分类： 地球科学 >> 地理学 提交时间： 2023-07-17 合作期刊: 《干旱区科学》
摘要：The shrinkage of the Aral Sea, which is closely related to the Amu Darya River, strongly affects the sustainability of the local natural ecosystem, agricultural production, and human well-being. In this study, we used the Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST) model to detect the historical change points in the variation of the Aral Sea and the Amu Darya River and analyse the causes of the Aral Sea shrinkage during the 1950–2016 period. Further, we applied multifractal detrend cross-correlation analysis (MF-DCCA) and quantitative analysis to investigate the responses of the Aral Sea to the runoff in the Amu Darya River, which is the main source of recharge to the Aral Sea. Our results showed that two significant trend change points in the water volume change of the Aral Sea occurred, in 1961 and 1974. Before 1961, the water volume in the Aral Sea was stable, after which it began to shrink, with a shrinkage rate fluctuating around 15.21 km3/a. After 1974, the water volume of the Aral Sea decreased substantially at a rate of up to 48.97 km3/a, which was the highest value recorded in this study. In addition, although the response of the Aral Sea's water volume to its recharge runoff demonstrated a complex non-linear relationship, the replenishment of the Aral Sea by the runoff in the lower reaches of the Amu Darya River was identified as the dominant factor affecting the Aral Sea shrinkage. Based on the scenario analyses, we concluded that it is possible to slow down the retreat of the Aral Sea and restore its ecosystem by increasing the efficiency of agricultural water use, decreasing agricultural water use in the middle and lower reaches, reducing ineffective evaporation from reservoirs and wetlands, and increasing the water coming from the lower reaches of the Amu Darya River to the 1961–1973 level. These measures would maintain and stabilise the water area and water volume of the Aral Sea in a state of ecological restoration. Therefore, this study focuses on how human consumption of recharge runoff affects the Aral Sea and provides scientific perspective on its ecological conservation and sustainable development.
分类： 地球科学 >> 地理学 提交时间： 2021-01-22 合作期刊: 《干旱区科学》
Durdiev KHAYDAR
CHEN Xi
HUANG Yue
Makhmudov ILKHOM
LIU Tie
Ochege FRIDAY
Abdullaev FARKHOD
Gafforov KHUSEN
Omarakunova GULKAIYR
摘要： High water consumption and inefficient irrigation management in the agriculture sector of the middle and lower reaches of the Amu Darya River Basin (ADRB) have significantly influenced the gradual shrinking of the Aral Sea and its ecosystem. In this study, we investigated the crop water consumption in the growing seasons and the irrigation water requirement for different crop types in the lower ADRB during 2004–2017. We applied the FAO Penman–Monteith method to estimate reference evapotranspiration (ET0) based on daily climatic data collected from four meteorological stations. Crop evapotranspiration (ETc) of specific crop types was calculated by the crop coefficient. Then, we analyzed the net irrigation requirement (NIR) based on the effective precipitation with crop water requirements. The results indicated that the lowest monthly ET0 values in the lower ADRB were found in December (18.2 mm) and January (16.0 mm), and the highest monthly ET0 values were found in June and July, with similar values of 211.6 mm. The annual ETc reached to 887.2, 1002.1, and 492.0 mm for cotton, rice, and wheat, respectively. The average regional NIR ranged from 514.9 to 715.0 mm in the 10 Irrigation System Management Organizations (UISs) in the study area, while the total required irrigation volume for the whole region ranged from 4.2×109 to 11.6×109 m3 during 2004–2017. The percentages of NIR in SIW (surface irrigation water) ranged from 46.4% to 65.2% during the study period, with the exceptions of the drought years of 2008 and 2011, in which there was a significantly less runoff in the Amu Darya River. This study provides an overview for local water authorities to achieve optimal regional water allocation in the study area.
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