Temporal analysis of rainfall and drought characteristics over Jalore District of S-W Rajasthan

Drought forecasting is being considered an important tool to help understand the rainfall pattern and climate change trend. Drought is a prolonged period of months or years in which an area, whether surface water or groundwater, becomes insufficient in its water supplies. Drought is considered as most difficult but least known environmental phenomenon, impacting more persons than any other. There are several indices used to classify droughts. For this study, precipitation-based drought indices are considered (i.e., SPI, RAI and Percentage Departure of Rainfall). The objective of the research is to examine and determine the possible rainfall trends over the Jalore district of South-West Rajasthan in Luni river basin. In this research, trend analysis using the rainfall data from the years 1901 to 2021 was carried out on monthly, seasonal and annual basis. To define the current trend path, the Mann-Kendall test and Sen's slope estimator test were used. In order to detect the trend and its change in magnitude over a particular period of time, Sen's slope estimator was used. During the southwest monsoon, declining rainfall leads to short-term meteorological droughts, which have severe effect on the agriculture sector and Jalore district's water supplies, while rising rainfall during other seasons tends to mitigate the severity of drought. The result of research reveals that there is rise of pre-monsoon and post-monsoon rainfall, but it also depicts a fall in the annual rainfall which reflects in reduced Winter and S-W monsoon rainfall.

Water vapor pressure trends in south and southwest Iran

Recognitionanddetectionofclimaticparameters inhave animportant role inclimate change monitoring. In this study, the analysis of oneofthe most importantparameters, water vapor pressure (WVP), was investigated. For this purpose, two non-parametric techniques, Mann-Kendall and Sen's Slope Estimator, were used to analyze the WVP trend and to determine the magnitude of the trends, respectively. To analyze these tests, ground station observations [10 stations for period of 44 years (1967-2010)] and gridded data [pixels with the dimension of 9 × 9 km over a 30-year period (1981-2010)] in South and SouthwestofIran were used. By programming in MATLAB software, the monthly, seasonal and annual WVP time series were extracted and MK and Sen's slope estimator tests were done. The results of monthly MK test on ground station observations showed that the significant downward trends are more considerable than significant upward trends. It also showed that the WVP highest frequency was more in warm months, April to September and the highest frequency of significant trends slope was in February and May. The spatial distribution of MK test of monthly gridded WVP time series showed that the upward trends were detected mostly in western zone and near the Persian Gulf in August. On the other hand, the downward trends through months. The maximum and minimum values of positive trends slope occurred in warm months and cold months, respectively. The analysis of the MK test of the annual WVP time series indicated the upward significant trends in the southeast and southwest zones of study area.

Analysis of long-term climatic changes at Hodeidah-Yemen during the period between 1984 and 2019

Yemen is one of the Arab country that is vulnerable to climate changes, and this is clear from the indicators of impact on water resources, coastal zone environments, etc. This work focuses on studying the climatic variability at Hodeidah city-Yemen during the period between 1984 and 2019. This study aimed to characterize trends in mean monthly, seasonal and annual temperature. To attain these objectives the collected data were analyzed using both parametric (linear regression) and non-parametric (Mann–Kendall, Spearman and Sen's slope estimator tests) methods to detect the trend and the magnitudes of rates of changes of temperature over time. Analysis of data indicates clear climatic fluctuations of temperature. The annual means of temperature during the period of study were varied between 26.9°C and 30.1°C. The warmest years were observed during the more recent years of the study period ( 2005 to 2018). The increasing rate of annual temperature is about + 0.075°C /year, + 0.37°C/5year, + 0.75°C/decade ,+2.53°C, over the whole period of study(1985 to 2019), + 3.7°C/50 year and increase to + 4.85°C in 2050. On a monthly timescale, there are similar magnitudes of rates of change from December to September with highest rates in October and November. The results also showed that most months and seasons have significant positive trends in temperature and (Z-α/2) values of the MK Test > 1.96 and positive value of Sen’s slope estimator indicates significant an increasing trend towards warmer years. Anomalies of temperature confirm significant increasing trends towards warmer years (2000s to 2019).

Rainfall trend analysis using Mann-Kendall and Sen’s slope estimator test in West Kalimantan

Climate change has been a prominent issue in the last decade. Climate change on a global scale does not necessarily have the same effect in different regions. Rainfall is a crucial weather element related to climate change. Rainfall trends analysis is an appropriate step in assessing the impact of climate change on water availability and food security. This study examines rainfall variations and changes at West Kalimantan, focusing on Mempawah and Kubu Raya from 2000-2019. The Mann-Kendall (MK) and Sen's Slope estimator test, which can determine rainfall variability and long-term monotonic trends, were utilized to analyze 12 rainfall stations. The findings revealed that the annual rainfall pattern prevailed in all locations. Mempawah region tends to experience a downward trend, while Kubu Raya had an upward trend. However, a significant trend (at 95% confidence level) was identified in Sungai Kunyit with a slope value of -33.20 mm/year. This trend indicates that Sungai Kunyit will become drier in the future. The results of monthly rainfall analysis showed that significant upward and downward trends were detected in eight locations. Rainfall trends indicate that climate change has occurred in this region.

Analysis of long-term climatic changes at Hodeidah-Yemen during the period between 1984 and 2019

Yemen is one of the Arab country that is vulnerable to climate changes, and this is clear from the indicators of impact on water resources, coastal zone environments, etc. This work focuses on studying the climatic variability at Hodeidah city-Yemen during the period between 1984 and 2019. This study aimed to characterize trends in mean monthly, seasonal and annual temperature. To attain these objectives the collected data were analyzed using both parametric (linear regression) and non-parametric (Mann–Kendall, Spearman and Sen's slope estimator tests) methods to detect the trend and the magnitudes of rates of changes of temperature over time. Analysis of data indicates clear climatic fluctuations of temperature. The annual means of temperature during the period of study were varied between 26.9°C and 30.1°C. The warmest years were observed during the more recent years of the study period ( 2005 to 2018). The increasing rate of annual temperature is about + 0.075°C /year, + 0.37°C/5year, + 0.75°C/decade ,+2.53°C, over the whole period of study(1985 to 2019), + 3.7°C/50 year and increase to + 4.85°C in 2050. On a monthly timescale, there are similar magnitudes of rates of change from December to September with highest rates in October and November. The results also showed that most months and seasons have significant positive trends in temperature and (Z-α/2) values of the MK Test > 1.96 and positive value of Sen’s slope estimator indicates significant an increasing trend towards warmer years. Anomalies of temperature confirm significant increasing trends towards warmer years (2000s to 2019).

Long Term Trend Analysis of Upstream and Middle-Stream River in Langat Basin, Malaysia

The present study investigates the trend in long term monthly streamflow of Sungai Lui (upstream) and Sungai Kajang (middle-stream) of the Sungai Langat Basin located in Selangor, Malaysia. The Mann-Kendall (MK) and Innovative Trend Method (ITM) tests were utilized to assess the trends at the two stations. The trend free pre-whitening (TFPW) and variance correction (VC) tests were used to assess the effects of serial correlation on the established trend, and Sen’s slope estimator was used to assess the magnitude of streamflow. Based on Sen’s Slope estimator results, the trend magnitude for Lui station is very small compared to the Kajang station. The Kajang station shows the highest increase in trend magnitude for November. The results of TFPW and VC trend tests showed that the most significant increasing trend of months occurred at Kajang station, while the less increasing significant trend of months occurred at Lui station. It can be concluded that similar trend results were obtained when the modified Mann-Kendall and ITM were applied to the same data for Sungai Lui and Sungai Kajang. The study found that there is a significant difference in terms of trend and magnitud between upstream and middle-stream.

Spatio-temporal Trend Detection of Rainfall for Climate Change Assessment in Ahmedabad-Gandhinagar District of Gujarat State, India

The present research aims to assess the historical change in rainfall patterns with the changing climate in the Ahmedabad-Gandhinagar district in the state of Gujarat in India. The Mann-Kendall (MK) test along with Sen’s slope estimator have been used for detecting the trend of rainfall data series. The trend of annual rainfall is carried out for – (1) six rain gauge stations established by the State Water Data Center (SWDC) and (2) 11 grid data available from the National Center for Environmental Prediction-Climate Forecast System Reanalysis (NCEP-CFSR) for 35 years starting from 1979 to 2013. Results obtained from these two data sets for the trend detection were found consistent. Furthermore, the analyses of annual and monthly rainfall using MK test and Sen’s slope estimator at six rain gauge stations are carried out in three time periods i.e. 1974-1987, 1988-2001 and 2002-2016. The inverse distance weighted (IDW) method of interpolation is used for the results obtained from the spatial distribution of the temporal rainfall trend for interpolating the station value over the study area. Annual rainfall for data length of 1979 to 2013 shows an increasing trend. The trend of annual and monthly rainfall for July and September shows a positive trend for the span 2002-2016. This study would be useful to the water resource department and policymakers for climate change adaptation in the study area.

Rainfall trend and variability over Opak River basin, Yogyakarta, Indonesia

Rainfall intensity seems to be increasing nowadays due to climate change as presented in many studies of both global and regional scale. Consequently, cities worldwide are now more vulnerable to flooding. In Indonesia, increasing frequency of floods was reported for the past decades by The National Agency for Disaster Countermeasure (BNPB). To understand the rainfall changes, long-term trend evaluation over a specific area is then crucial due to the large variability of spatial and temporal rainfall distribution. This study investigates the homogeneity and trend of rainfall data from 20 stations over the Opak River basin, Yogyakarta, Indonesia. A long-term ground observation rainfall data whose period varies from 1979 to 2019 were analyzed. Non-parametric Mann – Kendall test was applied to assess the trend, while the magnitude was calculated using the Sen’s slope estimator. An increasing annual maximum of daily rainfall intensity was observed at four stations on a 0.95 confidence level based on the Mann – Kendall test, while the Sen’s slope estimator shows a positive trend at almost all stations. The trend of heavy rainfall frequency was also found to be significantly increased, with only one station showed a decreasing trend. Furthermore, this paper also described the spatial and temporal rainfall variability. Positive trend was mostly found during the rainy season, while the negative trend occurred during the dry season. This could pose a challenge for water resource management engineering and design, such as water supply systems or reservoir management. Understanding this phenomena will benefit hydrologists in preparing future water resource engineering and management.