STOCHASTIC FLOW REGIME CLASSIFICATION AND INVERSE PRECIPITATION ESTIMATION FROM DISCHARGE IN THE HUMID TROPICS

Enrico Bonanno(1,2,3), Christian Birkel(4,5), Julian Klaus(1), and Gianluca Botter(3)

enrico.bonanno@list.lu LIST.lu

Context

The major processes for characterizing the hydrology of a basin can be

subdivided in three categories: recharge (1), losses (2) and storage of

water (3) (Rodríguez-Iturbe & Rinaldo [1997]).

Understanding streamflow variability in space and time is crucial for its

impact on ecological and morphological processes in river systems (natural

flow regime, Poff [1997]).

Problems

Catchment classification can be a useful tool for understanding streamflow

regimes. However, complex hydroclimatic and geomorphic environment

in data poor regions are difficult to study.

In this perspective, stochastic methods may serve as a parsimonious tool

for a better understanding of poorly gauged catchments.

In detail:

1. We apply a stochastic model (by Botter et al. [2013]) to different

catchments in tropical Costa Rica;

2. We infer catchment average rainfall-runoff characteristics in a

“hydrology backwards” approach…

…which will be used to:

3. Propose a novel and coherent hydroclimatic classification of Costa Rica

based on streamflow regime and precipitation characteristics.

18 Catchments – streamflow data from 01/01/1973–31/12/2003

The backward hydrology approach - different from Kirchner’s method

[2009] - allowed us to estimate rainfall intensity and frequency as

indicators of that specific catchment hydrological regime.

Novel and coherent hydro-climatic classification of Costa Rica

Miralles, D. G., Holmes, T. R. H., de Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A. & Dolman, A. J. (2011), Global land-surface evaporation estimated from satellite-based observations. Hydrology and Earth System Sciences, 15, 453–469, doi: 10.5194/hess-15-453-2011. Mu, Q., Zhao, M. & Running, S.W. (2011). Improvements to a MODIS Global Terrestrial Evapotranspiration Algorithm. Remote Sensing of Environment, Volume 115, pages 1781-1800.doi:10.1016/j.rse.2011.02.019. Poff, N. L., Allan, J. D., Bain, M. B., Karr, J. R., Prestegaard, K. L., Richter, B. D., Sparks, R. E. & Stromberg, J. C. (1997). The Natural Flow Regime. BioScience, vol. 47, No. 11 (Dec., 1997), pp. 769-

784. DOI: 10.2307/1313099

Rodriguez-Iturbe. I., & Rinaldo A. (1997). Fractal River Basins: Chance and Self-Organization. Cambridge Univ. Press. New York;

Acknowledgements EB acknowledges funding from the project PRIDE/15/10623093/HYDRO-CSI programme for part of this work. CB would like to acknowledge support by the University of Costa Rica Research Council (project 217-B3-34) and the Water and Global Change Observatory (OACG – ED3309). GB acknowledges funding from the ERC-2017-COG “DyNET” (Grant. N. 770999).

Effective rainfall distributed as a Poisson process: - Average frequency λ [T−1];

- Average intensity α [L].

k - hydrograph recession rate [T-1] dependingon morphological

features.

Linear storage-discharge relationship

Steady-state probability distribution function (pdf)

.

𝐶𝑉𝑄 = √𝑘 𝜆⁄

If λ/k > 1 the mean frequency of

effective rainfall is higher than

the flow decay rate.

If λ/k < 1 the mean frequency of

effective rainfall is smaller than

the flow decay rate.

Persistent regime Erratic regime

Streamflow regimes

After Botter et al. [2013]

After Botter et al. [2013]

Rainfall regimes and their variability

This work allowed us to classify and evaluate the seasonal streamflow and rainfall regime of 18 Costa Rican catchments.

The consequent microclimatic classification emphasizes the importance to relate hydrological, climatic and streamflow

patterns.

(3) Department of Civil, Architectural and Environmental Engineering (ICEA), University of Padova, Padova

(4) Department of Geography, University of Costa Rica, San José, Costa Rica

(5) Northern Rivers Institute, University of Aberdeen, Aberdeen, Scotland

Costa Rican volcanic soils (Losilla et al.

[2001]) explain the Persistent Regime for

the high majority of the catchments.

Backward hydrology approach

From streamflow to rainfall

1 2

3 4

5

References Botter G., Porporato A., Rodriguez-Iturbe I. & Rinaldo A. (2007). Basin-scale soil moisture dynamics and the probabilistic characterization of carrier hydrologic flows: Slow. leaching-prone components of the hydrologic response. Water Resources Research, 43, W02417. Botter, G., Basso, S., Rodriguez-Iturbe, I. & Rinaldo, A. (2013). Resilience of river flow regimes. Proceedings of the national Academy of Sciences of United States of America, 110(32): 12925-12930. Hengl, T., de Jesus, J. M., MacMillan, R. A., Batjes, N. H., Heuvelink, G. B. M., Ribeiro, E., et al. (2014). SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992. Kirchner, J. W. (2009). Catchments as simple dynamical systems: Catchment characterization,rainfall-runoff modeling, and doing hydrology backward. Water Resources Research, 45, W02429, doi:10.1029/2008WR006912. Losilla, M., Rodríguez, H., Schosinsky, G., Stimson, J. & Bethune, D. (2001). Los acuíferos volcánicos y el desarrollo sostenible en América Central, EUNED 1st edition, San José, Costa Rica.

(1) Catchment and Eco-Hydrology Group, Luxembourg Institute of Science and

Technology, Belvaux, Luxembourg

(2) Institute of Hydraulic and Water Resources Engineering, Vienna University of

Technology, Vienna, Austria