A preliminary analysis of rainfall spatial distribution at catchment scale

2015 ◽  
Author(s):  
Maura Rianna ◽  
Valeria Montesarchio ◽  
Francesco Napolitano ◽  
Lucio Ubertini
Keyword(s):  
Spatial Distribution ◽  
Preliminary Analysis ◽  
Catchment Scale ◽  
Rainfall Spatial Distribution

scholarly journals Location Matters: A Framework to Investigate the Spatial Characteristics of Distributed Flood Attenuation

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2706
Author(s):  
Federico Antolini ◽  
Eric Tate
Keyword(s):  
Spatial Distribution ◽  
Distributed Systems ◽  
Green Infrastructure ◽  
Multiple Scales ◽  
Flood Management ◽  
Ability To Work ◽  
Catchment Scale ◽  
Flood Magnitude ◽  
Spatially Distributed ◽  
Flood Attenuation

Distributed attenuation in flood management relies on small and low-impact runoff attenuating features variously distributed within a catchment. Distributed systems of reservoirs, natural flood management, and green infrastructure are practical examples of distributed attenuation. The effectiveness of attenuating features lies in their ability to work in concert, by reducing and slowing runoff in strategic parts of the catchment, and desynchronizing flows. The spatial distribution of attenuating features plays an essential role in the process. This article proposes a framework to place features in a hydrologic network, group them into spatially distributed systems, and analyze their flood attenuation effects. The framework is applied to study distributed systems of reservoirs in a rural watershed in Iowa, USA. The results show that distributed attenuation can be an effective alternative to a single centralized flood mitigation approach. The different flow peak attenuation of considered distributed systems suggest that the spatial distribution of features significantly influences flood magnitude at the catchment scale. The proposed framework can be applied to examine the effectiveness of distributed attenuation, and its viability as a widespread flood attenuation strategy in different landscapes and at multiple scales.

Infiltration in sewer systems: comparison of measurement methods

2005 ◽  
Vol 52 (3) ◽  
pp. 219-227 ◽  
Author(s):  
J. De Bénédittis ◽  
J.-L. Bertrand-Krajewski
Keyword(s):  
Spatial Distribution ◽  
Comparative Studies ◽  
Measurement Methods ◽  
Diagnostic Study ◽  
Catchment Scale ◽  
Sewer Systems ◽  
Minimum Night Flow ◽  
Conventional Methods ◽  
Made In

For 20 years, several methods for the estimation of infiltration have been developed in various countries. These conventional methods are subject to considerable uncertainties due to their underlying assumptions and general principles which are not estimated. Two extended comparative studies of the conventional methods have been made in order to assess the variability in infiltration estimations and associated uncertainties according to the method used. The choice of method is not critical when the objective of a sewer diagnostic study is to define the spatial distribution of infiltration contributions at sub-catchment scale. Nevertheless, the methods based on the analysis of the minimum night flow that are generally applied during one dry weather day should be applied during 8 to 10 dry weather days in order to provide estimations with acceptable uncertainties.

scholarly journals The assessment of annual rainfall field by applying different interpolation methods in the state of Rio Grande do Sul, Brazil

2021 ◽  
Vol 3 (7) ◽  
Author(s):  
Denis Rafael Silveira Ananias ◽  
Gilberto Rodrigues Liska ◽  
Luiz Alberto Beijo ◽  
Geraldo José Rodrigues Liska ◽  
Fortunato Silva de Menezes
Keyword(s):  
Spatial Distribution ◽  
Mean Squared Error ◽  
Rio Grande ◽  
The State ◽  
Annual Rainfall ◽  
Rio Grande Do Sul ◽  
Rainfall Distribution ◽  
Interpolation Methods ◽  
Squared Error ◽  
Rainfall Spatial Distribution

AbstractAn accurate analysis of spatial rainfall distribution is of great importance for managing watershed water resources, in addition to giving support to meteorological studies and agricultural planning. This work compares the performance of two interpolation methods: Inverse distance weighted (IDW) and Kriging, in the analysis of annual rainfall spatial distribution. We use annual rainfall data for the state of Rio Grande do Sul (Brazil) from 1961 to 2017. To determine which proportion of the sample results in more accurate rainfall distribution maps, we use a certain amount of points close to the estimated point. We use mean squared error (MSE), coefficient of determination (R2), root mean squared error (RMSE) and modified Willmott's concordance index (md). We conduct random fields simulations study, and the performance of the geostatistics and classic methods for the exposed case was evaluated in terms of precision and accuracy obtained by Monte Carlo simulation to support the results. The results indicate that the co-ordinary Kriging interpolator showed better goodness of fit, assuming altitude as a covariate. We concluded that the geostatistical method of Kriging using nine closer points (50% of nearest neighbors) was the one that better represented annual rainfall spatial distribution in the state of Rio Grande do Sul.

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