Search

Soil moisture content is one of the most important soil indices for agriculture production. With the increasing food requirement and limited irrigation water sources, it is of great significance to accurately and quickly measure the soil moisture content for precision irrigation, especially in deficient agricultural areas, such as North China Plain. To achieve this goal, more attention was paid to the application of unmanned aerial vehicle multispectral reflectance technology. However, it was urgent to enhance the regression models between spectral data and soil realistic moisture content, and there were limited studies about the regression research on deep soil layers. Thus, the farmland of winter wheat–summer maize double cropping at Yongnian District, Hebei, North China, was selected as the study area. A six-band multispectral camera mounted on a low-altitude unmanned aerial vehicle (UAV) was used to obtain the field spectral reflectance with bands from 470~810 nm, and meanwhile, soil moisture content at different depths (10, 20, 30, 40, 50, and 60 cm) was measured after maize sowing. Unary linear regression (ULR), multivariate linear regression (MLR), ridge regression (RR), and an artificial neural network (ANN) were employed to establish regression models. The results demonstrated that the sensitive bands of spectral reflectance were 690 nm, 470 nm, and 810 nm. Those models all established significant regression at the depths of 0–20 cm and 40–60 cm, particularly at 10, 50, and 60 cm soil layers. However, for a depth of 20–40 cm, the prediction accuracy was generally lower. Among MLR, RR, and BP models, the MLR exhibited the highest identification accuracy, which was most recommended for the application. The findings of this study provide technical guidance and effective regression for the multispectral reflectance on the farmland of North China Plain, especially for deep soil layer moisture prediction. [ABSTRACT FROM AUTHOR]

• Constructed a groundwater numerical model by Visual MODFLOW and studized the feasibility of mine water recharge to aquifers. • Analyzed the impact of mine water recharge on the water level and inflow of aquifers. • To ensure the safe mining in the future, the dynamic water inflow under different mining levels was predicted. Water inflow poses a critical safety concern in coal mining. The pressing challenge in current mine water inflow research is the need to enhance the prediction of dynamic changes in mine water inflow across different mining stages. In this study, the hydrogeological conditions and aquifer structural characteristics of the Wutongzhuang Coal Mine in Hebei Province, China were analyzed, and the results were combined with pumping test and drilling data. A numerical model of groundwater flow in the study area was established using Visual MODFLOW and the model was calibrated and verified by comparing its results with the measured values to ensure that it realistically reflected the state of groundwater movement in the study area. The results of numerical simulation indicated that: (1) The water level of the Ordovician aquifer varies significantly by season. A large exposed area of Ordovician limestone in the western mountainous region receives a large amount of rainfall infiltration recharge in the summer rainy period that raises the water level of the Ordovician aquifer in the study area. (2) The groundwater system in the study area is in an equilibrium state, with the water inflow approximately equal to the outflow. (3) The recharge of mine drainage water has a slight positive effect on the Ordovician water level and the floor water inflow, with the impact on the water level of the aquifer decreasing as the distance from the recharge well and the import of Ordovician limestone water increase. In cases in which there is mine water recharge, the water level of the Ordovician aquifer is approximately 0.33 to 1.37 m higher than in cases without recharge, resulting in an increase in water inflow of approximately 10.6 m3/d. (4) In cases in which there is recharge of all drainage water, the maximum water inflow into the fifth mining area is 3,491.3 m3/d, which is 12.5 m3/d higher than in the case without recharge. These results provide important technical references for the formulation of mining schemes and water prevention measures in mining areas. [ABSTRACT FROM AUTHOR]

• The ET value of various crops in different soils were determined by SWAP model. • Farmland target ET indicator was separated from the regional target ET. • Soil and water resources were optimally allocated under farmland target ET. • Multi-objective optimal allocation of soil and water resources model was established. • The results showed that the economic benefit and water use efficiency were improved. There is a mismatch between crop water demand, the spatial and temporal distribution of natural rainfall, surface water sources, and arable land resources in the North China Plain. This has been compensated for by massive groundwater exploitation, and as a result, ground water levels have continuously declined and groundwater landing funnels have formed in some areas. Consequently, there is an urgent need for the rational allocation of soil and water resources. In this study, regional soil types and the corresponding crops in Guangping County, Hebei Province, China, alongside the regional annual average total water consumption were used to determine reasonable allocations for crop planting structures, with an aim of maximizing the water utilization efficiency and economic benefits while also achieving a regional groundwater dynamic equilibrium. Daily meteorological data from 1973 to 2021, including precipitation, temperature, sunshine hours, wind speed, and humidity, as well as crop data, including irrigation systems and crop growth status, were collected. Water consumption models for eight soil types and seven typical crops forming 56 calculation partitions were established to obtain annual average water consumption values for the different crops. The maximum economic benefit and water-use efficiency were then used as the objective functions and total water consumption as the control condition for the non-dominated sorted genetic algorithm-Ⅱ (NSGA-II), to optimize the allocation of soil and water resources in the region; the adjusted quantities for the different crops cultivated under different soil types in the study area were obtained. The areas growing sweet potato and vegetable-fruits were found to increase by 0.5255 km2 and 4.4452 km2, respectively, when compared to the pre-optimization period, whereas the areas with winter wheat-summer maize, millet, peanut, cotton, and summer maize decreased by 1.3481 km2, 0.1812 km2, 0.7316 km2, 2.0896 km2, and 0.62 km2, respectively. The economic benefit increased from 810.37 to 853.64 million yuan, while the water-use efficiency increased from 1.5426 kg/m3 to 1.5859 kg/m3. The results provide a basis for soil and water resource management in the region and a technical reference for similar areas to improve agricultural water-use efficiency and economic benefits. [ABSTRACT FROM AUTHOR]