Title: The quantitative survey of drought effects on the barley yield in Eastern Azarbayjan by classical statistical ways
1The quantitative survey of
drought effects on the barley yield in Eastern
Azarbayjan by classical statistical ways
- Elham Rahmani1
-
- Dr.Abdolmajid Liaghat1 Prof.Ali Khalili1
- 1 Irr. Reclam. Eng. Faculty, Agro meteorology
Department, - university of Tehran, Tehran, Iran
- 10th International Meeting on Statistical
Climatology (10IMSC)
2Introduction
- The main drought definition is the lack of
gaining water in specific period of time and in a
distinct region. - Drought causes extensive damages to agricultural
products. - Rainfall has the major part in all definitions of
drought indexes. - The climatic parameters are usually used for
estimating crop products and predicting
agricultural droughts .
3Objective
- In this research ,
- the attempt is to define different models that
relate drought indexes and climatic parameters
combinatory on crop yield, using classical
(regression) methods.
4Methodology
- To develop regression models, different climatic
parameters and drought indexes were used to
relate them with crop yield. - Data were collected from north east of Iran,
Tabriz and Miane synoptic stations.
5Tabriz
Miane
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7Climatic Parameters
8Drought Indexes
9Estimated Drought Indexes
- The Percentage of Normal Precipitation Index
(PNPI) - Standard Index of Annual Precipitation (SIAP)
- Converted Selenianov Hydrothermal Index (HT)
- Nguyen Index (k)
- Rainfall Anomaly Index (RAI)
- Standardized Precipitation Index (SPI)
- Shashko Moisture Drought Index (MD)
- Transeau Index (Ih)
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12Single and Multivariate Regression Models
13single models
Climatic Parameters Irrigated barley yield Tabriz (30 years) Rain fed barley yield Tabriz (30 years) Rain fed barley yield Tabriz (17 years) Rain fed barley yield Miane (17 years)
Active temperature above 10 y -1E-05x² 0.0336x - 28.459 R2 0.1898 95 y -3E-06x² 0.0124x - 12.492 R2 0.113 95 y -8E-06x² 0.0258x - 20.916 R2 0.2958 95 y -3E-06x² 0.0085x - 4.4764 R2 0.3087 95
Rainfall y -7E-05x² 0.0429x - 6.0209 R2 0.3486 99 no meaningful function y -0.0001x² 0.0639x - 8.5302 R2 0.7578 99 y -3E-05x² 0.0249x - 4.6334 R2 0.4825 99
Relative humidity no meaningful function y 0.0053x² - 0.7383x 25.049 R2 0.1942 95 y 0.015x² - 1.5607x 40.075 R2 0.2661 95 no meaningful function
Average wind speed no meaningful function y 0.3904x² - 3.3671x 6.6908 R2 0.6137 99 no meaningful function no meaningful function
Sunshine hours y -1E-05x² 0.04x - 30.287 R2 0.2719 99 no meaningful function y -1E-05x² 0.0377x - 27.808 R2 0.4266 99 y -2E-06x² 0.0053x - 1.2811 R2 0.5582 99
Average min. temperature y 0.9757Ln(x) - 1.6294 R2 0.1342 95 y -0.0096x² 0.335x - 1.5499 R2 0.1797 95 no meaningful function y -3E-05x² 0.029x - 6.5016 R2 0.4585 99
Average max. temperature no meaningful function y -0.0067x² 0.3817x - 4.3719 R2 0.1299 95 no meaningful function no meaningful function
Average mean temperature no meaningful function y -0.0094x² 0.4038x - 3.2454 R2 0.1608 95 no meaningful function no meaningful function
Evaporation no meaningful function y 5E-06x² - 0.0037x - 0.4571 R2 0.5602 99 no meaningful function y -3E-05x² 0.029x - 6.5016 R2 0.4585 99
Vapor pressure no meaningful function no meaningful function y 0.0336x² - 3.6395x 98.052 R2 0.3149 95 y 0.0345x² - 3.9358x 111.49 R2 0.4426 99
14single models
Drought indexes Irrigated barley yield Tabriz (30 years) Rain fed barley yield Tabriz (30 years) Rain fed barley yield Tabriz (17 years) Rain fed barley yield Miane (17 years)
HT y -1.3012x² 4.913x - 4.0464 R2 0.3103 99 no meaningful function y -2.4479x² 8.4324x - 6.3427 R2 0.7611 99 y -0.7389x² 3.786x - 3.925 R2 0.4963 99
Md y -0.238x² 2.4767x - 5.9683 R2 0.2969 99 no meaningful function y -0.3345x² 3.4935x - 8.2593 R2 0.6992 99 y -0.0709x² 1.26x - 4.1423 R2 0.4602 99
k y -0.2222x² 1.4151x - 1.6616 R2 0.471 99 y -0.0557x² 0.6635x - 1.471 R2 0.2296 99 y -0.1895x² 1.0599x - 0.7591 R2 0.6815 99 no meaningful function
Ih no meaningful function no meaningful function y -44.775x² 35.065x - 5.7155 R2 0.6969 99 no meaningful function
SIAP y -0.2956x² 0.6115x 0.2956 R2 0.3486 99 no meaningful function y -0.4593x² 0.7706x 0.6192 R2 0.7578l 99 y -0.1145x² 0.7784x - 0.1811 R2 0.4825 99
PNPI y -4.0524x² 10.369x - 6.0209 R2 0.3486 99 no meaningful function y -6.2963x² 15.446x - 8.5302 R2 0.7578 99 y -1.5702x² 6.0225x - 4.6334 R2 0.4825 99
RAI y -0.0402x² 0.2116x 0.32 R2 0.3571 99 no meaningful function y -0.0582x² 0.2627x 0.6215 R2 0.7588 99 y 0.0052x² 0.171x - 0.0118 R2 0.5011 99
SPI3 y -0.0042x² 0.0971x 0.114 R2 0.2126 99 no meaningful function y -0.0072x² 0.124x 0.3717 R2 0.5184 99 y -0.0125x² 0.1159x 0.3273 R2 0.4054 99
SPI6, SPI9, SPI12, SPI24 no meaningful function no meaningful function SPI6 0.0027x² 0.1045x 0.0706 R2 0.361 99 no meaningful function
15Multivariate models
Rain fed barley yield Miane (17 years) Rain fed barley yield Tabriz (17 years) Rain fed barley yield Tabriz (30 years) Irrigated barley yield Tabriz (30 years) Multiple Relations
Y(Z) - 3.32 0.0124 P 0.672 wind - 0.000974 sunshine R2 75.0 R2(adj) 69.2 Y(Z)-8.910.0100P 0.0919RH0.250wind R2 64.4 R2(adj) 56.2 Y(Z) - 4.45 0.570 wind 0.00135 E 0.101 Tmin R2 72.7 R2(adj) 69.5 Y(Z) - 2.33 0.0107 P 0.0737 Tmin -0.00115 Sun 0.00168 E R2 57.7 R2(adj)49.6 Climatic parameters
Y(Z) - 3.02 1.25 HT 0.159 Md 0.22 K R2 55.2 R2(adj) 44.9 Y(Z)2.07-0.466K 0.0369 SPI24 R2 64.8 R2(adj) 59.8 Y(Z)-0.826 0.223 K - 0.0183 SPI24 R2 23.2 R2(adj) 17.3 Y(Z) 0.639 - 1.36 Ih 0.252 RAI 0.0170 SPI24 R2 47.8 R2(adj)41.8 Drought indexes
Y(Z) 0.02 - 0.00103 Tgt10 0.00981 P 0.658 wind - 0.00109 sunshine-0.403 K R2 76.8 R2(adj) 66.3 Y(Z) - 3.52 0.0641 RH 0.376 wind - 0.487 K 0.0374 SPI 24 R2 76.6 R2(adj) 68.8 Y(Z) - 5.87 - 0.0171 SPI24 0.00525 P 0.626 Wind 0.00133 E 0.0926 Tmin R2 78.4 R2(adj) 72.7 Y(Z) 2.86 0.236 RAI - 1.11 Ih 0.0615 Tmin - 0.00162 Sun 0.0131 SPI24 R2 65.4 R2(adj) 56.3 Combination of Climatic parameters and drought indexes
16CallingRegression Models
17Rain fed barley yield Miane(17 years) Rain fed barley yield Tabriz(17 years) Rain fed barley yield Tabriz(30 years) Irrigated barley yield Tabriz(30 years) Developed Models
3-1 2-1 1-1-R 1-1-I Active temp. above 10
3-2 2-2 1-2-R 1-2-I Rainfall
3-3 2-3 1-3-R 1-3-I Relative humidity
3-4 2-4 1-4-R 1-4-I Average wind speed
3-5 2-5 1-5-R 1-5-I Sunshine hours
3-6 2-6 1-6-R 1-6-I Average min. temperature
3-7 2-7 1-7-R 1-7-I Average max. temperature
3-8 2-8 1-8-R 1-8-I Average mean temperature
3-9 2-9 1-9-R 1-9-I Evaporation
3-10 2-10 1-10-R 1-10-I Vapor pressure
3-11 2-11 1-11-R 1-11-I Hydrothermal index (HT)
3-12 2-12 1-12-R 1-12-I Shashko moisture drought Index (Md)
3-13 2-13 1-13-R 1-13-I Nguyen Index (k)
3-14 2-14 1-14-R 1-14-I Transeau Index (Ih)
3-15 2-15 1-15-R 1-15-I Standard index of annual precipitation (SIAP)
3-16 2-16 1-16-R 1-16-I The Percentage of normal precipitation index (PNPI)
3-17 2-17 1-17-R 1-17-I Rainfall Anomaly Index (RAI)
3-18 2-18 1-18-R 1-18-I SPI3
3-19 2-19 1-19-R 1-19-I SPI6
3-20 2-20 1-20-R 1-20-I SPI9
3-21 2-21 1-21-R 1-21-I SPI12
3-22 2-22 1-22-R 1-22-I SPI24
3-23 2-23 1-23-R 1-23-I Climatic parameters
3-24 2-24 1-24-R 1-24-I Drought indexes
3-25 2-25 1-25-R 1-25-I Climatic parameters and drought indexes
18Evaluation of Model function indexes
19 The values of R , RMSE and MBE for models
Models R (test) RMSE (test) MBE (test) MBE (test)
1-25-I 0.73 0.56 0.234 -0.632
1-23-R 0.1 0.316 0.056 -0.067
1-25-R 0.529 0.319 0.318 -0.383
2-2 0.789 0.802 0.79 -6.58
2-11 0.695 0.634 0.254 -2.117
2-17 0.867 0.612 0.348 -9.2
2-25 0.937 0.816 0.15 -1.25
3-23 0.819 0.733 0.098 -0.516
3-25 0.795 0.724 0.036 -0.189
20Ranking Models
Ranking models Parameters Sum of Rank values MBE (test) RMSE (test) R (tset) Models
3-25 Tgt10 P wind Sunshine K 14 5 3 6 1-25-I
1-23-R wind E Tmin 12 2 1 9 1-23-R
3-23 P wind Sunshine 17 7 2 8 1-25-R
1-25-I RAI Ih SPI24 Sunshine Tmin 22 9 8 5 2-2
2-25 RH wind K SPI24 18 6 5 7 2-11
2-17 RAI 14 8 4 2 2-17
1-25-R SPI24 P Wind E Tmin 14 4 9 1 2-25
2-11 HT 13 3 7 3 3-23
2-2 P 11 1 6 4 3-25
21Conclusion
- The best multivariate regression model includes
P, wind, Sunshine, tgt10, K - Among the drought indexes studied in this
research, RAI, Ih, SPI24, K are the most
effective ones on the crop yield estimation. - The multiple models include the combination of
climatic parameters drought indexes together
are better for crop yield prediction. - To predict the yield of products, multiple models
are better than simple models.
22Thanks for your kind attention