This research is part of a regional collaborative project supported by the USDA-NIFA, Award No. 2011-68002-30190:

Cropping Systems Coordinated Agricultural Project: Climate Change, Mitigation, and Adaptation in Corn-based Cropping Systems

Project Web site: sustainablecorn.org

Soil Water Potential Control of the Relationship

between Moisture and Greenhouse Gases Fluxes in Corn-Soybean Field

Dinesh Panday* and Nsalambi V. Nkongolo

Department of Agriculture and Environmental Sciences, Lincoln University, MO

Introduction

• Agriculture is a significant source of three main biogenic GHGs (CO2, N2O and CH4) fluxes and the ways of management of soils, it can constitute as either a net source or sink of these GHGs.

• Greenhouse gases produced in soils move through the exchange of gas between the soil surface and the adjacent atmosphere. This exchange can occur by means of two mechanisms: diffusion and advection and it is done through the pore space.

• Both temperature and moisture are important controls on decomposition processes for GHGs but is more strongly related to soil water content (Conrad, 1989).

• The water status in soils is characterized by the amount of water present, called as soil water content (SWC, θ) and its energy state, called as soil water potential (SWP, Ψ).

• SWC is expressed on a gravimetric or volumetric basis and represented by percent whereas SWP measurement is pressure (Pa or bar) usually the expressed as a negative number.

• The term “suction” and “tension” are definitions developed to avoid using the negative sign and to represent the SWP as positive numbers.

• Several authors have studied the relationship between SWC and GHGs fluxes and most of them have quantified SWC but the energy state of that water or the potential at which this soil water was held was not measured.

• Tremendous efforts are devoted to understanding the relationship between GHGs and soil controlling factors such as soil moisture on daily, weekly, bi-weekly and monthly basic.

• However, to save energy, time and financial resources it would have been better if such measurements could have been done only when soil moisture was held at certain water potentials.

Objectives

To assess the relationship between soil moisture (θ) held at different water potentials () and GHGs fluxes in corn-soybean rotational field.

Methodology

• The experiment was conducted on silt loam soil at the Freeman farm of the Lincoln University of Missouri in 2011.

• Total of 48 plots with 12.19 m width by 21.34 m length for each, 3 factorial experiment in a RCBD with 16 treatment combinations and 3 replications.

• The 3 factors were (i) Tillage at 2 levels (No-Tillage vs Conventional Tillage), (ii) Cover crop at 2 levels (Rye vs No-Rye) and (iii) Cropping sequence or rotation at four levels (Continuous Corn, Continuous Soybean, Corn-Soybean and Soybean-Corn rotations).

Soil and Soil Air Sampling

• Soil samples were collected at four depths: 0-10, 10-20, 20-40 and 40-60 cm, then air-filled porosity (AFP) and other soil properties were calculated.

• Soil air samples for gas analysis were collected using 48 individual PVC static and vented chambers (30 cm Ht * 20 cm Dia) in each plot. Concentrations of CO2, N2O and CH4 from soil air samples were measured with a Shimadzu GC-2014 gas chromatograph.

Soil Moisture Measurement

• Soil samples were placed onto a ceramic porous plate and

wetted for overnight, the pressure chambers were closed and a specified pressure was applied by an air compressor.

• The sample started losing water that moved through the porous plate. After the water ceased to drain, the samples were collected at the specified pressure (SWP, = 0, -0.05, -0.1, -0.33 and -15 bar).

• The soil sample was then removed from the plate, weighted and placed into an oven, for gravimetric determination of soil water content.

Result and Discussions

Summary statistics for soil moisture at different matric potentials

Statistics m =0 m =-0.05 m =-0.1 m =-0.33 m =-15

Mean 0.33 0.21 0.13 0.12 0.09

SD 0.07 0.04 0.01 0.01 0.02

C.V. 21.86 21.61 9.25 8.61 18.47

Minimum 0.18 0.11 0.10 0.09 0.06

Median 0.34 0.21 0.13 0.12 0.09

Maximum 0.45 0.31 0.16 0.14 0.12

Skew -0.33 -0.12 -0.09 0.39 0.07

Kurtosis -1.09 0.71 -0.39 0.30 -1.40

Considerable differences were found in the mean soil moisture contents across the potential at 0 and -0.05 bar where moisture level was 33 and 21 percent respectively.

Statistics CO2 (mg m−2 h−1 ) N2O (μg m−2 h−1 ) CH4 (μg m−2 h−1 )

Mean 477.83 21.02 16.82

SD 125.67 100.87 292.21

C.V. 26.30 479.85 1737.10

Minimum 318.05 -108.49 -315.27

Median 462.37 -15.65 -110.04

Maximum 764.78 285.82 751.47

Skew 0.94 1.04 1.07

Kurtosis 0.03 0.45 0.20

Summary statistics for soil moisture at different matric potentials

y = 1535.4x - 277.91 R² = 0.4096

-50

0

50

100

150

200

250

300

350

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

Nit

rou

s o

xid

e (μg

m−2

h−1

)

Soil moisture at 0 matric potential

Fig.3. Relationship between m = 0 and N2O emissions

Relation between soil moisture (at m =0) and GHGs fluxes

Summary

When soil matric potential (m) was close to 0 bar i.e., saturated conditions at 0-10 cm depth, soil moisture was positively correlated with CO2 and N2O fluxes with correlation coefficients ranging from 0.49 to 0.64, but negatively correlation with CH4 (-0.43) fluxes at p<0.05.

Conclusions

We conclude that when soil water was held at matric potentials close to zero, there were higher CO2 and N2O emissions and higher CH4 uptake in 0–10 cm soil depth.

Since soil moisture availability is controlled by the matric potential at which this water is held, this study stresses the need to monitor soil water potential when monitoring greenhouse gases fluxes.