Doing Hydrology Backwards in New Mexico to Estimate a Statewide Water Budget

Published Date:

March 2016


Cameron Herrington and Ricardo González-Pinzón


Accurate statewide water budgets are dependent on the quality, quantity and availability of measured information in catchments. Given typical data acquisition constraints, water budgets rely on the measurement of a limited number of water fluxes (e.g., precipitation and streamflow) and on modeling tools that allow for estimation and scaling of other relevant, unmeasured fluxes. We seek to use a parsimonious modeling technique (Doing Hydrology Backward (DHB) from Kirchner (2009)) that utilizes discharge data alone to estimate catchment-averaged precipitation and evapotranspiration rates in New Mexico. Since the United States Geological Survey (USGS) now maintains a network of 23,000 stream gages nationally, with approximately 130 sites across the major catchments of New Mexico, estimating precipitation and evapotranspiration rates from streamflow data has enormous potential to provide catchment-scale information on processes that are not extensively monitored, but are key in estimating statewide water budgets. Ideally, the DHB method could take advantage of the highly scrutinized discharge datasets available from the USGS through the employment of a simple discharge-storage model to estimate catchment fluxes thus minimizing common modeling errors and bias caused by over-parameterization. We developed a MATLAB code capable of estimating catchment-average precipitation and evapotranspiration rates. We successfully validated the code using the original data presented by Kirchner (2009). Despite providing accurate estimates of hydrologic processes in humid catchments, the standard DHB model did not accurately represent precipitation rates observed in three dryland basins in New Mexico. As it is, the DHB code that we developed in MATLAB will be useful in humid catchments. However, it requires the addition and validation of snowmelt terms before it can be used in our characteristic New Mexico dryland basins.




Discharge, evapotranspiration, precipitation, water budget, dryland, climate change, equifinality, computer modeling, catchment, storage