New Investigation and Challenge for Spatiotemporal Drought Monitoring Using Bottom-Up Precipitation Dataset (SM2RAIN-ASCAT) and NDVI in Moroccan Arid and Semi-Arid Rangelands

Q3 Environmental Science

Ekologia Bratislava Pub Date : 2022-03-01 DOI:10.2478/eko-2022-0010

Asmae Zbiri, Azeddine Hachmi, Dominique Haesen, Fatima Ezzahrae El Alaoui-Faris

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引用次数: 4

Abstract

Abstract Remotely sensed soil moisture products showed sensitivity to vegetation cover density and soil typology at regional dryland level. In these regions, drought monitoring is significantly performed using soil moisture index and rainfall data. Recently, rainfall and soil moisture observations have increasingly become available. This has hampered scientific progress as regards characterization of land surface processes not just in meteorology. The purpose of this study was to investigate the relationship between a newly developed precipitation dataset, SM2RAIN (Advanced SCATterometer (SM2RAIN-ASCAT), and NDVI (eMODIS-TERRA) in monitoring drought events over diverse rangeland regions of Morocco. Results indicated that the highest polynomial correlation coefficient and the lowest root mean square error (RMSE) between SM2RAIN-ASCAT and NDVI were found in a 10-year period from 2007 to 2017 in all rangelands (R = 0.81; RMSE = 0.05). This relationship was strong for degraded rangeland, where there were strong positive correlation coefficients for NDVI and SM2RAIN (R = 0.99). High correlations were found for sparse and moderate correlations for shrub rangeland (R = 0.82 and 0.61, respectively). The anomalies maps showed a very good similarity between SM2RAIN and Normalized Difference Vegetation Index (NDVI) data. The results revealed that the SM2RAIN-ASCAT and NDVI product could accurately predict drought events in arid and semi-arid rangelands.

查看原文本刊更多论文

摩洛哥干旱和半干旱牧场利用自下而上降水数据集（SM2RAIN-ASCAT）和NDVI进行时空干旱监测的新调查和挑战

摘要遥感土壤水分产物对区域旱地植被覆盖密度和土壤类型具有敏感性。在这些地区，干旱监测主要使用土壤湿度指数和降雨量数据。最近，降雨和土壤湿度观测越来越多。这阻碍了陆地表面过程表征方面的科学进展，而不仅仅是在气象学方面。本研究的目的是研究新开发的降水数据集SM2RAIN（Advanced SCAT terometer，SM2RAIN-ASCAT）和NDVI（eMODIS TERRA）在监测摩洛哥不同牧场干旱事件中的关系。结果表明，在2007年至2017年的10年期间，所有牧场的SM2RAIN-ASCAT与NDVI之间的多项式相关系数最高，均方根误差（RMSE）最低（R=0.81；RMSE=0.05），其中NDVI和SM2RAIN具有较强的正相关系数（R=0.99）。灌木草地的稀疏相关性和中等相关性较高（分别为R=0.82和0.61）。异常图显示SM2RAIN与归一化植被指数（NDVI）数据具有很好的相似性。结果表明，SM2RAIN-ASCAT和NDVI产品可以准确预测干旱和半干旱牧场的干旱事件。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Ekologia Bratislava Environmental Science-Ecology

CiteScore

1.80

自引率

0.00%

发文量

审稿时长

10 weeks

期刊介绍： The Journal Ecology (Bratislava) places the main emphasis on papers dealing with complex characteristics of ecosystems. Treated are not only general, theoretical and methodological but also particular practical problems of landscape preservation and planning. The ecological problems of the biosphere are divided into four topics: ecology of populations: study of plant and animal populations as basic components of ecosystems, ecosystem studies: structure, processes, dynamics and functioning of ecosystems and their mathematical modelling, landscape ecology: theoretical and methodical aspects, complex ecological investigation of territorial entities and ecological optimization of landscape utilization,