scholarly journals Long-term meteorological and hydrological dryness and wetness conditions in the Zhujiang River Basin, South China

2012 ◽  
Vol 9 (9) ◽  
pp. 10525-10562
Author(s):  
T. Fischer ◽  
M. Gemmer ◽  
B. Su ◽  
T. Scholten
Keyword(s):  
Time Series ◽  
River Basin ◽  
Standardized Precipitation Index ◽  
Principal Component ◽  
Economic Losses ◽  
Xijiang River ◽  
The Xijiang River ◽  
Spatio Temporal ◽  
The Standardized Precipitation Index

Abstract. Floods and droughts are frequently causing large economic losses in China. These conditions vary in space, time, and magnitude. In this study, long-term meteorological and hydrological dryness and wetness conditions are analyzed for the Xijiang River Basin which is the largest tributary of the Zhujiang (Pearl) River. A very similar inter-annual course of precipitation and discharge can be observed. The standardized precipitation index (SPI) is used to show dryness and wetness pattern in the six sub-basins of the Xijiang River. The SPI-24 correlates high with the standardized discharge index (SDI-24) for Gaoyao hydrological station at the mouth of Xijiang River. Distinct long-term dryness and wetness sequences are found in the time series for the SPI-24 and SDI-24. The principal component analysis reveals many spatial interdependencies in dryness and wetness conditions for the sub-basins and explains some spatio-temporal disparities. Moderate dryness conditions have a larger spatial impact than moderate wetness conditions in the sub-basins. The loading pattern of the first principal component shows that the correlation with the entire Xijiang River Basin is highest in the eastern and lowest in the western sub-basins. Further spatial dipole conditions explain the spatio-temporal heterogeneity of dryness and wetness conditions. Accordingly, the precipitation in the eastern sub-basins contributes more to the hydrological wetness conditions than in the western sub-basins, which mainly contribute to dryness patterns. The spectral analysis for the SPI-24 (entire Xijiang River Basin) and SDI-24 shows similar peaks for periods of 11–14.7 yr, 2.8 yr, 3.4–3.7 yr, and 6.3–7.3 yr. The same periods can be found for the SPI-24 of Xijiang River's six sub-basins with some variability in the magnitude. The wavelet analysis shows that the most significant periods are stable over time since the 1980s. The extrapolations of the reconstructed time series do not suggest any spatial or temporal changes in the occurrence of dryness and wetness conditions in the next two decades but a continuation of the observed cycles at given magnitude. It can be concluded that long-term hydrological dryness and wetness conditions are directly caused by periodic cycles of meteorological conditions (i.e. precipitation). The applied methodologies prove to be able to identify spatial interdependencies and corresponding regional disparities, and to detect significant periodicities in long-term dryness and wetness conditions in the Xijiang River Basin.

scholarly journals Hydrological long-term dry and wet periods in the Xijiang River basin, South China

2013 ◽  
Vol 17 (1) ◽  
pp. 135-148 ◽  
Author(s):  
T. Fischer ◽  
M. Gemmer ◽  
B. Su ◽  
T. Scholten
Keyword(s):  
River Basin ◽  
South China ◽  
Standardized Precipitation Index ◽  
Principal Component ◽  
Spatial Disparities ◽  
Xijiang River ◽  
Daily Precipitation Data ◽  
The Xijiang River ◽  
The Standardized Precipitation Index

Abstract. In this study, hydrological long-term dry and wet periods are analyzed for the Xijiang River basin in South China. Daily precipitation data of 118 stations and data on daily discharge at Gaoyao hydrological station at the mouth of the Xijiang River for the period 1961–2007 are used. At a 24-month timescale, the standardized precipitation index (SPI-24) for the six sub-basins of the Xijiang River and the standardized discharge index (SDI-24) for Gaoyao station are applied. The monthly values of the SPI-24 averaged for the Xijiang River basin correlate highly with the monthly values of the SDI-24. Distinct long-term dry and wet sequences can be detected. The principal component analysis is applied and shows spatial disparities in dry and wet periods for the six sub-basins. The correlation between the SPI-24 of the six sub-basins and the first principal component score shows that 67% of the variability within the sub-basins can be explained by dry and wet periods in the east of the Xijiang River basin. The spatial dipole conditions (second and third principal component) explain spatiotemporal disparities in the variability of dry and wet periods. All sub-basins contribute to hydrological dry periods, while mainly the northeastern sub-basins cause wet periods in the Xijiang River. We can also conclude that long-term dry events are larger in spatial extent and cover all sub-basins while long-term wet events are regional phenomena. A spectral analysis is applied for the SPI-24 and the SDI-24. The results show significant peaks in periodicities of 11–14.7 yr, 2.8 yr, 3.4–3.7 yr, and 6.3–7.3 yr. The same periodic cycles can be found in the SPI-24 of the six sub-basins but with some variability in the mean magnitude. A wavelet analysis shows that significant periodicities have been stable over time since the 1980s. Extrapolations of the reconstructed SPI-24 and SDI-24 represent the continuation of observed significant periodicities at given magnitudes until 2030. The projected hydrological long-term dry and wet periods can be used for planning purposes in water resources management. The applied methodologies prove to be able to identify spatial disparities, and to detect significant periodicities in hydrological long-term dry and wet periods in the Xijiang River basin.

scholarly journals Spatiotemporal Variation of the Meteorological and Groundwater Droughts in Central Taiwan

2021 ◽  
Vol 3 ◽  
Author(s):  
Hsin-Fu Yeh
Keyword(s):  
River Basin ◽  
Groundwater Level ◽  
Standardized Precipitation Index ◽  
Extreme Drought ◽  
Water Shortages ◽  
Level Data ◽  
Groundwater Drought ◽  
Central Taiwan ◽  
The Standardized Precipitation Index

In recent years, Taiwan has been facing severe water shortages due to extreme drought. In addition, changes in rainfall patterns have resulted in an increasingly notable drought phenomenon, which affects the management and utilization of water resources. Therefore, this work examines basins in Central Taiwan. Long-term records from 13 rainfall and 17 groundwater stations were selected. The Standardized Precipitation Index (SPI) and Standardized Groundwater Level Index (SGI) were used to analyze the drought characteristics of this region. The rainfall and groundwater level data from basins in Central Taiwan were analyzed in this study. The results show that the year 2015 experienced extreme drought conditions due to a correlation with SPI and SGI signals. In addition, with regard to groundwater drought, more drought events occurred in the Da'an River basin; however, the duration and intensity of these events were relatively low, in contrast to those of the Wu River basin. Finally, the correlation between SPI and SGI was observed to vary in different basins, but a certain degree of correlation was observed in all basins. The results show that drought intensity increases with longer drought durations. Moreover, severe droughts caused by rainfall tend to occur at a greater frequency than those caused by groundwater.

scholarly journals Long-Term Rainfall Trends and Future Projections over Xijiang River Basin, China

2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
Muhammad Touseef ◽  
Lihua Chen ◽  
Kaipeng Yang ◽  
Yunyao Chen
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Scenarios ◽  
Emission Scenarios ◽  
Xijiang River ◽  
The Xijiang River

Precipitation trend detection is vital for water resources development and decision support systems. This study predicts the climate change impacts on long-term precipitation trends. It deals with the analysis of observed historical (1960–2010) and arithmetic mean method in assembling precipitation from CMIP5 Global Climate Models (GCMs) datasets for a future period (2020–2099) under four emission scenarios. Daily precipitation data of 32 weather stations in the Xijiang River Basin were provided by National Meteorological Information Centre (NMIC) of the China Meteorological Administration (CMA) and Global Climate Models (GCMs) with all four emission scenarios statistically downscaled using Bias Correction Special Disaggregation (BCSD) and applied for bias correction via Climate Change Toolkit (CCT). Nonparametric Mann–Kendall test was applied for statistical significance trend analysis while the magnitude of the trends was determined by nonparametric Sen’s estimator method on a monthly scale to detect monotonic trends in annual and seasonal precipitation time series. The results showed a declined trend was observed for the past 50 years over the basin with negative values of MK test (Z) and Sen’s slope Q. Historical GCMs precipitation detected decreasing trends except for NoerESM1-M which observed slightly increasing trends. The results are further validated by historical precipitation recorded by the Climate Research Unit (CRU-TS-3.1). The future scenarios will likely be positive trends for annual rainfall. Significant positive trends were observed in monsoon and winter seasons while premonsoon and postmonsoon seasons will likely be slightly downward trends. The 2040s will likely observe the lowest increase of 6.6% while the 2050s will observe the highest increase of 11.5% over the 21st century under future scenarios. However, due to the uncertainties in CMIP5, the future precipitation projections should be interpreted with caution. Thus, it could be concluded that the trend of change in precipitation around the Xijiang River Basin is on the increase under future scenarios. The results can be valuable to water resources and agriculture management policies, as well as the approach for managing floods and droughts under the perspective of global climate change.

DROUGHT OCCURRENCE UNDER LITHUANIAN CLIMATIC CONDITIONS

2015 ◽  
Author(s):  
Laima TAPARAUSKIENĖ ◽  
Veronika LUKŠEVIČIŪTĖ
Keyword(s):  
Meteorological Data ◽  
Standardized Precipitation Index ◽  
Vegetation Period ◽  
Climatic Conditions ◽  
Precipitation Record ◽  
Calculation Step ◽  
Drought Conditions ◽  
The Standardized Precipitation Index ◽  
June July

This study provides the analysis of drought conditions of vegetation period in 1982-2014 year in two Lithuanian regions: Kaunas and Telšiai. To identify drought conditions the Standardized Precipitation Index (SPI) was applied. SPI was calculated using the long-term precipitation record of 1982–2014 with in-situ meteorological data. Calculation step of SPI was taken 1 month considering only vegetation period (May, June, July, August, September). The purpose of investigation was to evaluate the humidity/aridity of vegetation period and find out the probability of droughts occurrence under Lithuanian climatic conditions. It was found out that according SPI results droughts occurred in 14.5 % of all months in Kaunas region and in 15.8 % in Telšiai region. Wet periods in Kaunas region occurred in 15.8 %, and in Telšiai region occurrence of wet periods was – 18.8 % from all evaluated months. According SPI evaluation near normal were 69.7 % of total months during period of investigation in Kaunas and respectively – 65.5 % in Telšiai. The probability for extremely dry period under Lithuania climatic conditions are pretty low – 3.0 % in middle Lithuania and 2.4 % in western part of Lithuania.

Study on the hydrochemistry character and carbon sink in the middle and upper reaches of the Xijiang River basin, China

2014 ◽  
Vol 74 (2) ◽  
pp. 997-1005 ◽  
Author(s):  
Shi Yu ◽  
Wenyue Du ◽  
Pingan Sun ◽  
Shiyi He ◽  
Yiming Kuo ◽  
...  
Keyword(s):  
River Basin ◽  
Carbon Sink ◽  
Xijiang River ◽  
The Xijiang River

Evaluation on uncertainty sources in projecting hydrological changes over the Xijiang River basin in South China

2017 ◽  
Vol 554 ◽  
pp. 434-450 ◽  
Author(s):  
Fei Yuan ◽  
Chongxu Zhao ◽  
Yong Jiang ◽  
Liliang Ren ◽  
Hongcui Shan ◽  
...  
Keyword(s):  
River Basin ◽  
South China ◽  
Xijiang River ◽  
Uncertainty Sources ◽  
Hydrological Changes ◽  
The Xijiang River

scholarly journals CONSTRUCTION AND ANALYSIS OF LONG-TERM SURFACE TEMPERATURE DATASET IN FUJIAN PROVINCE

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1223-1227 ◽  
Author(s):  
W. E. Li ◽  
X. Q. Wang ◽  
H. Su
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Land Surface ◽  
Rapid Development ◽  
Temporal Distribution ◽  
Heat Fluxes ◽  
Urban Region ◽  
Fujian Province ◽  
Spatio Temporal

Land surface temperature (LST) is a key parameter of land surface physical processes on global and regional scales, linking the heat fluxes and interactions between the ground and atmosphere. Based on MODIS 8-day LST products (MOD11A2) from the split-window algorithms, we constructed and obtained the monthly and annual LST dataset of Fujian Province from 2000 to 2015. Then, we analyzed the monthly and yearly time series LST data and further investigated the LST distribution and its evolution features. The average LST of Fujian Province reached the highest in July, while the lowest in January. The monthly and annual LST time series present a significantly periodic features (annual and interannual) from 2000 to 2015. The spatial distribution showed that the LST in North and West was lower than South and East in Fujian Province. With the rapid development and urbanization of the coastal area in Fujian Province, the LST in coastal urban region was significantly higher than that in mountainous rural region. The LST distributions might affected by the climate, topography and land cover types. The spatio-temporal distribution characteristics of LST could provide good references for the agricultural layout and environment monitoring in Fujian Province.

scholarly journals Space-time variability of hydrological drought and wetness in Iran using NCEP/NCAR and GPCC datasets

2010 ◽  
Vol 14 (10) ◽  
pp. 1919-1930 ◽  
Author(s):  
T. Raziei ◽  
I. Bordi ◽  
L. S. Pereira ◽  
A. Sutera
Keyword(s):  
Time Series ◽  
Singular Spectrum Analysis ◽  
Standardized Precipitation Index ◽  
Principal Component ◽  
Reanalysis Data ◽  
Space Time ◽  
Hydrological Drought ◽  
Time Variability ◽  
Climate Conditions ◽  
Good Agreement

Abstract. Space-time variability of hydrological drought and wetness over Iran is investigated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and the Global Precipitation Climatology Centre (GPCC) dataset for the common period 1948–2007. The aim is to complement previous studies on the detection of long-term trends in drought/wetness time series and on the applicability of reanalysis data for drought monitoring in Iran. Climate conditions of the area are assessed through the Standardized Precipitation Index (SPI) on 24-month time scale, while Principal Component Analysis (PCA) and Varimax rotation are used for investigating drought/wetness variability, and drought regionalization, respectively. Singular Spectrum Analysis (SSA) is applied to the time series of interest to extract the leading nonlinear components and compare them with linear fittings. Differences in drought and wetness area coverage resulting from the two datasets are discussed also in relation to the change occurred in recent years. NCEP/NCAR and GPCC are in good agreement in identifying four sub-regions as principal spatial modes of drought variability. However, the climate variability in each area is not univocally represented by the two datasets: a good agreement is found for south-eastern and north-western regions, while noticeable discrepancies occur for central and Caspian sea regions. A comparison with NCEP Reanalysis II for the period 1979–2007, seems to exclude that the discrepancies are merely due to the introduction of satellite data into the reanalysis assimilation scheme.

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