# Climate-Smart Agro-Hydroological Model for a Large Scale Rice Irrigation Scheme in Malaysia
## 1 Introduction  
Water crises are a global issue of significant concern. Water is becoming a scarce resource, not only for agriculture, but also for most sectors in most locations across the globe. This is due to efforts to meet industrial and urbanization demands. Climate change is reported to be the main driver of hydrological variations in catchments [1]. The competition for water has increased in recent years to a stage of physical scarcity [2]. In some areas, the streamflow, which is largely the source of water for irrigation, has decreased in recent decades, and projected water declines threaten the sustainability of downstream areas [3]. Future streamflows are also projected to decrease with the impact of climate change [4; 5; 6; 7]. Failure of climate change mitigation and adaptation is among the biggest global risks. Agricultural production will be a significant challenge due to population growth and climate change [8]. Agricultural production is one of the most vulnerable sectors to climate change [9]. Soil water balances, evapotranspiration, physiology, and phenology have been altered due to climatechange, which has consequently affected irrigation water requirements. These effects are more severe for a rice crop that consumes high water [10]. The creative, strategic, and economic advancement of food security development in the context of climate change to achieve sustainable agriculture can reduce such threats [9]. Agriculture, therefore, must be 'climate-smart', and agricultural systems must be transformed and reoriented to promote food production under these new climate change realities. Improvements in the effectiveness of agricultural water use could result in sufficient water for domestic use in high-competition watersheds. This potentially represents a significant adaptation approach for global change [11]. The information linked to agro-hydrological procedures is helpful for improving watershed hydrological modeling and agricultural production [12]. Agro-hydrological water management frameworks help to integrate expected planned management and expedite regulation of water allocation for agricultural production. Low production is not only due to the variability of available water during the crop growing seasons, but also due to poor water management decisions, such as not considering the available water for irrigation [13]. A climate-smart agro-hydrological model can be a robust solution for wise water management decisions in a large-scale irrigation scheme to cope with the risk of water and food security under the new realities of climate change. Several approaches have been adopted for the integration and analysis of large input data to improve decision making in agriculture. For instance, a context-aware systems (CAS) was developed to automate a manual irrigation method by integrating two engineering methodologies: ontology and information systems [14]. A climate-smart decision support system (CSDSS) was developed for analyzing the water demand of a large-scale rice irrigation scheme [15]. An agricultural data analysis approach, which can estimate the weight of onions during the growth stages, was introduced using a functional regression model [16]. A seasonal furrow irrigation model was developed using different data sets to estimate and analyze information of every event of furrow irrigation for maize crop production [17]. A process-based regional economic optimization (PBREOP) tool was developed to optimize the irrigation water use efficiency and economic benefit of an irrigation area, which reduced the total amount of irrigation water used by an average of 23% without a reduction in benefits [18]. The PBREOP model is a two-level optimization model with combined use of an agro-hydrological model (SWAP-EPIC). An agro-hydrological model, Soil-Water-Atmosphere-Plant (SWAP) was applied to assess the effects of management of irrigation water on water and salt balances [19].