https://journal.ipb.ac.id/index.php/agromet <p><strong>Agromet</strong> is published twice a year by the Indonesian Association of Agricultural Meteorology (PERHIMPI) in collaboration with Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, IPB University. Agromet publishes original research articles or reviews that have not been published elsewhere. The scope of publication related to weather and climate issues (agriculture, forestry, water resources, environment, ecology, and health as affected by weather and climate variability and change).&nbsp;</p> en-US agromet@apps.ipb.ac.id (Muh Taufik) adistiprefta@apps.ipb.ac.id (Adisti Prefta) Tue, 29 Apr 2025 20:17:40 +0700 OJS 3.1.2.4 http://blogs.law.harvard.edu/tech/rss 60 https://journal.ipb.ac.id/index.php/agromet/article/view/53333 <p>Evapotranspiration is defined as the loss of water from soil and vegetation to the atmosphere, driven by weather conditions. It reduces the availability of water for agricultural purposes, which affects the amount of irrigation water, particularly during the dry season. The objective of this paper is to present a comparative analysis of the estimated reference evapotranspiration value based on artificial neural networks (ANN) with backpropagation bias 1 (BP-1) and backpropagation bias 0 (BP-0) architectures. The model was fed with data of air temperature, relative humidity, and solar radiation. The model is utilized to calculate the evapotranspiration using the Hargreaves method as the training data. The performance of ANN model was evaluated using the mean square error (MSE), root mean square error (RMSE), and coefficient determination (R²). Our results showed that both ANN models performed well as indicated by low error (MSE &lt; 0.01) and high R² (&gt;0.99). Also, we found that air temperature and relative humidity determine the optimal prediction. Further, this proposed model can serve as a reference for other models seeking to determine the most appropriate computational model for evapotranspiration value estimation.</p> Abdul Haris, Marimin, Sri Wahjuni, Budi Indra Setiawan Copyright (c) 2025 Abdul Haris, Marimin, Sri Wahjuni, Budi Indra Setiawan https://creativecommons.org/licenses/by-nc/4.0 https://journal.ipb.ac.id/index.php/agromet/article/view/53333 Tue, 29 Apr 2025 20:22:50 +0700 https://journal.ipb.ac.id/index.php/agromet/article/view/62281 <p>Agriculture is one of the most vulnerable sectors to climate change, which can significantly impact national food security. In addition to climate change, agricultural development faces challenges, including the conversion of agricultural land for non-agricultural purposes. As a result, agricultural extensification has expanded into marginal lands, such as tidal swamplands. This paper presents a literature review on the characteristics of tidal swamplands, the principles of the surjan system, and its relevance in addressing climate change, particularly in the context of food security and ecosystem sustainability. Various literature sources were analyzed to assess the advantages, challenges, and sustainable management strategies of tidal swamplands. The review highlights the importance of effective land management to create suitable soil conditions for optimal plant growth and increased productivity. The surjan system, a land management approach practiced by tidal swampland farmers, demonstrates high adaptability in mitigating the impacts of climate change. This system integrates cultural, ecological, and economic perspectives by combining local knowledge with technological advancements. Key components of the surjan system include a one-way water management system with flap-gates and stoplogs, as well as the use of climate-adaptive crop varieties on tidal swamplands.</p> Ani Susilawati, Lutfi Izhar, Achmad Adi Surya Sustama Copyright (c) 2025 Ani Susilawati, Lutfi Izhar, Achmad Adi Surya Sustama https://creativecommons.org/licenses/by-nc/4.0 https://journal.ipb.ac.id/index.php/agromet/article/view/62281 Mon, 05 May 2025 16:17:31 +0700