Statistical evaluation and hydrologic simulation capacity of different satellite-based precipitation products (SbPPs) in the Upper Nan River Basin, Northern Thailand

Gunathilake, Miyuru B.; Amaratunga, Yasasna V.; Perera, Anushka; Karunanayake, Chamaka; Gunathilake, Anura S.; Rathnayake, Upaka

doi:10.1016/j.ejrh.2020.100743

Cited by 14 publications

(13 citation statements)

References 71 publications

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“…Although RG data are the most accurate method of measuring rainfall [5], there are significant challenges faced when maintaining rain gauge networks. ese challenges are due to complex geographical features, harsh climatological environments, and high financial burdens [6]. Some of the reported shortcomings of RG data are missing rainfall days, data transmission dropouts, calibration errors of the RGs, and local wind effects affecting rainfall level estimations [7,8].…”

Section: Introductionmentioning

confidence: 99%

“…ey are radars, satellites, and reanalysis products. However, high costs for installment and maintenance of radar networks are unbearable for the developing world to adopt radar networks [6]. On the other hand, reanalysis products have significant biases [10].…”

Section: Introductionmentioning

confidence: 99%

“…Following this requirement, many research studies have been conducted around the world to assess the accuracy and reliability of SRPs with respect to RG data [6,[18][19][20]. Many studies have demonstrated that TRMM (TMPA) is comparatively better than other SRPs since it used available gauge measurements in its calibration process [21,22].…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Satellite Rainfall Products over the Mahaweli River Basin in Sri Lanka

Perera

Fernando

Gunathilake

et al. 2022

Advances in Meteorology

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The availability of accurate spatiotemporal rainfall data is of utmost importance for reliable predictions from hydroclimatological studies. Challenges and limitations faced due to the absence of dense rain gauge (RG) networks are seen especially in the developing countries. Therefore, alternative rainfall measurements such as satellite rainfall products (SRPs) are used when RG networks are scarce or completely do not exist. Noteworthy, rainfall data retrieved from satellites also possess several uncertainties. Hence, these SRPs should essentially be validated beforehand. The Mahaweli River Basin (MRB), the largest river basin in Sri Lanka, is the heart of the country’s water resources contributing to a significant share of the hydropower production and agricultural sector. Given the importance of the MRB, this study explored the suitability of SRPs as an alternative for RG data for the basin. Daily rainfall data of six types of SRPs were extracted at 14 locations within the MRB. Thereafter, statistical analysis was carried out using continuous and categorical evaluation indices to evaluate the accuracy of SRPs. Nonparametric tests, including the Mann-Kendall and Sen’s slope estimator tests, were used to detect the possibility of trends and the magnitude, respectively. Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) outperformed among all SRPs, while Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products showed dire performances. However, IMERG also demonstrated underestimations when compared to RG data. Trend analysis results showcased that the IMERG product agreed more with RG data on monthly and annual time scales while Tropical Rainfall Measurement Mission Multisatellite Precipitation Analysis–3B42 (TRMM-3B42) agreed more on the seasonal scale. Overall, IMERG turned out to be the best alternative among the SRPs analyzed for MRB. However, it was clear that these products possess significant errors which cannot be ignored when using them in hydrological applications. The results of the study will be valuable for many parties including river basin authorities, agriculturists, meteorologists, hydrologists, and many other stakeholders.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluation of Satellite Rainfall Products over the Mahaweli River Basin in Sri Lanka

Perera

Fernando

Gunathilake

et al. 2022

Advances in Meteorology

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“…However, collecting continuous rain gauge data are a di cult task in many parts of the world due to administrative and technical constraints [6]. Due to complex topographical features, installation and maintaining ground-based rain gauges have been limited [7]. e distribution of rain gauges is limited due to high installation and maintenance costs mainly in developing countries [8].…”

Section: Introductionmentioning

confidence: 99%

“…However, these SbPPs are only used after a careful investigation in the desired study area. Since it was discovered that these SbPPs have certain uncertainties, such as accuracy that is affected by topographical features of the study area and precipitation mechanism due to seasonal and regional climate conditions, such accuracy evaluations of the products with respect to rain gauge data are done for each area of concern [7,9,10], which cannot be ignored if we plan to use them in hydrological applications [6]. A study done by et al, [13] in the Ganzi river basin of the Tibetan plateau to evaluate the impact of satellite data sets to be used in hydrological modeling for that area used CMORPH-CRT, PERSIANN-CDR, 3B42RT, and 3B42 satellite data sets against observed rainfall data using HEC-HMS model to find out that TRMM-3B42RT and CMORPH-CRT show good performance in the respective area and they also suggested that TRMM-3B42RT is a better choice overall for hydrological models in the Ganzi river basin of Tibetan plateau.…”

Section: Introductionmentioning

confidence: 99%

Statistical Evaluation and Trend Analysis of ANN Based Satellite Products (PERSIANN) for the Kelani River Basin, Sri Lanka

Perera

Gunathilake

Panditharathne

et al. 2022

Applied Computational Intelligence and Soft Computing

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Satellite-based precipitation products, (SbPPs) have piqued the interest of a number of researchers as a reliable replacement for observed rainfall data which often have limited time spans and missing days. The SbPPs possess certain uncertainties, thus, they cannot be directly used without comparing against observed rainfall data prior to use. The Kelani river basin is Sri Lanka’s fourth longest river and the main source of water for almost 5 million people. Therefore, this research study aims to identify the potential of using SbPPs as a different method to measure rain besides using a rain gauge. Furthermore, the aim of the work is to examine the trends in precipitation products in the Kelani river basin. Three SbPPs, precipitation estimation using remotely sensed information using artificial neural networks (PERSIANN), PERSIANN-cloud classification system (CCS), and PERSIANN-climate data record (CDR) and ground observed rain gauge daily rainfall data at nine locations were used for the analysis. Four continuous evaluation indices, namely, root mean square error (RMSE), (percent bias) PBias, correlation coefficient (CC), and Nash‒Sutcliffe efficiency (NSE) were used to determine the accuracy by comparing against observed rainfall data. Four categorical indices including probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), and proportional constant (PC) were used to evaluate the rainfall detection capability of SbPPs. Mann‒Kendall test and Sen’s slope estimator were used to identifying whether a trend was present while the magnitudes of these were calculated by Sen’s slope. PERSIANN-CDR performed well by showing better performance in both POD and CSI. When compared to observed rainfall data, the PERSIANN product had the lowest RMSE value, while all products indicated underestimations. The CC and NSE of all three products with observed rainfall data were also low. Mixed results were obtained for the trend analysis as well. The overall results showed that all three products are not a better choice for the chosen study area.

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Evaluating hydrological responses of satellite precipitation products over an Indian tropical catchment through a distributed physical model

Kalura,

Pandey,

Chowdary

et al. 2024

Hydrological Processes

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Significant advancements in satellite‐based precipitation retrieval algorithms have led to the development of continuous, quasi‐global precipitation products, offering unique opportunities for hydrometeorological and climate research. In this context, six satellite‐based precipitation products (SPPs), including CHIRPS, CMORPH, GSMaP, IMERG, MSWEP, and PERSIANN, were thoroughly investigated for their application in hydrological simulations over the Wardha River basin in India. The observed gridded precipitation product developed by India Meteorological Department (IMD) has been used as reference data to evaluate the performance of SPPs. Hydrological variables such as runoff, soil moisture (SM) and evapotranspiration (ET) were simulated using the Variable Infiltration Capacity model. The performances of SPPs are critically assessed using various statistical metrics, including Pearson's correlation coefficient (R), Klinga‐Gupta Efficiency (KGE), Percent Bias (PBIAS), root mean square error (RMSE), and the RMSE to standard deviation ratio (RSR). The model‐simulated discharge was compared with streamflow observations at a single gauging site, while a spatially distributed comparison was conducted between simulated SM and ET and satellite‐based SM and ET. The IMD dataset consistently shows superior performance for discharge simulation at both daily and monthly scales, with KGE values of 0.85 and 0.91, respectively. Among SPPs, MSWEP and CHIRPS excel in simulating daily and monthly discharge, respectively. For ET simulation, CHIRPS outperforms IMD and other SPPs, achieving an overall KGE value of 0.37. In contrast, PERSIANN is the most effective for simulating SM compared to other precipitation products.

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Statistical evaluation and hydrologic simulation capacity of different satellite-based precipitation products (SbPPs) in the Upper Nan River Basin, Northern Thailand

Cited by 14 publications

References 71 publications

Evaluation of Satellite Rainfall Products over the Mahaweli River Basin in Sri Lanka

Evaluation of Satellite Rainfall Products over the Mahaweli River Basin in Sri Lanka

Statistical Evaluation and Trend Analysis of ANN Based Satellite Products (PERSIANN) for the Kelani River Basin, Sri Lanka

Evaluating hydrological responses of satellite precipitation products over an Indian tropical catchment through a distributed physical model

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