Preprints
https://doi.org/10.5194/hess-2018-449
https://doi.org/10.5194/hess-2018-449
17 Sep 2018
 | 17 Sep 2018
Status: this preprint was under review for the journal HESS but the revision was not accepted.

Catchment-scale groundwater recharge and vegetation water use efficiency

Peter A. Troch, Ravindra Dwivedi, Tao Liu, Antonio Alves Meira Neto, Tirthankar Roy, Rodrigo Valdés-Pineda, Matej Durcik, Saúl Arciniega-Esparza, and José Agustín Breña-Naranjo

Abstract. Precipitation undergoes a two-step partitioning when it falls on the land surface. At the land surface and in the shallow subsurface, rainfall or snowmelt can either runoff as infiltration/saturation excess or quick subsurface flow. The rest will be stored temporarily in the root zone. From the root zone, water can leave the catchment as evapotranspiration or percolate further and recharge deep storage. It was recently shown that an index of vegetation water use efficiency, the Horton index (HI), could predict deep storage dynamics. Here we test this finding using 247 MOPEX catchments across the conterminous US. Our results show that the observed HI is indeed a reliable predictor of deep storage dynamics. We also find that the HI can reliably predict the long-term average recharge rate. Our results compare favorably with estimates of average recharge rates from the US Geological Survey. Previous research has shown that HI can be estimated based on aridity index, mean slope and mean elevation of a catchment (Voepel et al., 2011). We recalibrated Voepel’s model and used it to predict the HI for our catchments. We then used these predicted values of the HI to estimate average recharge rates for our catchments, and compared them with those estimated from observed HI. We find that the accuracies of our predictions based on observed and predicted HI are similar. This provides a novel estimation method of catchment-scale long-term average recharge rates based on simple catchment characteristics, such as climate and topography, and free of discharge measurements.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Peter A. Troch, Ravindra Dwivedi, Tao Liu, Antonio Alves Meira Neto, Tirthankar Roy, Rodrigo Valdés-Pineda, Matej Durcik, Saúl Arciniega-Esparza, and José Agustín Breña-Naranjo
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Peter A. Troch, Ravindra Dwivedi, Tao Liu, Antonio Alves Meira Neto, Tirthankar Roy, Rodrigo Valdés-Pineda, Matej Durcik, Saúl Arciniega-Esparza, and José Agustín Breña-Naranjo
Peter A. Troch, Ravindra Dwivedi, Tao Liu, Antonio Alves Meira Neto, Tirthankar Roy, Rodrigo Valdés-Pineda, Matej Durcik, Saúl Arciniega-Esparza, and José Agustín Breña-Naranjo

Viewed

Total article views: 2,871 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,195 623 53 2,871 64 66
  • HTML: 2,195
  • PDF: 623
  • XML: 53
  • Total: 2,871
  • BibTeX: 64
  • EndNote: 66
Views and downloads (calculated since 17 Sep 2018)
Cumulative views and downloads (calculated since 17 Sep 2018)

Viewed (geographical distribution)

Total article views: 2,573 (including HTML, PDF, and XML) Thereof 2,551 with geography defined and 22 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 14 Dec 2024
Download
Short summary
Recharge to bedrock aquifers is an important source of water availability and sustains streamflow during long dry periods. It is therefore an important component in the catchment water balance that sustains aquatic ecosystems. Our study shows that it is possible to predict average recharge rates at the catchment scale using only climate and landscape properties. This is an important finding as it is notoriously difficult to measure and/or estimate recharge rates at large spatial scales.