Projecting the Effects of Climate Change on Water irrigation needs for Maize Production Systems Using the LARS-WG and Hargreaves Method

¹ Department of Agricultural Engineering, Faculty of Agricultural Technology, University of Jember, Tegal Boto Campus, Jl. Kalimantan No. 37, Jember 68121, Indonesia
² Department of Agricultural Engineering, Faculty of Agricultural Technology, University of Jember, Tegal Boto Campus, Jl. Kalimantan No. 37, Jember 68121, Indonesia
³ Faculty of Engineering, Chiang Mai University, 239 Huay Kaew Road, Mueang District, Chiang Mai 50200, Thailand
⁴ Faculty of Resource Science and Technology, Universiti Malaysia Sarawak, Level 2, Chancellery Building, 94300 Kota Samarahan, Sarawak, Malaysia
⁵ Department of Agricultural Engineering, Faculty of Agricultural Technology, University of Jember, Tegal Boto Campus, Jl. Kalimantan No. 37, Jember 68121, Indonesia

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

The production of food crops is severely hampered by climate change, which is characterized by rising temperatures and changes in precipitation. This is especially true for maize, a cornerstone of Indonesia's food security. This study aims to forecast future climatic conditions over the next two decades and estimate the resulting irrigation water demands for maize cultivation in East Java, West Sumatra, and North Maluku. Future climate scenarios were generated using the LARS-WG model, which incorporated the HadGEM3-GC31-LL General Circulation Model and three CMIP6 pathways (SSP126, SSP245, and SSP585). The Hargreaves method was then applied to calculate reference evapotranspiration and, subsequently, crop irrigation requirements. To validate the model's reliability, historical climate data (2004–2023) was analyzed using the Kolmogorov-Smirnov, t-test, and f-test at an α = 0.05 significance level. Model calibration and evaluation were conducted using the R², MSE, and RMSE metrics. The results show that LARS-WG effectively simulated local climate variables, and the evapotranspiration estimates were consistent with regional characteristics. The analysis revealed that while temperature has a positive correlation with irrigation demand, effective precipitation has a negative one. Furthermore, mean temperature and effective precipitation showed no significant direct effect on maize yields, whereas extreme temperatures had a minor impact. These findings suggest that future climate scenarios could increase irrigation needs, highlighting the necessity for adaptive management of water resources strategies.