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Sciences in Cold and Arid Regions ›› 2019, Vol. 11 ›› Issue (1): 62-80.doi: 10.3724/SP.J.1226.2019.00062

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How changes of groundwater level affect the desert riparian forest ecosystem in the Ejina Oasis, Northwest China

HaiYang Xi1,2,*(),JingTian Zhang1,4,Qi Feng1,2,Lu Zhang3,JianHua Si1,2,TengFei Yu1,2   

  1. 1. Key Laboratory of Ecohydrology of Inland River Basin, Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
    2. Alashan Desert Eco-hydrology Experimental Research Station, Ejina, Inner Mongolia 735400, China
    3. CSIRO Land and Water Flagship, Canberra, ACT 2601, Australia
    4. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2018-08-23 Accepted:2018-10-30 Online:2019-02-01 Published:2019-03-22
  • Contact: HaiYang Xi E-mail:xihy@lzb.ac.cn
  • About author:HaiYang Xi, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences. No. 320, West Donggang Road, Lanzhou, Gansu 730000, China. Tel: +86-931-4967139; E-mail:xihy@lzb.ac.cn

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Abstract:

Groundwater is a key factor controlling the growth of vegetation in desert riparian systems. It is important to recognise how groundwater changes affect the riparian forest ecosystem. This information will not only help us to understand the ecological and hydrological process of the riparian forest but also provide support for ecological recovery of riparian forests and water-resources management of arid inland river basins. This study aims to estimate the suitability of the Water Vegetation Energy and Solute Modelling (WAVES) model to simulate the Ejina Desert riparian forest ecosystem changes, China, to assess effects of groundwater-depth change on the canopy leaf area index (LAI) and water budgets, and to ascertain the suitable groundwater depth for preserving the stability and structure of desert riparian forest. Results demonstrated that the WAVES model can simulate changes to ecological and hydrological processes. The annual mean water consumption of a Tamarix chinensis riparian forest was less than that of a Populus euphratica riparian forest, and the canopy LAI of the desert riparian forest should increase as groundwater depth decreases. Groundwater changes could significantly influence water budgets for T. chinensis and P. euphratica riparian forests and show the positive and negative effects on vegetation growth and water budgets of riparian forests. Maintaining the annual mean groundwater depth at around 1.7?2.7 m is critical for healthy riparian forest growth. This study highlights the importance of considering groundwater-change impacts on desert riparian vegetation and water-balance applications in ecological restoration and efficient water-resource management in the Heihe River Basin.

Key words: groundwater changes, desert riparian forest, Ejina Oasis, WAVES, leaf area index (LAI), water budgets

Figure 1

Locations of field experimental sites in the study area: (a) the Heihe River Basin, (b) the lower reaches of the Heihe River Basin, (c) T. chinensis forest experimental site, and (d) P. euphratica forest experimental site"

Table 1

Names, units, and parameter value of key physiological parameters of the WAVES model"

No. Parameters T. chinensis forest P. euphratica forest
1 1 minus albedo of the canopy (?) 0.7 0.8
2 1 minus albedo of the soil albedo (?) 0.90 0.90
3 Rainfall-interception coefficient (m/(d?LAI)), 0.0002 0.0003
4 Light-extinction coefficient (?) ?0.90 ?0.85
5 Maximum carbon-assimilation rate (kg C/(m2·d)) 0.019 0.020
6 Slope parameter (?) 1.2 1.2
7 Maximum water potential (m) ?400 ?400
8 IRM weighting of water (?) 3.0 2.5
9 IRM weighting of nutrients (?) 1 1
10 Ratio of stomatal to mesophyll conductance (?) 0.2 0.2
11 Temperature when the growth rate is half of the optimum (°C) 10 10
12 Temperature when the growth rate is the optimum (°C) 30 30
13 Year-day of germination (d) 10 30
14 Degree-daylight hours of the growing season (°C·h) 48,000 48,000
15 Saturation-light intensity (μmol/(m2·d)) 1,000 1,300
16 Maximum rooting depth (m) 1.8 2.0
17 Specific leaf area (LAI/(kg C)) 6.0 10.5
18 Leaf-respiration coefficient (kg C/(kg C)) 0.0006 0.0008
19 Stem-respiration coefficient (kg C/(kg C)) 0.0001 0.0005
20 Root-respiration coefficient (kg C/(kg C)) 0.0005 0.0005
21 Leaf mortality (proportion leaf C/d) 0.0020 0.0013
22 Aboveground partitioning factor (?) 0.70 0.39
23 Salt-sensitivity factor (?) 0.3 0.6
24 Aerodynamic resistance (s/m) 10 20
25 Crop-harvest index (?) 0 0
26 Crop-harvest factor (?) 0 0

Figure 2

Comparison between simulated and observed ET of T. chinensis forest from January 2011 to December 2012 (a) and (c); ET of P. euphratica forest from July 2013 to December 2014 (b) and (d)"

Figure 3

Comparison between simulated and observed leaf area index (LAI) of T. chinensis forest from 2001 to 2013 (a) and (c); LAI of P. euphratica forest from 2001 to 2014 (b) and (d)"

Figure 4

Comparison between simulated and observed soil-water content (SWC) of T. chinensis forest from January 2012 to July 2013 (a1: SWC at 0.1 m depth, a2: SWC at 0.3 m depth, a3: SWC at 0.5 m depth, a4: SWC at 0.8 m depth, a5: SWC at 1.5 m depth); SWC of P. euphratica forest from January to September 2013 (b1: SWC at 0.1 m depth, b2: SWC at 0.3 m depth, b3: SWC at 0.5 m depth, b4: SWC at 0.8 m depth, b5: SWC at 1.5 m depth)"

Table 2

Goodness-of-fit measures to compare observed and simulated ET, LAI, and soil-water content values of different depths (0.1 to 1.5 m)"

Study sites Goodness of fit ET LAI SWC 0.1 m SWC 0.3 m SWC 0.5 m SWC 0.8 m SWC 1.5 m
T. chinensis forest PBIAS (%) 8.5 ?5.2 13.6 12.2 2.3 9.3 ?10.2
R 2 0.79 0.94 0.82 0.79 0.89 0.61 0.92
NSE 0.74 0.93 0.62 0.63 0.89 0.50 0.21
RMSE 0.82 0.03 0.04 0.04 0.03 0.07 0.09
P. euphratica forest PBIAS (%) ?0.2 ?7.8 ?2.4 ?7.2 1.4 3.0 25.4
R 2 0.69 0.93 0.79 0.97 0.98 0.96 0.9
NSE 0.68 0.91 0.75 ?2.23 ?5.33 ?4.33 ?2.64
RMSE 1.03 0.04 0.01 0.02 0.02 0.03 0.10

Figure 5

Relationship between the annual mean runoff of Langxin Mountain and the groundwater depth: (a) Annual mean runoff through Langxin Mountain vs. groundwater depth at P. euphratica forest experimental site, (b) annual mean runoff through Langxin Mountain vs. groundwater depth at T. chinensis forest experimental site, (c) scatter diagram of annual mean runoff through Langxin Mountain vs. groundwater depth at P. euphratica forest experimental site, and (d) scatter diagram of annual mean runoff through Langxin Mountain vs. groundwater depth at T. chinensis forest experimental site"

Figure 6

The Pearson III frequency curve of annual mean runoff through Langxin Mountain Station"

Table 3

Four scenarios of runoff through the Langxin Mountain Station and the mean groundwater depths simulated on two experimental sites under different guaranteed rate of water transfer"

Scenarios Guaranteed rate of water transfer (P) Runoff passing by Langxin Mountain Station (×106 m3) Annual mean groundwater depth (m)
T. chinensis forest P. euphratica forest
Reference 2.01 1.90
Scenario 1 25% 609.5 1.77 1.70
Scenario 2 50% 447.9 1.92 1.82
Scenario 3 75% 318.0 2.05 1.91
Scenario 4 90% 225.7 2.13 1.97

Figure 7

Change and difference in water budgets by comparing the P. euphratica riparian forest with the T. chinensis riparian forest. Water balance of storage (a), water balance of rainfall (b), water balance of ET (c), lateral fluxes and groundwater extraction (d)"

Figure 8

Changes of soil-water content at T. chinensis forest from 2000 to 2013 (a) and P. euphratica forest from 2000 to 2014 (b)"

Figure 9

Modeled-effect groundwater changes on ET, rainfall infiltration, and storage at T. chinensis forest experimental site. Time series from 2000 to 2013 (a) and annual means (b)"

Figure 10

Modeled-effect groundwater changes on ET, rainfall infiltration, and storage at P. euphratica forest experimental site. Annual variations from 2000 to 2014 (a) and annual mean variations (b)"

Figure 11

Effect of groundwater changes on LAI. Annual variations from 2000 to 2013 at T. chinensis forest experimental site (a); annual mean variations at T. chinensis forest experimental site (b); annual variations from 2000 to 2014 at P. euphratica forest experimental site (c); annual mean variations at P. euphratica forest experimental site (d)"

Figure 12

Shift of water budgets due to groundwater changes at T. chinensis forest experimental site (a); and at P. euphratica forest experimental site (b)"

Figure 13

Scatter relationship plot between annual mean of groundwater depth and LAI under different scenarios at T. chinensis forest experimental site (a); and P. euphratica forest experimental site (b)"

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