Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union

Journal metrics

  • IF value: 3.535 IF 3.535
  • IF 5-year<br/> value: 4.292 IF 5-year
    4.292
  • SNIP value: 1.523 SNIP 1.523
  • IPP value: 3.478 IPP 3.478
  • SJR value: 1.859 SJR 1.859
  • h5-index value: 54 h5-index 54
HESS cover
Executive editors:
Erwin
 
Zehe
,
Alberto
 
Guadagnini
,
Alison D.
 
Reeves
 &
Hubert H.G.
 
Savenije

Hydrology and Earth System Sciences (HESS) is an international two-stage open-access journal for the publication of original research in hydrology, placed within a holistic Earth system science context. HESS encourages and supports fundamental and applied research that seeks to understand the interactions between water, earth, ecosystems, and humans. A multi-disciplinary approach is encouraged that enables a broadening of the hydrologic perspective and the advancement of hydrologic science through the integration with other cognate sciences, and the cross-fertilization across disciplinary boundaries.

News

Direct settlement of APCs for scientists from the University of Potsdam

01 Jul 2015

The Potsdam University Library and Copernicus Publications have signed an agreement on direct settlement of article processing charges (APCs).

Update data policy

29 Jun 2015

We have updated our data policy: it now also refers to the Data Citation Principles and stresses the necessity of data availability.

HESS awarded DOAJ Seal

25 Jun 2015

Hydrology and Earth System Sciences (HESS) has received the new DOAJ Seal which recognizes journals with an exceptionally high level of publishing standards and best practice.

Recent articles

Highlight articles

Water storages and fluxes on land are key variables in the Earth system. To provide context for local investigations and to understand phenomena that emerge at large spatial scales, information on continental freshwater dynamics is needed. This paper presents a methodology to estimate continental-scale runoff on a 0.5° spatial grid, which combines the advantages of in situ observations with the power of machine learning regression. The resulting runoff estimates compare well with observations.

L. Gudmundsson and S. I. Seneviratne

Our paper is one of very few studies where the influence of stochastic internal atmospheric variability (IAV) on the hydrological response is analyzed. On the basis of ensemble experiments with GCM and hydrological models, we found, e.g., that averaging over ensemble members filters the stochastic term related to IAV, and that a considerable portion of the simulated trend in annual Lena R. runoff can be explained by the externally forced signal (global SST and SIC changes in our experiments).

A. Gelfan, V. A. Semenov, E. Gusev, Y. Motovilov, O. Nasonova, I. Krylenko, and E. Kovalev

We present an empirical study of the rates of increase in precipitation intensity with air temperature using high-resolution 10 min precipitation records in Switzerland. We estimated the scaling rates for lightning (convective) and non-lightning event subsets and show that scaling rates are between 7 and 14%/C for convective rain and that mixing of storm types exaggerates the relations to air temperature. Doubled CC rates reported by other studies are an exception in our data set.

P. Molnar, S. Fatichi, L. Gaal, J. Szolgay, and P. Burlando

In this study, we analyze a set of high-resolution, surface-based, 2-D ground-penetrating radar (GPR) observations of artificially induced subsurface water dynamics. In particular, we place close scrutiny on the evolution of the capillary fringe in a highly dynamic regime with surface-based time-lapse GPR. We thoroughly explain all observed phenomena based on theoretical soil physical considerations and numerical simulations of both subsurface water flow and the expected GPR response.

P. Klenk, S. Jaumann, and K. Roth

We present a systematic comparison of changes in historical extreme precipitation in station observations (HadEX2) and 15 climate models from the CMIP5 (as the largest and most recent sets of available observational and modeled data sets), on global and continental scales for 1901-2010, using both parametric (linear regression) and non-parametric (the Mann-Kendall as well as Sen’s slope estimator) methods, taking care to sample observations and models spatially and temporally in comparable ways.

B. Asadieh and N. Y. Krakauer

Publications Copernicus