Research Frontiers: Research & Advances in Agricultural Water Management

Multiscale Water Cycle Mechanisms and Return Flow Utilization in Paddy Fields of Plain Irrigation Districts

Jie Zhang — 2026-08-25

This study aimed to reveal the characteristics of returned water in paddy fields at different scales and the rules of its reuse in China’s Ganfu Plain Irrigation District through multiscale (field, lateral canal, main canal, small watershed) observations, thereby optimizing water resource management and improving water use efficiency. Subsequent investigations during the 2021–2022 double-cropping rice seasons revealed that the tillering stage emerged as a critical drainage period, with 49.5% and 52.2% of total drainage occurring during this phase in early and late rice, respectively. Multiscale drainage heterogeneity displayed distinct patterns, with early rice following a “decrease-increase” trend while late rice exhibited “decrease-peak-decline” dynamics. Smaller scales (field and lateral canal) produced 37.1% higher drainage than larger scales (main canal and small watershed) during the reviving stage. In contrast, post-jointing-booting stages showed 103.6% higher drainage at larger scales. Return flow utilization peaked at the field-lateral canal scales, while dynamic regulation of Fangxi Lake’s storage capacity achieved 60% reuse efficiency at the watershed scale. We propose an integrated optimization strategy combining tillering-stage irrigation/drainage control, multiscale hydraulic interception (control gates and pond weirs), and dynamic watershed storage scheduling. This framework provides theoretical and practical insights for enhancing water use efficiency and mitigating non-point source pollution in plain irrigation districts.

Informer–UNet: A Hybrid Deep Learning Framework for Multi-Point Soil Moisture Prediction and Precision Irrigation in Winter Wheat

Dingkun Zheng — 2026-08-17

Soil moisture prediction is essential for precision irrigation in water-limited agricultural systems. This study presents a deep learning-driven irrigation framework for winter wheat, integrating a novel Informer–UNet model with a Comprehensive Irrigation Index for adaptive water management. The Informer–UNet combines ProbSparse self-attention mechanisms with UNet’s multi-scale feature fusion, enabling simultaneous prediction of soil moisture at 27 monitoring points across three depths, 10, 30, and 50 cm, while quantifying prediction uncertainty through Monte Carlo Dropout. A Comprehensive Irrigation Index incorporating moisture deviation, spatial variance, and confidence interval width was developed, with weights optimized via genetic algorithm. Field experiments were conducted in Chengdu, China, over two winter wheat growing seasons. The Informer–UNet achieved superior prediction accuracy, R² greater than 0.98, RMSE less than 0.65, compared to LSTM, Transformer, and standard Informer models, with the fastest convergence and lowest validation loss. The proposed DeepIndexIrr strategy maintained soil moisture within the target range, 55% to 75%, for over 81% of the irrigation period, reducing water consumption by 38.2% compared to fixed-threshold control and 19.2% compared to expert manual scheduling. These results demonstrate that integrating spatially distributed deep learning predictions with uncertainty-informed decision rules offers a promising approach for sustainable precision irrigation.

The Effects of CO2-EnrichedWater Irrigation on Agricultural Crop Growth

Laura Feodorov — 2026-08-25

CO₂, a major industrial (waste)water treatment process byproduct, significantly contributes to climate change, desertification and overall water depletion. Therefore, there is a significant interest in decreasing CO₂ amounts, generated by various technological processes, through a wide range of methods from geological sequestration to biological sequestration. The CO₂ (waste)water treatment byproduct sequestration into agricultural CO₂-enhanced irrigation water offers several benefits by enhancing crop yield and repurposing emissions. This sustainable approach supports climate neutrality via biological sequestration, promotes circular economy principles, and strengthens the link between agriculture and climate change. In this study, the effect of CO₂-enriched water irrigation was analyzed in a complex network of plants germination, soil bacterial populations’ dynamics and soil composition. Results showed that germination rates of plants irrigated with CO₂-enriched water were species specific. Sage plants increased their germination and growth when irrigated with CO₂-enriched water compared with plants irrigated with plain water. Moreover, CO₂ addition favored the development of soil anaerobic bacteria in detriment of aerobic bacteria and subsequently changing organic and nitrogenous compounds soil composition compared to plain water irrigation. For the first time, the germination process influenced by CO₂ was correlated with on overall possible CO₂ effects on bacterial population growth dynamics and soil quality metabolites availability.

Maintaining Yield While Enhancing Fruit Quality and Economic Returns Through Deficit Irrigation and Potassium Optimization in Jujube (Ziziphus jujuba Mill.)

Pengrui Ai — 2026-08-25

Under conditions of limited irrigation and excessive fertilizer application in the arid regions of Xinjiang, it is essential to adopt well-coordinated strategies to improve yield and crop water productivity (WP). In this study, a comparative experiment was conducted with three irrigation levels, T1 (100% crop evapotranspiration, ET_c), T2 (75% ET_c), and T3 (50% ET_c), combined with three potassium application rates, K1 (540 kg ha⁻¹), K2 (360 kg ha⁻¹), and K3 (180 kg ha⁻¹). The objective was to investigate their effects on the yield, quality, and economic benefits of jujube trees. Limited irrigation amounts significantly affected the photosynthetic characteristics, growth parameters, and ET_c of jujube trees, whereas potassium fertilizer levels primarily regulated fruit development and yield formation. Compared with full irrigation, mild deficit irrigation caused a moderate yield reduction but significantly enhanced economic returns due to the improved water productivity and fruit quality. In contrast, severe water deficit led to substantial decreases in growth parameters and economic benefits by 12.87–45.70% and 81.69%, respectively. Potassium application demonstrated a significant threshold effect, with the K2 treatment showing greater improvements in fruit quality indices, including reducing sugars, vitamin C, and other key quality parameters, compared to the K3 treatment. Based on hierarchical–grey relational analysis, the combination of 75% ET_c and 300 kg K ha⁻¹ was identified as the optimal water–potassium management strategy. The net profit was 29,199 CNY. The benefit–cost ratio increased to 3.63, and the WP improved by 16.17% compared to full irrigation. Thus, this study provides an important theoretical basis and technical support for water-saving and quality-improving cultivation of jujube trees in arid regions.

Effects of Irrigation Regimes on Khalas Date Palm Yield Under Surface and Enhanced Subsurface Irrigation Systems with Smart Control Application

A. W. Abdelhadi — 2026-05-21

The date palm Phoenix dactylifera L. is an essential desert food crop. A study was conducted for two years to determine Khalas palm variety yield response to different irrigation regimes. Bubbler system (BS) and enhanced subsurface stonewool drip system (ESDS) were tested in the Kingdom of Bahrain during the period of 2021–2023. A split-plot design was used with BS and ESDS as main plots. Irrigation regimes of 20, 30, and 50% (D2–D3) as subplots compared with crop water requirements (D1) based on Penman Monteith FAO method (PMFM). A smart volume-based control system was used in the 2nd year. The results revealed no significant differences in date yield, average weight of bunches, and soft fruits (Rutab) percent between the BS and ESDS systems (p > 0.05). No significant yield differences were obtained between the irrigation regimes at p > 0.05. Water productivity was highly significant (p = 0.0003 and 0.0001) regarding irrigation regimes for the two years, respectively. Compared to 1st year, the 2nd year yield has improved by 78.5 and 53.5% under ESDS and BS systems, respectively. Apart from seasonal palm yield variations, smart application has the most impact on yield improvement. It is concluded that published palm K_C coefficients may overestimate water requirements by about 50%. More water saving can be attained using smart volume-control application under BS or ESDS systems. It is vital to develop local crop coefficients for date palms under desert and humid climatic conditions similar to Bahrain.