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多任务卫星数据同化在研究南美洲储水变化中的应用。

The application of multi-mission satellite data assimilation for studying water storage changes over South America.

机构信息

School of Earth and Planetary Sciences, Spatial Sciences, Curtin University, Perth, Australia; School of Engineering, University of Newcastle, Callaghan, New South Wales, Australia.

School of Earth and Planetary Sciences, Spatial Sciences, Curtin University, Perth, Australia.

出版信息

Sci Total Environ. 2019 Jan 10;647:1557-1572. doi: 10.1016/j.scitotenv.2018.08.079. Epub 2018 Aug 8.

Abstract

Constant monitoring of total water storage (TWS; surface, groundwater, and soil moisture) is essential for water management and policy decisions, especially due to the impacts of climate change and anthropogenic factors. Moreover, for most countries in Africa, Asia, and South America that depend on soil moisture and groundwater for agricultural productivity, monitoring of climate change and anthropogenic impacts on TWS becomes crucial. Hydrological models are widely being used to monitor water storage changes in various regions around the world. Such models, however, comes with uncertainties mainly due to data limitations that warrant enhancement from remotely sensed satellite products. In this study over South America, remotely sensed TWS from the Gravity Recovery And Climate Experiment (GRACE) satellite mission is used to constrain the World-Wide Water Resources Assessment (W3RA) model estimates in order to improve their reliabilities. To this end, GRACE-derived TWS and soil moisture observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and Soil Moisture and Ocean Salinity (SMOS) are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) in order to separately analyze groundwater and soil moisture changes for the period 2002-2013. Following the assimilation analysis, Tropical Rainfall Measuring Mission (TRMM)'s rainfall data over 15 major basins of South America and El Niño/Southern Oscillation (ENSO) data are employed to demonstrate the advantages gained by the model from the assimilation of GRACE TWS and satellite soil moisture products in studying climatically induced TWS changes. From the results, it can be seen that assimilating these observations improves the performance of W3RA hydrological model. Significant improvements are also achieved as seen from increased correlations between TWS products and both precipitation and ENSO over a majority of basins. The improved knowledge of sub-surface water storages, especially groundwater and soil moisture variations, can be largely helpful for agricultural productivity over South America.

摘要

持续监测总水资源储量(TWS;地表水、地下水和土壤湿度)对于水资源管理和政策决策至关重要,尤其是由于气候变化和人为因素的影响。此外,对于依赖土壤湿度和地下水来提高农业生产力的大多数非洲、亚洲和南美洲国家来说,监测气候变化和人为因素对 TWS 的影响变得至关重要。水文模型广泛用于监测世界各地不同地区的水资源储量变化。然而,这些模型存在不确定性,主要是由于数据限制,需要通过遥感卫星产品加以增强。在这项针对南美洲的研究中,利用重力恢复与气候实验(GRACE)卫星任务提供的遥感 TWS 来约束世界水资源评估(W3RA)模型的估算,以提高其可靠性。为此,利用集合平方根滤波器(EnSRF)将 GRACE 衍生的 TWS 和来自先进微波扫描辐射计-地球观测系统(AMSR-E)和土壤湿度和海洋盐度(SMOS)的土壤湿度观测值同化到 W3RA 中,以便分别分析 2002 年至 2013 年期间的地下水和土壤湿度变化。在同化分析之后,利用热带降雨测量任务(TRMM)在南美洲 15 个主要流域上空的降雨数据和厄尔尼诺/南方涛动(ENSO)数据,演示了该模型从 GRACE TWS 和卫星土壤湿度产品同化中获得的优势,用于研究气候引起的 TWS 变化。结果表明,同化这些观测值可提高 W3RA 水文模型的性能。从与大多数流域的降水和 ENSO 的相关性来看,还实现了显著的改进。对地下水资源,特别是地下水和土壤湿度变化的认识的提高,对南美洲的农业生产力有很大的帮助。

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