ERRA -- an R script for Ensemble Rainfall-Runoff Analysis

ERRA is a data-driven, nonparametric, model-independent method for quantifying rainfall-runoff relationships across a spectrum of time lags, in systems that may be nonlinear, nonstationary, and spatially heterogeneous.

Researchers using ERRA in published work should cite J.W. Kirchner, "Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using Ensemble Rainfall-Runoff Analysis (ERRA): proof of concept", Hydrology and Earth System Sciences, 2024 (for ERRA itself) and J.W. Kirchner, "Impulse response functions for nonlinear, nonstationary, and heterogeneous systems, estimated by deconvolution and de-mixing of noisy time series", Sensors, 22(9), 3291, https://doi.org/10.3390/s22093291, 2022 (for the underlying mathematics).

This data set includes two versions of the ERRA script written in the open-source programming language R, a detailed user's guide, and sample scripts and source data for all of the results in Kirchner (2024).

These scripts are made publicly available under GNU General Public License 3; for details see https://www.gnu.org/licenses/. The data and documentation are made available under Creative Commons Attribution Share-Alike CC-BY-SA.

ETH Zurich, WSL, and James Kirchner make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose. Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

• ETH Zurich (link) (Grant/Award: --)

Kirchner, J. W. (2022). Impulse response functions for nonlinear nonstationary and heterogeneous systems. EnviDat. https://www.doi.org/10.16904/envidat.312.

Kirchner J.W. (2022) Impulse response functions for nonlinear, nonstationary, and heterogeneous systems, estimated by deconvolution and demixing of noisy time series. Sensors. 22(9), 3291 (44 pp.). doi.org/10.3390/s22093291