scholarly journals Analysis of the Spatio-Temporal Variability of Precipitation and Drought Intensity in an Arid Catchment in South Africa

Climate ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 70
Author(s):  
Achamyeleh G. Mengistu ◽  
Weldemichael A. Tesfuhuney ◽  
Yali E. Woyessa ◽  
Leon D. van Rensburg
Keyword(s):  
South Africa ◽  
Temporal Variability ◽  
Assessment Tool ◽  
Winter Season ◽  
Aridity Index ◽  
Annual Precipitation ◽  
Trend Test ◽  
Monthly Precipitation ◽  
Drought Intensity ◽  
Spatio Temporal

Water deficit is high and precipitation varies spatio-temporally in arid areas. This study was conducted to analyse the spatio-temporal variability of precipitation and drought intensity in an arid catchment in South Africa. The Soil and Water Assessment Tool (SWAT) was used to estimate the spatio-temporal precipitation where nine meteorological stations were used as input to the model. The model was calibrated and validated by regionalization with a physical similarity approach. SWAT only predicts precipitation at sub-basin level. Hence, the mean precipitation was further interpolated by using the inverse distance weighted method (IDW). The Mann–Kendall trend test shows that there was no trend in annual precipitation whereas in the monthly precipitation there was a 0.01 mm decrease. Daily precipitation varied from 0.1 to 4 mm whereas in a monthly basis, it varied from 6 mm (September) to 43.4 mm (February). The annual precipitation varied from 169 mm (1983) to 415 mm (2003) with a long-term mean of 280.8 mm. Precipitation is also highly variable in space throughout the catchment. Generally, annual precipitation decreased from north to south; however, during the winter season, the reverse was true due to the influence of rain-bearing condition from the south- western direction. Based on the aridity index (AI), the catchment is categorized as arid. The SPI shows that the 1983 drought was the worst whereas the 2003 and 2004 years were relatively wet. The results from this study provide baseline information for further research in climate change adaptation and environmental monitoring programs in the region.

scholarly journals Characterization of Interannual and Seasonal Variability of Hydro-Climatic Trends in the Upper Indus Basin

2021 ◽  
Author(s):  
Muhammad Usman Liaqat ◽  
Giovanna Grossi ◽  
Shabeh ul Hasson ◽  
Roberto Ranzi
Keyword(s):  
Trend Analysis ◽  
Hydrological Cycle ◽  
Winter Season ◽  
Rain Gauge ◽  
Indus Basin ◽  
Annual Precipitation ◽  
Monthly Precipitation ◽  
Catchment Scale ◽  
Upper Indus Basin ◽  
Annual Scale

Abstract A high resolution seasonal and annual precipitation climatology of the Upper Indus Basin was developed, based on 1995-2017 precipitation normals obtained from four different gridded datasets (Aphrodite, CHIRPS, PERSIANN-CDR and ERA5) and quality-controlled high and mid elevation ground observations. Monthly precipitation values were estimated through the anomaly method at the catchment scale and compared with runoff data (1975-2017) for verification and detection of changes in the hydrological cycle. The gridded dataset is then analysed using running trends and spectral analysis and the Mann–Kendall test was employed to detect significant trends. The nonparametric Pettitt test was also used to identify the change point in precipitation and runoff time series. The results indicated that bias corrected CHIRPS precipitation dataset, followed by ERA5, performed better in terms of RMSE, MAE, MAPE and BIAS in simulating rain gauge-observed precipitation. The running trend analysis of annual precipitation exhibited a very slight increase whereas a more significant increase was found in the winter season (DJF). A runoff coefficient value greater than one, especially in glacierized catchments (Shigar, Shyok and Gilgit) indicate that precipitation was likely underestimated and glacial melt in a warming climate provides excess runoff volumes. As far as the streamflow is concerned, variabilities are more pronounced at the seasonal rather than at the annual scale. At the annual scale, trend analysis of discharge shows slightly significant increasing trend for the Indus River at the downstream Kachura, Shyok and Gilgit stations. Seasonal flow analysis reveals more complex regimes and its comparison with the variability of precipitation favours a deeper understanding of precipitation, snow- and ice-melt runoff dynamics, addressing the hydroclimatic behaviour of the Karakoram region.

The spatio-temporal variability of annual precipitation and its local impact factors during 1724-2010 in Beijing, China

2013 ◽  
Vol 28 (4) ◽  
pp. 2192-2201 ◽  
Author(s):  
Yuanzheng Zhai ◽  
Yongli Guo ◽  
Jun Zhou ◽  
Na Guo ◽  
Jinsheng Wang ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Annual Precipitation ◽  
Impact Factors ◽  
Local Impact ◽  
Spatio Temporal ◽  
Beijing China

scholarly journals Elevation Dependency of Precipitation over Southern Slope of Central Himalaya

Jalawaayu ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 1-14
Author(s):  
Shankar Sharma ◽  
Nitesh Khadka ◽  
Bikash Nepal ◽  
Shravan Kumar Ghimire ◽  
Nirajan Luintel ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Precipitation Amount ◽  
Winter Season ◽  
Annual Precipitation ◽  
Spatial And Temporal Variation ◽  
Mean Annual Precipitation ◽  
Eastern Region ◽  
Monthly Precipitation ◽  
Monsoon Precipitation ◽  
Post Monsoon

Precipitation plays vital roles in the global water cycle, knowledge of the spatial and temporal variation of the precipitation is essential to understanding extreme environmental phenomena such as floods, landslides, and drought. In this paper, the integrated characteristics of precipitation during 1980–2016 over Nepal along with the seasonal elevation dependency of precipitation were examined for three different regions over the country using Multi-Source Weighted-Ensemble Precipitation (MSWEP) product. The spatial distribution of mean annual precipitation varies significantly with the highest (lowest) precipitation of ~5500 (~100) mm/year in the Arun valley (Manang and Mustang). The precipitation regime of the country is determined by the contribution of the monthly precipitation amount with distinct spatial gradients between the eastern and the western sides during pre-monsoon, post-monsoon, and winter seasons. On the contrary, the spatial distribution of monsoon precipitation tends to more heterogeneous with visible differences between the lowland, midland, and highlands as similar to the annual one. Further, elevation dependency of seasonal precipitation revealed that the winter and post-monsoon precipitation distribution in western and central are very similar, whereas post-monsoon precipitation was found slightly higher than winter season in the eastern region. The highest precipitation areas in eastern and central region are located between 2000-2500 m, which is between 500 and 1000 m in the western region of the country. Overall, the pre-monsoon, summer monsoon and annual precipitation increases gradually with elevation upto 2500 m and then decreases with increasing elevation, whereas winter and post-monsoon precipitation are almost identical to each elevation interval of 500 m.

Analysis of the spatio-temporal variability of soil water dynamics in an arid catchment in South Africa

2021 ◽  
pp. e00395
Author(s):  
Achamyeleh G. Mengistu ◽  
Weldemichael A. Tesfuhuney ◽  
Yali E. Woyessa ◽  
Leon D. van Rensburg
Keyword(s):  
South Africa ◽  
Soil Water ◽  
Temporal Variability ◽  
Water Dynamics ◽  
Soil Water Dynamics ◽  
Spatio Temporal

scholarly journals Cellular time series: a data structure for spatio-temporal analysis and management of geoscience information

2019 ◽  
Vol 21 (6) ◽  
pp. 999-1013
Author(s):  
Sina Nabaei ◽  
Bahram Saghafian
Keyword(s):  
Time Series ◽  
Data Structure ◽  
Temporal Analysis ◽  
Change Point Detection ◽  
Trend Test ◽  
Homogeneity Test ◽  
Monthly Precipitation ◽  
Detection Techniques ◽  
Standard Normal Homogeneity Test ◽  
Spatio Temporal

Abstract Geoscientists are continuously confronted by difficulties involved in handling varieties of data formats. Configuration of data only in time or space domains leads to the use of multiple stand-alone software in the spatio-temporal analysis which is a time-consuming approach. In this paper, the concept of cellular time series (CTS) and three types of meta data are introduced to improve the handling of CTS in the spatio-temporal analysis. The data structure was designed via Python programming language; however, the structure could also be implemented by other languages (e.g., R and MATLAB). We used this concept in the hydro-meteorological discipline. In our application, CTS of monthly precipitation was generated by employing data of 102 stations across Iran. The non-parametric Mann–Kendall trend test and change point detection techniques, including Pettitt's test, standard normal homogeneity test, and the Buishand range test were applied on the generated CTS. Results revealed a negative annual trend in the eastern parts, as well as being sporadically spread over the southern and western parts of the country. Furthermore, the year 1998 was detected as a significant change year in the eastern and southern regions of Iran. The proposed structure may be used by geoscientists and data providers for straightforward simultaneous spatio-temporal analysis.

scholarly journals Trends in precipitation: analysis of long annual and monthly time series from mainland Portugal

2010 ◽  
Vol 25 ◽  
pp. 155-160 ◽  
Author(s):  
M. I. P. de Lima ◽  
S. C. P. Carvalho ◽  
J. L. M. P. de Lima ◽  
M. F. E. S. Coelho
Keyword(s):  
Time Series ◽  
Parametric Method ◽  
Annual Precipitation ◽  
Trend Test ◽  
Monthly Precipitation ◽  
Mainland Portugal ◽  
Long Time ◽  
Increasing Trends ◽  
The 19Th Century ◽  
Non Parametric

Abstract. The purpose of this work is to investigate trends in annual and monthly precipitation in mainland Portugal by studying long time series. The data are from ten measuring stations scattered over mainland Portugal; some of the time series date back from the 19th century. Trends in these precipitation series were examined using the Mann-Kendall non-parametric trend test and the Sen's non-parametric method. Both full monotonic trends (i.e., over the record period) and partial trends were investigated. Results provide no evidences for rejecting the null hypothesis of no trend in annual precipitation, when a monotonic linear model was used. On the other hand, the analyses of partial trends in the time series identified a sequence of alternating decreasing and increasing trends in annual precipitation, which are sometimes statistically significant. This type of behaviour was also observed for the monthly precipitation.

scholarly journals Analysis of Trends, Recurrences, Severity and Frequency of Droughts using SPI: Case of OR Tambo DM, Eastern Cape in South Africa

2021 ◽  
Author(s):  
M Nkamisa ◽  
Simbarashe Ndhleve ◽  
MDV Nakin ◽  
A Mngeni ◽  
H Kabiti
Keyword(s):  
South Africa ◽  
National Level ◽  
Standardized Precipitation Index ◽  
Hydrological Drought ◽  
Average Intensity ◽  
Monthly Precipitation ◽  
Drought Frequency ◽  
Drought Intensity ◽  
Local Municipalities

Abstract South Africa is susceptible to droughts. However, there is little documentation on drought occurrence in South Africa at national level and its various administrative boundaries. The study aimed to profile the hydrological drought in ORTDM from 1998–2018; computing their frequency, severity and intensity so as to show areas of high vulnerability. Data used on this study was obtained from South African Weather Services in Pretoria. Standardized Precipitation Index (SPI) was calculated using the Meteorological Drought Monitor (MDM) software computing drought frequency, severity and intensity using 3 and 6 months SPI. The results showed a wide variation in monthly precipitation throughout the year. Coastal areas receive high rainfall than inland municipalities. When recorded in descending order, the drought intensity Nyandeni shows the highest drought frequency with a percentage of 62%, Mhlontlo (58%), KSDM (57%), Ngquza Hill (55%) and Port St Johns showing the least at (52%). The hydrological drought severity frequency and duration varied between 7 days to 9 weeks. Drought intensity class exposed the annual average intensity for the 5 local municipalities represented as follows; KSDM (-0.71), PSJM (-0.99), Ngquza Hill (-0.81), Nyandeni (-0.71) and Mhlontlo (-0.62). Maximum drought intensity for the 5 local municipalities showed the following results KSDM (-2.4), PSJM (-1.8), Ngquza Hill M (-1.9), Nyandeni M (-2.8) and Mhlontlo M (-3.1). The longest drought duration across OR Tambo was experienced in 2014 and has the following durations: KSDM (3 weeks), PSJM (5 weeks), Ngquza Hill (7 weeks), Nyandeni (8 weeks) and Mhlontlo (11 weeks). ORTDM is susceptible to hydrological droughts and the extent vary across local municipalities. The results could be used as a guide to the allocation of resources for drought relief purpose in a way that seeks to prioritize drought prone areas and vulnerable municipality. The SPI could be a useful when forecasting and estimating the frequency, duration and intensity of droughts. However, emphasis should be placed on improving the quality of data as this is key in improving the quality of its outcome.

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