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Development and Assessment of the SMAP Enhanced Passive Soil Moisture Product.SMAP增强型被动土壤湿度产品的开发与评估。
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2
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L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting.L波段微波遥感和陆地数据同化改善了用于水文预报的风暴前土壤湿度条件的表征。
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将基于哨兵1号和土壤湿度主动被动遥感卫星(SMAP)的卫星土壤湿度反演数据同化到SWAT水文模型中:卫星重访时间和产品空间分辨率对小流域洪水模拟的影响。

Assimilation of Sentinel 1 and SMAP - based satellite soil moisture retrievals into SWAT hydrological model: the impact of satellite revisit time and product spatial resolution on flood simulations in small basins.

作者信息

Azimi Shima, Dariane Alireza B, Modanesi Sara, Bauer-Marschallinger Bernhard, Bindlish Rajat, Wagner Wolfgang, Massari Christian

机构信息

Khaje Nasir Toosi University of Technology Faculty of Civil Engineering, Tehran, Iran.

National Research Council (CNR), Research Institute for Geo-Hydrological Protection, Perugia, Italy.

出版信息

J Hydrol (Amst). 2020 Feb;581. doi: 10.1016/j.jhydrol.2019.124367. Epub 2019 Nov 22.

DOI:10.1016/j.jhydrol.2019.124367
PMID:33154604
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7608049/
Abstract

In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events in response to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small (< 500 km) and hydrologically different catchments located in Central Italy. We ingested 1) the Soil Moisture Active and Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km EASE-Grid soil moisture, 2) the Advanced SCATterometer (ASCAT) H113 soil moisture product released within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) which has a nearly daily temporal resolution and sampling of 12.5 km, and 3) a fused ASCAT/Sentinel-1 (S1) satellite soil moisture product named SCATSAR-SWI with temporal and spatial sampling of 1 day and 1 km, respectively into SWAT hydrological model via the Ensemble Kalman Filter (EnKF). Different configurations were tested with the aim of exploring the effect of the hydrological regime, the land use conditions, the spatial sampling and the revisit time of the products (which controls the amount of available data to be potentially ingested). Results show a general improvement of SWAT discharge simulations for all products in terms of error and Nash Sutcliffe efficiency index. In particular, we found a relatively good behavior of both the active and the passive products in terms of low flows improvement especially for the catchment characterized by a higher baseflow component. The benefit of the higher spatial resolution of SCATSAR-SWI obtained via S1 over ASCAT was small, likely due to very challenging areas for the S1 retrieval. Eventually, better performances were obtained for the passive product in the more forested catchment. With the aim of exploring the benefit of having more frequent satellite soil moisture observations to be ingested, we tested the performance of the ASCAT product with a reduced temporal sampling obtained by temporally matching ASCAT observations to that of SMAP. The results show a significant reduction of the performance of ASCAT, suggesting that the correction frequency (due to the higher number of observations available) for small catchments is an important aspect for improving flood forecasting as it helps to adjust more frequently the pre-storm soil moisture conditions.

摘要

在径流产生过程中,土壤湿度起着重要作用,因为它控制着对降雨输入响应的洪水事件的规模。在本研究中,我们调查了新一代卫星土壤湿度反演通过数据同化土壤湿度来改进土壤与水资源评估工具(SWAT)日流量模拟的能力,研究对象是位于意大利中部的两个面积较小(<500平方公里)且水文特征不同的流域。我们将以下数据通过集合卡尔曼滤波器(EnKF)输入到SWAT水文模型中:1)土壤湿度主动和被动(SMAP)增强型L3辐射计全球每日9公里增强分辨率多极格网(EASE-Grid)土壤湿度数据;2)欧洲气象卫星应用组织(EUMETSAT)支持业务水文和水资源管理卫星应用设施(H-SAF)发布的先进散射计(ASCAT)H113土壤湿度产品,其时间分辨率接近每日,采样间隔为12.5公里;3)一种融合的ASCAT/哨兵1号(S1)卫星土壤湿度产品,名为SCATSAR-SWI,时间采样为1天,空间采样为1公里。为了探究水文状况、土地利用条件、空间采样以及产品重访时间(这控制着可潜在输入的可用数据量)的影响,我们测试了不同的配置。结果表明,就误差和纳什-萨特克利夫效率指数而言,所有产品的SWAT流量模拟都有总体改善。特别是,我们发现主动和被动产品在改善低流量方面表现相对良好,尤其是对于基流成分较高的流域。通过S1获得的SCATSAR-SWI的高空间分辨率相对于ASCAT的优势较小,这可能是由于S1反演在某些区域面临很大挑战。最终,在森林覆盖率更高的流域中,被动产品表现出更好性能。为了探究输入更频繁的卫星土壤湿度观测数据的益处,我们通过将ASCAT观测数据与SMAP观测数据在时间上匹配,测试了时间采样减少的ASCAT产品的性能。结果表明ASCAT的性能显著下降,这表明对于小流域而言,校正频率(由于可用观测数据数量更多)是改善洪水预报的一个重要方面,因为它有助于更频繁地调整暴雨前的土壤湿度状况。

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