Analysis of Changes in Precipitation and Drought in Aksu River Basin, Northwest China

Abstract

The analysis of the spatiotemporal trends of precipitation and drought is relevant for the future development and sustainable management of water resources in a given region. In this study, precipitation and Standardized Precipitation Index (SPI) trends were analyzed through applying linear regression, Mann–Kendall, and Spearman’s Rho tests at the 5% significance level. For this goal, meteorological data from 9 meteorological stations in and around Aksu Basin during the period 1960–2010 was used, and two main annual drought periods were detected (1978-1979 and 1983–1986), while the extremely dry years were recorded in 1975 and 1985 at almost all of the stations. The monthly analysis of precipitation series indicates that all stations had increasing trend in July, October, and December, while both increasing and decreasing trends were found in other months. For the seasonal scale, precipitation series had increasing trends in summer and winter. 33% of the stations had the decreasing trend on precipitation in the spring series, and it was 11% in the autumn. At the same time, the SPI-12 values of all stations had the increasing trend. The significant trends were detected at Aheqi, Baicheng, Keping, and Kuche stations.

Spatial assessment of meteorological drought features over different climate regions in Iran

“…Trend analysis is usually conducted to investigate the long‐term systematic changes in climatic variables (Wang et al ., ; Dinpashoh et al ., ; Sonali and Nagesh Kumar, ; Goyal, ; Li et al ., ; Rashid et al ., ; Zhang et al ., ; Araghi et al ., ; Şen, ). Different trend detection methods (e.g., parametric, nonparametric and Bayesian) have been developed to assess trends in hydroclimatic time series (Reeves et al ., ; Khaliq et al ., ; Sonali and Nagesh Kumar, ; Dabanlı et al ., ) which include Mann–Kendall (MK) test, Sen's slope estimator, Spearman's rho tests, linear regression and innovative trend test (Şen method).…”

“…Different trend detection methods (e.g., parametric, nonparametric and Bayesian) have been developed to assess trends in hydroclimatic time series (Reeves et al ., ; Khaliq et al ., ; Sonali and Nagesh Kumar, ; Dabanlı et al ., ) which include Mann–Kendall (MK) test, Sen's slope estimator, Spearman's rho tests, linear regression and innovative trend test (Şen method). Those methods have been widely employed to detect trends in meteorological drought indices (Partal and Kahya, ; Liu et al ., ; Zhai et al ., ; Tabari et al ., ; Gocic and Trajkovic, ; Zhang et al ., ). Trends in SPI for different orders (e.g., 1, 3, 6, 9, 12, 24 months) have been assessed to understand the changes in droughts, mainly SPI in most of the previous studies (Hui‐Mean et al ., ; Mathbout et al ., ).…”

Quantile Regression Based Methods for Investigating Rainfall Trends Associated with Flooding and Drought Conditions

“…The magnitude, length and duration of the droughts can be indicated by a very low value of SPI. Researchers have revealed that precipitation generally follows the law of gamma distribution (Zhang et al 2015). The areal average of monthly precipitation data in the Dee river basin is computed and checked to see whether the underlying distributions of the data follow gamma distribution.…”

Hydrological Modelling for Integrated Water Resources Management in a Changing Climate

“…Similar techniques that are employed for detecting precipitation trends are also used in this respect. As one of the many examples, the popular Mann-Kendall test was used by Zhang et al (2015) to look into the trend of droughts as represented by the SPI time series.…”

“…The magnitude, length and duration of drought can be calculated with the SPI. Researchers have revealed that precipitation is follow the law of gamma distribution (Ganguli and Reddy, 2014;Zhang et al, 2015). The SPI can be computed for given periods (3, 6, 9, 12, 24 or 48 months).…”