MODELING WATER AND NITROGEN FATE FROM MODELING WATER AND NITROGEN FATE FROM

SWEET SORGHUM IRRIGATED WITH FRESH AND SWEET SORGHUM IRRIGATED WITH FRESH AND

BLENDED SALINE WATERS USING HYDRUS-2DBLENDED SALINE WATERS USING HYDRUS-2D

T. B. RamosT. B. Ramos11, J. Šim, J. Šimůůneknek22, M. C. Gonçalves, M. C. Gonçalves33, J. C. Martins, J. C. Martins33,,

A. PrazeresA. Prazeres33 & L. S. Pereira & L. S. Pereira11

11 Institute of Agronomy, Technical University of Lisbon, Lisbon, PortugalInstitute of Agronomy, Technical University of Lisbon, Lisbon, Portugal22 Department of Environmental Sciences, University of California, Riverside, USA Department of Environmental Sciences, University of California, Riverside, USA33 National Institute of Agronomic and Veterinarian Research,National Institute of Agronomic and Veterinarian Research, INIAV, Oeiras, Portugal INIAV, Oeiras, Portugal

44thth HYDRUS Workshop, March 21 – 22, 2013, Prague, Czech HYDRUS Workshop, March 21 – 22, 2013, Prague, Czech RepublicRepublic

OBJECTIVESOBJECTIVES

The Alentejo region of southern Portugal normally exhibits The Alentejo region of southern Portugal normally exhibits high summer temperatures and very low rainfall that limit high summer temperatures and very low rainfall that limit crop production.crop production.

In this water scarce region, irrigation plays a fundamental In this water scarce region, irrigation plays a fundamental economical and social role but has enhanced several economical and social role but has enhanced several environmental problems as a result of poor irrigation and environmental problems as a result of poor irrigation and water management practices.water management practices.

Human-Human-induced induced salinization and sodificationsalinization and sodification, and , and non-point non-point source pollutionsource pollution from agricultural fertilization are among the from agricultural fertilization are among the recognized problems.recognized problems.

Modeling of subsurface water flow and the transport of major Modeling of subsurface water flow and the transport of major soluble ions in and below the root zone is essential for soluble ions in and below the root zone is essential for predicting groundwater quality, implementing better predicting groundwater quality, implementing better irrigation and fertilization practicesirrigation and fertilization practices

PREVIOUS PREVIOUS STUDIESSTUDIES

Gonçalves, M.C., Šimůnek, J., Ramos, T.B., Martins, J.C., Neves, M.J., Pires, F.P., Gonçalves, M.C., Šimůnek, J., Ramos, T.B., Martins, J.C., Neves, M.J., Pires, F.P., 2006. 2006. Multicomponent solute transport Multicomponent solute transport in soil lysimeters irrigated with waters of in soil lysimeters irrigated with waters of different qualitydifferent quality. . Water Resour. Res.Water Resour. Res. 42, 17, W08401, doi:10.1029/2005WR004802. 42, 17, W08401, doi:10.1029/2005WR004802.

Salt transport in soil lysimeters with the Salt transport in soil lysimeters with the UNSATCHEM modelUNSATCHEM model

50 cm

0

2

4

6

8

10

0 200 400 600 800 1000 1200 1400

SA

R (

me

q L-1

)0.5

10 cm

0

10

20

30

40

50

0 200 400 600 800 1000 1200 1400

Na

Co

nc

en

tra

tio

n [

me

q/L

]SARSAR

NaNa++

0

20

40

60

80

100

120

140

01-06-04 18-12-04 06-07-05 22-01-06 10-08-06 26-02-07

0

20

40

60

80

100

120

140

01-06-04 18-12-04 06-07-05 22-01-06 10-08-06 26-02-07

Time

I I I

Na

conc

entr

atio

n(m

mol

(c)L

-1)

I I I

Na

conc

entr

atio

n(m

mol

(c)L

-1)

PREVIOUS PREVIOUS STUDIESSTUDIES

Ramos, T.B., Šimůnek, J., Gonçalves, M.C., Martins, J.C., Prazeres, A., Castanheira, Ramos, T.B., Šimůnek, J., Gonçalves, M.C., Martins, J.C., Prazeres, A., Castanheira, N.L., Pereira, L. S., 2011. N.L., Pereira, L. S., 2011. Field Evaluation of a multicomponent solute transport Field Evaluation of a multicomponent solute transport model in soils irrigated with saline watersmodel in soils irrigated with saline waters. . J. Hydrol.J. Hydrol. 407: 129-144, 407: 129-144, doi:doi:10.1016/j.jhydrol.2011.07.016.10.1016/j.jhydrol.2011.07.016.

Salt and nitrogen transport in the soil with HYDRUS-Salt and nitrogen transport in the soil with HYDRUS-1D1D

0

5

10

15

20

25

30

01-06-2004 18-12-2004 06-07-2005 22-01-2006 10-08-2006 26-02-2007

Time

N-N

O3-

conc

entr

atio

n(m

mol

(c)L

-1)

I I I

N-N

O3-

conc

entr

atio

n(m

mol

(c)L

-1)

I I I

0

10

20

30

40

01-06-04 18-12-04 06-07-05 22-01-06 10-08-06 26-02-07

0

10

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40

01-06-04 18-12-04 06-07-05 22-01-06 10-08-06 26-02-07

Time

I I I

Mg

conc

entr

atio

n(m

mol

(c)L

-1)

I I I

Mg

conc

entr

atio

n(m

mol

(c)L

-1)

NaNa++

MgMg2+2+ N-NON-NO33--

OBJECTIVESOBJECTIVES

Ramos, T.B., Šimůnek, J., Gonçalves, M.C., Martins, J.C., Prazeres, A., Pereira, L.S., 2012. Ramos, T.B., Šimůnek, J., Gonçalves, M.C., Martins, J.C., Prazeres, A., Pereira, L.S., 2012. Two-dimensional modeling of water and nitrogen fate from sweet sorghum irrigated Two-dimensional modeling of water and nitrogen fate from sweet sorghum irrigated with fresh and blended saline waterswith fresh and blended saline waters. . Agric. Water Manage.Agric. Water Manage. 111: 87-104, 111: 87-104, doi:10.1016/j.agwat.2012.05.007. doi:10.1016/j.agwat.2012.05.007.

Evaluate the effectiveness of HYDRUS-2D to:Evaluate the effectiveness of HYDRUS-2D to:

(i)(i) Predict water contents and fluxes, Predict water contents and fluxes,

(ii)(ii) Predict overall salinity given by EC Predict overall salinity given by ECswsw,,

(iii)(iii) Quantify water uptake reductions due to the use of Quantify water uptake reductions due to the use of

saline waters,saline waters,

(iv)(iv) Predict N-H Predict N-H44++ and N-NO and N-NO33

-- concentrations in the soil concentrations in the soil

and leaching.and leaching.

Two-dimensional modeling of Two-dimensional modeling of waterwater and and nitrogennitrogen fate in a plot with sweet sorghum fate in a plot with sweet sorghum grown under Mediterranean conditions while grown under Mediterranean conditions while considering different drip fertigation and considering different drip fertigation and water water qualityquality scenarios. scenarios.

FIELD EXPERIMENTFIELD EXPERIMENT

• Fluvisol with loam textureFluvisol with loam texture

• Time periodTime periodMay 2007 to April 2010May 2007 to April 20103 irrigation cycles and 3 rainfall leaching cycles3 irrigation cycles and 3 rainfall leaching cycles

• CultureCultureSweet sorghumSweet sorghum

• Water appliedWater applied425, 522, and 546 mm in 2007, 2008, and 2009, respectively425, 522, and 546 mm in 2007, 2008, and 2009, respectively

• Trickle irrigation systemTrickle irrigation systemA triple emitter source irrigation system was A triple emitter source irrigation system was

used to used to apply water, salt apply water, salt (Na(Na++), and fertilizer ), and fertilizer (NH(NH44NONO33)).

Based on Based on Israeli designs used to obtain yield Israeli designs used to obtain yield functionsfunctions

FIELD EXPERIMENTFIELD EXPERIMENT

Layout of the TES systemLayout of the TES system

FIELD EXPERIMENTFIELD EXPERIMENT

FIELD EXPERIMENTFIELD EXPERIMENT

12 experimental plots12 experimental plots

FIELD EXPERIMENTFIELD EXPERIMENT

Salt gradient:Salt gradient:- 60 to 2166 g m- 60 to 2166 g m22 y y-1-1

- 0.8 to 10.6 dS m- 0.8 to 10.6 dS m-1-1

FIELD EXPERIMENTFIELD EXPERIMENT

Nitrogen gradient:Nitrogen gradient:- 56.8 to 0 g m- 56.8 to 0 g m-2-2 y y-1-1

- 95.0 to 0.15 mmol- 95.0 to 0.15 mmolcc L L-1-1

HYDRUS-2D SIMULATIONSHYDRUS-2D SIMULATIONS

37.5 cm

Simulation domain

100 cm

75 cm

Nitrogen water

Saline water

Fresh water

Drip emitter

Mixing pump

X

Z

Y

Ceramic cups

TDR probes

20 cm20 cm

37.5 cm

Simulation domain

100 cm

75 cm

Nitrogen water

Saline water

Fresh water

Drip emitter

Mixing pump

X

Z

Y

Ceramic cups

TDR probes

20 cm20 cm

Location of a point source emitter and monitoring sites Location of a point source emitter and monitoring sites in the experimental plotin the experimental plot

HYDRUS-2D SIMULATIONSHYDRUS-2D SIMULATIONS

100 cm

37.5 cm

Drip EmitterDrip Emitter

ObservationObservationpointspoints

20 cm

40 cm

60 cm

r

Z

20 cm

Free drainageFree drainage

AtmosphericAtmosphericboundary conditionboundary condition

Flux boundaryFlux boundaryconditioncondition

20 cm 17.5 cm

durationareawettedsurface

appliedwaterofvolumeq

AXISYMMETRICAL DOMAIN AXISYMMETRICAL DOMAIN GEOMETRYGEOMETRY

Monitoring irrigation and leaching cycles (20, 40, and 60 cm)

• Soil water content (TDR)

• Electrical conductivity from soil solution (ceramic cups)• Soluble ions from soil solution (ceramic cups)

INPUT DATAINPUT DATA

Measured in representative soil profile at 20, 40 and 60 cmMeasured in representative soil profile at 20, 40 and 60 cm

Soil Initial ConditionsSoil Initial Conditions

Soil Hydraulic PropertiesSoil Hydraulic Properties

Solute Transport ParametersSolute Transport Parameters

• Soil water content, TDRSoil water content, TDR

• Dry bulk densityDry bulk density

• Electrical conductivity of the soil solution (ECElectrical conductivity of the soil solution (ECswsw))

• Suction tablesSuction tables

• Pressure PlatePressure Plate

• Evaporation MethodEvaporation Method

• Hot Air MethodHot Air Method

Described with Mualem-van Described with Mualem-van Genuchten equationsGenuchten equations

• Chloride Breakthrough CurvesChloride Breakthrough Curves

• CXTFIT 2.1CXTFIT 2.1

• Rainfall (daily) / Irrigation waterRainfall (daily) / Irrigation water

• Daily ETDaily ET0 0 (Penman-Monteith)(Penman-Monteith)

• ETETcc = (K = (Kcbcb + K + Kee) ET) ET00 (dual Kc approach from FAO (dual Kc approach from FAO

56)56)

• KKcb midcb mid = K = Kc minc min + (K + (Kcb fullcb full – K – Kc minc min))(1-e(-0.7 LAI))(1-e(-0.7 LAI))

(Leaf Area Index measured every week)(Leaf Area Index measured every week)

TIME-VARIABLE BOUNDARY CONDITIONSTIME-VARIABLE BOUNDARY CONDITIONS

MODELING APROACHMODELING APROACH

Linear Adsorption IsothermLinear Adsorption Isotherm

kk,dk cKc KKd,NH4+d,NH4+ = 3.5 cm = 3.5 cm33 g g-1-1

KKd,NO3-d,NO3- = 0 cm = 0 cm33 g g-1-1

KKd,ECswd,ECsw = 0 cm = 0 cm33 g g-1-1

Hanson et al. Hanson et al. (2006)(2006)

4444

4444

NHNNHN,sNHNNHN,w

NHNNHN,sNHNNHN,w

cc

cc

µµww = 0.2 d = 0.2 d-1-1

µµss = 0.2 d = 0.2 d-1-1

NitrificationNitrificationSequential first-order decay chain:Sequential first-order decay chain:

MODELING APROACHMODELING APROACH

Root distributionRoot distributionRoot Water UptakeRoot Water Uptake

Feddes et al. (1978)Feddes et al. (1978)

Water stressWater stress

Salinity stressSalinity stress

Maas’s (1990) threshold and slope functionMaas’s (1990) threshold and slope function s01.0ECEC1h T2

swECe ECkEC KKEC EC = 2= 2

Nutrient uptakeNutrient uptake

Only considering passive nutrient uptakeOnly considering passive nutrient uptake

CCmaxmax is the maximum concentration of the root uptake is the maximum concentration of the root uptake

RESULTSRESULTS

Wat

er c

on

ten

t (c

m3

cm-3

)

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 04-12-07 21-06-08 07-01-09 26-07-09 11-02-10 30-08-10

Season1

Season2

Season3

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 29-09-08 11-02-10

Série1

Série2

Série4

Série5

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 29-09-08 11-02-10

Série1

Série2

Série4

Série5

Measured data (Plot with saline waters)

Measured data (Plot with fresh waters)

HYDRUS-2D simulation (Plot with saline waters)

HYDRUS-2D simulation (Plot fresh waters)

Time

40 cm40 cm

WATER FLOWWATER FLOW

RMSE = 0.03 cmRMSE = 0.03 cm33 cm cm-3-3

• Tp: 360 - 457 mmTp: 360 - 457 mm

• Ta: 264 - 364 mmTa: 264 - 364 mm

• Tp reductions due to water stress: 21.9 – 27.4 %Tp reductions due to water stress: 21.9 – 27.4 %

Water stress was a function of the irrigation schedule during each seasonWater stress was a function of the irrigation schedule during each season

ECECswsw

0

5

10

15

20

25

18-05-07 04-12-07 21-06-08 07-01-09 26-07-09 11-02-10 30-08-10

EC

sw (

dS

m-1)

40 cm40 cm

RMSE = 1.764 dS mRMSE = 1.764 dS m-1-1

Wat

er

con

ten

t (c

m3

cm-3

)

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 04-12-07 21-06-08 07-01-09 26-07-09 11-02-10 30-08-10

Season1

Season2

Season3

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 29-09-08 11-02-10

Série1

Série2

Série4

Série5

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 29-09-08 11-02-10

Série1

Série2

Série4

Série5

Measured data (Plot with saline waters)

Measured data (Plot with fresh waters)

HYDRUS-2D simulation (Plot with saline waters)

HYDRUS-2D simulation (Plot fresh waters)

Time

• Tp reductions due to water and salinity stress:Tp reductions due to water and salinity stress:

24.2 – 33.3 % (plots with saline waters)24.2 – 33.3 % (plots with saline waters)

SALINITY DISTRIBUTIONSALINITY DISTRIBUTION

The continuous use of The continuous use of synthetic saline irrigation synthetic saline irrigation waters led to soil waters led to soil salinization over the years salinization over the years and to transpiration and to transpiration reductionsreductions

2007: 2007: 0 %0 %

2008: 2008: 2.3 - 4.7 %2.3 - 4.7 %

2009: 2009: 4.6 – 7.0 %4.6 – 7.0 %

Sweet sorghum showed to Sweet sorghum showed to be tolerant to the use of be tolerant to the use of saline waters during one saline waters during one crop season.crop season.

Salinity stress: Salinity stress:

SALINITY DISTRIBUTIONSALINITY DISTRIBUTION

Transpiration in plots Transpiration in plots with fresh irrigation with fresh irrigation waters were not affected waters were not affected by the osmotic stress by the osmotic stress

N-NHN-NH44++

Wat

er

con

ten

t (c

m3

cm-3

)

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 04-12-07 21-06-08 07-01-09 26-07-09 11-02-10 30-08-10

Season1

Season2

Season3

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 29-09-08 11-02-10

Série1

Série2

Série4

Série5

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 29-09-08 11-02-10

Série1

Série2

Série4

Série5

Measured data (Plot with saline waters)

Measured data (Plot with fresh waters)

HYDRUS-2D simulation (Plot with saline waters)

HYDRUS-2D simulation (Plot fresh waters)

Time

RMSE = 0.042 mmolRMSE = 0.042 mmolcc L L-1-1

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 04-12-07 21-06-08 07-01-09 26-07-09 11-02-10 30-08-10

N-N

H4+

(mm

ol c

L-1

) 40 cm40 cm

N-NON-NO33--

Wat

er

con

ten

t (c

m3

cm-3

)

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 04-12-07 21-06-08 07-01-09 26-07-09 11-02-10 30-08-10

Season1

Season2

Season3

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 29-09-08 11-02-10

Série1

Série2

Série4

Série5

0.0

0.1

0.2

0.3

0.4

0.5

18-05-07 29-09-08 11-02-10

Série1

Série2

Série4

Série5

Measured data (Plot with saline waters)

Measured data (Plot with fresh waters)

HYDRUS-2D simulation (Plot with saline waters)

HYDRUS-2D simulation (Plot fresh waters)

Time

RMSE = 3.078 mmolRMSE = 3.078 mmolcc L L-1-1

0

10

20

30

40

18-05-07 04-12-07 21-06-08 07-01-09 26-07-09 11-02-10 30-08-10

N-N

O3-

(mm

ol c

L-1

) 40 cm40 cm

NITROGEN BALANCENITROGEN BALANCE

• The leaching of N out of the root zone depended closely on The leaching of N out of the root zone depended closely on drainage, the amount of N applied, the form of N in the drainage, the amount of N applied, the form of N in the fertilizer, and the time and number of fertigation events.fertilizer, and the time and number of fertigation events.

• The effects of the salinity stress on nutrient uptake (and The effects of the salinity stress on nutrient uptake (and inversely on nutrient leaching) was relatively small since sweet inversely on nutrient leaching) was relatively small since sweet sorghum has a medium to high tolerance to salinitysorghum has a medium to high tolerance to salinity

• N-NON-NO33− − leaching:leaching: • N-NON-NO33

− − uptake:uptake:

2007: 2007: 51 - 53 %51 - 53 %

2008: 2008: 41 %41 %

2009: 2009: 68 - 70 %68 - 70 %

2007: 2007: 37 %37 %

2008: 2008: 39 - 42 %39 - 42 %

2009: 2009: 23 - 25 %23 - 25 %

• Fertigation events:Fertigation events:

2007: 2007: 44

2008: 2008: 66

2009: 2009: 33

N-NO3- uptake (kg/ha)

Dry

bio

mas

s(k

g/h

a)

y = 2818.59Ln(x) + 6223.58

R2 = 0.71

5000

10000

15000

20000

25000

30000

0 50 100 150 200 250 300

y = 2818.59Ln(x) + 6223.58

R2 = 0.71

5000

10000

15000

20000

25000

30000

0 100 200 300

Series1

Series2

Series3

Log. (Series1)

y = 2818.59Ln(x) + 6223.58

R2 = 0.71

5000

10000

15000

20000

25000

30000

0 100 200 300

Series1

Series2

Series3

Log. (Series1)

data from plots with saline watersdata from plots with fresh waters

YIELD FUNCTIONYIELD FUNCTION

An An additional incremental change of additional incremental change of N-NON-NO33-- uptake uptake produced produced

diminishing returnsdiminishing returns in the in the total dry biomass response with total dry biomass response with optimum levels beingoptimum levels being reached at 130-180 kg/ha reached at 130-180 kg/ha

CONCLUSIONSCONCLUSIONS

CONCLUSIONSCONCLUSIONS

• The relatively low water needs (360-457 mm) and N The relatively low water needs (360-457 mm) and N requirements (130-180 kg/ha) of sweet sorghum makes it a good requirements (130-180 kg/ha) of sweet sorghum makes it a good alternative when compared to other traditional crops grown in alternative when compared to other traditional crops grown in the region.the region.

• Saline waters can be viewed as an important source of Saline waters can be viewed as an important source of irrigation water during drought seasons, the use of marginal irrigation water during drought seasons, the use of marginal waters showed viability for irrigating sweet sorghum during a waters showed viability for irrigating sweet sorghum during a limited time period (one crop season).limited time period (one crop season).

• HYDRUS-2D successfully estimated the fate of nitrogen in field HYDRUS-2D successfully estimated the fate of nitrogen in field plots grown with sweet sorghum in Alentejo.plots grown with sweet sorghum in Alentejo.

• The modeling approach helped us understand the best The modeling approach helped us understand the best irrigation and fertigation management practices to be adopted irrigation and fertigation management practices to be adopted in future practical applications for increasing nutrient uptake in future practical applications for increasing nutrient uptake and reducing nutrient leaching.and reducing nutrient leaching.