Drought and water availability analysis for irrigation and household water needs in the Krueng Jrue sub-watershed

PeerJ

article

Hairul Basri¹  Sufardi Sufardi¹  Helmi Helmi¹  Syakur Syakur¹  Sugianto Sugianto¹  Azmeri Azmeri²  Helmi Helmi³ 

[1] Soil Science Department, Faculty of Agriculture, Universitas Syiah Kuala;Civil Engineering Department, Faculty of Engineering, Universitas Syiah Kuala;Forestry Department, Teungku Chik Pante Kulu, School of Forestry Science

关键词: Z-score statistics;    Mock model;    Water availability;    Water needs;    Agricultural water management;    Watershed management;    Drought analysis;   

DOI  :  10.7717/peerj.14830

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

This study aimed to analyze drought conditions and evaluate irrigation water availability and household water needs in the Krueng Jrue sub-watershed, Aceh Province, Indonesia. The Z-score statistics method was developed to analyze the drought, and the Mock model was used to generate discharges. We performed model validation using linear regression, which produced a coefficient of determination (R2 = 0.90**) and coefficient of regression (r = 0.95**). In general, this area had a normal Z-score for precipitation (ZSP) class with 90 events (75%) and a normal Z-score for a discharge (ZSD) class with 89 events (74.2%). There were 0–11 (0–9.2%) moderate wet, very wet, extreme wet, moderate drought, and severe drought events. The consistency between the ZSP and ZSD indices reached 85.8%, indicating consensus between the meteorological droughts that were analyzed based on rainfall (ZSP) and hydrological droughts analyzed based on water discharge (ZSD). ZSP and ZSD indices showed negative values during the dry season (April to September) and positive values during the rainy season (October to March). There was a surplus of water availability for irrigation and household water needs during the rainy season and a deficit during the dry season. However, water deficits also occurred in certain months during the rainy rendeng planting season, for example, in October 2009, 2013, 2016, and 2017 as well as in February between 2008 to 2011 and from 2014 to 2017. This observation was probably due to the influence of global climate variables that need to be substantiated. This study offers necessary information for farmers, the community, and the local government when anticipating drought phenomenon, organizing the rice planting season, and evaluating water availability in other watersheds.

【 授权许可】

CC BY