Chapter 3: MATERIALS AND METHODS
2. Materials and Methods
3.3 WINDS Calibration
After the parameters were improved, the WINDS model was calibrated with the adjusted data. Figure 8 shows the ETc graph of PI full irrigation regime of the 2018 experiment. The 2020 experiment had a similar ETc curve but is not shown. The calibration showed a reasonable agreement of soil moisture content for each layer. Figures 5 and 7 illustrate the agreement of soil moisture for each layer for all treatments for 2018 and 2020. For 2018, the model accurately simulated the upper root zone, with the best agreement from 10 cm to 60 cm. There was high variability in neutron probe readings in lower layers between replicates. For the deficit irrigation experiments in 2018, the model showed that soil moisture in the lower layers mostly remained at the field capacity with a decline toward the end season.
Percent depletion was also generated by the WINDS model. Figure 9 shows the percent depletion for each soil layer for the 2018 guar experiment for two irrigation treatments: PI_F and PI_Vst. There is more variation in the depletion in the evaporation layer compared to other layers during the early stage. Between the two irrigation regimes, the top layers of PI_Vst are also seen as more depleted during the vegetative stage. During the late season, layers 4 and 5 represent depths from 40 cm to 80 cm are more sensitive to water depletion. Similar graphs for 2020 (Figure 10) showed that the depletion for PI_F mainly is towards the end of mid-season and late-season;
however, for the PI_Vst treatment, the top three layers (from 20 cm to 60 cm) were depleted from the vegetative stage until the end of the season.
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Root Mean Square Error (RMSE) was calculated between modeled and field-measured soil moisture for neutron reading days for each treatment of both years. Table 9 shows the average RMSE values presented by averaging data of all soil layers for the days and then an overall average of the season. The RMSE of soil moisture analysis showed a range from 0.018 to 0.035. The overall results in Table 9 show that the model effectively simulated the soil moisture content in this deficit irrigation experiment.
The NDVI values were used to calculate Kcb during 2020, and the calculated Kcb values had reasonably close agreement with the daily Kcb values generated by the volume balance and WINDS model analyses (Figure 11).
This experiment had extensive plant measurements and limited resources. This is not unusual in plant science and irrigation research. For these experiments to be meaningful, augmentation of the field research with analysis such as that shown in this paper is essential and can greatly increase the value of experiments.
4. Conclusions
The purpose of this study was to demonstrate the capability of the WINDS model to simulate deficit irrigation experiments, to detect erroneous data, and to fill in the gaps between infrequent soil moisture measurement readings. Initially, the WINDS model determined the field capacity and wilting point for each layer of the soil profile. The analysis method detected errors in neutron probe readings and the required partition of runoff during the large rainfall events. With adjustments, the WINDS model also was able to provide a reasonable simulation of the guar experiments. This extensive study is an example of the importance of models in the validation and
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improvement of field measurements. It also shows that despite a limited dataset, the WINDS model was able to not only identify errors but produce an adequate daily simulation that will be useful for the generation of an input dataset for AquaCrop.
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153 List of Tables
Table 1: Average monthly weather indicators for growing season of guar in 2018 and 2020 Year Month Rainfall Temperature ETo Relative humidity Wind Speed
(mm) (°C) (mm) (%) (m/s)
Table 2: Sowing and harvesting time of the year for guar experiment.
Time
2018 2020
Date Day of Year Date Day of Year
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Pre-Irrigation June 15 166 May 15 136
Sowing July 03 184 June 02 154
Harvesting November 16 320 October 21 295
Table 3: Irrigation schedule for the guar experiment for all irrigation regimes for 2018 and 2020.
Day of Year Full Irrigation
2018 Irrigation Schedule for PI Condition Guar Experiment
167 43.18 43.18 43.18 43.18
2020 Irrigation Schedule for PI Condition Guar Experiment
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Table 4: Comparison of rainfall data between NOAA and Ziamet stations for the growing periods of guar
Growing season NMSU rainfall (mm) NOAA rainfall (mm)
Difference in rainfall (mm)
2018 262 342 80
2020 143.5 157 13.5
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Table 5: Model determined field capacity and wilting point for each layer of the soil profile for the pre-irrigation condition for full irrigation treatment.
Layers (cm)
Field Capacity Permanent Wilting Point
2018 2020 2018 2020
10 - 20 32 32 19 18
20 – 40 36 34 18 18
40 – 60 34 34 19 19
60 – 80 30 26 19 16
80 – 100 25 17 17 14
100 – 120 25 18 15 12
120 – 140 25 22.5 13 13
Table 6: Comparison of modeled, FAO-56, and NDVI methods for Kcb calculations
Year
FAO-56 Kcb NDVI-Kcb Modeled Kcb
F F F Vst Rst Rainf
2018 1.12 1.102 1.1 1.1 0.9 0.6
2020 1.17 1.092 1.12 1.1 0.9 0.9
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Table 7: A section from the water balance calculations to show example of erroneous data from 2018 for the full irrigation treatment.
Table 8: Data improvement in ET calculations for the year 2018
DOY in
Table 9: Root Mean Square Error (RMSE) of the irrigation treatments of guar experiments 2018 and 2020.
Treatments RMSE
2018 2020
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Full irrigation 0.035 0.025
Stress at vegetative stage 0.019 0.025
Stress at reproductive stage 0.018 0.019
Rainfed 0.026 0.021
159 List of Figures
Figure 1: Weather station at Clovis Agriculture Science Center (ASC), New Mexico. Picture courtesy: Ziamet Climate Center.
Figure 2: Study area of the guar experiments. Both seasons were run on the same field in Clovis ASC, NM.
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Figure 3: Distribution of factors on the field where the two wedges are divided in to 4 replicates marked as R1, R2, R3, and R4. Each replicate has two pre-irrigation conditions marked with distinct boundary lines. Further, each block has all four irrigation treatments as presented.
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Figure 4: Graphical representation of all neutron probe days showing ET from erroneous data (left) and improved ET (right) between intervals for 2018 guar experiment. a) full irrigation b) stress at vegetative stage c)
a)
b)
c)
d)
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10 – 20 cm 20 – 40 cm 40 – 60 cm 60 – 80 cm 80 – 100 cm 100 – 120 cm 120 - 140cm
a)
b)
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Figure 5: WINDS model calibration for guar experiment of 2018. Comparison of soil moisture content between daily simulated value with the neutron probe readings for each treatment. Soil moisture analysis for pre-irrigation condition treatments are a) no stress treatment b) stress at vegetative stress c) stress at reproductive stage, and d) rainfed.
c)
d)
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Figure 6: Graphical representation of all neutron probe days showing ET from erroneous data (left) and improved ET (right) between intervals for 2020 guar experiment. a) full irrigation b) stress at vegetative stage c) stress at reproductive stage, and d) rainfed treatment.
a)
b)
c)
d)
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10 – 20 cm 20 – 40 cm 40 – 60 cm 60 – 80 cm 80 – 100 cm 100 – 120 cm 120 - 140cm
a)
b)
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Figure 7: WINDS model calibration for guar experiment of 2020. Comparison of soil moisture content between daily simulated value with the neutron probe readings for each treatment. Soil moisture analysis for pre-irrigation condition treatments are a) no stress treatment b) stress at vegetative stress c) stress at reproductive stage, and d) rainfed.
c)
d)
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Figure 8: Simulated daily ETc curve also showing distribution between Evaporation (E) and Transpiration (T) for guar 2018 experiment for pre-irrigation full irrigation regime.
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Figure 9: Comparison of percent depletion for each soil layer simulated by the WINDS model for guar experiment 2018. A): precent depletion of PI full irrigation B) percent depletion of PI stress at vegetative stage.
A
B
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Figure 10: Comparison of percent depletion for each soil layer simulated by the WINDS model for guar experiment 2020. A): precent depletion of PI full irrigation B) percent depletion of PI stress at vegetative stage.
B A
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Figure 11. NDVI Kcb values and crop coefficient curves for full and stressed treatments during 2020 from the WINDS model analysis.