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Sciences in Cold and Arid Regions ›› 2020, Vol. 12 ›› Issue (1): 34-46.doi: 10.3724/SP.J.1226.2020.00034.

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Soil-moisture dynamics and tree-water status in a Picea crassifolia forest, Qilian Mountains, China

Hu Liu1,2,Lin Li1,2,3,SiJia Wang1,2,3,QiYue Yang1,2,WenZhi Zhao1,2()   

  1. 1.Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Lanzhou, Gansu 730000, China
    2.Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
    3.University of Chinese Academy of Sciences, Beijing 100029, China
  • Received:2019-07-01 Accepted:2019-09-10 Online:2020-02-29 Published:2020-03-17
  • Contact: WenZhi Zhao E-mail:zhaowzh@lzb.ac.cn

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Abstract:

Landscapes of the mountainous regions in northwestern China comprise a unique pattern of vegetation, consisting of a mosaic of grassland and shrub-forest. Forests generally self-organize into ordered structures and coalesce into blocks on north-facing slopes or stripes along southeast-facing slopes, with Picea crassifolia being the most representative and dominant tree species. We investigated the tree-water status and soil-moisture dynamics at a forest site (Guantan) of the Qilian Mountains in northwest China. The 30-minute-interval measurements of tree-sap flow during the growing season of 2008 are presented, and the potential functional relations between tree transpiration and environmental factors are evaluated. Soil moisture and solar energy were identified as the most influential factors, explaining more than 70% of the variance in sap flow. Based on field measurements obtained at the forest site, a stochastic model of soil-moisture dynamics was tested; and the steady-state probability density functions (PDFs) of the long-term soil-moisture dynamics and static tree-water stress were estimated using the validated model and parameters. We found that the model reproduced measured soil moisture well, despite all the simplifying assumptions. The generated PDF of long-term soil moisture was relatively open, with middle to low average values; and the calculated density of the static tree-water stress at the forest site was largely concentrated between 0 and 0.6, suggesting a moderate water-stress situation in most cases. We argue that both water and energy are limiting factors for vegetation at the forest site. In addition, the tradeoff between reduced evapotranspiration (ET) from limited solar energy and increased soil-moisture availability may create a stressed but tolerable environment and, in turn, produce a relatively constant ecological niche favorable to Picea crassifolia growth.

Key words: sap flow, soil moisture, stochastic modeling, semiarid alpine ecosystem

Figure 1

Self-organized alpine landscapes in arid northwest China. The forests generally self-organize into ordered structures and coalesce into blocks on shady slopes ((a), north-facing) or stripes along half-shady slopes ((b), southeast-facing) in the altitude range of 2,600 to 3,200 m; and (c) location of the study (Dayekou catchment, modified from Yang et al. (2005))"

Table 1

Structural characteristics of Picea crassifolia forest on south-facing shady slopes in the Dayekou watershed, Qilian Mountains"

PlotsSlopeAspectAltitude (m)Density (h/m2)Height (m)DBH (cm)Canopy gapLAI (m2/m2)
130°25°2,6551,3509.847.4168.98%0.4-1.5
227°30°2,8352,4759.447.1377.02%1.8-3.2
325°12°2,8892,2257.787.1380.34%2.4-2.8
421°8°3,0052,2007.047.2071.70%2.2-2.7
522°18°3,1068256.882.4957.01%1.8-2.4
634°355°3,2603755.212.4322.15%0.7-1.9

Figure 2

Time evolution of the sap-flow density and microclimate elements at the Guantan forest site during the growing season of 2008: (a) daily average sap-flow density and eddy-covariance evapotranspiration; (b) vapor-pressure deficit and net solar radiation; (c) relative soil moisture and rainfall; and (d) air and soil temperature"

Table 2

Biometric and physiological parameters of sap-flow measurements"

No.Stem diameter at breast height (mm)Canopy-base height (m)Height (m)Crown width (m)Sapwood radius (m)Bark depth (mm)Sapwood area (mm2)
115.14.613.83.43379,569
219.34.914.24.337718,710
336.35.716.24.840733,422

Figure 3

Hourly courses of sap flow, net radiation, and vapor-pressure deficit (VPD) on typical days of the growing season: (a, b) bright days (May 11 and July 5, 2008, representing frost-affected and frost-unaffected days, respectively), (c) cloudy day (September 7, 2008), and (d) rainy day (August 11, 2008, 8.6-mm precipitation)"

Figure 4

Relationship between daily sap-flow rate and (a) solar radiation, (b) soil moisture, and (c) vapor-pressure deficit (VPD) for the forest site during the entire growing season; piecewise fit curves for the open-circle data points are shown with the solid line"

Table 3

Parameters of soil, plant, and climate characteristics at the forest site*"

ParametersUnitsDescriptionValue
n-Soil porosity, Equation (2)0.77
ZrcmRoot-zone depth, Equation (2)60.00
sw-Wilting point, Equations (2, 3)0.19
s*-Point of incipient stomatal closure, Equations (2, 3)0.57
sfc-Field capacity, Equation (3)0.71
ΔmmCanopy-interception threshold1.00
k-Canopy-throughfall coefficient, Equation (3)0.85
Emaxmm/dayMaximal evapotranspiration rate3.90
αmmLong-term mean rainfall depth per event6.70
λ/dayLong-term rainfall frequency0.51
q-Measure of the nonlinearity, Equation (3)3.00*

Figure 5

Relationships (a) between the sap flow and soil moisture, and (b) between the eddy-covariance ET and soil moisture over the root-zone depth of 0-60 cm during the period of July 1 to September 30, 2008 (when soil moisture was drying out and there was no rainfall); piecewise fit curves are shown with the solid line; sw , s*, and sfc refer to the wilting point, the point of incipient stomatal closure, and the filed capacity, respectively"

Figure 6

Daily precipitation (bars, right scale); measured (line) and calculated (circle) daily average soil-moisture content (left scale) for the period of July 1 to September 30 in (a) 2008 and (b) 2010. Comparison between measured and modeled soil moisture shows the corresponding cumulative distribution functions (CDFs), probability density functions (PDFs), and histograms of the data for the period of July 1 to September 30 in (c) 2008 and (d) 2010. The parameters used for soil characteristics were sw = 0.19, s* = 0.57, and sfc= 0.71"

Figure 7

(a) Estimated PDFs of the long-term soil moisture s and (b) static water stress ζ for the forest site (the atoms of probability at ζ=0 and ζ=1 are 1.5 and 0.6, respectively). Parameters of the graphs are α = 6.7, λ = 0.51, Emax =4.4, and q = 3"

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