Investigation of Irrigation Water Requirements for Major Crops Using CROPWAT Model Based on Climate Data

Yatsiuk

et al. 2023

Preprint

When droughts occur and temperatures rise, water demand increases when growing crops. For these conditions, system management of irrigation is proposed as a system approach, which ensures the efficient use of water resources and their savings. A method for estimating the increase in water resources under climate change is proposed. The method is based on a comparison of water balance deficits, ranked by estimated moisture supply of the year, at two time intervals: in recent 30 years and in past decades before (1960–1990 and 1991–2021). System management of irrigation combines instrumental and calculative methods. Instrumental methods using an automated tensiometer and Watermark provide feedback on the daily soil moisture status in the field. According to the calculative methods, irrigation forecasting is carried out using Internet weather services and optimal control is carried out on a sliding interval. An algorithm of the instrumental-calculative method is proposed within system irrigation management. When the algorithm is combined with biologically optimal irrigation regimes, the effective use of available water is achieved. When using the parameters of water-saving irrigation regimes, water resources are saved up to 30%, which is important in a changing climate.

Section: Discussion Of Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

System management of irrigation under climate change conditions for determining the crop water demand and solutions for the water-saving

Yatsiuk

et al. 2023

Preprint

J. Degrade. Min. Land Manage.

“…Data for water potential and availability variables on the island were analyzed using the Thornthwaite and Mather regional water balance method (Steenhuis et al, 1986). Plant water requirements were measured using the Penman-Monteith evapotranspiration (ET) approach (Allen et al, 1998;Khan et al, 2021), and the amount of water given to plants was determined using the CROPWAT-8 software (Ihuoma and Madramootoo, 2017;Thazin, 2019;Solangi et al, 2022). Daily water consumption was analyzed based on SNI 19-6728.1-2002 standard using the following Equation 2.…”

Section: Sto = (Fc-wp) X Dz ………… (1)mentioning

confidence: 99%

Analysis of the availability and water requirements of dryland farming and the water needs of residents in Hiri Island, Ternate City, North Maluku

Hadun,

Umasugi,

Sudjud

et al. 2024

Dryland farming is one of the main agricultural models farmers use on the islands of North Maluku, so it is very dependent on the availability of rainwater. The water for crops is available in the rainy season, and drought is experienced in the dry season, one of which occurs on Hiri Island. This study aimed to analyze the availability and water needs of plants based on land characteristics and use to provide information for the development of dryland farming on Hiri Island. The method for calculating water availability used the land water balance approach using rainfall data for the last ten years, while the analysis of plant water needs was based on the soil moisture content and plant coefficient approach. The results of the analysis of water availability based on the land water balance of 2,236.4 mm with an average monthly rainfall of 186.4 mm and according to the type of land use on Hiri Island show that the highest available water in agroforestry was 40.92% in the secondary forest was 39.04%, in coconut, plantations was 35.72%, in fields was 35.18%, and undergrowth was 34.67%. Plant cultivation businesses must meet the water needs of plants to increase production. The people on Hiri Island need 29,340 L of water to fulfill their daily needs.

“…Obtain more accurate agricultural water data at a finer temporal resolution (e.g., second, minute, hour) Time-consuming, labor-intensive, and expensive to conduct large-area experiments [29,30] Non-spatial crop model Simulate agricultural water use for different crops at different growth periods at the point scale Difficult to reveal fine-resolution spatial characteristics [31,32] Spatial crop model…”

Section: Field Observationmentioning

confidence: 99%

Impacts of Crop Type and Climate Changes on Agricultural Water Dynamics in Northeast China from 2000 to 2020

Xiao,

Zhang,

Liu

2024

Remote Sensing

Northeast China (NEC) is one of the most important national agricultural production bases, and its agricultural water dynamics are essential for food security and sustainable agricultural development. However, the dynamics of long-term annual crop-specific agricultural water and its crop type and climate impacts remain largely unknown, compromising water-saving practices and water-efficiency agricultural management in this vital area. Thus, this study used multi-source data of the crop type, climate factors, and the digital elevation model (DEM), and multiple digital agriculture technologies of remote sensing (RS), the geographic information system (GIS), the Soil Conservation Service of the United States Department of Agriculture (USDA-SCS) model, the Food and Agriculture Organization of the United Nations Penman–Monteith (FAO P-M) model, and the water supply–demand index (M) to map the annual spatiotemporal distribution of effective precipitation (Pe), crop water requirement (ETc), irrigation water requirement (IWR), and the supply–demand situation in the NEC from 2000 to 2020. The study further analyzed the impacts of the crop type and climate changes on agricultural water dynamics and revealed the reasons and policy implications for their spatiotemporal heterogeneity. The results indicated that the annual average Pe, ETc, IWR, and M increased by 1.56%/a, 0.74%/a, 0.42%/a, and 0.83%/a in the NEC, respectively. Crop-specifically, the annual average Pe increased by 1.15%/a, 2.04%/a, and 2.09%/a, ETc decreased by 0.46%/a, 0.79%/a, and 0.89%/a, IWR decreased by 1.03%/a, 1.32%/a, and 3.42%/a, and M increased by 1.48%/a, 2.67%/a, and 2.87%/a for maize, rice, and soybean, respectively. Although the ETc and IWR for all crops decreased, regional averages still increased due to the expansion of water-intensive maize and rice. The crop type and climate changes jointly influenced agricultural water dynamics. Crop type transfer contributed 39.28% and 41.25% of the total IWR increase, and the remaining 60.72% and 58.75% were caused by cropland expansion in the NEC from 2000 to 2010 and 2010 to 2020, respectively. ETc and IWR increased with increasing temperature and solar radiation, and increasing precipitation led to decreasing IWR in the NEC. The adjustment of crop planting structure and the implementation of water-saving practices need to comprehensively consider the spatiotemporally heterogeneous impacts of crop and climate changes on agricultural water dynamics. The findings of this study can aid RS-GIS-based agricultural water simulations and applications and support the scientific basis for agricultural water management and sustainable agricultural development.