Spatio-temporal characterization of rainfall using an innovative trend and discrete wavelet transformation approaches in Bhakra catchment, India

Author(s):  
Neha Gupta ◽  
Sagar Chavan

<p>Using a high-resolution daily gridded rainfall data of 0.25° from the Indian Meteorological Department (IMD), the present study investigates the detailed characteristics of rainfall in the Bhakra Catchment from 1901 to 2019. The long term spatial and temporal rainfall variations in Bhakra Catchment are not well explored. The spatial pattern of rainfall regimes in this catchment is identified by estimating index like the precipitation concentration index (PCI) and seasonality index (SI). Extreme rainfall trends on annual and seasonal basis are examined using the innovative trend analysis (ITA) method. Reliability of ITA was assessed by comparing them with widely applied Mann–Kendall (MK) or modified Mann–Kendall (mMK) test results. Furthermore, the change in two halves of rainfall series is estimated using percent bias technique for estimating changes in rainfall. Changes in slopes are estimated by using Sen’s slope estimator (Q). Discrete wavelet transform (DWT) in conjunction with Sequential Mann–Kendall test (SQMK) is employed to find out the dominant periodicity in rainfall patterns. The effectiveness of the graphical method in qualitative analysis can be seen, while DWT is found efficient in identifying periodicity. Both positive and negative trends are detected in annual and seasonal time series over the study area. The outcomes of this study may be helpful in the planning and management of water resources projects in the catchment along with the planning of mitigation measures to alleviate the effects of climate change under extreme rainfall conditions.</p>

2021 ◽  
Author(s):  
Quarban Aliyar ◽  
Santosh Dhungana ◽  
Sangam Shrestha

Abstract The civil war, harsh climate, tough topography and lack of accurate meteorological stations has limited observed data across Afghanistan. In order to fulfill the gap, this study analyzed the trend in precipitation and its extremes using Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) daily dataset between 1951 to 2010 at the spatial resolution of 0.25˚˟0.25˚. Non-parametric modified Mann-Kendall test and Sen’s slope estimator were employed to detect trend and quantify it at the significance level of 5%. Significant decreasing trends were observed only in small clusters of southwestern regions ranging between 0 to -1.5mm/year and northeastern region between -1.5 to -6 mm/year for the annual time series. Similar trend pattern was observed in spring season decreasing at the rate of -0.15 to 0.54 mm/year in northeastern and 0 to -0.15 mm/year southwestern region. Decrease in spring precipitation is expected to affect crop production especially in northeastern region which host 22 % of the arable area. Increasing trend in eastern region at maximum of 0.16 mm/year was observed which could intensify the flooding events. Trend analysis of extreme precipitation indices indicated similar spatial distribution to the mean precipitation, concentrated around southwestern, northeastern, and eastern regions. Increasing frequency of consecutive dry days in western region and very heavy precipitation (R10mm) and extremely heavy precipitation (R20mm) in eastern region are fueling the occurrence of droughts and floods respectively. Taking these findings of erratic nature of rainfall and extreme events into consideration for sustainable management of water resources would be fruitful.


Author(s):  
Desalew Meseret Moges ◽  
H. Gangadhara Bhat

Abstract This study aims to investigate the spatio-temporal variability and trends in climate and its implications for rainfed agriculture in the Rib watershed, north-western highland Ethiopia from 1986 to 2050. The daily rainfall and temperature records for the period 1986–2017 were used to detect the variability and trends of the current climate using the coefficient of variation, precipitation concentration index, Mann–Kendall test, and Sen's slope estimator. On the other hand, future climate changes (2018–2050) were analyzed based on the Coupled Model Intercomparison Project version 5 (CMIP5) model outputs under under two representative concentration pathway (RCP) scenarios, RCP 4.5 and 8.5. The results showed high inter-seasonal and inter-annual variability of rainfall and temperature in the studied watershed over the last four decades. The annual and Kiremt (June–September) rainfall showed a generally increasing trend, while the Belg (March–May) rainfall exhibited a decreasing trend between 1986 and 2017. Conversely, the minimum, maximum and mean temperature demonstrated increasing trends over the study period although most of the detected trends were statistically insignificant at 5 and 10% level of significance. Future climate analysis results showed an increase in future temperature and annual and Kiremt rainfall while Belg rainfall declined.


2019 ◽  
pp. 01-16
Author(s):  
Dang Nguyen Dong Phuong ◽  
Dang Kien Cuong ◽  
Duong Ton Dam ◽  
Nguyen Kim Loi

The Vietnamese Mekong Delta is among the most vulnerable deltas to climate–related hazards across the globe. In this study, the annual mean and extreme temperatures from 11 meteorological stations over the Vietnamese Mekong Delta were subjected to normality, homogeneity and trend analysis by employing a number of powerful statistical tests (i.e. Shapiro–Wilk, Buishand Range test, classical/modified Mann–Kendall test and Sen’s slope estimator). As for spatio–temporal assessment, the well–known (0.5° × 0.5°) high–resolution gridded dataset (i.e. CRU TS4.02) was also utilized to examine trend possibilities for three different time periods (i.e. 1901–2017, 1951–2017 and 1981–2017) by integrating spatial interpolation algorithms (i.e. IDW and Ordinary Kriging) with statistical trend tests. Comparing the calculated test–statistics to their critical values (a = 0.05), it is evident that most of the temperature records can be considered to be normal and non–homogeneous with respect to normality and homogeneity test respectively. As for temporal trend detection, the outcomes show high domination of significantly increasing trends. Additionally, the results of trend estimation indicate that the magnitude of increase in minimum temperature was mostly greater than mean and maximum ones and the recent period (1981–2017) also revealed greater increasing rates compared to the entire analyzed period and second half of the 20th century. In general, these findings yield various evident indications of warming tendency in the Vietnamese Mekong Delta over the last three decades.


Climate ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 107
Author(s):  
Sabrina Mehzabin ◽  
M. Shahjahan Mondal

This study analyzed the variability of rainfall and temperature in southwest coastal Bangladesh and assessed the impact of such variability on local livelihood in the last two decades. The variability analysis involved the use of coefficient of variation (CV), standardized precipitation anomaly (Z), and precipitation concentration index (PCI). Linear regression analysis was conducted to assess the trends, and a Mann–Kendall test was performed to detect the significance of the trends. The impact of climate variability was assessed by using a livelihood vulnerability index (LVI), which consisted of six livelihood components with several sub-components under each component. Primary data to construct the LVIs were collected through a semi-structed questionnaire survey of 132 households in a coastal polder. The survey data were triangulated and supplemented with qualitative data from focused group discussions and key informant interviews. The results showed significant rises in temperature in southwest coastal Bangladesh. Though there were no discernable trends in annual and seasonal rainfalls, the anomalies increased in the dry season. The annual PCI and Z were found to capture the climate variability better than the currently used mean monthly standard deviation. The comparison of the LVIs of the present decade with the past indicated that the livelihood vulnerability, particularly in the water component, had increased in the coastal polder due to the increases in natural hazards and climate variability. The index-based vulnerability analysis conducted in this study can be adapted for livelihood vulnerability assessment in deltaic coastal areas of Asia and Africa.


2021 ◽  
Vol 14 ◽  
pp. 117862212110133
Author(s):  
Hadi Eskandari Damaneh ◽  
Meysam Jafari ◽  
Hamed Eskandari Damaneh ◽  
Marjan Behnia ◽  
Asadollah Khoorani ◽  
...  

Projections of future scenarios are scarce in developing countries where human activities are increasing and impacting land uses. We present a research based on the assessment of the baseline trends of normalized difference vegetation index (NDVI), precipitation, and temperature data for the Khuzestan Province, Iran, from 1984 to 2015 compiled from ground-based and remotely sensed sources. To achieve this goal, the Sen’s slope estimator, the Mann-Kendall test, and Pearson’s correlation test were used. After that, future trends in precipitation and temperature were estimated using the Canadian Earth System Model (CanESM2) model and were then used to estimate the NDVI trend for two future periods: from 2016 to 2046 and from 2046 to 2075. Our results showed that during the baseline period, precipitation decreased at all stations: 33.3% displayed a significant trend and the others were insignificant ones. Over the same period, the temperature increased at 66.7% of stations while NDVI decreased at all stations. The NDVI–precipitation relationship was positive while NDVI–temperature showed an inverse trend. During the first of the possible future periods and under the RCP2.6, RCP4.5, and RCP8.5 scenarios, NDVI and precipitation decreased, and temperatures significantly increased. In addition, the same trends were observed during the second future period; most of these were statistically significant. We conclude that much assessments are valuable and integral components of effective ecosystem planning and decisions.


2020 ◽  
Vol 18 (1) ◽  
pp. 89-96
Author(s):  
Ahmad Nur Akma Juangga Fura ◽  
Retno Utami Agung Wiyono ◽  
Indarto Indarto

Madura subject to a high level of flood hazard. One of the main causes of flood is extreme rainfall. Global warming generates changes in the amount of extreme rainfall. This research is conducted to identify and to analyze the trends, changes, and randomness of 24-hour extreme rainfall data on Madura Island. The method used is a non-parametric method which includes the Median Crossing test, the Mann-Kendall test, and the Rank-Sum test at the significance level of α =0.05. The analysis was carried out on 31 rain gauge stations. The recording period observed is between 1991-2015. The results of the analysis show that based on the Median Crossing test, most rainfall stations have data originating from random processes. The result shows also that the maximum 24-hour extreme rainfall trend is significantly decreased in a few locations, while for the majority of other stations have no experience a significant trend.


2018 ◽  
Vol 22 (6) ◽  
pp. 3105-3124 ◽  
Author(s):  
Zilefac Elvis Asong ◽  
Howard Simon Wheater ◽  
Barrie Bonsal ◽  
Saman Razavi ◽  
Sopan Kurkute

Abstract. Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950–2013. The Mann–Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified – the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific–North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.


2012 ◽  
Vol 16 (1) ◽  
pp. 65-75 ◽  
Author(s):  
Dugin Kaown ◽  
Yunjung Hyun ◽  
Gwang-Ok Bae ◽  
Chang Whan Oh ◽  
Kang-Kun Lee

2020 ◽  
Vol 1000 (1000) ◽  
Author(s):  
Wakhidatik Nurfaida ◽  
Hendra Ramdhani ◽  
Takenori Shimozono ◽  
Indri Triawati ◽  
Muhammad Sulaiman

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.


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