The new technologies of surface irrigation require the adoption of effective Laser-controlled precision land levelling (PLL) to reach the high irrigation performance standards, with significant benefits on water saving, salinity control, crop productivity, and farmer’s income. This study aimed to assess the performance and the impacts of PLL on surface irrigation systems, focusing the maize crop on the irrigation districts Hetao (China) and Lower-Mondego (Portugal). The experimental study at field scale assessed the PLL and evaluated the on-farm irrigation under precise levelled fields and well management practices. PLL operators have been inquired to improve the knowledge about hiring services. The design of surface irrigation scenarios allowed to explain the effects of field size and slope on irrigation and land levelling performance. The best practice to manage the PLL maintenance is an important issue to guarantee a high effectiveness of irrigation performance. The optimization of PLL appeals the application of best soil tillage practices and the monitoring of soil surface elevations with newest information technologies. Efficient operational guidelines to support the PLL planning, schedule, and operation, well trained operators and carefully adjusted equipment, are key factors to the improvement.

Controlled drainage (CD) is an important agricultural measure for maintaining soil moisture and nutrients, controlling groundwater level, and increasing crop yield. In arid regions, CD can be used to improve the water supply in agriculture and reduce environmental pollution. In this study, we investigated the effects of CD, including drainage depths of 40 cm (CWT1) and 70 cm (CWT2) during the plant growth stages, free drainage (FD), and open-ditch drainage (OD), on the migration of water, nutrients, and salts in the soil, the dynamics of the groundwater level, the loss of soil nitrogen, and the growth of oilseed sunflower plants. Compared with FD, CD increased the water and nutrient content in the soil, reduced nitrogen loss, and enhanced the ability of the soil to continuously supply nitrogen to the oilseed sunflower plants, which benefited plant growth at later growth stages and reduced environmental pollution. During the period between irrigation at the budding stage and the harvest stage, the average soil water content in the 0–20 cm soil layer in CWT1 increased by 3.67%, 4.78%, and 0.55%, respectively, compared with that in CWT2, FD, and OD. The soil mineral content in CWT1 was 25.17%, 35.05%, and 17.78% higher than that in CWT2, FD, and OD, respectively, indicating that higher soil salinity occurred at the later stage of plant growth in CWT1, which actually had little effect on the plants due to their enhanced salt tolerance and increased need for water and nutrients at that stage. In addition, CD delayed the decline in groundwater level, which allowed the plants to use groundwater at later growth stages, and as a result, the yield and water-use efficiency were improved. CWT1 significantly increased oilseed sunflower yield by 4.52–11.14% and increased water-use efficiency by 1.16–10.8%. Moreover, CWT1 also increased the survival rate of the oilseed sunflower plants by 2.62–2.92%, and the plants demonstrated good growth. Therefore, under CD conditions, plants used soil water and nitrogen more efficiently and, as a result, their productivity was increased, and the water quality was improved.

Terrestrial ecosystems depend heavily on their vegetation; it is possible to forecast future growth trends of regional vegetation by keeping an eye on changes in vegetation dynamics. To circumvent the potential reduction in prediction accuracy caused by the non-stationarity of meteorological changes, we analyzed the characteristics of NDVI (Normalized Difference Vegetation Index) spatial and temporal changes and the influencing factors over the past 20 years in the Maowusu Sandland of China via attribution analysis. We also constructed a comprehensive analysis system for vegetation pre-restoration. Moreover, we combined meteorological data from 2000 to 2018 and presented a deep-learning NDVI-Informer prediction model with a self-attentive mechanism. We also used distillation operation and fusion convolutional neural network for NDVI prediction. Incorporating a probsparse self-attention method successfully overcomes Transformer weaknesses by lowering the memory use and complexity of large time series. It significantly accelerates the inference speed of long time series prediction and works well with non-smooth data. The primary findings were: (1) the Maowusu Sandland’s 20-year average showed a consistent increasing trend in the NDVI at 0.0034 a⁻¹, which was mostly caused by climate change, with a relative contribution rate of 55.47%; (2) The Informer-based model accurately forecasted the NDVI in the research region based on meteorological elements and conducted a thorough analysis of the MAPE (mean absolute percentage error) (2.24%). This suggests that it can effectively lower the data’s volatility and increase prediction accuracy. The anticipated outcomes indicate that the trend will stabilize during the following ten years. To attain more sustainable and efficient agricultural production, the results of this study may be used to accurately estimate future crop yields and NDVI using previous data.

The agro-pastoral ecotone in northern China is the main production area of agriculture and animal husbandry, in which agricultural development relies entirely on groundwater. Due to the increasing water consumption of groundwater year by year, groundwater resources are becoming increasingly scarce. The substantial water demand and low germination rate in the first year are the main characteristics of alfalfa (Medicago sativa L.) yield in the agro-pastoral ecotone in northern China. Due to unscientific irrigation, water resources are seriously wasted, which restricts the development of local agriculture and animal husbandry. The study constructed the Dssat-Forages-Alfalfa model and used soil water content, leaf area index, and yield data collected with in situ observation experiments in 2022 and 2023 to calibrate and validate the parameters. The study found ARE < 10%, E_NRMS < 15%, and R² ≥ 0.85. The model simulation accuracy was acceptable. The study revealed that the water consumption at the surface soil layer (0–20 cm) was more than 6~12% and 13~31% than that at the 20–40 cm and 40–60 cm soil layers, respectively. The study showed when the irrigation quota was 30 mm, the annual yield of alfalfa (Medicago sativa L.) (7435 kg/ha) was consistent with that of the irrigation quota of 33 mm, and increased by 3.99% to 5.34% and 6.86% to 10.67% compared with that of irrigation quotas of 27 mm and 24 mm, respectively. To ensure the germination rate of alfalfa (Medicago sativa L.), it is recommended to control the initial soil water content at 0.8 θ_fc~1.0 θ_fc, with an irrigation quota of 30 mm, which was the best scheme for water-use efficiency and economic yield. The study aimed to provide technological support for the rational utilization of groundwater and the scientific improvement of alfalfa yield in the agro-pastoral ecotone in northern China.

As an effective method to improve saline–alkali land, the drainage from subsurface pipes has been extensively studied in typical arid and semi-arid agricultural areas (Hetao Irrigation District). However, there are few studies on the improvement of subsurface pipe layout and the long-term soil salinization control in the process of leaching and soil amendment with subsurface pipes in this area. This study investigated the water and salt migration in the process of amending the heavy saline soil. Field experiments growing sunflowers and numerical model calculation were combined in this research. It was found in the field experiment that the salt concentration in the surface pipe drainage was positively correlated with the salt content in the soil and the depth of the pipe, while it was negatively correlated with the amount of irrigation water and the spacing of crops. Thus, the soil desalting rate (N) and salt control rate (SCR) were positively correlated with the depth of the pipe, and they were negatively correlated with the spacing. The leaching effect of irrigation would decrease when the soil salt content decreased. On the basis of field experiments, the DRAINMOD model and drainmod equation were used to calculate the water and salt migration in 38 different field plots during 2019 and 2020. When N was the same, the soil salinity in several plots with large burial depth could be controlled below the salt tolerance threshold of sunflowers during the growth period in the second year. The quantitative relationship between N and SCR, soil salt content before leaching, water amount of leaching, pipe spacing and buried depth was already established. These results can help develop strategies for desalination and salt control in the soil in the arid and semi-arid areas with the optimal layout of subsurface pipes.

The subsurface pipe drainage project is essential in farmland drainage operations and is globally recognized as an effective saline–alkali land improvement measure owing to its efficient drainage capacity and low land occupation rate. This study aimed to establish enhanced methods for improving saline–alkali land by combining ditching with subsurface pipe drainage. The ditching was conducted at a depth of 60 cm based on the existing subsurface pipe arrangement. The calibrated DRAINMOD-S model was employed to simulate the test area with different ditching depths and subsurface pipe arrangement parameters. Furthermore, the law of soil water and salt transport in the subsurface pipe drainage system at different ditching depths was investigated. After ditching, the total unit drainage volume of leaching increased by an average of 14.65% over two years and the water storage of different soil layers in the different plots decreased by 1.37–1.48 mm on average. Ditching demonstrated a superior salt-leaching effect in areas with subsurface pipe layouts. The soil desalination rate of different soil layers increased by 6.40–13.40% on average, with a more significant impact on the surface soil desalination rate. The effect of the increased desalination rate was more apparent as the ditching depth increased. However, as the buried depth of the subsurface pipe increased, the relationship between the ditching depth and soil desalination rate became insignificant. Ditching improved the salt-leaching effect of subsurface pipe drainage projects, which can effectively reduce the cost of subsurface pipe burial, consequently promoting subsurface pipe use.