1. Van-Genuchten-Mualem parameters
Climate change impacts on the water regime of a brown forest soil
Gelybó, Gy., Tóth, E.*, Bakacsi, Zs., Molnár, S., Farkas, Cs.
Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences
H-1022 Budapest, Herman Ottó út 15. *
Abstract
In this study the effects of climate change on forest soils has been evaluated with scenario analyses based on mathematical modelling. Meteorological data were originated from the FORSEE database, which provides bias-corrected climate data based on the ENSEMBLES EU project, soil properties data were obtained from the TIM database. The intraannual variability of soil water regime was examined on 18 representative years sampled from the whole period. We concluded that the main annual temperature will gradually increase, although the amount of precipitation will decrease in the near future (A1B55) and increase in the far future (A1B100). The number of days with extreme high precipitation (more than 20 mm per day) will increase, while the number of rainy days will be decreased. Evaporation and transpiration will increase in the near and the far future in both wet and dry years.
Material and methods
Climate data.
Climate data (bias corrected temperature and precipitation) used in this study were obtained from the 1/6 × 1/6 degree resolution FORESEE database (DOBOR et al., 2012) that is based on the results of the ENSEMBLES project. The database provides continuous dataset for the period, characterizing climate variables by one common reference dataset for the past ( ) and eight different climate model runs for the future ( ) considering A1B emission scenario. Results of the RegCM (International Centre for Theoretical Physics) regional climate model were used in model calculation. For average values of past, near future, far future subperiods see Table 1.
Figure 1. Geographical location of soil sampling points.
Soil data
Soil characteristics of the study area were obtaine from the Soil Information and Monitoring System (Várallyay, 2002; Table 2.). We analyzed possible changes in soil water regime for soil profile #E7705 (Figure 1)
Table 2. Soil data for the study site ID
Depth [cm]
Plast. Index
SAND
SILT
CLAY
Org. Cont
Genetic Soil Type
E7705
0-4
40.00
31.87
36.90
31.23
7.52
brown forest soil with clay illuviation
4-29
41.00
28.23
35.85
35.92
1.63
29-79
48.00
27.72
31.12
41.16
0.65
79-129
37.63
29.50
32.87
0.20
42.00
32.51
30.96
36.53
0.24
Table 1. Climate data in the studí period.
Modeling
The SWAP (Soil-Water-Atmosphere-Plant) model (VAN DAM, 2000) simulates water movement in the unsaturated zone in relation to plant growth for one or more successive vegetation periods. Principally, the model is based on physical equations but also incorporates semi-empirical and empirical relationships. Meteorological, plant and soil data, as well as initial and boundary conditions are required to run the model. We used the SWAT 2.2 model version for our studies. Soil hydraulic functions determining soil water regime are defined according to the Van Genuchten-Mualem analytical expressions.
Sample year selection
Representative dry, wet and average sample years were selected based on the statistical evaluation of annual total precipitations (RT) in each subperiod.
The probability of a year with RT less than a certain amount is shown in Table 1. A year is considered dry, wet and average if RT equals to the lower, upper quartile or the median, respectively (allowing 2% discrepancy).
The resulting 2 to 5 years in each subperiod and were ranked based on their Simple Daily Intenzity Index (SDII). Years with the highest and lowest SDII were retained for further analysis (ensuring consideration of precipitation intensity); see Table 4.
Table 3. SWAP model parameters
Van-Genuchten-Mualem parameters
E_7705
A (0-4cm)
B (4-29cm)
C (29-79cm)
D (79-129cm)
E ( cm)
saturated soil water content
WRC (cm3 cm-3)
0.45
0.54
0.49
0.51
residual water content
WRS (cm3 cm-3)
0.01
fitting parameters
Alpha (cm-1)
0.02
0.04
0.03
n (-)
1.16
1.17
1.98
1.19
1.22
Results
Climatologic characteristics
Soil moisture regime and soil water balance elements
Table 4 Sample years (precipitation)
Table 5 Sample years (water balance)
Ref
A1B50
A1B100
minSDII
maxSDII
0.25
(dry) RT
687
674
726
714
760
765
RR1
112 99
121 92
110
SDII
6.1
6.8
6.0
7.76
6.9
8.3
0.5
(average)
811
831
837
841
856
854
149
103
116
105
119 96
5.4
8.1
7.2
8.01
8.9
0.75
(wet)
939
955
917
908
941
943
129
108
135
123
122
7.3
8.8
7.4
7.7
8.4
Ref
A1B50
A1B100
minSDII
maxSDII
0.25
(dry) EV
165
173
202
172
207
192 TR
417
475
499
410
551
481 DP 11 1
147 2
242
0.5
(average)
195
174
189
212
220
198
479
506
517
599
554
593 3
143 4 12 96
0.75
(wet)
205
209
217
197
570
574
571
681
625
633 79 18
191
127 5
416
Figure 3. Number of days with optimal soil water content
Climatology (Figure 2)
SDII increases (not significant): precipitation intensity increases, not uniformly distributed through the year
Soil water regime
Number of days with optimal soil water content (Dopt) will increase in dry years (Figure 3),
The change is smaller in average or wet years,
The effect of smaller amount of rainfall can be detected in the number of days with optimal soil moisture content in the near future, especially in years with average amount of precipitation.
Number of those days when soil moisture content is below the wilting point Dhp shows similar patterns (Figure 4)
Soil water balance elements
Changes in soil water balance elements will be demonstrated altogether for 18 years representing the studied period (Table 5). In the near and the far future evaporation and transpiration will be increased in both the wet and the dry years as well, which can be explained with the higher amount of precipitation. Values of deep percolation do not show any general tendency.
Figure 4. Number of days with soil water content below wilting point
Figure 2. Average SDII in the three subperiods
References:
Dobor, L., Barcza, Z., Havasi, Á., Fodor, N., Preparation of high resolution climate scenarios for agricultural impact analysis in Hungary. (poster) European Geosciences Union, General Assembly 2012, Vienna, Austria, April, 2012
Van Dam., Field-scale water flow and solute transport. PhD thesis Wageningen University, the Netherlands, 167 p.
Várallyay, Gy. (2002). Soil survey and soil monitoring in Hungary. In European Soil Bureau - Research Report 9, ESB, Ispra, 139–149.
Acknowledgements
The research was supported by the Hungarian National Research Foundation (OTKA, Grant No. K , K ), and the CarpathCC and TÁMOP A-1/1/KONV research projects.