scholarly journals Assessment of 13 Gridded Precipitation Datasets for Hydrological Modeling in a Mountainous Basin

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 143
Author(s):  
Hamed Hafizi ◽  
Ali Arda Sorman
Keyword(s):  
Hydrological Modeling ◽  
Poor Performance ◽  
Time Step ◽  
Precipitation Measurement ◽  
Temporal Validation ◽  
Daily Precipitation Data ◽  
Daily Time Step ◽  
Low Performance ◽  
Optimum Manner ◽  
Mountainous Basin

Precipitation measurement with high spatial and temporal resolution over highly elevated and complex terrain in the eastern part of Turkey is an essential task to manage the water structures in an optimum manner. The objective of this study is to evaluate the consistency and hydrologic utility of 13 Gridded Precipitation Datasets (GPDs) (CPCv1, MSWEPv2.8, ERA5, CHIRPSv2.0, CHIRPv2.0, IMERGHHFv06, IMERGHHEv06, IMERGHHLv06, TMPA-3B42v7, TMPA-3B42RTv7, PERSIANN-CDR, PERSIANN-CCS, and PERSIANN) over a mountainous test basin (Karasu) at a daily time step. The Kling-Gupta Efficiency (KGE), including its three components (correlation, bias, and variability ratio), and the Nash-Sutcliffe Efficiency (NSE) are used for GPD evaluation. Moreover, the Hanssen-Kuiper (HK) score is considered to evaluate the detectability strength of selected GPDs for different precipitation events. Precipitation frequencies are evaluated considering the Probability Density Function (PDF). Daily precipitation data from 23 meteorological stations are provided as a reference for the period of 2015–2019. The TUW model is used for hydrological simulations regarding observed discharge located at the outlet of the basin. The model is calibrated in two ways, with observed precipitation only and by each GPD individually. Overall, CPCv1 shows the highest performance (median KGE; 0.46) over time and space. MSWEPv2.8 and CHIRPSv2.0 deliver the best performance among multi-source merging datasets, followed by CHIRPv2.0, whereas IMERGHHFv06, PERSIANN-CDR, and TMPA-3B42v7 show poor performance. IMERGHHLv06 is able to present the best performance (median KGE; 0.17) compared to other satellite-based GPDs (PERSIANN-CCS, PERSIANN, IMERGHHEv06, and TMPA-3B42RTv7). ERA5 performs well both in spatial and temporal validation compared to satellite-based GPDs, though it shows low performance in producing a streamflow simulation. Overall, all gridded precipitation datasets show better performance in generating streamflow when the model is calibrated by each GPD separately.

scholarly journals Assessment of Satellite and Reanalysis Precipitation Products for Rainfall–Runoff Modelling in a Mountainous Basin

2021 ◽  
Vol 8 (1) ◽  
pp. 25
Author(s):  
Hamed Hafizi ◽  
Ali Arda Sorman
Keyword(s):  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Rainfall Runoff ◽  
Precipitation Measurement ◽  
Gauge Data ◽  
Low Performance ◽  
Rainfall Runoff Model ◽  
Mountainous Basin ◽  
Runoff Model ◽  
Precipitation Events

Precipitation measurement over a complex topography and highly elevated regions has always been a great challenge in recent decades. On the other hand, satellite-based and numerical weather prediction model outputs can be an alternative to fill this gap. Hence, the goal of this study is to evaluate the spatiotemporal stability and hydrologic utility of four precipitation products (TMPA-3B42v7, IMERGHHFv06, ERA5, and PERSIANN) over a mountainous basin (Karasu basin) located in the eastern part of Turkey. Moreover, the Kling–Gupta efficiency (KGE), including its correlation, bias, and variability ratio components, are used for a direct comparison of precipitation products (PPs) with observed gauge data, and the Hansen–Kuiper (HK) score is utilized to assess the detectability strength of PPs for different precipitation events. In the same way, the hydrologic utility of PPs is tested by exploiting a conceptual rainfall–runoff model under Kling–Gupta efficiency (KGE) and Nash–Sutcliffe efficiency (NSE) metrics. Generally, all PPs show low performance for a direct comparison with observed data while their performance considerably increases for streamflow simulation. TMPA-3B42v7 has high reproducibility in streamflow (KGE = 0.84), followed by IMERGHHFv06 (KGE = 0.76), ERA5 (KGE = 0.75), and PERSIANN (KGE = 0.70), for the entire period (2015–2019) of this study.

scholarly journals Evaluating the Performance of Secondary Precipitation Products through Statistical and Hydrological Modeling in a Mountainous Tropical Basin of India

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Kolluru Venkatesh ◽  
N. Y. Krakauer ◽  
E. Sharifi ◽  
H. Ramesh
Keyword(s):  
Climate Change ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Extreme Event ◽  
Poor Performance ◽  
Event Analysis ◽  
Time Step ◽  
Global Precipitation Climatology Centre ◽  
Statistical Metrics ◽  
Trmm 3B42

This paper investigates the performance of gridded rainfall datasets for precipitation detection and streamflow simulations in Indiaʼs Tungabhadra river basin. Sixteen precipitation datasets categorized under gauge-based, satellite-only, reanalysis, and gauge-adjusted datasets were compared statistically against the gridded Indian Meteorological Dataset (IMD) employing two categorical and three continuous statistical metrics. Further, the precipitation datasets’ performance in simulating streamflow was assessed by using the Soil and Water Assessment Tool (SWAT) hydrological model. Based on the statistical metrics, Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) furnished very good results in terms of detecting rainfall, followed by Climate Hazards Group Infrared Precipitation (CHIRP), National Centres for Environmental Prediction-Climate Forecast System Reanalysis (NCEP CFSR), Tropical Rainfall Measurement Mission (TRMM) 3B42 v7, Global Satellite Mapping of Precipitation Gauge Reanalysis v6 (GSMaP_Gauge_RNL), and Multisource Weighted Ensemble Precipitation (MSWEP) datasets which had good-to-moderate performances at a monthly time step. From the hydrological simulations, TRMM 3B42 v7, CHIRP, CHIRPS 0.05°, and GSMaP_Gauge_RNL v6 produced very good results with a high degree of correlation to observed streamflow, while Soil Moisture 2 Rain-Climate Change Initiative (SM2RAIN-CCI) dataset exhibited poor performance. From the extreme flow event analysis, it was observed that CHIRP, TRMM 3B42 v7, Global Precipitation Climatology Centre v7 (GPCC), and APHRODITE datasets captured more peak flow events and hence can be further implemented for extreme event analysis. Overall, we found that TRMM 3B42 v7, CHIRP, and CHIRPS 0.05° datasets performed better than other datasets and can be used for hydrological modeling and climate change studies in similar topographic and climatic watersheds in India.

ASSESSMENT OF MAXIMUM INSTANT DISCHARGE OF VARIOUS FREQUENCY AT UNGAUGED MOUNTAINOUS RIVER KHEMCHIK (TUVA REPUBLIC) BASED ON MATHEMATICAL MODELLING

2019 ◽  
Vol 13 (2) ◽  
pp. 36-51 ◽  
Author(s):  
O. M. Makarieva ◽  
N. V. Nesterova ◽  
G. P. Yampolsky ◽  
E. Y. Kudymova
Keyword(s):  
Coniferous Forest ◽  
Frequency Interval ◽  
Time Step ◽  
Model Calculations ◽  
Runoff Formation ◽  
Emergency Situations ◽  
Daily Streamflow ◽  
Standard Methodology ◽  
Maximum Elevation ◽  
Daily Time Step

Abstract: the article presents the results of application of distributed deterministic hydrological model Hydrograph for estimation of maximum discharge values of different frequency at the ungauged catchment of the Khemchik River (Khemchik village, Tuva Republic). The catchment area is 1750 km2 , the average and maximum elevation — 2200 and 3600 m, respectively. Due to the lack of detailed information, a schematization of the catchment and the parameterization of the model are proposed, based on general ideas about the water balance and the processes of runoff formation of the main landscapes — rocky talus, coniferous forest and steppe. Parameters and algorithms are verified based on the results of streamflow modeling at two studied catchments: the Tapsy River — Kara-Khol (302 km2 ) and the Khemchik River — Iyme (25500 km2 ). Modelling of runoff formation processes with daily time step for the Khemchik River — Khemchik village was conducted for the period 1966–2012 using observational data at Teeli meteorological station. For the transition from daily to instant discharges, the dependence of the observed values of instant and daily streamflow at the studied gauges has been applied. On the basis of simulated discharge series, the frequency curve was built and the obtained curve was compared with the calculation data according to the standard methodology SP 33-101-2003 “Determination of the main calculated hydrological characteristics” using the analogue river. Simulated maximum instant discharges for entire frequency interval of up to 1% are 1.3–5 times higher than the values obtained by standard methodology SP 33-101-2003. The results of model calculations is indirectly confirmed by the evidences of regular flooding of the Khemchik village provided by the Ministry of Emergency Situations of the Tuva Republic, which is not predicted by the values obtained by the standard methods.

Alternative climate data sources for distributed hydrological modelling on a daily time step

2010 ◽  
Vol 25 (10) ◽  
pp. 1542-1557 ◽  
Author(s):  
Ashraf El-Sadek ◽  
Max Bleiweiss ◽  
Manoj Shukla ◽  
Steve Guldan ◽  
Alexander Fernald
Keyword(s):  
Hydrological Modelling ◽  
Data Sources ◽  
Climate Data ◽  
Time Step ◽  
Daily Time Step ◽  
Distributed Hydrological Modelling ◽  
Daily Time

scholarly journals Systematical Evaluation of GPM IMERG and TRMM 3B42V7 Precipitation Products in the Huang-Huai-Hai Plain, China

2019 ◽  
Vol 11 (6) ◽  
pp. 697 ◽  
Author(s):  
Fenglin Xu ◽  
Bin Guo ◽  
Bei Ye ◽  
Qia Ye ◽  
Huining Chen ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Accurate Estimation ◽  
Detection Capability ◽  
Satellite Precipitation ◽  
Precipitation Measurement ◽  
Daily Precipitation Data ◽  
Precipitation Estimates ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Precipitation Events

Accurate estimation of high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) and Tropical Rainfall Measuring Mission (TRMM) is critical for hydrological and meteorological research, providing a benchmark for the continued development and future improvement of these products. This study aims to comprehensively evaluate the Integrated Multi-Satellite Retrievals for GPM (IMERG) and TRMM 3B42V7 products at multiple temporal scales from 1 January 2015 to 31 December 2017 over the Huang-Huai-Hai Plain in China, using daily precipitation data from 59 meteorological stations. Three commonly used statistical metrics (CC, RB, and RMSE) are adopted to quantitatively verify the accuracy of two satellite precipitation products. The assessment also takes into account the precipitation detection capability (POD, FAR, CSI, and ACC) and frequency of different precipitation intensities. The results show that the IMERG and 3B42V7 present strong correlation with meteorological stations observations at annual and monthly scales (CC > 0.90), whereas moderate at the daily scale (CC = 0.76 and 0.69 for IMERG and 3B42V7, respectively). The spatial variability of the annual and seasonal precipitation is well captured by these two satellite products. And spatial patterns of precipitation gradually decrease from south to north over the Huang-Huai-Hai Plain. Both IMERG and 3B42V7 products overestimate precipitation compared with the station observations, of which 3B42V7 has a lower degree of overestimation. Relative to the IMERG, annual precipitation estimates from 3B42V7 show lower RMSE (118.96 mm and 142.67 mm, respectively), but opposite at the daily, monthly, and seasonal scales. IMERG has a better precipitation detection capability than 3B42V7 (POD = 0.83 and 0.67, respectively), especially when detecting trace and solid precipitation. The two precipitation products tend to overestimate moderate (2–10 mm/d) and heavy (10–50 mm/d) precipitation events, but underestimate violent (>50 mm/d) precipitation events. The IMERG is not found capable to detecting precipitation events of different frequencies more precisely. In general, the accuracy of IMERG is better than 3B42V7 product in the Huang-Huai-Hai Plain. The IMERG satellite precipitation product with higher temporal and spatial resolutions can be regarded a reliable data sources in studying hydrological and climatic research.

scholarly journals Non-literal language and semantic dementia

2013 ◽  
Vol 7 (4) ◽  
pp. 424-427
Author(s):  
Mariana Ribeiro Hur ◽  
Leonardo Caixeta
Keyword(s):  
Alzheimer’S Disease ◽  
Frontotemporal Lobar Degeneration ◽  
Screening Test ◽  
Poor Performance ◽  
Semantic Dementia ◽  
Test Results ◽  
Language Abilities ◽  
Attention Span ◽  
Language Interpretation ◽  
Low Performance

ABSTRACT Semantic dementia is characterized by fluent, phonologically adequate speech with various anomias and semantic paraphasias. Performance on semantic tasks is well documented in these patients, although little is known regarding performance on more complex language tasks, such as those involving non-literal language (interpretation of metaphors and proverbs and recognition of irony). Objective: To report the investigation of non-literal language in cases of semantic dementia. Methods: Two cases of semantic dementia were investigated for the presence of deficits in non-literal language abilities using the screening test for Alzheimer's disease with proverbs, metaphor test and irony test. Results: Both patients were found to have low performance on the tests applied, particularly for interpretation of proverbs. Conclusion: This poor performance was attributed largely to the characteristic semantic changes of the disease, but some frontal symptoms inherent to other forms of frontotemporal lobar degeneration were also observed which interfered in the testing, such as negativism, reduced attention span, concretism and perseverations.

scholarly journals Seasonal Effect on Spatial and Temporal Consistency of the New GPM-Based IMERG-v5 and GSMaP-v7 Satellite Precipitation Estimates in Brazil’s Central Plateau Region

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 668 ◽  
Author(s):  
Leandro Salles ◽  
Frédéric Satgé ◽  
Henrique Roig ◽  
Tati Almeida ◽  
Diogo Olivetti ◽  
...  
Keyword(s):  
Daily Basis ◽  
Seasonal Effect ◽  
Temporal Consistency ◽  
Time Step ◽  
Central Plateau ◽  
Satellite Precipitation ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Global Precipitation Measurement ◽  
Global Precipitation

This study assesses the performance of the new Global Precipitation Measurement (GPM)-based satellite precipitation estimates (SPEs) datasets in the Brazilian Central Plateau and compares it with the previous Tropical Rainfall Measurement Mission (TRMM)-era datasets. To do so, the Integrated Multi-satellitE Retrievals for GPM (IMERG)-v5 and the Global Satellite Mapping of Precipitation (GSMaP)-v7 were evaluated at their original 0.1° spatial resolution and for a 0.25° grid for comparison with TRMM Multi-satellite Precipitation Analysis (TMPA). The assessment was made on an annual, monthly, and daily basis for both wet and dry seasons. Overall, IMERG presents the best annual and monthly results. In both time steps, IMERG’s precipitation estimations present bias with lower magnitudes and smaller root-mean-square error. However, GSMaP performs slightly better for the daily time step based on categorical and quantitative statistical analysis. Both IMERG and GSMaP estimates are seasonally influenced, with the highest difficulty in estimating precipitation occurring during the dry season. Additionally, the study indicates that GPM-based SPEs products are capable of continuing TRMM-based precipitation monitoring with similar or even better accuracy than obtained previously with the widely used TMPA product.

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