INTRODUCTION- determining water resource availability

HYDRUS‐1D Modeling of an IrrigatedAgricultural Plot with Application toAquifer Recharge Estimationabba

J. Jiménez‐Martínez ; T.H. Skaggs ; M. Th. van Genuchten ; L.Candela• Estimating aquifer recharge• Arid and semi-arid regions- assessing aquifer vulnerability to pollutants
recharge estimation can be difficult(predominately focused recharge)• Recharge is additionally complicated by irrigation

aDepartment of Geotechnical Engineering and Geosciences, TechnicalUniversityof Catalonia, UPC, Barcelona, Spainb
U.S. Salinity Laboratory, USDA‐ARS, Riverside, CA, USA- may remove water fromfocused recharge sources- creating new sourcesof diffuse recharge(Scanlon et al. 2002)• In irrigated regions, accurate knowledge of recharge, evaporation, andtranspiration is especially important for the sustainable management of scarce waterresources.
(Garatuza-Payan et al. 1998)

HYDRUS workshop in Prague
March 28th 2008

HYDROGEOLOGY GROUPINTRODUCTION (2)STUDY LOCATION: Campo de Cartagena• Estimate groundwater recharge• Campo de Cartagena

The methodologies
can be grouped- Surface-water- Unsaturated zone
- Saturated zone

- Average annual rainfall 300 mm- Physical techniques- Tracers techniques- Numerical modeling approaches

Depends

The best choice- Surface 1440 km2- Mean annual temperature 18ºC
- ETp = 800-1200 mm y-1 (Sánchez et al. 1989)- Spatial and temporal scales- Intended application(Scanlon et al. 2002)- Row crops ( principally lettuce and melon) 128.1 km2• Objective

to estimate the contribution of irrigation to aquifer recharge
with a modeling approach based on HYDRUS-1D (Šimůneket al. 2005) simulations of root-zone water dynamics. We
only present preliminary results demonstrating themodeling approach and the calibration of the model toexperimental data.

• Primary land use is agriculture- Perennial vegetables ( principally artichoke) 34.1 km2- Fruit trees ( principally citrus) 136.8 km2

Drip irrigation is used widely in the region due to the scarcity of water resources
and the need for water conservation.

FIELD SITE AND EXPERIMENTHYDRUS‐1D ModelingExperimental plot at the Tomas Ferro Agricultural Science Center (Technical University of Cartagena)
Agricultural practices was managed according to standard in Campo de Cartagena, including
cultivating crops (melon and lettuce) and drip irrigation (Ø 16 mm; emmiters spacing 30 cm; 4 L h-1)

Simulation

root zone water dynamics

Included

HYDRUS-1D (Šimůnek et al. 2005)- Irrigation- Evaporation- Root water uptake process

Input

ROSSETA(pedotransfer function)

Sand, silt and clay contents

Outputθr, θs, α, n, and Ks

Bulk density

Refinements
Tensiometers (Soilmoisture Equipment Corp, Goleta, CA, USA)
Model fitting(subset of the measured θ and h data)

TRIME-FM TDR access (Imko,Germany)
Meteorological data from the Servicio de Información Agraria de Murcia (http://siam.imida.es)

HYDRUS‐1D Modeling (2)Implementing the atmospheric boundary conditiondaily- irrigation- precipitation- potential evaporation- transpiration• Reference evapotranspiration, ET0(t)Penman - Monteith method• Potential evapotranspiration, ETp(t)ETp (t ) = Kc (t )·ET 0 (t ) (Allen et al. 1998)• Potential evaporation, Ep(t)Ep(t ) = ETp(t )·e−β· LAI (t )β : radiation extinction coefficient (≈ 0.4)

• Potential transpiration, Tp(t)(Kroes and Van Dam, 2003)

RESULTS
The most intensive data collection- The root zone θ and h data from this period

Feddes et al. (1978) model(database HYDRUS-1D)

Test and adjust the calibrationof the soil hydraulic property model- The inverse parameter optimization routines(HYDRUS-1D)- number of soil layers

Several possible parameterizations were considered- number of hydraulic parameters

LAI(t): leaf area index- four soil layers

The best parameterization

Tp (t ) = ETp (t ) − Ep(t )• Root water uptake reduction

cultivation of melon, 5/17/2007 to 9/10/2007 (Day Of Year 137-253)

Textural fractions (%)- α and n, fitted for each layer

The best correlation between
measured and simulated
θ and h values
R2 = 0.90

Sand

Silt

ClayBulk
densityg∙cm-3θr
cm cm-3

θscm cm-3

α (Fit)cm-1

n (Fit)-Ks
cm d-1

0-30

18.7

76.0

3.5

1.45

0.04

0.38

0.078

1.16

46.4

30-60

13.8

80.2

6.0

1.52

0.05

0.38

0.046

1.23

29.9

60-90

19.577.2

3.3

1.58

0.04

0.35

0.014

1.27

30.1

90-150

10.8

82.0

6.6

1.70

0.04

0.36

0.020

1.46

13.2

Depthcm

RESULTS (2)CONCLUSIONS

Cultivation of melon, 5/17/2007 to 9/10/2007(Day Of Year 137-253)
The best correlation between measured
and simulated θ and h values
R2 = 0.90
Final soil parameterization
Predict (HYDRUS-1D)• Good agreement was obtained between the calibrated HYDRUS
simulation model and the root zone measurements.

• Calibrated model

it will be possible to compute for various croppingand irrigation scenarios the fraction of irrigation waterthat passes below the root zone and contributes
to aquifer recharge.

• Combining data of land use and cropping patterns for the Campo de Cartagena,
it will be possible to estimate the amount of recharge associated with irrigatedagriculture.
using a different methodology

Root zone soil moisturedynamics for other crops

estimated

Correlation between measured
and simulated θ and h values• Spanish Geological Survey (IGME, 1994)

R2 = 0.82

1st Lettuce

total recharge to the top
unconfined aquifer 69 hm3 y-1- 46 hm3 y-1 natural recharge- 23 hm3 y-1 irrigation return

2/7/2007 to 5/16/2007 (DOY 38-136)

2nd Lettuce

R2 = 0.82

9/25/2007 to12/24/2007 (DOY 268-358)

THANK YOU

Our preliminary calculations

slightly larger value for recharge due to irrigation

This aspect of our work will be the subject of a future publication