Investigating Spatiotemporal Variation of Evapotranspiration Trends using Non Parametric Statistical Techniques across North Eastern Dry Zone of Karnataka, India

Adarsha, Manoj Kumar G, Gowtham, Sagara R, Devappa
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Abstract

This paper examines the temporal variation of ETo over the 10 main subdistricts of the North Eastern Dry Zone of Karnataka, India, during the period 1982-2022 using non-parametric statistical analysis. The findings show that ETo variability also exhibits diverse spatial and temporal characteristics in the study area. February month shows the highest decrease in the values (ZMK -2.33 to -1.72, p<0.05). Winter and summer shows highly significant decreasing trends, Manvi showing the maximum decreasing trend in winter (ZMK = -2.57, p < 0.01) and Raichur in summer (ZMK = -2.89, p < 0.01). Sen’s slope estimates show average decrease of -0.18 to -0.15 mm/month in winter and an average value of -0.246 mm/month in summer. For monsoon and post monsoon, the trends are weaker and not significant ranging from -0.05 to 0.03 mm/month. Yearly changes reveal slightly negative values (-0.12 to -0.04 mm/month). Spatial interpolation of the ETo changes is done using ArcGIS’s inverse distance weighting (IDW) method to show the regional differences. An increase in air temperature results in the rise in the trends in some months while, a decline in wind speed may be reason in other region. These findings are useful in understanding the ETo dynamics in the region and its relation to water and agriculture. More studies are required to understand why there was a reduction in wind speed as well as to develop individual water management strategies that will adapt to these changes.
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利用非参数统计技术调查印度卡纳塔克邦东北干旱区蒸散趋势的时空变化
本文采用非参数统计分析方法,研究了 1982-2022 年期间印度卡纳塔克邦东北干旱区 10 个主要分区的蒸散发系数的时间变化。研究结果表明,研究区域的蒸散发变化也呈现出不同的时空特征。二月份的数值降幅最大(ZMK -2.33 至 -1.72, p<0.05)。冬季和夏季呈现非常明显的下降趋势,Manvi 的冬季下降趋势最大(ZMK = -2.57,p < 0.01),Raichur 的夏季下降趋势最大(ZMK = -2.89,p < 0.01)。森氏斜率估计值显示,冬季平均每月减少-0.18 至-0.15 毫米,夏季平均每月减少-0.246 毫米。季风期和后季风期的趋势较弱且不显著,为-0.05 至 0.03 毫米/月。年度变化显示出轻微的负值(-0.12 至-0.04 毫米/月)。利用 ArcGIS 的反距离加权(IDW)方法对 ETo 变化进行了空间插值,以显示区域差异。气温上升导致某些月份的趋势上升,而风速下降可能是其他地区的原因。这些发现有助于了解该地区的蒸散发动态及其与水和农业的关系。需要开展更多的研究,以了解风速下降的原因,并制定适应这些变化的水管理策略。
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