Spatial Evaluation and Assimilation of SMAP, SMOS, and ASCAT Satellite Soil Moisture Products Over Africa Using Statistical Techniques

Mousa, B. G.; Hong, Su Young

doi:10.1029/2019ea000841

Cited by 22 publications

(11 citation statements)

References 68 publications

(110 reference statements)

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“…Based on the error coefficient distribution for each product in Hunan province, the high-r-value area is mainly concentrated in the central region, while the low-r-value area is primarily in the west and south (Figure 3). These results show that microwave remote sensing can capture changes in the surface SM in the central part of Hunan province and most of the evaluation indices showed good performance and were comparable with relevant studies (Mousa and Shu, 2020;Wang et al, 2021b). Therefore, the observation products of microwave remote sensing show high reliability.…”

Section: Authenticity Assessment Of Multisource Remote Sensing-based ...supporting

confidence: 74%

Evaluation of Six Satellite-Based Soil Moisture Products Based on in situ Measurements in Hunan Province, Central China

Fan

Han²,

Tan³

et al. 2022

Front. Environ. Sci.

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Long-term near-surface soil moisture (SM) data can be obtained on a regional scale through microwave remote sensing. Therefore, to quantitatively analyze the accuracy of multisource remote sensing–based observation products, improve the retrieval algorithm, and effectively use in terminal environments, a standardized comprehensive evaluation is imperative. The SM data obtained by the China Meteorological Administration and Ministry of Water Resources were used as reference data to verify the performance of six passive microwave remote sensing–based SM products from the SMOS, SMAP, GCOM-W, FY-3B, and FY-3C satellites in Hunan province, China. These data were also used to analyze the effects of topographical, land cover, and meteorological factors on SM retrieval accuracy. Results show that SMAP shows the best overall performance in Hunan province; furthermore, it exhibits stable accuracy and is not easily affected by environmental factors. The FY series of satellite products shows the worst performance, and some grid remote sensing data are negatively correlated with the ground measurement data. AMSR2 possesses the largest amount of data and the largest deviation, and only this product exhibits significant differences with the fluctuation trend of the measured SM and precipitation. Passive microwave detection technology presents the best performance in the central part of Hunan province and the largest bias in the Dongting Lake area. SMOS-L3 and SMOS-IC, two products of the same satellite, show the lowest bias but present differences in the SM fluctuation range, orbital accuracy, as well as dry or wet bias. Furthermore, FY-3B and FY-3C, two satellites belonging to the same series, exhibit excellent consistency in performance. The evaluation results and accuracy variation between products as well as other factors identified in the study provide a baseline reference for improving the retrieval algorithm. This study provides a quantitative basis for developing improved applications of passive microwave SM products.

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Section: Authenticity Assessment Of Multisource Remote Sensing-based ...supporting

confidence: 74%

Evaluation of Six Satellite-Based Soil Moisture Products Based on in situ Measurements in Hunan Province, Central China

Fan

Han²,

Tan³

et al. 2022

Front. Environ. Sci.

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“…A comparison of soil moisture from different simulations with observed soil moisture could provide further insights on the role of precipitation uncertainty in soil moisture simulations; however, such an exercise is not possible due to the lack of observed soil moisture products for the MRB. Further, even the comparison with SMAP data should be interpreted with caution, especially in the southeastern part of the LMRB, because SMAP data likely include substantial uncertainties in these densely vegetated and forested areas (Mousa & Shu, 2020; Zhang et al., 2019).…”

Section: Resultsmentioning

confidence: 99%

On the Precipitation‐Induced Uncertainties in Process‐Based Hydrological Modeling in the Mekong River Basin

Kabir

Pokhrel

Felfelani

2022

Water Resources Research

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Numerous studies have examined the reliability of various precipitation products over the Mekong River Basin (MRB) and modeled its basin hydrology. However, there is a lack of comprehensive studies on precipitation‐induced uncertainties in hydrological simulations using process‐based land surface models. This study examines the propagation of precipitation uncertainty into hydrological simulations over the entire MRB using the Community Land Model version 5 (CLM5) at a high spatial resolution of 0.05° (∼5 km) and without any parameter calibration. Simulations conducted using different precipitation datasets are compared to investigate the discrepancies in streamflow, terrestrial water storage (TWS), soil moisture, and evapotranspiration (ET) caused by precipitation uncertainty. Results indicate that precipitation is a key determinant of simulated streamflow in the MRB; peak flow and soil moisture are particularly sensitive to precipitation input. Further, precipitation data with a higher spatial resolution did not improve the simulations, contrary to the common perception that using meteorological forcing with higher spatial resolution would improve hydrological simulations. In addition, since high flow indicators are particularly influenced by precipitation data, the choice of precipitation data could directly impact flood pulse simulations in the MRB. Notable differences are also found among TWS, soil moisture, and ET simulated using different precipitation products. Moreover, TWS, soil moisture, and ET exhibit a varying degree of sensitivity to precipitation uncertainty. This study provides crucial insights on precipitation‐induced uncertainties in process‐based hydrological modeling and uncovers these uncertainties in the MRB.

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“…Reviews of SM remote-sensing techniques including also thermal and optical approaches are provided, e.g., by Mohanty et al (2017) and Babaeian et al (2019). Over Africa, Mousa and Shu (2020) investigated the performance of different microwave soil moisture products.…”

Section: Microwave Remote Sensingmentioning

confidence: 99%

The Role of Space-Based Observations for Groundwater Resource Monitoring over Africa

et al. 2023

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Africa is particularly vulnerable to climate change impacts, which threatens food security, ecosystem protection and restoration initiatives, and fresh water resources availability and quality. Groundwater largely contributes to the mitigation of climate change effects by offering short- to long-term transient water storage. However, groundwater storage remains extremely difficult to monitor. In this paper, we review the strengths and weaknesses of satellite remote sensing techniques for addressing groundwater quantity issues with a focus on GRACE space gravimetry, as well as concepts to combine satellite observations with numerical models and ground observations. One particular focus is the quantification of changes in groundwater resources in the different climatic regions of Africa and the discussion of possible climatic and anthropogenic drivers. We include a thorough literature review on studies that use satellite observations for groundwater research in Africa. Finally, we identify gaps in research and possible future directions for employing satellite remote sensing to groundwater monitoring and management on the African continent. Article Highlights Overview on the distribution and characteristics of African groundwater resources including future projections Combination of satellite and in situ observations with numerical models allows us to obtain a synoptic view of groundwater-related processes Summary of current concepts and achievements of satellite remote sensing-based groundwater monitoring and decision making over Africa

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Spatial Evaluation and Assimilation of SMAP, SMOS, and ASCAT Satellite Soil Moisture Products Over Africa Using Statistical Techniques

Cited by 22 publications

References 68 publications

Evaluation of Six Satellite-Based Soil Moisture Products Based on in situ Measurements in Hunan Province, Central China

Evaluation of Six Satellite-Based Soil Moisture Products Based on in situ Measurements in Hunan Province, Central China

On the Precipitation‐Induced Uncertainties in Process‐Based Hydrological Modeling in the Mekong River Basin

The Role of Space-Based Observations for Groundwater Resource Monitoring over Africa

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