Hydroclimatological Predictions Based on Basin's Humidity Index

The use of long-term records of observational data to determine the variability of land surface moisture fluxes and storages is essential for answering key science questions concerning the degree to which the global hydrologic cycle is intensifying in response to potential anthropogenic climate forcings and to assess the potential for improving predictability of floods and droughts. In addition to climate anomalies, accurate characterization of land surface states enhances runoff predictability. Energy fluxes and precipitation control runoff and evapotranspiration rates. In arid regions where available energy supply is greater than the latent heat required to evaporate total precipitation, evapotranspiration equals or approaches total precipitation. On the other hand, in more humid regions the available energy supply can be less than the latent heat required to evaporate all the precipitation and hence actual evapotranspiration approaches potential evapotranspiration.

Here, we present a new empirical model that predicts the control of available energy and precipitation in determining values of evapotranspiration was developed. The model is a very simple one-parameter formula that takes into account the expected dominant vegetation type while maintaining Budyko's assumptions related to the concept of “geographical zonality”: that (a) the biome type is determined by the aridity (or humidity) index and (b) the evaporation efficiency is a function only of the aridity (or humidity) index. Computed evapotranspiration values for 314 watersheds within the Arkansas/Red River system agreed reasonably well with the empirical model predictions. The model was extended to develop two other formulae that were used successfully to predict the sensitivity of runoff and evapotranspiration to precipitation variations. The empirical model can serve as a useful tool to estimate the changes in various components of the hydrologic cycle as a result of climate change.