{"id":928,"date":"2019-07-20T18:58:44","date_gmt":"2019-07-20T22:58:44","guid":{"rendered":"http:\/\/hydrouncertainty.org\/?p=928"},"modified":"2019-07-20T18:58:49","modified_gmt":"2019-07-20T22:58:49","slug":"latest-publications-on-hydrologic-uncertainty-june-2019","status":"publish","type":"post","link":"http:\/\/hydrouncertainty.org\/2019\/07\/20\/latest-publications-on-hydrologic-uncertainty-june-2019\/","title":{"rendered":"Latest Publications on \u2018Hydrologic Uncertainty\u2019 \u2013 June 2019"},"content":{"rendered":"\n

Water Resources Research: <\/strong><\/h2>\n\n\n\n
  1. Tang,\nY., Marshall, L., Sharma, A., Ajami, H., & Nott, D. J. (2019).\nEcohydrologic error models for improved Bayesian inference in remotely sensed\ncatchments. Water Resources Research<\/em>. https:\/\/doi.org\/10.1029\/2019WR025055<\/a> <\/li>
  2. Brunner, M. I., Hingray, B., Zappa, M., &\nFavre, A. C. Future trends in the interdependence between flood peaks and\nvolumes: hydro\u2010climatological drivers and uncertainty. Water Resources\nResearch<\/em>. https:\/\/doi.org\/10.1029\/2019WR024701<\/a> <\/li>
  3. Lee, T., & Ouarda, T. B. (2019).\nMultivariate Nonstationary Oscillation Simulation of Climate Indices with Empirical\nMode Decomposition. Water Resources Research<\/em>. https:\/\/doi.org\/10.1029\/2018WR023892<\/a> <\/li>
  4. Apurv, T., & Cai, X. Evaluation of the\nstationarity assumption for meteorological drought risk estimation at the\nmulti\u2010decadal scale in contiguous US. Water Resources Research<\/em>.\nhttps:\/\/doi.org\/10.1029\/2018WR024047<\/a><\/li><\/ol>\n\n\n\n

    Environmental Modelling and Software:<\/strong><\/h2>\n\n\n\n