Effect of spatiotemporal variation of rainfall on dissolved oxygen depletion in integrated catchment studies

Conference paper (2016)

Authors

A. Moreno Rodenas Sanitary Engineering -

F. Cecinati University of Bristol

J.A.E. ten Veldhuis Water Resources -

J.G. Langeveld Partners4UrbanWater, Sanitary Engineering -

Jeroen Langeveld Partners4UrbanWater, Sanitary Engineering -

F.H.L.R. Clemens Sanitary Engineering - , Deltares

Research Group

Sanitary Engineering () (TU Delft)

Water quality Geostatistics Integrated Catchment Modelling; Rainfall spatiotemporal variability

To reference this document use:

http://resolver.tudelft.nl/uuid:f5ed68cd-ba37-4450-b686-0e15aa477691

More Info

expand_more

Published Date

2016

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Civil Engineering & Geosciences

Department

Water Management

Research Group

Sanitary Engineering

Abstract

This study addresses the effect of spatial and temporal resolution of rainfall fields on the performance of a simplified integrated catchment model for predicting dissolved oxygen concentrations in a river. For that purpose we propose a procedure to generate rainfall products with increasing spatial information at different time step accumulations (10’, 30’ and 60’) at the spatial support of lumped urban catchment systems. Using a rain gauge network and single-polarization C-Band Radar data we generate 4 rainfall products; 1) Homogeneous rainfall from a single rain gauge, 2) Block kriging interpolation from a network of 13 rain gauges, 3) Averaged Radar estimation and 4) Universal block kriging from a rain gauge network and using Radar as an external covariate. Comparison of the model predictions with
monitoring data in the river showed a low sensitivity to the temporal scales proposed and a relative improvement with increasing spatial information linked to the climatological characteristics of the storm period.

Files

SPN8_ConfPaper_2016.pdf

(pdf | 0.905 Mb)

Unknown license