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The Sistan region in Southeastern Iran is one of the world's most sensitive areas when it comes to sandstorms and wind erosion. One of the most influential factors in interpreting sandstorms is sand drift potential (DP), which is directly related to wind speed. Accurately, monitoring this phenomenon is still being determined, considering various temporal scales. Therefore, the main aim of this research is to analyze the trend of DP on monthly and annual scales. Our results showed that monthly variations of DP reached the highest and lowest values in July (609 VU) and January (47 VU), respectively. Blowing sand predominantly moved southeast, and the directional index fluctuated from 0.88 to 0.94. The annual DP was measured equal to 2700 VU, signifying a relatively high value when compared to other arid regions worldwide. The trend analysis results obtained from the Mann–Kendall test revealed both positive trends during the period 1987–2001 and negative ones from 2002 to 2016). However, the positive trend was found statistically insignificant. Furthermore, Sen's slope test results demonstrated that a negative trend could be observed with a steeper slope during July, September, and August, while a positive trend could be observed with a steeper pitch during November, December, and June. We recommend that land managers and stakeholders involved in controlling blowing sand using biological and physical methods should consider these trends in the Sistan region. Implementing nature-based solutions or control strategies should focus on these temporal sequences. [ABSTRACT FROM AUTHOR]

Purpose: Agricultural management as tillage systems and manure application can contribute effectively to controlling physical surface crusts (SCs), improving the soil's technical characteristics and germination rates. While agronomic practices are generally applied to winter wheat fields in southern Iraq, no previous study has explored their impact in combination with SCs and soil physical attributes on wheat productivity (WP) under different soil textures. Materials and methods: The impact of different agronomic management practices on the formation of soil physical surface crusts (SCs), soil compaction (measured by soil penetration resistance, SPR), soil volumetric water content (VWC), soil bulk density (ρb), mean weight diameter of aggregates (MWD), and WP was examined in two soil textures (clay loam, clay) during 2020 and 2022. Experimental data were subjected to an identical and randomized complete block design (RCBD) under a nested-factorial experimental design, where nine treatments with three replicates each were selected. This included three tillage practices (conventional tillage system (CT), till-plant (TP), and rotational tillage (NTCT)), alongside a sub-treatment with organic fertilizers (cattle manure (CF), and wheat straw (WR)), or without added fertilizer (WT). Results and discussion: Results showed that CT treatment increased SCs during wheat growth stages by significantly increasing aggregate stability. A significant difference in ρb and SPR and a higher distribution of VWC were seen under CT treatment when compared to TP and NTCT treatments. TP treatment showed a significantly increased in SPR and ρb, particularly in clay loam. The MWD under TP and NTCT was significantly different to CT treatment, which may be explained by an increase in soil stability due to their management practices. Additionally, both organic fertilizers (CF and WR) significantly enhanced SCs, SPR, VWC, ρb, MWD, and WP. Conclusions: These data showed a strong relationship between SCs and ρb and between VWC and SPR, which are directly affected by the soil's water content. [ABSTRACT FROM AUTHOR]

The design and application of multiple tools to map soil micronutrients is key to efficient land management. While collecting a representative number of soil samples is time consuming and expensive, digital soil mapping could provide maps of soil properties fast and reliably. The objective of this research was to predict the spatial distribution of soil micronutrients within the piedmont plain in northeastern Iran using random forest (RF) and support vector regression (SVR) algorithms. Sixty-eight locations with different land uses were sampled to determine the content of iron, manganese, zinc and copper in the topsoil (0–20 cm). Forty-one digital covariates were used as input to the models and were derived from a digital elevation model, open-source remote sensing (RS) data (Landsat 8 OLI and Sentinel 2A MSI images), WorldClim climate database and maps of soil properties. Covariates were grouped into 11 scenarios: I–III, based on RS data; IV–VI, including RS, topographic, climate and soil covariates; VII, VIII and IX, based only on topographic, climate and soil covariates, respectively; X and XI, based on recursive feature elimination and expert opinion, respectively. The RF algorithm gave 91, 94, 91 and 108% normalized root mean squared error values for iron, manganese, zinc and copper, respectively, for the validation dataset with scenario XI. The most important digital covariates for micronutrients prediction with both RF and SVR models were precipitation seasonality, mean annual temperature and the mean saturation index based on Sentinel 2A MSI data. Digital maps produced at 30 m spatial resolution using scenario XI could be used to effectively identify micronutrient deficiencies and excess hotspots. [ABSTRACT FROM AUTHOR]

The intensification of specific land management operations (tillage, herbicide, etc.) is increasing land degradation and contributing to ecosystem pollution. Mulches can be a sustainable tool to counter these processes. This is particularly relevant for rural areas in low-income countries where agriculture is a vital sector. In this research, the environmental impact of different rates of wheat residues (no residues, 25, 50, 75, and 100%) in corn silage cultivation was evaluated using the life cycle assessment (LCA) method under conventional tillage (CT) and no-tillage (NT) systems in a semi-arid region in Karaj, Iran. Results showed that in both tillage systems, marine aquatic ecotoxicity (ME) and global warming potential (GWP) had the highest levels of pollution among the environmental impact indicators. In CT systems, the minimum (17,730.70 kg 1,4-dichlorobenzene (DB) eq.) and maximum (33,683.97 kg 1,4-DB eq.) amounts of ME were related to 0 and 100% wheat residue rates, respectively. Also, in the CT system, 0 and 100% wheat residue rates resulted in minimum (176.72 kg CO2 eq.) and maximum (324.95 kg CO2 eq.) amounts of GWP, respectively. However, in the NT system, the 100% wheat residue rate showed the minimum amounts of ME (11,442.39 kg 1,4-DB eq.) and GWP (120.21 kg CO2 eq.). Also, in the NT system, maximum amounts of ME (17,174 kg 1,4-DB eq.) and GWP (175.60 kg CO2 eq.) were observed with a zero wheat residue rate. On-farm emissions and nitrogen fertilizers were the two factors with the highest contribution to the degradation related to environmental parameters at all rates of wheat residues. Moreover, in the CT system, the number of environmental pollutants increased with the addition of a higher wheat residue rate, while in the NT system, increasing residue rates decreased the amount of environmental pollutants. In conclusion, this LCA demonstrates that the NT system with the full retention of wheat residues (100%) is a more environmentally sustainable practice for corn silage production. Therefore, it may be considered one of the most adequate management strategies in this region and similar semi-arid conditions. Further long-term research and considering more environmental impact categories are required to assess the real potential of crop residues and tillage management for sustainable corn silage production. [ABSTRACT FROM AUTHOR]