Improved Flood Forecasting in Basins with no Precipitation Station: Constrained Runoff Correction Using Multiple Satellite Precipitation Products


Authors:
Owners: This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource.
Resource type: Composite Resource
Storage: The size of this resource is 276.8 KB
Created: Aug 02, 2021 at 6:10 a.m.
Last updated: Oct 26, 2021 at 9:31 a.m.
Citation: See how to cite this resource
Sharing Status: Public
Views: 162
Downloads: 6
+1 Votes: Be the first one to 
 this.
Comments: No comments (yet)

Abstract

Satellite-based precipitation products (SPPs) with short latencies provide a new opportunity for flood forecasting in basins with no precipitation station. However, the larger uncertainties associated with such near-real-time SPPs can influence the accuracy of flood forecasts. Here we propose a real-time updating method, referred to as “Constrained Runoff Correction using Multiple SPPs” (CRC-M). The method is based on the hypothesis that the range of runoff volumes computed using different near-real-time SPPs provides an indication of the approximate range in which the true runoff volume lies. Accordingly, a constrained runoff correction is performed using the discharge observed at the basin outlet within this range. Evaluation using real data indicates that the new method performs well, with Nash–Sutcliffe (NS) values of 0.85 and 0.87 during calibration and evaluation, respectively. The necessity of imposing constraints using multiple SPPs is demonstrated by comparing CRC-M against 2 controls, referred to as “Unconstrained Runoff Correction using Single SPP” (URC-S) and “Constrained Runoff Correction using Single SPP with perturbations” (CRC-S). Experiments indicate that the key factors that result in good performance are 1) relatively reliable SPPs, and 2) wider constraint ranges. Overall, the CRC-M method can result in accurate and stable flood forecasts in basins with no precipitation station, without the shortening of leading time and the need for increased model complexity (i.e., the numbers of model parameters).

Subject Keywords

Deleting all keywords will set the resource sharing status to private.

Content

How to Cite

Dou, Y., L. Ye, H. V. Gupta, H. Zhang, A. Behrangi, H. Zhou (2021). Improved Flood Forecasting in Basins with no Precipitation Station: Constrained Runoff Correction Using Multiple Satellite Precipitation Products, HydroShare, http://www.hydroshare.org/resource/20f34ab024d94ce19333414b77626bf2

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

Comments

There are currently no comments

New Comment

required