Soil moisture content (SMC) plays a critical role in soil science via its influences on agriculture, water resources management, and climate conditions. There is broad interest in finding relationships between groundwater recharge, soil characteristics, and plant properties for the quantification of SMC. The objective of this study was to assess the potential of optical satellite imagery for estimating the SMC over cropland areas. For this purpose, we collected 394 soil samples as targets in Gonbad-e Kavus in the Golestan province in the north of Iran, where a variety of crop types are cultivated. As input data, we first computed several spectral indices from Sentinel 2 (S2) and Landsat 8 (L8) images, such as the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Normalized Difference Salinity Index (NDSI), and then analyzed their relationships with surveyed SMC using four machine learning regression algorithms: random forests (RFs), XGBoost, extra tree decision (EDT), and support vector machine (SVM). Results revealed a high and rather similar correlation between the spectral indices and measured SMC values for both S2 and L8 data. The EDT regression algorithm yielded the highest accuracy, with an R² = 0.82, MAE = 3.74, and RMSE = 1.08 for S2 and R² = 0.88, RMSE = 2.42, and MAE = 1.08 for L8 images. Results also revealed that MNDWI, NDWI, and NDSI responded most sensitively to SMC estimation.

Application of biochar as a soil amendment for reducing nitrate leaching from agricultural soils has attracted much attention. The objective of this study was to investigate the effect of biochar amendment on nitrate sorption and leaching in a sandy loam Inceptisols soil. Biochar was produced from two common biomass feedstock materials of the region, one was winter wheat (Triticum aestivum) straw and another was apple tree (Malus domestica) wood, each pyrolyzed at 300 °C and 550 °C. The results from the batch experiment indicated that the type of feedstock, pyrolysis temperature, and biochar addition rate had significant effects on nitrate sorption. Application of woody biochar produced from apple tree feedstock increased sorption of the nitrate significantly, compared to the control (no biochar application), whereas grassy biochar produced from wheat straw feedstock showed no significant nitrate removal ability. In addition, increasing pyrolysis temperature from 300 to 550 °C significantly increased the sorption ability of biochar to aqueous nitrate. The results obtained from the column leaching experiments were consistent with findings of the batch sorption experiment, indicating that biochar with the highest nitrate sorption in the batch experiment caused the least nitrate leaching when added to the soil columns. These findings suggest that the selection of appropriate biochar feedstock and pyrolysis condition can effectively reduce nitrate leaching from agricultural soils and contribute to improved nitrogen management and environmental sustainability.