MODELING OF PLANT ADAPTATION TO CLIMATIC DROUGHT INDUCED WATER DEFICIT
Laszlo Huzsvai1, Kalman Rajkai2
1Centre
for Agricultural Sciences and Engineering, University of Debrecen, Debrecen, Hungary
e-mail: huzsvai@agr.unideb.hu
2Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of
Sciences, Budapest, Hungary; e-mail: krajkai@rissac.hu
Agronomic and climatic factors affect both directly and indirectly on soil hydrology. One group of
indirect effects acts through plants covering the soil. While natural plant covers are formulated by
multi-layer canopy structure agricultural crops are usually monocultures not counting of weeds.
Plant growth itself has many different effects on hydro-physical properties of soils (e.g. Farkas et al.,
2000). Water flow parameters determined on soil samples involve organic matter effects. Recently the
hydrophobic nature of soil organic substances is discovered. Soil repellency causes delayed and
reduced infiltration of water into the soil matrix (e.g. Orfanus et al, 2008).
Soil moister flux is considered generally as the main factor determining the transpiration intensity of
plants. This assumption is valid if plant physiological conditions are optimal and there is no any
physical barrier for water evaporation from the leaves.
Water flow pathways in the soil-plant-atmosphere are involved in plant growth models. They are
described with different complexity starting from the simpler capacitive water balance type to the more
complicated Darcyan laminar flow equation generalized for unsaturated flow by Richards as partial
differential equation. In capacitive models the amount of water in soil is changing by additions
(precipitation, capillary rise) and subtractions (evaporation, transpiration, deep drainage) of plant
usable water (e.g. Bossel 1986). In rather complex deterministic mechanistic models as the Couple
heat and mass transfer model (Jansson and Karlberg 2001) or Ceres (Hanks and Ritchie 1984) the
soil is divided into several layers and for each of them hydraulic function’s parameter values has to be
given. In both type of models transpiration intensity or plant water requirement depends on the plant
development stage. Number of model parameters is differing according to model’s complexity. The
slowest flow process determines intensity of water flow in the soil-plant-atmosphere pathway. The
highest probability of limiting water availability or too slow moisture transport occurs in soil. However,
in case of climatic drought the water flow in plant can be the slowest.
A new algorithm we built into a growth model describing the plant adaptation in case of climatic
drought. The adaptation algorithm of Doorenbos et al. (1978) we developed further defining that soil
moisture content where closure of stomas is initiated. Stoma’s closure starts in spite of that plenty
plant available water in the soil exists. The critical soil moisture content is however not constant but
varying according to PET and physiological status of plant. When the soil moisture content is between
field capacity (θf) and the newly defined limited availability (θla) transpiration (ET) is equal with PET.
When soil moisture content is less than θla ET can be very variable depending on drought tolerance of
the plant.
Newly developed drought tolerance algorithm is demonstrated on a maize field of chernozem soil at
the loess plateau in the East Hungary. In severe climatic drought the plant water uptake is slower than
the ET consequently scarcity of water is formulating and dry matter build up slows down in plants.
Parallel stomas closure starts in spite that there is plant available water in the soil. This protecting
reaction is assuring plants’ survival in climatic drought periods (Szász 1977).
For maize the simulated critical soil moisture content values as a function of PET and drought
tolerance of plants are given in table 1. The used θ f and θf values for the chernozem soil is 0,3 and
0,12 m3m-3 consecutively. The maize crop belongs to the 3th drought tolerance category.
Plant drought
tolerance
Table 1. Critical soil moisture content values of the chernozem soil (m 3 m-3)
2
1
2
3
4
5
3
0,22
0,19
0,17
0,15
0,13
4
0,24
0,21
0,19
0,17
0,15
PET (mm/day)
5
0,25
0,26
0,23
0,24
0,20
0,22
0,19
0,20
0,17
0,18
6
7
0,26
0,25
0,23
0,21
0,19
8
0,27
0,25
0,24
0,22
0,20
0,27
0,26
0,24
0,23
0,21
The time variation of simulated and measured water storages of the 1,2 meter soil profile are shown in
Figure 1. Measured water storages are calculated from the summed soil moisture content readings of
a BR-150 capacitance probe (Andrén et al., 1991). In 2003 year the difference between measured and
simulated soil water storages is not significant while in the flowering period of 2004 and 2006 model
estimates lower than field measurements. Flowering period is crucial since water consumption of
maize is the highest. Beside that simulation indicates low water storage values in 2006 autumn and
the first half of 2007 leaded to low maize production in 2007.
In general it can be established that water flow processes in soil are influenced, triggered or
moderated by plants and other organisms living in or on the soil. This is why majority of soil water flow
phenomena is part of biohydrology.
450
400
Water storage of 1.2 m soil (mm)
350
300
250
200
150
100
Simulated
Measured
Time of flowering
50
0
2003
2004
2005
2006
2007
Time (day)
Figure 1. Simulated (solid line) and measured (small squares) water storage values soil in upper 1,2 m
(2003-2007). The 50% flowering time is indicated by big squares.
Keywords: Climatic drought, plant water deficit, drought adaptation, crop model
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