A Spatial Interpolation Using Clustering Adaptive Inverse Distance Weighting Algorithm with Linear Regression

Zhu, L.; Hou, Gengchen; Song, Xiaoling; Wei, Yonggang; Wang, Yu

doi:10.1007/978-3-031-10986-7_21

Cited by 3 publications

(1 citation statement)

References 22 publications

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“…Inverse Distance Weight IDW data's performance is a non-geostatistical spatial interpolation and heavily dependent on the season (Chae et al, 2022;Adelodun et al, 2023). IDW is a well-liked interpolation technique because of its low complexity (Zhu et al, 2022). According to the literatures, the effectiveness of different spatial interpolation techniques, such as IDW, in estimating climate data demonstrates that the interpolated error values' low-level error by IDW is not significantly different from that of the other approaches (Meng et al, 2019;Tan et al, 2021;Liu et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Climatic and anthropogenic impacts on the water balance of Issyk-Kul Lake through its main catchments

Uwamahoro,

Liu,

Nzabarinda

et al. 2024

Front. Water

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Lake Issyk-Kul is an endorheic lake in arid Central Asia that is vital to the region's ecological sustainability and socio-economic development. Climate change and anthropogenic water consumption led to fluctuations in the lake's water level, which affected the water resource. The goal of this study was to examine the impacts of climate change and human activities on the Issyk-Kul water balance by combining the Coupled Model Intercomparison Project Phase 6 (CMIP6) scenarios with hydrological modeling. The Soil and Water Assessment Tool (SWAT) model was used to incorporate signals of future precipitation and temperature changes. According to the scenarios, the total discharge of the three catchments showed an overall increasing trend with a maximum value of 28.02%. The snow and ice-melt water from March to August was revealed, and the increasing trends only occurred from March to May, with the snow and ice melting peak variations ranging from 0.5% to 2%. The high increase in change appeared in northern catchment of the lake. There was an exceptional upward precipitation trend over the northern catchment, with annual increases ranging from 0.7 to 14.5%, and an average annual temperature of 1.72°C. With slight similarities, the total runoff would increase for all catchments, with an average annual value of 10.6%. The northern catchment was significantly more sensitive to precipitation and warming than the southeastern catchments. Under land use land cover change, average annual discharge decreased with agricultural expansion, with discharge differences ranging from −0.005 to −1.06 m3/s. The findings are useful for decision-makers addressing the challenges of climate change mitigation and local water resource management.

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