Temporal analysis of rainfall (1871–2012) and drought characteristics over a tropical monsoon-dominated State (Kerala) of India

Thomas, Jobin; Prasannakumar, V.

doi:10.1016/j.jhydrol.2016.01.013

Cited by 131 publications

(52 citation statements)

References 76 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These tropical regions are characterized by high annual precipitation, but a strong seasonality in precipitation could lead to drought conditions [2]. In recent years, research on tropical droughts has received substantial attention from researchers and policy makers due to the awareness on climate change [3][4][5][6]. For instance, occurrences of the 2010 Amazon drought [7], the 1997-1998 Malaysia drought [8], the 2015 Indonesia drought [9] and the 2012 Northeast Brazil drought [10] have turned the tropical forest from a net carbon sink to a source, thus impacting local communities and ecosystems.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of TRMM Product for Monitoring Drought in the Kelantan River Basin, Malaysia

Tan

Chua

et al. 2017

Water

View full text Add to dashboard Cite

Assessment of satellite precipitation products' capability for monitoring drought is relatively new in tropical regions. The purpose of this paper is to evaluate the reliability of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B43 product in estimating the standardized precipitation index (SPI) in the Kelantan River Basin, Malaysia from 1998 to 2014, by comparing it with data from 42 rain gauges. Overall, the TMPA-3B43 performed well in the monthly precipitation estimation, but performed moderately in the seasonal scale. Better performance was found in the northeast monsoon (wet season) than in the southwest monsoon (dry season). The product is more reliable in the northern and north-eastern regions (coastal zone) compared to the central, southern and south-eastern regions (mountainous area). For drought assessment, the correlations between the TMPA-3B43 and ground observations are moderate at various time-scales (one to twelve months), with better performance at shorter time-scales. The TMPA-3B43 shows similar temporal drought behavior by capturing most of the drought events at various time-scales, except for the 2008-2009 drought. These findings show that the TMPA-3B43 is not suitable to be used directly for SPI estimation in this basin. More bias correction and algorithm improvement work are needed to improve the accuracy of the TMPA-3B43 in drought monitoring.

show abstract

Section: Introductionmentioning

confidence: 99%

Evaluation of TRMM Product for Monitoring Drought in the Kelantan River Basin, Malaysia

Tan

Chua

et al. 2017

Water

View full text Add to dashboard Cite

show abstract

“…The monthly rainfall data of Kerala, Telangana, and Orissa subdivisions for the period 1871–2012 was collected from Indian Institute of Tropical Meteorology Pune (htpp://http://www.tropmet.res.in) and used for determining SPI3 values of the three regions. In the past, several researchers have used these datasets for spatio‐temporal trend analysis of rainfall and droughts over different regions in India (Adarsh & Janga Reddy, ; Ganguli & Janga Reddy, ; Joshi et al, ; Thomas & Prasannakumar, ). The time series of the monthly rainfall data of the three subdivisions are presented in Figure .…”

Section: Study Area and Datasetsmentioning

confidence: 99%

“…Therefore, analysis of spatial extent of droughts and drought prediction are important for agricultural planning and management. In recent past, few studies focused on analysing the variability and risks of droughts in different parts of India (Ganguli & Janga Reddy, , ; Janga Reddy & Ganguli, ; Joshi, Gupta, Suryavanshi, Adamowski, & Madramootoo, ; Thomas, Nayak, & Ghosh, ; Thomas & Prasannakumar, ). Over the years, many univariate and multivariate indices were proposed for modelling and risk assessment of droughts (Kao & Govindaraju, ; Mishra & Singh, ; Zargar, Sadiq, Naser, & Khan, ).…”

Section: Introductionmentioning

confidence: 99%

“…Telangana subdivision(15°N-19°N, 77°E-82°E)is one of the low rainfall receiving regions (semiarid characteristics) in the peninsular India and is not having any oceanic proximity, and the region is also declared as drought affected region by state government several times in the recent past.The monthly rainfall data of Kerala, Telangana, and Orissa subdivisions for the period 1871-2012 was collected from Indian Institute of Tropical Meteorology Pune (htpp://www.tropmet.res.in) and used for determining SPI3 values of the three regions. In the past, several researchers have used these datasets for spatio-temporal trend analysis of rainfall and droughts over different regions in India(Adarsh & Janga Reddy, 2015;Ganguli & Janga Reddy, 2013;Joshi et al, 2016;Thomas & Prasannakumar, 2016). The time series of the monthly rainfall data of the three subdivisions are presented inFigure 2.4 | RESULTS AND DISCUSSION 4.1 | Trend analysis of SPI3 series…”

mentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of trends and predictability of short‐term droughts in three meteorological subdivisions of India using multivariate EMD‐based hybrid modelling

Adarsh

Reddy

2018

Hydrological Processes

View full text Add to dashboard Cite

This paper presented trend analysis of droughts in Kerala, Telangana, and Orissa meteorological subdivisions in India and proposed a framework for drought prediction by employing the Empirical Mode Decomposition (EMD)‐based prediction models. The study used 3‐month standardized precipitation index (SPI3) for drought analysis. The trend analysis of SPI3 series for the period 1871–2012 using Mann–Kendall method showed statistically significant increasing trend in Kerala and Telangana subdivisions and a decreasing trend in Orissa subdivision. In addition, the non‐linear trend component extracted from EMD showed statistically significant changes in all the three subdivisions. Then, the study proposed a hybrid approach for prediction of short‐term droughts by coupling multivariate extension of EMD (MEMD) with stepwise linear regression (SLR) and genetic programming (GP) methods. First, the multivariate dataset comprising the SPI3 series of current and lagged time steps are decomposed using the MEMD. Then, SLR/GP models are developed to predict each subseries of SPI3 of desired time step considering the subseries of predictor variables at the corresponding timescales as inputs. The resulting models at different timescales are recombined to obtain the SPI3 values of the desired time step. The method is applied for prediction of short‐term droughts in the three subdivisions. The results obtained by the hybrid models are compared with that obtained by conventional prediction models using M5 Model Trees and GP. The rigorous performance evaluation based on multiple statistical criteria clearly exhibited the superiority of the hybrid approaches (i.e., prediction models with MEMD‐based decomposition over models without decomposition) for prediction of SPI3 in three subdivisions. Further, the study found that MEMD‐GP model performs marginally better than the MEMD‐SLR model due to its efficacy in modelling high frequency modes.

show abstract

“…Kerala experiences tropical monsoon climate with heavy annual rainfall of 3000 mm. In recent years, there is both spatial and temporal variation in monsoon rainfall [44] along with more intense short term droughts [45] compared to the previous years. The temperature reaches up to more than 32°C during March to April with a relative humidity of 73-89%.…”

Section: Study Areamentioning

confidence: 99%

Sensitivity analysis of a climate vulnerability index - a case study from Indian watershed development programmes

Sathyan

Funk

Aenis

et al. 2018

Clim Chang Responses

View full text Add to dashboard Cite

Background: This paper presents a detailed analysis of a composite Climate Vulnerability Index (CVI) to examine and compare climate change vulnerability and its dimensions adaptive capacity, sensitivity and exposure. Thereby, we are mainly interested on climate change vulnerability at community-level watershed development programmes and how the different implementing agencies could help to address the problems associated with climate change in future planning and implementation. Method: The primary data used for this study was obtained from household surveys (n = 215) in three watershed communities of Kerala, India. We use bootstrap sampling and a leave-one-out sensitivity analysis to compare the climate vulnerability of the three examined watersheds in detail. By introducing the bootstrapping method and sensitivity analysis into the research field of climate vulnerability, the paper describes significant differences in CVI values and the influencing indicators to the overall vulnerability at the watershed community level. Results:The results show that there are significant differences in the exposure and sensitivity dimensions of vulnerability even if the overall CVI shows less variability and no significant differences among the three watersheds. The sensitivity analysis emphasizes that 'Livelihood Strategies' and 'Social Network' are the most influencing major components of vulnerability. This suggests that implementing agencies should focus on these two major components in order to improve the watershed development programmes. Conclusion:The bootstrapping approach is transferable to evaluate the degree of influence of indicators on a composite index like the CVI. Moreover, it allows us to evaluate the potential effectiveness of various other climate change programmes where the evaluation is commonly done by field surveys. This thereby helps to increase the credibility in the examination of the impacts of climate change at different scales in order to find key areas for better policy planning.

show abstract

Temporal analysis of rainfall (1871–2012) and drought characteristics over a tropical monsoon-dominated State (Kerala) of India

Cited by 131 publications

References 76 publications

Evaluation of TRMM Product for Monitoring Drought in the Kelantan River Basin, Malaysia

Evaluation of TRMM Product for Monitoring Drought in the Kelantan River Basin, Malaysia

Evaluation of trends and predictability of short‐term droughts in three meteorological subdivisions of India using multivariate EMD‐based hybrid modelling

Sensitivity analysis of a climate vulnerability index - a case study from Indian watershed development programmes

Contact Info

Product

Resources

About