Response of Hydrological Drought to Meteorological Drought under the Influence of Large Reservoir

Abstract

Based on monthly streamflow and precipitation data from 1960 to 2010 in the Jinjiang River Basin of China, Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were used to represent meteorological and hydrological drought, respectively. The response of hydrological drought to meteorological drought under the influence of Shanmei reservoir was investigated. The results indicate that SPI and SSI have a decreasing trend during recent several decades. Monthly scales of SSI series have a significant decreasing trend from November to the following February and a significant increasing trend from May to July at Shilong hydrological station. There are three significant periodic variations with a cycle of 6-7 years, 11-12 years, and 20-21 years for annual scales of SSI series. SPI series have the same periodic variations before the 1980s, but they have not been synchronous with SSI since the 1980s at Shilong due to influences of Shanmei reservoir, especially at the periodic variations of 20-21 years. The variation of the lag time of hydrological drought in response to meteorological drought is significant at the seasonal scale. The lag time of hydrological drought to meteorological drought extends one month on average in spring, summer, and autumn but about three months in winter.

Hydrological Drought Instantaneous Propagation Speed Based on the Variable Motion Relationship of Speed‐Time Process

“…Thus, according to the K‐S test criterion (see the supporting information), the Log‐normal distribution is the better probability density function than others to describe the streamflow over three consecutive months for the study area. In fact, this result is consistent with findings reported for other regions, such as central Italy (Solakova et al, ), northwest Iran (Tabari et al, ), and southern China (Niu et al, ; Wu et al, ). Thus, in the following sections, the Log‐normal function is applied to calculate the 3 months SSI of the each study area.…”

“…Previous studies have focused on the analysis of hydrological drought frequency including risk, return period, trend, periodicity, change trends of duration and magnitude, as well as the multivariate joint distributions (Al‐Faraj & Scholz, ; Chang et al, ; Lopez‐Moreno et al, ; Shiau, ; Wong et al, ; Wu et al, , ). Several recent studies have analyzed the propagation time from meteorological drought to hydrological drought (Lorenzo‐Lacruz et al, ; Van Loon et al, ) and the impact factors on the propagation time (such as temperature, catchment characteristics, land use/cover change, reservoir regulation) using linear and nonlinear correlation analysis methods (e.g., Pearson correlation analysis, Spearman correlation analysis, Budyko hypothesis, and logarithmic function; Apurv et al, ; Barker et al, ; Huang et al, ; Van Loon et al, ; Wu et al, , ). However, most of these previous studies did not take into account the internal processes (i.e., from the time of the drought development to the time of the drought recovery) of the hydrological drought propagation.…”

Revisiting hydrological drought propagation and recovery considering water quantity and quality

“…Based on National Oceanic and Atmospheric Administration reports, two meteorological dry periods from June 2001 to May 2002 and January 2008 to January 2009 were declared affecting the entire United States and southern United States, respectively. There is usually a time lag between meteorological drought and hydrological response, which can last on average between 1 and 4 (or even longer) months depending on hydrological conditions and drought severity (Halsinger, Koffler, Schoner, & Laaha, ; Lorenzo‐Lacruz, Vincente‐Serrano, Gonzalez‐Hidalgo, Loperz‐Moreno, & Cortesi, ; Wu et al, ). To provide additional supporting evidence, the USDM reports are also compared with this study results for 2002 and 2008 drought episodes.…”

Analisis Spasial Indeks Kekeringan Di Daerah Aliran Sungai (Das) Kampar Provinsi Riau

“…Pemanasan global telah meningkatkan frekuensi dan intensitas peristiwa iklim ekstrem seperti kekeringan (Wu, et al, 2016). Definisi kekeringan yang paling sederhana adalah kekurangan air untuk memenuhi kebutuhan.…”