Seasonal forecasts have sufficient skill to inform some agricultural decisions
Seasonal forecasts, which look several months into the future, are currently underutilized in active decision-making, particularly for agricultural and natural resource management. This underutilization can be attributed to the absence of forecasts for decision-relevant variables at the required spa...
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| Format: | Article |
| Language: | English |
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IOP Publishing
2024-01-01
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| Series: | Environmental Research Letters |
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| Online Access: | https://doi.org/10.1088/1748-9326/ad8bde |
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| author | Ashish Kondal Katherine Hegewisch Mingliang Liu John T Abatzoglou Jennifer C Adam Bart Nijssen Kirti Rajagopalan |
| author_facet | Ashish Kondal Katherine Hegewisch Mingliang Liu John T Abatzoglou Jennifer C Adam Bart Nijssen Kirti Rajagopalan |
| author_sort | Ashish Kondal |
| collection | DOAJ |
| description | Seasonal forecasts, which look several months into the future, are currently underutilized in active decision-making, particularly for agricultural and natural resource management. This underutilization can be attributed to the absence of forecasts for decision-relevant variables at the required spatiotemporal resolution and at the time when the decisions are made and a perception of poor skill by decision-makers. Addressing these constraints, we quantified the skill of seasonal forecasts in informing two agricultural decisions with differing decision timeframes and influencer variables: (a) whether to apply fertilizer in fall or wait until spring based on expected winter temperatures, and (b) drought response, such as whether to lease water based on expectations of drought. We also looked into how early the forecast can be provided without significant degradation in skill. Currently, drought response decisions are typically formulated in April, utilizing drought forecasts issued in the same month, while fall fertilization decisions are generally made between August and September. There is growing interest among stakeholders in the availability of earlier forecasts to inform these critical choices. We utilized the North American multi-model ensemble (NMME) hindcasts for the time period 1982–2020 over the Pacific Northwest US (PNW) to obtain meteorological variables. Runoff was estimated via simulations of the coupled crop-hydrology VIC-CropSyst model. The skill assessment with the Heidke Skill Score (HSS) yielded promising outcomes in both decisions for the entire PNW region. Notably, NMME’s positive skill (median HSS of 30%) in predicting warmer winters identifies years when fertilizer application should be avoided to prevent fertilizer loss through mineralization (and associated costs). Similarly, there is skill in forecasting drought conditions in most irrigated watersheds for up to two months in advance of April, the current decision time. In conclusion, our findings affirm that contrary to the perception of low skill and resulting underutilization, current seasonal forecasts hold the potential to inform at least some key agricultural decisions. |
| format | Article |
| id | doaj-art-e004f93fbb0f4018adbca387ca1d241d |
| institution | Kabale University |
| issn | 1748-9326 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj-art-e004f93fbb0f4018adbca387ca1d241d2024-11-15T08:01:11ZengIOP PublishingEnvironmental Research Letters1748-93262024-01-01191212404910.1088/1748-9326/ad8bdeSeasonal forecasts have sufficient skill to inform some agricultural decisionsAshish Kondal0https://orcid.org/0000-0002-9739-5760Katherine Hegewisch1https://orcid.org/0000-0002-9539-2929Mingliang Liu2https://orcid.org/0000-0002-1963-5933John T Abatzoglou3https://orcid.org/0000-0001-7599-9750Jennifer C Adam4https://orcid.org/0000-0003-4205-8860Bart Nijssen5https://orcid.org/0000-0002-4062-0322Kirti Rajagopalan6https://orcid.org/0000-0002-7086-9858Washington State University, Civil and Environmental Engineering , Pullman, WA 99163-2618, United States of AmericaUniversity of California Merced, Management of Complex Systems , Merced, CA 95343-5001, United States of AmericaWashington State University, Civil and Environmental Engineering , Pullman, WA 99163-2618, United States of AmericaUniversity of California Merced, Management of Complex Systems , Merced, CA 95343-5001, United States of AmericaWashington State University, Civil and Environmental Engineering , Pullman, WA 99163-2618, United States of AmericaUniversity of Washington, Civil and Environmental Engineering , Seattle, WA 98195-2700, United States of AmericaWashington State University, Biological Systems Engineering , Pullman, WA 99163-2618, United States of AmericaSeasonal forecasts, which look several months into the future, are currently underutilized in active decision-making, particularly for agricultural and natural resource management. This underutilization can be attributed to the absence of forecasts for decision-relevant variables at the required spatiotemporal resolution and at the time when the decisions are made and a perception of poor skill by decision-makers. Addressing these constraints, we quantified the skill of seasonal forecasts in informing two agricultural decisions with differing decision timeframes and influencer variables: (a) whether to apply fertilizer in fall or wait until spring based on expected winter temperatures, and (b) drought response, such as whether to lease water based on expectations of drought. We also looked into how early the forecast can be provided without significant degradation in skill. Currently, drought response decisions are typically formulated in April, utilizing drought forecasts issued in the same month, while fall fertilization decisions are generally made between August and September. There is growing interest among stakeholders in the availability of earlier forecasts to inform these critical choices. We utilized the North American multi-model ensemble (NMME) hindcasts for the time period 1982–2020 over the Pacific Northwest US (PNW) to obtain meteorological variables. Runoff was estimated via simulations of the coupled crop-hydrology VIC-CropSyst model. The skill assessment with the Heidke Skill Score (HSS) yielded promising outcomes in both decisions for the entire PNW region. Notably, NMME’s positive skill (median HSS of 30%) in predicting warmer winters identifies years when fertilizer application should be avoided to prevent fertilizer loss through mineralization (and associated costs). Similarly, there is skill in forecasting drought conditions in most irrigated watersheds for up to two months in advance of April, the current decision time. In conclusion, our findings affirm that contrary to the perception of low skill and resulting underutilization, current seasonal forecasts hold the potential to inform at least some key agricultural decisions.https://doi.org/10.1088/1748-9326/ad8bdeseasonal forecastsNMMEforecast skillseasonal climate forecastagricultural decision-makingdrought forecasting |
| spellingShingle | Ashish Kondal Katherine Hegewisch Mingliang Liu John T Abatzoglou Jennifer C Adam Bart Nijssen Kirti Rajagopalan Seasonal forecasts have sufficient skill to inform some agricultural decisions Environmental Research Letters seasonal forecasts NMME forecast skill seasonal climate forecast agricultural decision-making drought forecasting |
| title | Seasonal forecasts have sufficient skill to inform some agricultural decisions |
| title_full | Seasonal forecasts have sufficient skill to inform some agricultural decisions |
| title_fullStr | Seasonal forecasts have sufficient skill to inform some agricultural decisions |
| title_full_unstemmed | Seasonal forecasts have sufficient skill to inform some agricultural decisions |
| title_short | Seasonal forecasts have sufficient skill to inform some agricultural decisions |
| title_sort | seasonal forecasts have sufficient skill to inform some agricultural decisions |
| topic | seasonal forecasts NMME forecast skill seasonal climate forecast agricultural decision-making drought forecasting |
| url | https://doi.org/10.1088/1748-9326/ad8bde |
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