient (denoted by broken line) and their variations during autumn runoff recession (left, a). The numerical value indicates the precipitation at different period. Simple scatterplot for correlation analysis between the precipitation and the runoff (right, b), white circle indicate the total runoff, that exhibited the middle statistical significance with Pearson correlation analysis (R2=0.357, p<0.01), and black circle indicate the direct runoff that exhibited the highly significant correlation with Pearson correlation analysis (R=0.83, p<0.001). 35 / 46

Table 1 Some information of advices used in this research Name of Advices Soil temperature sensor

Characteristics

Production Company

Accuracy

HMP45AC, a thermal

Vaisala, Finland

±0.02°C

Campbell, USA

±2%

resistance sensor Soil moisture sensor

CS616,

a

frequency

domain reflectometer Snow depth sensor

SR50A, a ultrasonic

Campbell, USA

pulses transducer Ground water level

HOBO U20, built-in

Data Loggers

pressure type

Daily rainfall monitor

52202-L30, leveling

resolutions of 0.25 mm with ±1 cm

ONSET, USA R. M. Yong, USA

adjustment,

resolution of 0.014 kPa with 0.14 cm. resolutions of 0.1 mm with 2%-3%

thermostatic control air temperature monitor

HMP155-L15, stability and withstands for

Vaisala, Finland

±1%RH, ±2% standard deviation limits

harsh environments

36 / 46

Table 2. Model parameters used in this study Parameter

Description

Value

Unit

E

actual daily evapotranspiration

measured

mm



Surface soil infiltration rate

0.33-0.65

mm/min

9

infiltration capacity curve

measured

mm/min

9A ,

study period

9

Soil field water capacity

23.0-37.0

%

saturated water contents

measured

m3/m3

residual water contents

0.05

m3/m3

K

.

hydraulic conductivity

(m/s)

permeability

m2

ks

saturated permeability

Sr

#$A

Residual water saturation

0.05*

Soil water saturation at field water capacity

0.57-0.64

T

C!

soil temperature

C

Freezing point temperature

CA

actual soil temperatures at site E in the study measured

°C

watershed

C2]

soil temperatures at water saturation

°C

P



daily precipitation




rainfall intensity




catchment




infiltration excess runoff production

mm

saturation

mm

4

catchment

-

impedance factor

5*

Fitting parameter

0.1*

a

9%

soil water content of the study site during the measured

1×10−13*

%

m2

°C -0.7-0.0

measured

soil temperature at the bottom of the measured

°C

°C

suprapermafrost groundwater aquifer mm

measured

saturation excess runoff in non-permafrost

excess

runoff

in

37 / 46

mm/min mm

permafrost

∅

W0

Soil porosity

36.0-65.0

%

previous soil water content

measured

%

Note, * indicates that the value is obtained from Ge et al. (2011)

38 / 46

Figure 1

Figure 1 Study catchment in the experimental Fenghuo Mountains located in centre permafrost region of Qinghai-Tibet plateau, China. The soil temperature and moisture monitoring sites (in each site, there was a 1.6-m deep borehole for soil temperature and moisture monitoring) in the headwater catchment are used in this study (That is also seen in detail in Wang et al., 2015).

39 / 46

Figure 2

15.0 4920-10cm

a

4920-90cm

10.0

Soil temperature (

)

4870-10cm 4870-90cm

5.0

0.0

-5.0

-10.0 28-Mar27-Apr27-May26-Jun 26-Jul 25-Aug 24-Sep 24-Oct 23-Nov

140.0

b 120.0

4870-90cm 4870-10cm

Soil moisture (%)

4920-90cm 100.0

4920-10cm

80.0 60.0 40.0 20.0 0.0 12-Apr 12-May 11-Jun 11-Jul 10-Aug 9-Sep 9-Oct 8-Nov

Figure 2. Background of soil temperature and humidity in the study catchment, (a) spatio-temporal differences of soil temperature at a 10-cm and 90-cm depth with different elevations of 4920 m and 4870 m a.s.l., respectively; (b) spatio-temporal differences of soil moisture dynamics at a 10-cm and 90-cm depth with different elevation of 4920 m and 4870 m a.s.l., respectively.

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Figure 3 Meteorological observation of P, Ta; Field observation of E, soil temperature T, , and ; soil moisture , and

Determining the

,

,

Runoff of Spring season ≤ Equation (4)

,

,

Runoff of Autumn season

≤ Equation (5)

Equation (8)

Parameter determination and model verification and validation simulation of spring and autumn runoff

separate the composition of the total runoff

Figure 3 The flowchart diagram illustrating the major steps of the approach development and practice in the study permafrost watershed

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Figure 4

Observation15

7

Simulation15 Observation14

6 Runoff (mm)

Precipitation (mm)

80

8

Simulation14

5

a

60

2015 2014

40 20 0 June

July

4 Thawing processes

3 2 1 0 17-Jun 21-Jun 25-Jun 29-Jun 3-Jul

8.0

7-Jul

11-Jul 15-Jul 19-Jul

b

Simulation runoff (mm)

7.0

1:1 line

6.0 5.0 4.0

R² = 0.971

3.0 2.0 1.0 0.0 0.0

1.0

2.0 3.0 4.0 5.0 Observation runoff (mm)

6.0

7.0

Figure 4 Comparison of simulating hydrograph with field-observed runoff processes during the spring thawing period, (a) Fitting hydrograph of simulation using equation (4) and (5) with observation in 2014 and 2015, respectively, the inset chart shows the precipitation differences in June and July of 2014 and 2015; (b) Correlation between simulation runoff and observation runoff with two spring seasons’ data of 2014 and 2015 for fitting analysis that exhibited highly precision. The dotted line is 1:1 line while the solid line is the fitting trend with R2=0.971.

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Figure 5

0.3 2015

2014

Interflow
in (mm)

0.25 0.2

0.15 0.1

0.05 0 15-Jun 20-Jun 25-Jun 30-Jun

5-Jul

10-Jul

15-Jul

20-Jul

25-Jul

Figure 5. The variation of the interflow
P from ice melt snow melt water infiltration during earlier thawing processes that saturated the surface thawed soil layer in a permafrost catchment..

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Figure 6 7.0

Freezing processes

6.0 y = 0.7199e0.6157x R² = 0.8398

Runoff (mm)

5.0 4.0 3.0 2.0 1.0 0.0 0.0

0.5 1.0 1.5 2.0 2.5 3.0 soil temperature at 90 cm depth ( )

3.5

Figure 6 Based on the field monitoring data of mean daily soil temperature C2] at 90 cm depth located on the mid-slope point of 4870 m and the runoff during the autumn runoff recession period, the relationship between suprapermafrost groundwater discharge varied with C2] is approximately determined by using statistic regression method.

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Figure 7

7

Simulation 2014 Observation 2014

6

Runoff (mm)

5

160

P

140

Ts-9

120

Ts-10

2.5 2 1.5

100 80

1

60

0.5

40 0

20 0

-0.5 2013

4

)

a

Soil temperature (

Observation 2013

Precipitation (mm)

Simulation 2013

2014

Freezing Processes

3 2 1

0 31-Aug 5-Sep 10-Sep 15-Sep 20-Sep 25-Sep 30-Sep 5-Oct 10-Oct

b

Figure 7 Comparison of simulated hydrograph with observed runoff during the autumn recession processes in two years of 2013 and 2014. (a) Fitting runoff hydrographs of simulation using equation (6) with observation during autumn season in 2013 and 2014, respectively. The inset charts shows the differences of soil temperature at top 20 cm depth in September (Ts-9) and October (Ts-10), and the differences of precipitation during summer season in 2013 and 2014, respectively. (b) Correlation between simulation runoff and observation runoff with two autumn seasons’ data of 2013 and 2014 for fitting analysis; Solid line indicated the fitting trend, and dotted line indicated the 1:1 trend.

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Figure 8

22.3

0.8

1.5 12.8

1.8

1 0.8

14.5

0.7

0.7

0.6

0.6

0.5

0.5

0.4

0.4

0.3

0.3

0.2

0.2

0.1

0.1

0

6

0.9

Direct runoff

b

Total runoff

5 Runoff (mm)

Ratio of groundwater to runoff

18.3

Direct runoff coefficient

a

1 0.9

R² = 0.357

4 3 2

R² = 0.8394

1

0 1-15 Sep 2013

16-30 Sep 1-10 Oct 2014 2013-Rc 2014-Rc

0 0

2

4 6 precipitation (mm)

8

10

Figure 8. The mean half month ratio of groundwater discharge to total runoff (denoted by bar graph), direct runoff coefficient (denoted by broken line) and their variations during autumn runoff recession (left, a). The numerical value indicates the precipitation at different period. Simple scatterplot for correlation analysis between the precipitation and the runoff (right, b), white circle indicate the total runoff, that exhibited the middle statistical significance with Pearson correlation analysis (R2=0.357, p<0.01), and black circle indicate the direct runoff that exhibited the highly significant correlation with Pearson correlation analysis (R2=0.839, p<0.001).

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