scholarly journals Performance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), Ethiopia

2020 ◽  
Author(s):  
Gizachew Kabite Wedajo ◽  
Misgana Kebede Muleta ◽  
Berhan Gessesse Awoke
Keyword(s):  
Performance Evaluation ◽  
River Basin ◽  
Rainfall Variability ◽  
Spatiotemporal Variability ◽  
Analysis Tool ◽  
Hydrologic Simulation ◽  
Hydrologic Modelling ◽  
Rain Gauges ◽  
Groundwater Flux ◽  
Many Sources

Abstract. Precipitation is a crucial driver of hydrological processes. Ironically, reliable characterization of its spatiotemporal variability is challenging. Ground-based rainfall measurements using rain gauges can be more accurate. However, installing a dense gauging network to capture rainfall variability can be impractical. Satellite-based rainfall estimates (SREs) can be good alternatives, especially for data-scarce basins like in Ethiopia. However, SREs rainfall is plagued with uncertainties arising from many sources. The objective of this study was to evaluate the performance of the latest versions of several SREs products (i.e., CHIRPS2, IMERG6, TAMSAT3, and 3B42/3) for the Dhidhessa River Basin (DRB). Both statistical and hydrologic modelling approaches were used for performance evaluation. The Soil and Water Analysis Tool (SWAT) was used for hydrological simulations. The results showed that whereas all four SREs products are promising to estimate and detect rainfall for the DRB, the CHIRPS2 dataset performed the best at annual, seasonal, and monthly timescales. The hydrologic simulation-based evaluation showed that SWAT's calibration results are sensitive to the rainfall dataset. The hydrologic response of the basin is found to be dominated by the subsurface processes, primarily by the groundwater flux. Overall, the study showed that both CHIRPS2 and IMERG6 products can be reliable rainfall data sources for hydrologic analysis of the Dhidhessa River Basin.

scholarly journals Performance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), Ethiopia

2021 ◽  
Vol 14 (3) ◽  
pp. 2299-2316
Author(s):  
Gizachew Kabite Wedajo ◽  
Misgana Kebede Muleta ◽  
Berhan Gessesse Awoke
Keyword(s):  
Performance Evaluation ◽  
River Basin ◽  
Hydrological Modeling ◽  
Rainfall Variability ◽  
Estimation Algorithm ◽  
Spatiotemporal Variability ◽  
Analysis Tool ◽  
Hydrological Simulation ◽  
Groundwater Flux ◽  
Many Sources

Abstract. Precipitation is a crucial driver of hydrological processes. Ironically, a reliable characterization of its spatiotemporal variability is challenging. Ground-based rainfall measurement using rain gauges is more accurate. However, installing a dense gauging network to capture rainfall variability can be impractical. Satellite-based rainfall estimates (SREs) could be good alternatives, especially for data-scarce basins like in Ethiopia. However, SRE rainfall is plagued with uncertainties arising from many sources. The objective of this study was to evaluate the performance of the latest versions of several SRE products (i.e., CHIRPS2, IMERG6, TAMSAT3 and 3B42/3) for the Dhidhessa River Basin (DRB). Both statistical and hydrological modeling approaches were used for the performance evaluation. The Soil and Water Analysis Tool (SWAT) was used for hydrological simulations. The results showed that whereas all four SRE products are promising to estimate and detect rainfall for the DRB, the CHIRPS2 dataset performed the best at annual, seasonal and monthly timescales. The hydrological simulation-based evaluation showed that SWAT's calibration results are sensitive to the rainfall dataset. The hydrological response of the basin is found to be dominated by the subsurface processes, primarily by the groundwater flux. Overall, the study showed that both CHIRPS2 and IMERG6 products could be reliable rainfall data sources for the hydrological analysis of the DRB. Moreover, the climatic season in the DRB influences rainfall and streamflow estimation. Such information is important for rainfall estimation algorithm developers.

A dense network of rain gauges within an urban area: Rainfall uncertainty and variability

2021 ◽  
Author(s):  
Luc Neppel ◽  
Pierre Marchand ◽  
Pascal Finaud-Guyot ◽  
Vincent Guinot ◽  
Christian Salles
Keyword(s):  
Spatial Variability ◽  
Urban Area ◽  
Urban Areas ◽  
Rainfall Variability ◽  
Temporal Structure ◽  
Drainage System ◽  
Spatiotemporal Variability ◽  
Small Scale ◽  
Rain Gauges ◽  
Rain Gauges Network

<p>This study presents a new high density rain gauges network installed in urban area to study spatio-temporal structure and variability of precipitation at small scales. The preliminary results concerning gauges calibration and characterization of the rainfall spatial variability at fine scale are discussed.</p><p>In urban areas, the impervious surfaces connected to the drainage system leads to highly dynamic flows. The flood and runoff risk characterization requires  fine spatiotemporal scale to describe hydrological model input data :rainfall within spatial scale of less than 1km and temporal scale close to 1minis necessary for urban hydrological applications and risk assessment. In order to characterize small-scale rainfall spatiotemporal variability, a dense rain gauges network is deployed at Montpellier (France) with inter-gauges distances from 100m to 1km. Currently, 9 tipping bucket rain gauges  associated with 9 anemometers are acquiring rainfall and wind norm intensity every minutes. The network density and extension will be increased soon.</p><p>The first year measurements highlight a spatial variability of the 1-minute rainfall at the subkilometer scale. This observed variability is analyzed in view of the measurement uncertainty (gauge calibration, gauge error, bias due to the gauge location) to identify the natural rainfall variability.</p><p>This contribution presents the new densely extensive rainfall  network measurement, the typing bucket raingauge calibration and highlights that the observed 1-minute rainfall intensity variability  is significant and cannot be only explained by the measurement uncertainties.</p>

scholarly journals Analysis of the Spatiotemporal Annual Rainfall Variability in the Wadi Cheliff Basin (Algeria) over the Period 1970 to 2018

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1477
Author(s):  
Mohammed Achite ◽  
Tommaso Caloiero ◽  
Andrzej Wałęga ◽  
Nir Krakauer ◽  
Tarek Hartani
Keyword(s):  
Rainfall Variability ◽  
Central Area ◽  
Nonparametric Tests ◽  
Spatiotemporal Variability ◽  
Change Points ◽  
Annual Rainfall ◽  
Spatial Gradient ◽  
Arid Zones ◽  
Precipitation Trend ◽  
Rain Gauges

In the context of climate variability and hydrological extremes, especially in arid and semi-arid zones, the issue of natural risks and more particularly the risks related to rainfall is a topical subject in Algeria and worldwide. In this direction, the spatiotemporal variability of precipitation in the Wadi Cheliff basin (Algeria) has been evaluated by means of annual time series of precipitation observed on 150 rain gauges in the period 1970–2018. First, in order to identify the natural year-to-year variability of precipitation, for each series, the coefficient of variation (CV) has been evaluated and spatially distributed. Then, the precipitation trend at annual scale has been analyzed using two nonparametric tests. Finally, the presence of possible change points in the data has been investigated. The results showed an inverse spatial pattern between CV and the annual rainfall, with a spatial gradient between the southern and the northern sides of the basin. Results of the trend analysis evidenced a marked negative trend of the annual rainfall (22% of the rain gauges for a significant level equal to 95%) involving mainly the northern and the western-central area of the basin. Finally, possible change points have been identified between 1980 and 1985.

scholarly journals Spatio-temporal analysis of remotely sensed rainfall datasets retrieved for the transboundary basin of the Madeira River in Amazonia

Atmósfera ◽  
2020 ◽  
Author(s):  
Vinicius Alexandre Sikora de Souza ◽  
Daniel Medeiros Moreira ◽  
Otto Corrêa Rotunno Filho ◽  
Anderson Paulo Rudke ◽  
Claudia Daza Andrade ◽  
...  
Keyword(s):  
River Basin ◽  
Rainfall Variability ◽  
Temporal Analysis ◽  
Remotely Sensed ◽  
Rain Gauges ◽  
Madeira River ◽  
Satellite Rainfall ◽  
Climate Hazards ◽  
Spatio Temporal ◽  
Madeira River Basin

Rainfall is recognized as the most important driving force of the hydrologic cycle. To accurately represent the spatio-temporal rainfall variability continues to be an enormous hydrological task when using commonly sparse, if available, rain gauges networks. Therefore, the present study devoted a special effort to analyze the robustness of some satellite rainfall products, notably the datasets hereafter named as (i) CHIRP (Climate Hazards Group InfraRed Precipitation), (ii) CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), (iii) 3B42, and (iv) 3B42RT of the Tropical Rainfall Measuring Mission (TRMM), to adequately represent the pluviometric regime in the Madeira river basin. To assess the accuracy of acquired remotely sensed rainfall products, comparisons to observational available rain gauges usually taken as ground-truth in the literature, despite their well-known limitations, were performed. Wavelet analysis was also used to validate the performance of the referred satellite products by means of extracting the corresponding cycles, frequencies, and tendencies along the available time series across the studied basin. The results showed that the data sources CHIRPS and CHIRP better represent the pluviometric phenomenon by means of their monthly accumulated rainfall in the Madeira river basin when compared to the 3B42 and 3B42RT products taking into account rain gauges as baseline information. The CHIRPS product performed the best among the selected rainfall estimators for the Madeira river basin. Further analysis brought up also another very interesting result related to non-rainfall periods, which is usually not reported. However, such evaluation is quite important in hydrology when examining run sequences of droughts and consequent effects in the water balance at the watershed scale. Highly accurate estimates in the sense of identifying non-rainfall periods by remotely sensed information was achieved, which represents an additional and valuable asset of satellite rainfall products. It is worthwhile to say that this perspective deserves to receive much more attention in the literature in order to deeply discuss the water-energy-food nexus.

Spatiotemporal variability of vegetation due to drought dynamics (2012–2017): a case study of the Upper Paraíba River basin, Brazil

2020 ◽  
Vol 102 (3) ◽  
pp. 939-964
Author(s):  
Glauciene Justino Ferreira da Silva ◽  
Nádja Melo de Oliveira ◽  
Celso Augusto Guimarães Santos ◽  
Richarde Marques da Silva
Keyword(s):  
River Basin ◽  
Spatiotemporal Variability

scholarly journals On the nature of rainfall intermittency as revealed by different metrics and sampling approaches

2013 ◽  
Vol 17 (1) ◽  
pp. 355-369 ◽  
Author(s):  
G. Mascaro ◽  
R. Deidda ◽  
M. Hellies
Keyword(s):  
Scale Invariance ◽  
Weather Forecasting ◽  
Rainfall Variability ◽  
Analysis Tool ◽  
Systematic Analysis ◽  
Local Climate ◽  
Rainfall Occurrence ◽  
Frontal Systems ◽  
Intensity Fluctuations ◽  
The Time Domain

Abstract. A general consensus on the concept of rainfall intermittency has not yet been reached, and intermittency is often attributed to different aspects of rainfall variability, including the fragmentation of the rainfall support (i.e., the alternation of wet and dry intervals) and the strength of intensity fluctuations and bursts. To explore these different aspects, a systematic analysis of rainfall intermittency properties in the time domain is presented using high-resolution (1-min) data recorded by a network of 201 tipping-bucket gauges covering the entire island of Sardinia (Italy). Four techniques, including spectral and scale invariance analysis, and computation of clustering and intermittency exponents, are applied to quantify the contribution of the alternation of dry and wet intervals (i.e., the rainfall support fragmentation), and the fluctuations of intensity amplitudes, to the overall intermittency of the rainfall process. The presence of three ranges of scaling regimes between 1 min to ~ 45 days is first demonstrated. In accordance with past studies, these regimes can be associated with a range dominated by single storms, a regime typical of frontal systems, and a transition zone. The positions of the breaking points separating these regimes change with the applied technique, suggesting that different tools explain different aspects of rainfall variability. Results indicate that the intermittency properties of rainfall support are fairly similar across the island, while metrics related to rainfall intensity fluctuations are characterized by significant spatial variability, implying that the local climate has a significant effect on the amplitude of rainfall fluctuations and minimal influence on the process of rainfall occurrence. In addition, for each analysis tool, evidence is shown of spatial patterns of the scaling exponents computed in the range of frontal systems. These patterns resemble the main pluviometric regimes observed on the island and, thus, can be associated with the corresponding synoptic circulation patterns. Last but not least, we demonstrate how the methodology adopted to sample the rainfall signal from the records of the tipping instants can significantly affect the intermittency analysis, especially at smaller scales. The multifractal scale invariance analysis is the only tool that is insensitive to the sampling approach. Results of this work may be useful to improve the calibration of stochastic algorithms used to downscale coarse rainfall predictions of climate and weather forecasting models, as well as the parameterization of intensity-duration-frequency curves, adopted for land planning and design of civil infrastructures.

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