17 Apr 2020
Research article | 17 Apr 2020
Quantifying the impacts of human water use and climate variations on recent drying of Lake Urmia basin: the value of different sets of spaceborne and in situ data for calibrating a global hydrological model
Seyed-Mohammad Hosseini-Moghari et al.
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12 citations as recorded by crossref.
- Effects of Water Level Decline in Lake Urmia, Iran, on Local Climate Conditions A. Dehghanipour et al. 10.3390/w12082153
- Modeling the volatility changes in Lake Urmia water level time series F. Fathian & B. Vaheddoost 10.1007/s00704-020-03417-8
- Visualized spatiotemporal data mining in investigation of Urmia Lake drought effects on increasing of PM10 in Tabriz using Space-Time Cube (2004-2019) H. Ahmadi et al. 10.1016/j.scs.2021.103399
- A quantile-based realization of the indirect-link between large-scale atmospheric oscillation and lake water level F. Fathian et al. 10.1007/s12517-021-08961-9
- Institutional analysis of organizations active in the restoration of Lake Urmia: the application of the social network analysis approach S. Es’haghi et al. 10.1080/02626667.2022.2026950
- Quantifying Lake-Aquifer Water Exchange: The Case of Lake Urmia, Iran E. Parizi et al. 10.1080/02626667.2022.2044044
- Impacts of different human activities on hydrological drought in the Huaihe River Basin based on scenario comparison H. Cheng et al. 10.1016/j.ejrh.2021.100909
- Streamflow trends during recent decades at some near-natural catchments in Iran Q. Zhang et al. 10.1080/02626667.2021.2011287
- Land deformation and sinkhole occurrence in response to the fluctuations of groundwater storage: an integrated assessment of GRACE gravity measurements, ICESat/ICESat-2 altimetry data, and hydrologic models B. Khorrami et al. 10.1080/15481603.2021.2000349
- Assessment of agricultural development preventive policies for restoration of Urmia Lake in Barandoz Basin, Iran R. Esmaeilnezhad et al. 10.1016/j.ejrs.2021.10.005
- Soil moisture and streamflow deficit anomaly index: an approach to quantify drought hazards by combining deficit and anomaly E. Popat & P. Döll 10.5194/nhess-21-1337-2021
- Quantifying streamflow drivers by anthropogenic time series attribution method in human-nature system S. Nabaei & B. Saghafian 10.1007/s00704-021-03598-w
Latest update: 28 Jan 2023