气候变化领域集成服务门户(CCPortal): Analyzing the Impact of Storm 'Daniel' and Subsequent Flooding on Thessaly's Soil Chemistry through Causal Inference

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DOI	10.3390/agriculture14040549
	Analyzing the Impact of Storm 'Daniel' and Subsequent Flooding on Thessaly's Soil Chemistry through Causal Inference
	Iatrou, Miltiadis; Tziouvalekas, Miltiadis; Tsitouras, Alexandros; Evangelou, Elefterios; Noulas, Christos; Vlachostergios, Dimitrios; Aschonitis, Vassilis; Arampatzis, George; Metaxa, Irene; Karydas, Christos; Tziachris, Panagiotis
发表日期	2024
EISSN	2077-0472
起始页码	14
结束页码	4
卷号	14 期号:4
英文摘要	Storm 'Daniel' caused the most severe flood phenomenon that Greece has ever experienced, with thousands of hectares of farmland submerged for days. This led to sediment deposition in the inundated areas, which significantly altered the chemical properties of the soil, as revealed by extensive soil sampling and laboratory analysis. The causal relationships between the soil chemical properties and sediment deposition were extracted using the DirectLiNGAM algorithm. The results of the causality analysis showed that the sediment deposition affected the CaCO3 concentration in the soil. Also, causal relationships were identified between CaCO3 and the available phosphorus (P-Olsen), as well as those between the sediment deposit depth and available manganese. The quantified relationships between the soil variables were then used to generate data using a Multiple Linear Perceptron (MLP) regressor for various levels of deposit depth (0, 5, 10, 15, 20, 25, and 30 cm). Then, linear regression equations were fitted across the different levels of deposit depth to determine the effect of the deposit depth on CaCO3, P, and Mn. The results revealed quadratic equations for CaCO3, P, and Mn as follows: 0.001XCaCO32 + 0.08XCaCO3 + 6.42, 0.004XP2 - 0.26XP + 12.29, and 0.003XMn2 - 0.08XMn + 22.47, respectively. The statistical analysis indicated that corn growing in soils with a sediment over 10 cm requires a 31.8% increase in the P rate to prevent yield decline. Additional notifications regarding cropping strategies in the near future are also discussed.
英文关键词	causal machine learning; soil analysis; causal discovery; crop fertilization; flood; agriculture; deposition; climate change
语种	英语
WOS研究方向	Agriculture
WOS类目	Agronomy
WOS记录号	WOS:001210135400001
来源期刊	AGRICULTURE-BASEL
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/299922
推荐引用方式 GB/T 7714	Iatrou, Miltiadis,Tziouvalekas, Miltiadis,Tsitouras, Alexandros,et al. Analyzing the Impact of Storm 'Daniel' and Subsequent Flooding on Thessaly's Soil Chemistry through Causal Inference[J],2024,14(4).
APA	Iatrou, Miltiadis.,Tziouvalekas, Miltiadis.,Tsitouras, Alexandros.,Evangelou, Elefterios.,Noulas, Christos.,...&Tziachris, Panagiotis.(2024).Analyzing the Impact of Storm 'Daniel' and Subsequent Flooding on Thessaly's Soil Chemistry through Causal Inference.AGRICULTURE-BASEL,14(4).
MLA	Iatrou, Miltiadis,et al."Analyzing the Impact of Storm 'Daniel' and Subsequent Flooding on Thessaly's Soil Chemistry through Causal Inference".AGRICULTURE-BASEL 14.4(2024).