Evaluation of Satellite Precipitation Estimates over the South West Pacific Region

Wild, Ashley; Chua, Zhi‐Weng; Kuleshov, Yuriy

doi:10.3390/rs13193929

Cited by 19 publications

(6 citation statements)

References 43 publications

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“…A comprehensive analysis of the SWCEM satellite precipitation data performed over Australia showed that blended satellite-gauge products had higher correlations and smaller errors than gauge analysis [48][49][50][51][52][53]. Similarly, earlier studies demonstrated the usefulness of satellite precipitation data not only for Australia but also for countries in the Pacific region [54,55], which means that the SWCEM data as well as the developed in this study flood risk assessment methodology could potentially be used in other countries in the Asia-Pacific region.…”

Section: Flood Hazard Indicators and Data Collectionsupporting

confidence: 59%

Flood Risk Assessment and Mapping: A Case Study from Australia’s Hawkesbury-Nepean Catchment

et al. 2023

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Floods are the most common and costliest natural disaster in Australia. Australian flood risk assessments (FRAs) are mostly conducted on relatively small scales using modelling outputs. The aim of this study was to develop a novel approach of index-based analysis using a multi-criteria decision-making (MCDM) method for FRA on a large spatial domain. The selected case study area was the Hawkesbury-Nepean Catchment (HNC) in New South Wales, which is historically one of the most flood-prone regions of Australia. The HNC’s high flood risk was made distinctly clear during recent significant flood events in 2021 and 2022. Using a MCDM method, an overall Flood Risk Index (FRI) for the HNC was calculated based on flood hazard, flood exposure, and flood vulnerability indices. Inputs for the indices were selected to ensure that they are scalable and replicable, allowing them to be applied elsewhere for future flood management plans. The results of this study demonstrate that the HNC displays high flood risk, especially on its urbanised floodplain. For the examined March 2021 flood event, the HNC was found to have over 73% (or over 15,900 km2) of its area at ‘Severe’ or ‘Extreme’ flood risk. Validating the developed FRI for correspondence to actual flooding observations during the March 2021 flood event using the Receiver Operating Characteristic (ROC) statistical test, a value of 0.803 was obtained (i.e., very good). The developed proof-of-concept methodology for flood risk assessment on a large spatial scale has the potential to be used as a framework for further index-based FRA approaches.

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Section: Flood Hazard Indicators and Data Collectionsupporting

confidence: 59%

Flood Risk Assessment and Mapping: A Case Study from Australia’s Hawkesbury-Nepean Catchment

et al. 2023

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“…Traditional ground-based instruments (weather stations and radars) are considered as the most reliable sources of precipitation measurements [2]. However, the main difficulties in accessing the uninterrupted measurements of precipitation for many applications in mountainous and remote areas are the rugged topography and an inequitable distribution of weather stations [3][4][5][6]. The Himalayan Mountains also have similar constraints on obtaining precipitation data due to sparse or non-uniform installation of meteorological stations.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Multi-Satellite Precipitation Products over the Himalayan Mountains of Pakistan, South Asia

et al. 2022

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Performance assessment of satellite-based precipitation products (SPPs) is critical for their application and development. This study assessed the accuracies of four satellite-based precipitation products (PERSIANN-CDR, PERSIANN-CCS, PERSIANN-DIR, and PERSIANN) using data of in situ weather stations installed over the Himalayan Mountains of Pakistan. All SPPs were evaluated on annual, seasonal, monthly, and daily bases from 2010 to 2017, over the whole spatial domain and at point-to-pixel scale. The assessment was conducted using widely used evaluation indices (root mean square error (RMSE), correlation coefficient (CC), bias, and relative bias (rBias)) along with categorical indices (false alarm ratio (FAR), probability of detection (POD), success ratio (SR), and critical success index (CSI)). Results showed: (1) PERSIANN and PERSIANN-DIR products efficiently traced the spatio-temporal distribution of precipitation over the Himalayan Mountains. (2) On monthly scale, the estimates of all SPPs were more consistent with the reference data than on the daily scale. (3) On seasonal scale, PERSIANN and PERSIANN-DIR showed better performances than the PERSIANN-CDR and PERSIANN-CCS products. (4) All SPPs were less accurate in sensing daily light to medium intensity precipitation events. Subsequently, for future hydro-meteorological investigations in the Himalayan range, we advocate the use of monthly PERSIANN and PERSIANN-DIR products.

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“…To aid, prepare and warn communities of drought, the operational implementation of satellite monitoring rainfall products is becoming more commonplace in the Pacific region as remote-sensing research progresses [15][16][17][18]. Yet, satellite SM evaluation is a relatively under-explored research space, owing to the minimal-to-none in situ SM stations or water balance models that can be used to evaluate satellite SM products in the Pacific region.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Satellite Soil Moisture Datasets for Drought Monitoring in Australia and the South-West Pacific

et al. 2022

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Soil moisture (SM) is critical in monitoring the time-lagged impacts of agrometeorological drought. In Australia and several south-west Pacific Small Island Developing States (SIDS), there are a limited number of in situ SM stations that can adequately assess soil-water availability in a near-real-time context. Satellite SM datasets provide a viable alternative for SM monitoring and agrometeorological drought provision in these regions. In this study, we investigated the performance of Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Operational Products System (SMOPS), SM from the Advanced Microwave Scanning Radiometer 2 (AMSR-2) and SM from the Advanced Scatterometer (ASCAT) over Australia and south-west Pacific SIDS. Products were first evaluated in Australia, given the presence of several in-situ SM monitoring stations and a state-of-the-art hydrological model—the Australian Water Resources Assessment Landscape modelling system (AWRA-L). We further investigated the accuracy of SM satellite datasets in Australia and the south-west Pacific through Triple Collocation analysis with two other SM reference datasets—ERA5 reanalysis SM data and model data from the Global Land Data Assimilation System (GLDAS) dataset. All datasets have differing observation periods ranging from 1911-now, with a common period of observations between 2015–2021. Results demonstrated that ASCAT and SMOS were consistently superior in their performance. Analysis in the six south-west Pacific SIDS indicated reduced performance for all products, with ASCAT and SMOS still performing better than others for most SIDS with median R values ranging between 0.3–0.9. We conducted a case study of the 2015 El Niño and Positive Indian Ocean Dipole-induced drought in Papua New Guinea. It was shown that ASCAT is a valuable dataset indicative of agrometeorological drought for the nation, highlighting the value of using satellite SM products to provide early warning of drought in data-sparse regions in the south-west Pacific.

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Evaluation of Satellite Precipitation Estimates over the South West Pacific Region

Cited by 19 publications

References 43 publications

Flood Risk Assessment and Mapping: A Case Study from Australia’s Hawkesbury-Nepean Catchment

Flood Risk Assessment and Mapping: A Case Study from Australia’s Hawkesbury-Nepean Catchment

Assessment of Multi-Satellite Precipitation Products over the Himalayan Mountains of Pakistan, South Asia

Evaluating Satellite Soil Moisture Datasets for Drought Monitoring in Australia and the South-West Pacific

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