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- Author:
- Seyyedian, Hamid, et al. ; Mahdavi, Ali; Show all 2 Author
- Source:
- Water resources management 2013 v.27 no.8 pp. 2785-2806
- ISSN:
- 0920-4741
- Subject:
- aquifers; basins; equations; groundwater; groundwater recharge; image analysis; stream flow
- Abstract:
- ... The purpose of this work is to present analytical solution for linearized Boussinesq equation in triangular-shaped aquifers in response to transient recharge from an overlaying basin. Four different configurations of hydrogeological boundary conditions (constant-head and no-flow) are considered. At first, the solutions for the rectangular-shaped aquifers are obtained through the well known image w ...
- DOI:
- 10.1007/s11269-013-0315-2
-
http://dx.doi.org/10.1007/s11269-013-0315-2
- Author:
- Safavi, Hamid R., et al. ; Esmikhani, Mahdieh; Show all 2 Author
- Source:
- Water resources management 2013 v.27 no.7 pp. 2623-2644
- ISSN:
- 0920-4741
- Subject:
- algorithms; basins; equipment; groundwater; hydrologic models; irrigation rates; irrigation systems; irrigation water; rain; surface water; watersheds; Iran
- Abstract:
- ... Combined simulation-optimization models have been widely used to address the management of water resources issues. This paper presents a simulation-optimization model for conjunctive use of surface water and groundwater at a basin-wide scale, the Zayandehrood river basin in west central Iran. In the Zayandehrood basin, in the past 10 years, a historical low rainfall in the head of the basin, combi ...
- DOI:
- 10.1007/s11269-013-0307-2
-
http://dx.doi.org/10.1007/s11269-013-0307-2
- Author:
- Abyaneh, Hamid Zare, et al. ; Marofi, Safar; Tabari, Hossein; Show all 3 Authors
- Source:
- Water resources management 2011 v.25 no.5 pp. 1417-1435
- ISSN:
- 0920-4741
- Subject:
- algorithms; artificial intelligence; basins; kriging; latitude; longitude; neural networks; prediction; snow; water resources; Iran
- Abstract:
- ... The evaluation of water resources given by snowfall is very important in the mountainous basins. In this study, the snow depth (SD) and snow water equivalent (SWE) were investigated to quantify the water resources stored in the snow. Multivariate non-linear regression (MNLR) method, four types of artificial neural network (ANN) and neural network-genetic algorithm (NNGA) model were initially evalu ...
- DOI:
- 10.1007/s11269-010-9751-4
-
http://dx.doi.org/10.1007/s11269-010-9751-4