Ecological Engineering & Environmental Technology (Oct 2024)

Relationships Among Global Climate Indices, Rainfall Patterns, and Crop Productivity in the Southern Part of Java, Indonesia

  • Bayu Dwi Apri Nugroho,
  • Chusnul Arif,
  • Fadila Suryandika,
  • Hertiyana Nur Annisa,
  • Syintianuri Intan Wijayanti

DOI
https://doi.org/10.12912/27197050/191332
Journal volume & issue
Vol. 25, no. 10
pp. 87 – 95

Abstract

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In tropical countries, especially Indonesia, even though there is a notable correlation between rainfall pattern and indices of global climate, limited proof exists regarding the impact on crop productivity. Global climate indices are one of the indicators to identify the occurrence of climate change, but there is little research on climate change in Indonesia. In this research, relationships among indices of global climate, are represented by The Southern Oscillation Index (SOI) and The Sea Surface Temperature (SST) such as Nino.West, The Indian Ocean Basin-Wide (IOBW), and Nino3, then the pattern of rainfall distribution and crop productivity during 10 years from 2012 to 2022 in The Southern Part of Java. The Southern Part of Java which is represented by Gunung Kidul District is a rain-fed area, and its location is in hilly topography so rainfall will be an important factor in this area, not only for daily life but also for agricultural sector purposes. The purpose of the study is to discover the relationship between global climate indices, rainfall distribution pattern and crop productivity in the Southern Part of Java, Indonesia. Rainfall distribution pattern for 10 years was calculated and displayed with spatial method, then Principal Component Analysis (PCA) was used to analyse SST, and correlation analyses were used along with wet and dry seasons and crop productivity. The results showed that from 2012 to 2022, high rainfall and correlation with global climate indices occurred in the southern and western part of Gunung Kidul district, and correlation among rainfall patterns and crop productivity showed significant correlations in some sub-districts. This result also showed that relationships among global climate indices and rainfall distribution pattern can be influenced the agricultural productivity in the rainfed areas.

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