Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT
The study is conducted to examine the climate change impact on rice Crop Water Requirement (CWR) and Net Irrigation Requirement (NIR) using the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) coupled with the CROPWAT 8.0 model. The maximum temperature (Tmax), minimum temperature (T...
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| Format: | Article |
| Language: | English |
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IWA Publishing
2023-04-01
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| Series: | Journal of Water and Climate Change |
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| Online Access: | http://jwcc.iwaponline.com/content/14/4/1147 |
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| author | Abhishek Agrawal Prashant Kumar Srivastava Vinod Kumar Tripathi Swati Maurya Reema Sharma Shrinivasa D. J. |
| author_facet | Abhishek Agrawal Prashant Kumar Srivastava Vinod Kumar Tripathi Swati Maurya Reema Sharma Shrinivasa D. J. |
| author_sort | Abhishek Agrawal |
| collection | DOAJ |
| description | The study is conducted to examine the climate change impact on rice Crop Water Requirement (CWR) and Net Irrigation Requirement (NIR) using the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) coupled with the CROPWAT 8.0 model. The maximum temperature (Tmax), minimum temperature (Tmin), and rainfall projections for the baseline (years 1981–2015) and future (years 2030 and 2040) under Representative Concentration Pathway (RCP) 4.5 were derived from NEX-GDDP. To reduce the bias, linear scaling (LS) and the modified difference approach (MDA) were employed. Results show that LS performed better than the MDA along with improved statistical measures such as mean (μ), standard deviation (σ), and percent bias (Pbias), in the case of Tmax and Tmin (μ = 31.14 and 19.63 °C, σ = 5.75 and 6.78 °C, Pbias = 1.43 and 0.33%), followed by rainfall (μ = 2.67 mm, σ = 4.94 mm, and Pbias = 2.4%). The future climatic projections showed an increasing trend in both Tmax and Tmin, which are expected to increase by 1.7 °C by 2040. This would cause an increased range of 1.2 and 2% in 2030 and 2040, respectively. Due to a wide variation in effective rainfall (Peff), NIR could increase by 4 and 9% in 2030 and 2040, respectively. The above results may help formulate adaptation measures to alleviate the impacts of climate change on rice production.
HIGHLIGHTS
Global Climate Model (GCM) data should not be used directly in crop growth models.;
To reduce bias corrections, linear scaling performs better than the modified difference approach.;
The average seasonal irrigation water requirement for rice crops would vary from 4 to 9% by the year 2040 as compared to the baseline.; |
| first_indexed | 2024-04-09T13:43:34Z |
| format | Article |
| id | doaj.art-f0df371e99dd40759172ed07c0fbbc0e |
| institution | Directory Open Access Journal |
| issn | 2040-2244 2408-9354 |
| language | English |
| last_indexed | 2024-04-24T08:09:59Z |
| publishDate | 2023-04-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Journal of Water and Climate Change |
| spelling | doaj.art-f0df371e99dd40759172ed07c0fbbc0e2024-04-17T08:20:01ZengIWA PublishingJournal of Water and Climate Change2040-22442408-93542023-04-011441147116110.2166/wcc.2023.349349Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWATAbhishek Agrawal0Prashant Kumar Srivastava1Vinod Kumar Tripathi2Swati Maurya3Reema Sharma4Shrinivasa D. J.5 Department of Agricultural Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India Department of Agricultural Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India Department of Agricultural Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India Department of Agricultural Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India The study is conducted to examine the climate change impact on rice Crop Water Requirement (CWR) and Net Irrigation Requirement (NIR) using the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) coupled with the CROPWAT 8.0 model. The maximum temperature (Tmax), minimum temperature (Tmin), and rainfall projections for the baseline (years 1981–2015) and future (years 2030 and 2040) under Representative Concentration Pathway (RCP) 4.5 were derived from NEX-GDDP. To reduce the bias, linear scaling (LS) and the modified difference approach (MDA) were employed. Results show that LS performed better than the MDA along with improved statistical measures such as mean (μ), standard deviation (σ), and percent bias (Pbias), in the case of Tmax and Tmin (μ = 31.14 and 19.63 °C, σ = 5.75 and 6.78 °C, Pbias = 1.43 and 0.33%), followed by rainfall (μ = 2.67 mm, σ = 4.94 mm, and Pbias = 2.4%). The future climatic projections showed an increasing trend in both Tmax and Tmin, which are expected to increase by 1.7 °C by 2040. This would cause an increased range of 1.2 and 2% in 2030 and 2040, respectively. Due to a wide variation in effective rainfall (Peff), NIR could increase by 4 and 9% in 2030 and 2040, respectively. The above results may help formulate adaptation measures to alleviate the impacts of climate change on rice production. HIGHLIGHTS Global Climate Model (GCM) data should not be used directly in crop growth models.; To reduce bias corrections, linear scaling performs better than the modified difference approach.; The average seasonal irrigation water requirement for rice crops would vary from 4 to 9% by the year 2040 as compared to the baseline.;http://jwcc.iwaponline.com/content/14/4/1147climate changebias correctioncrop water requirementirrigation water requirement |
| spellingShingle | Abhishek Agrawal Prashant Kumar Srivastava Vinod Kumar Tripathi Swati Maurya Reema Sharma Shrinivasa D. J. Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT Journal of Water and Climate Change climate change bias correction crop water requirement irrigation water requirement |
| title | Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT |
| title_full | Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT |
| title_fullStr | Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT |
| title_full_unstemmed | Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT |
| title_short | Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT |
| title_sort | future projections of crop water and irrigation water requirements using a bias corrected regional climate model coupled with cropwat |
| topic | climate change bias correction crop water requirement irrigation water requirement |
| url | http://jwcc.iwaponline.com/content/14/4/1147 |
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