SIMULATION OF VAPOR AND HEAT FLUXES OVER WET AND DRY REGIME IN PADDY FIELD ENVIRONMENT

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 05, May 2019, pp. 181–189, Article ID: IJCIET_10_05_020
Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJCIET&VType=10&IType=5
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication
SIMULATION OF VAPOR AND HEAT FLUXES
OVER WET AND DRY REGIME IN PADDY
FIELD ENVIRONMENT
Satyanto Krido Saptomo
Department of Civil and Environmental Engineering, IPB University (Bogor Agricultural
University), FATETA Building, Dramaga Campus, Bogor 16680, Indonesia
ABSTRACT
Alternating dry-wet paddy field management such as System of Rice Intensification
(SRI) had become an interesting subject in research and development in paddy
cultivation which also been subject for trial for its implementation. The field’s
environment’s variation of biophysical parameters related to production had also
become important to be studied. This study aims to simulate the variation of
evaporation and thermal condition over a wet and dry regime of paddy field. The
simulation model used in this study was a combination of numerical surface energy
balance and soil water flow model consisting two layered resistance energy balance
model for non-ponded field, one-dimensional atmospheric boundary layer model of
wind, temperature and vapor changes, and soil heat transfer and soil water flow
models. Meteorological parameters at the site were measured and utilized as input for
the simulation. The simulation shows the fluctuating latent, sensible and ground heat
flux and also the variation of temperature, and soil condition for wet and dry regime
of paddy field.
Key words: Numerical model, heat balance, evapotranspiration, micrometeorology,
hydrology
Cite this Article: Satyanto Krido Saptomo, Simulation of Vapor and Heat Fluxes over
Wet and Dry Regime in Paddy Field Environment, International Journal of Civil
Engineering and Technology 10(5), 2019, pp. 181–189.
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=5
1. INTRODUCTION
System of Rice Intensification (SRI) [1] had become an interesting subject in paddy
cultivation research and development which also been subject for trial for its implementation.
SRI also commonly uses intermittent irrigation which affects the thermal condition between
alternating dry and wet condition [2]. The field’s environment’s variation of biophysical
parameters related to production had also become important to be studied.
Apart from the water balance, other micro-environment parameters like soil temperature
and foliage temperature also have an effect on the productivity and the variation of these
parameters are interesting to be observed and studied. Temperature impact on productivity
was presented by [3], cited the benefit of small temperature increase to paddy productivity.

Simulation of Vapor and Heat Fluxes over Wet and Dry Regime in Paddy Field Environment
The prediction of the availability of water, consumptive use of water and the planning of
irrigation water supply can be done by analyzing water and energy balance over a production
land. The energy balance relates to water balance through the latent heat energy term which is
evapotranspiration term in the equation of water balance.
Evapotranspiration can be estimated with energy balance calculation using a computer
model and by using the site’s meteorological data. This study aims to simulate the variation of
evaporation and thermal condition over a wet and dry regime of paddy field using combined
surface energy balance and soil water flow models.
2. METHODOLOGY
2.1. Simulation Model
Models of wind, humidity and temperature distribution in the lower atmosphere and soil heat
transfer are required for calculation of upper boundary and lower boundary conditions for
surface energy balance model which will supply temperature, humidity, wind velocity and
soil temperature for the calculation. These are derived from [4] and [5] with the assumption
of a uniform surface, where potential temperature a, wind velocity u, and specific humidity q
are assumed to change only in vertical direction z. The equations are as follows.
(1)
a a
K
t z z
    
  
   
(2)
(3)
Km, Kh, Kv are turbulent eddy diffusivities of momentum, thermal and vapor diffusivities,
where it was assumed Km = Kh = Kv = Kd(z) and was obtained from
Kd(z)=(z-d)u*/(z/L) (4)
With  is air stability function,  is von Karman constant, u* is friction velocity and d is
displacement height. The atmosphere stability function’s index is represented by Monin-
Obukhov length L [6][7].
2.2. Soil Heat Transfer
With uniform properties of soil, one-dimensional distribution of vertical soil temperature can
be expressed with the following equation
(5)
with T is soil temperature, and Ks is thermal conductivity of the soil
2.3. Energy Balance
The energy balance equation can be written as :
Rn=G+H+LE (6)
where : Rn : net radiation (W m-2
); G : ground heat flux (W m-2
); H : sensible heat flux (W
m-2
); L : latent heat flux (J Kg-1
); E : water vapor (Kg m-2
s-1
). A resistance model that follows













z
u
K
zt
u
m













z
q
K
zt
q
v













z
T
K
zt
T
s

the analogy of electrical circuit was used for calculation of energy balance at the field, which
model also incorporates atmospheric processes and soil heat transport [5] following the multi-
layered resistance model of energy fluxes transfer on soil, plant, and atmosphere presented by
[8]. The model gives sensible and latent heat fluxes outputs for each of the layers.
Evaporation and transpiration were calculated from latent heat fluxes. The values then fed to
soil water flow model to provide upper boundary and root uptake sink.
2.4. Soil Water Flow (SWF)
Soil water flow model used in the model was based on Darcy-Richards equation in one
dimension as follows.
(7)
Volumetric water content relation to soil water potential was modeled following [9]
    










0;
0;
1
h
h
hh
s
mn
rs
r





n
1
1m  ; 1n  (8)
and unsaturated hydraulic conductivity was calculated following [10]
(9)
with S is the degree of saturation:
(10)
The detailed algorithm for the numerical solution of the equations for simulating soil
water flow was explained in [11]
Evaporation is applied as upward flux from the soil top as upper boundary or at the 0th
(uppermost) node in the SWF model. Water extraction by root uptake is termed sink (-S) and
occurs at the lower soil column in the root zone. The values of latent heat fluxes for canopy
and ground surface layers were obtained separately from the two-layered resistances model.
These are equal to the actual transpiration and evaporation if appropriately calculated and can
be used to calculate the amount of evaporative flux and sink with the same unit as in the SWF
model, which is cm/sec.
Transpiration Tp must be used for sink calculation with a simple approach of root water
uptake calculation by assuming the equal distribution of root length density over a rooting
depth Lr. The equation is as follows
S = α(h) Sp (11)
Sp = 1/Lr Tp (12)
and the root water uptake for each depth of z is
S(z) = 1/Lr Tp (13)
1
h
K S
t z z
     
        
 
2
1
1 1
m
m
s e eK S K S S
  
      
   
r
e
s r
S
 
 




There are many others approaches for estimation of root water uptake such as in [12]
which take advanced form for 3 directional or the collection of models presented by [13],
however, this study used the simplest approach.
The computer program of soil water flow and energy balance was developed and
presented in [14]. The schematics of the model is shown in Figure 1. The leftmost, middle and
rightmost are the schemes of stratification of atmosphere and soil for numerical simulation of
processes of wind, humidity and temperature, energy balance simulation, and the model for
processes in soil, especially soil moisture dynamics. The energy balance model shows
radiation energy fluxes exchanges over two layers which are canopy and ground.
Figure 1 Energy balance and soil water flow model as proposed by [14]
2.5. Simulation Setting
The term wet and dry in this paper directly correspond to their water table condition so be
kept during the experiment, which is 0 cm for wet and 20 cm below the surface for a dry field
in the experimental plots. These were the lower boundary condition of the model in the
simulation, set by assigning the value of soil potential (pF) at saturation. Evaporation resulted
from energy balance calculation was applied at the soil surface. Root water uptake was
determined by using transpiration that was calculated from the amount of latent heat energy
from the canopy. Leaf area index of paddy was assumed 4.2 (m2
/m2
) at 70 cm height, which
represent the full growth paddy rice with the roughness length and wind displacement height
were estimated at 9 and 44 cm. In this paper, only one full day was picked for simulation,
chosen among days with relatively clear. Two simulations were conducted, with measured
solar radiation and with estimated solar radiation from the model.
3. RESULTS AND DISCUSSIONS
Energy fluxes and temperatures resulted from simulation using meteorological data are shown
in Figure 2 and Figure 4. In Figure 2, left charts show the total energy fluxes on the field; the
right charts depict the components of net radiation, latent heat, and sensible heat fluxes at the
canopy and ground level. The upper charts show Rn, Rs, H, E and G in radiation intensity
(flux), and their components at canopy or ground surface in the dry regime, while the lower
charts show from the wet regime. It is not difficult to see the differences of G, H, and LE at
the ground surface between wet and dry regimes. The values of ground surface H and LE are
lower in wet regime compared to the dry regime.

Figure 2 Energy fluxes variation of dry field (upper chart) and wet field (lower chart) resulted from
the simulation with measured solar radiation input.
Figure 3 Simulated sensible heat, latent heat, and ground heat fluxes at the ground surface below the
canopy.
The detailed fluctuation of H, LE, and G at the ground surface can be seen in Figure 3. In
wet regime, H was lower for the wet regime which will lead to lower air temperature.
Evaporation from the ground surface also lower, as seen in the smaller LE in the wet regime.
A considerable portion of energy dissipated into G in the wet regime, which affects to less
energy available for evaporation or other processes.
Figure 4 depicted temperatures observed in numerically simulated atmosphere and soil
including temperatures of the air above the canopy, canopy, air around the canopy and air at
1.6m above soil surface; temperatures of the soil surface, the soil at 0-5cm depth and 5-10cm
depth. While there are no considerable differences in the above surface temperatures between
dry (upper charts) and wet (lower charts), differences between soil temperatures in the wet
and dry regime are easy to notice, and shown wet condition decreased soil temperatures.
Soil temperatures were lower at the wet field than in the dry field as shown in the result.
The latent heat fluxes were higher in the dry field compared to the wet field, which means
greater evapotranspiration. More energy dissipated into ground heat flux and perhaps changes
in energy storage in the wet soil. This somehow did not fit the condition that wetter field
should have higher evaporation. This condition could also happen as a result of higher soil
temperature in the dry soil. Comparing all heat fluxes over the dry and wet regime, the only
difference in latent and ground heat fluxes were noticeable.

Figure 4 Temperatures variations of dry field (upper chart) and wet field (lower chart) resulted from
simulation using measured solar radiation input.
Simulations results using calculated solar radiation shows the smoother fluctuation of
fluxes compared to when measured data (Figure 5 and Figure 6). Measured solar radiation
was affected by clouds even in the relatively fine day. The calculated solar radiation was
obtained by using extraterrestrial radiation, latitude and time, which formula is described in
[15], this was done to simulate solar radiation that arrives above vegetation canopy to conduct
a simulation in clear day. Using the calculated radiation, the maximum available net energy
can be estimated and latent heat and sensible heat fluxes during this condition can be
obtained.
’
Figure 5 Energy fluxes variations of dry field (upper chart) and wet field (lower chart) resulted from
simulation using calculated solar radiation input

Figure 6 Temperatures variation of dry field (upper chart) and wet field (lower chart) resulted from
simulation using calculated solar radiation input.
The figures confirmed the similar condition in the simulation with calculated data to the
result from simulation using measured meteorological data, which can be said that there was
no significant alternation between the dry and wet regime, except for ground level sensible,
latent and ground heat fluxes that were affected by the presence of moisture.
Figure 7 and Figure 8 show soil water potential resulted from SWF simulation and the
corresponding volumetric water contents estimated with van Genuchten formula for the site’s
soil at depths 0 – 20 cm beneath the surface. The soil was driest during mid of the day, due to
sinks of evaporation and transpiration (root uptake) shown by higher soil potential (suction)
and the lower soil moisture. As well as the previous charts, simulation results will be
smoother when calculated meteorological data was used.
This simulation program can be improved by taking into account stages in paddy
development such as presented by [16], that will affect the energy balance calculation by the
increase of height and number of foliage. Also, the influences of the geographical condition
and climate change scenarios are interesting future study to improve the present research.
Figure 7 Soil potential and soil water content from the simulated dry field with measured radiation

Figure 8 Soil potential and the soil water content from the simulated dry field with calculated
radiation.
4. CONCLUSION
Simulation of energy balance for the dry and wet regime of paddy field had been conducted to
estimate the component of heat energy fluxes on the surface. The simulation had resulted in
the variation of energy fluxes, temperatures and soil moisture of the simulated land. The
results revealed that there were not many differences in the number of energy components
between the dry and wet field and confirms the temperature differences between simulation
and data on the dry and wet field. The greatest difference was in the dissipation of energy at
ground level into sensible, latent and ground heat fluxes which were affected by soil moisture.
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