Spatio-temporal rainfall trend assessment over a semi-arid region of Karnataka state, using non-parametric techniques

Harishnaika, N; Ahmed, Shakeel; Kumar, Sanjay; Arpitha, M

doi:10.1007/s12517-022-10665-7

Cited by 6 publications

(1 citation statement)

References 35 publications

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“…This study has been conducted in Kolar and Chikkaballapura districts lying between 12⁰ 45'N -13⁰ 57'N latitude and 77⁰ 24'E -78⁰ 35'E longitude as shown in figure 1. These areas are stationed in the south-eastern region, which is the semi-arid agro-climatic zone of Karnataka state, As per the Köppen Geiger climate classification system, 30 sub-types and 5 main classes are defined to classify the world climate pattern [19]. The climate classification for the research area is defined by Equatorial Winter Dry (Aw) covering the major portion and along the northern part of the districts, we find Arid Steppe Hot (BSh) Figure1.…”

Section: Study Areamentioning

confidence: 99%

Analysis of Drought Severity and Vegetation Condition Prediction Using Satellite Remote Sensing Indices in Kolar and Chikkaballapura Districts, Karnataka State

2023

EESRR

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Drought is a natural hazard with far-reaching effects including economic losses, and soil damages, and threatens the health of residents and livelihood. The present research aimed to observe the vegetation health index across the semi-arid regions of Karnataka state in 2015-2019 using GIS and remote sensing techniques. Landsat-8 dataset images, with a 30 m spatial resolution and from various platforms were used to recognize the Vegetation Condition Index and Temperature Condition Index. The VCI is dependent on the NDVI datasets. The Temperature Condition Index used LST. As an outcome, the VHI was generated and classified into 5 categories of drought: no drought, mild, moderate, severe, and extreme drought. The results indicate that the highest % of the extreme agricultural drought found in Chinthamani taluk is about 740.20 squares Km (20%) area. In the S-W monsoon showed Bagepalli is about 397.70 squares Km (18%), and Sidhlaghatta taluk is about 26 % (338.55 squares Km). In the North-east Monsoon extreme drought severity was affected in Malur at 22% (704.05 squares Km), Mulubhagilu at 26 % (909.99 squares Km), and Bangarapete at 21% (879.64 sq. km) of the area have severely affected the agriculture and vegetation from 2015-2019 respectively. Severe to moderate drought occurred in the north–east part of both areas of Kolar and Chikkaballapura districts. 2016 and 2017 experienced a less level of drought % with compared to the other study years. This study allows the monitoring of decision-makers, resolves drought conditions, and investigates more beneficially.

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Section: Study Areamentioning

confidence: 99%

Analysis of Drought Severity and Vegetation Condition Prediction Using Satellite Remote Sensing Indices in Kolar and Chikkaballapura Districts, Karnataka State

2023

EESRR

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Detection of spatiotemporal patterns of rainfall trends, using non-parametric statistical techniques, in Karnataka state, India

Harishnaika

Ahmed

2023

Environ Monit Assess

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Spatiotemporal Rainfall Variability and Trend Analysis of Shimsha River Basin, India

Bharath

Maddamsetty

Manjunatha

et al. 2023

Environ Sci Pollut Res

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The current study aims to determine the variability and trend in rainfall data. From 1989 to 2018, daily rainfall data was gathered for the Shimsha basin, a sub-basin of the Cauvery basin in Karnataka, India, and aggregated into annual, seasonal, and monthly rainfall totals as well as the number of rainy days. In this study, the time series are subjected to statistical methods to examine rainfall variability and trend. The mean, standard deviation, skewness, kurtosis, coefficient of variation (CV), and Standardized Anomaly Index (SAI) are all used in the preliminary and variability analysis. To understand the rainfall distribution characteristics, Kurtosis and skewness were used. To identify homogenous and serially independent series, homogeneity and serial correlation tests were used. Mann-Kendall (MK) and Spearman's rank correlation (SRC) tests were performed to identify the trend in the homogenous and serially independent series. Sen's slope (SS) technique is applied to quantify the amount of the trend, and the Sequential Mann-Kendall (SQMK) test was used to assess the trend change point. The statistical tests indicated in this work were performed using open-source R packages such as "trend," "modifiedmk" and "trendchange". The study area's average rainfall was 801.86 mm, and CV ranges from 43.3% to 22.27%. The basin receives the highest rainfall in southwest monsoon season (SWM) followed by post-monsoon, summer, and winter seasons, respectively.Out of 162 series, 11-time series were found to be non-homogeneous and were omitted. Then out of 151 homogeneous series, 21 series showed a significant increasing trend while 99 and 31 series showed a little rising and declining trend, respectively. The study's results will help in water resource management, agricultural planning and socioeconomic development in the area.

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Spatio-temporal rainfall trend assessment over a semi-arid region of Karnataka state, using non-parametric techniques

Cited by 6 publications

References 35 publications

Analysis of Drought Severity and Vegetation Condition Prediction Using Satellite Remote Sensing Indices in Kolar and Chikkaballapura Districts, Karnataka State

Analysis of Drought Severity and Vegetation Condition Prediction Using Satellite Remote Sensing Indices in Kolar and Chikkaballapura Districts, Karnataka State

Detection of spatiotemporal patterns of rainfall trends, using non-parametric statistical techniques, in Karnataka state, India

Spatiotemporal Rainfall Variability and Trend Analysis of Shimsha River Basin, India

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