气候变化领域集成服务门户(CCPortal): PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts

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DOI	10.3390/rs16071116
	PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts
	Paolini, Giovanni; Escorihuela, Maria Jose; Bellvert, Joaquim; Merlin, Olivier; Pellarin, Thierry
发表日期	2024
EISSN	2072-4292
起始页码	16
结束页码	7
卷号	16 期号:7
英文摘要	Efficient water management strategies are of utmost importance in drought-prone regions, given the fundamental role irrigation plays in avoiding yield losses and food shortages. Traditional methodologies for estimating irrigation amounts face limitations in terms of overall precision and operational scalability. This study proposes to estimate irrigation amounts from soil moisture (SM) data by adapting the PrISM (Precipitation Inferred from Soil Moisture) methodology. The PrISM assimilates SM into a simple Antecedent Precipitation Index (API) model using a particle filter approach, which allows the creation and estimation of irrigation events. The methodology is applied in a semi-arid region in the Ebro basin, located in the north-east of Spain (Catalonia), from 2016 to 2023. Multi-year drought, which started in 2020, particularly affected the region starting from the spring of 2023, which led to significant reductions in irrigation district water allocations in some of the areas of the region. This study demonstrates that the PrISM approach can correctly identify areas where water restrictions were adopted in 2023, and monitor the water usage with good performances and reliable results. When compared with in situ data for 8 consecutive years, PrISM showed a significant person's correlation between 0.58 and 0.76 and a cumulative weekly root mean squared error (rmse) between 7 and 11 mm. Additionally, PrISM was applied to three irrigation districts with different levels of modernization, due to the different predominant irrigation systems: flood, sprinkler, and drip. This analysis underlined the strengths and limitations of PrISM depending on the irrigation techniques monitored. PrISM has good performances in areas irrigated by sprinkler and flood systems, while difficulties are present over drip irrigated areas, where the very localized and limited irrigation amounts could not be detected from SM observations.
英文关键词	irrigation estimates; data assimilation; soil moisture; remote sensing; PrISM
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:001200831200001
来源期刊	REMOTE SENSING
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/301869
作者单位	IRTA; INRAE; Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Centre National de la Recherche Scientifique (CNRS); Institut de Recherche pour le Developpement (IRD); Centre National de la Recherche Scientifique (CNRS); Institut de Recherche pour le Developpement (IRD); Communaute Universite Grenoble Alpes; Universite Grenoble Alpes (UGA)
推荐引用方式 GB/T 7714	Paolini, Giovanni,Escorihuela, Maria Jose,Bellvert, Joaquim,et al. PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts[J],2024,16(7).
APA	Paolini, Giovanni,Escorihuela, Maria Jose,Bellvert, Joaquim,Merlin, Olivier,&Pellarin, Thierry.(2024).PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts.REMOTE SENSING,16(7).
MLA	Paolini, Giovanni,et al."PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts".REMOTE SENSING 16.7(2024).