Lake Urmia, as the largest lake in Iran, has suffered from water-level decline and this problem needs to be investigated accurately. The major reason for the decline is controversial. The current paper aimed to study the hydro-environmental variables over the Lake Urmia basin using remote sensing tools, artificial neural networks, wavelet transforms, and Mann–Kendall trend tests from 1995 to 2019 in order to determine the primary reason of the decline and to find the most important hydrologic periodicities over the basin. The results indicated that for the monthly-, seasonally-, and annually-based time series, the components with 4-month and 16-month, 24- and 48-month, and 2- and 4-year, respectively, are the most dominant periodicities over the basin. The agricultural increase according to the vegetation index and evapotranspiration and their close relationship with the water-level change indicated that human land-use is the main reason for the decline. The increasing agriculture, in the situations that the precipitation has not increased, caused the inflow runoff to the lake to decline and the remaining smaller discharge is not sufficient to stabilize the water level. Temperature time series, also, has experienced a significant positive trend which intensified the water-level change.

乌尔米亚湖是伊朗最大的湖泊，水位不断下降，需要对此问题进行准确调查。下降的主要原因是有争议的。本论文旨在利用遥感工具，人工神经网络，小波变换和Mann-Kendall趋势检验从1995年至2019年研究乌尔米亚湖流域的水环境变量，以确定水位下降的主要原因并找出流域最重要的水文周期性。结果表明，对于基于月度，季节和年度的时间序列，分别以4个月和16个月，24个月和48个月以及2年和4年的分量最多。流域的主要周期性。根据植被指数和蒸散量的农业增长及其与水位变化的密切关系表明，人类土地利用量下降是主要原因。在降水量没有增加的情况下，不断增加的农业活动导致流入湖泊的径流减少，剩余的较小流量不足以稳定水位。温度时间序列也经历了明显的积极趋势，加剧了水位变化。导致流入湖泊的径流减少，剩余的较小流量不足以稳定水位。温度时间序列也经历了明显的积极趋势，加剧了水位变化。导致流入湖泊的径流减少，剩余的较小流量不足以稳定水位。温度时间序列也经历了明显的积极趋势，加剧了水位变化。