Soil Erosion Research Articles

A review on soil erosion and its control techniques

This study focuses on Soil erosion, which is a critical environmental challenge, and has profound impacts on agriculture, biodiversity, and water quality. This paper explores the historical and contemporary perspectives of soil erosion in India and globally, highlighting its causes, impacts, and mitigation strategies. India's agrarian economy has long grappled with soil erosion, exacerbated by monsoon-driven climates and unsustainable practices. Traditional conservation methods were undermined during colonial and industrial periods, but modern initiatives like watershed management and soil loss estimation models have renewed focus on combating erosion. At the global level, projects like the GLASOD provide insights into the severity of degradation and the urgency for sustainable practices. In India's arid regions, such as the Thar Desert, wind patterns play a significant role in soil erosion. Seasonal winds cause displacement and nutrient loss, affecting agriculture, infrastructure, and ecosystems. The paper outlines various mitigation strategies, including vegetative barriers, sand fences, chemical stabilizers, and advanced technologies like precision agriculture and geotextiles. Despite progress, challenges persist, such as integrating traditional knowledge with modern techniques and addressing socio-economic barriers. Future directions emphasize holistic approaches, community involvement, and climate-resilient strategies to ensure sustainable soil and ecosystem management.

Investigating how reproductive traits in rice respond to abiotic stress.

Oryza sativa is one of the most important crops and a food source for billions of people. Anthropic global warming, soil erosion, and unstable environmental conditions affect both its vegetative and reproductive growth, and consequently the final yield of its cultivation. The reproductive phase starts with the transition of apical meristem from vegetative to reproductive, which develops into a panicle, proceeds through the differentiation of the floret, and, after fertilization, the filling of the grain. The physiological events that occur during these stages influence the ability of new seeds to respond to stresses during the future seed germination phase, a key step for successful seedling growth and future plant establishment. This review explores the impacts of different abiotic stresses on the physiological and molecular pathways of the reproductive growth.

In-situ Polymerization Induced Seed-Root Anchoring Structure for Enhancing Stability and Efficiency in Perovskite Solar Modules.

The escape of organic cations over time from defective perovskite interface leads to non-stoichiometric terminals, significantly affecting the stability of perovskite solar cells (PSCs). How to stabilize the interface composition under environmental stress remains a grand challenge. To address this issue, we utilize thiol-functionalized particles as a "seed" and conduct in situ polymerization of 2,2,3,4,4,4-hexafluorobutyl methacrylate (HFMA) as a "root" at the bottom of the perovskite layer. In this process, the thiol group acts as the initiation site for the polymerization of HFMA, while the fluorine groups in HFMA firmly anchor the organic cations of the perovskite through multiple hydrogen bonds. This strategy resembles how seeds take root in soil to prevent soil erosion. This bionic seed-rooting structure effectively stabilizes the stoichiometry of the perovskite, thus suppressing the escape of organic cations. As a result, the perovskite films with seed-rooting structures exhibit enhanced stability under harsh vacuum thermal conditions (150 °C, < 10 Pa). The resulting PCS achieves an efficiency of 25.64% and a 22.4 cm2 module efficiency of 22.61%. After 1300 hours of 1-sun illumination at 85% relative humidity and 65 °C (ISOS-L-3 protocol), the perovskite solar module maintains 90% of its initial efficiency.

Effects of extreme precipitation on soil erosion affected by typhoons in central Shandong Province, China

Effects of extreme precipitation on soil erosion affected by typhoons in central Shandong Province, China

Influence of Gravel Coverage on Hydraulic Characteristics and Sediment Transport Capacity of Runoff on Steep Slopes

Gravel coverage on slopes influences overland flow and soil erosion. However, the effect of different gravel sizes on the soil erosion process remains underexplored. In this study, a runoff scour test was performed to examine the effects of gravel coverage on the hydrodynamic characteristics of slope runoff and sediment transport capacity (Tc). The slope gradient varied from 18% to 84%, the unit flow discharge ranged from 0.27 × 10−3 to 1.11 × 10−3 m2 s−1, and gravel coverage was adjusted from 0% to 90%. The results reveal that water depth, shear stress, and stream power increased with gravel coverage. However, once coverage exceeded 20%, flow velocity and unit stream power decreased and stabilized. As gravel coverage increased, the hydraulic regimes transitioned from laminar to turbulent flow and shifted from supercritical to subcritical. Consequently, Tc first increased and then decreased with the increase in gravel coverage, reaching a peak at 20% coverage (1.66 kg m−1 s−1). Moreover, the degree of coverage indirectly influenced Tc through grain shear stress. The new equations, based on the Box–Lucas function, incorporated slope, grain shear stress, and flow velocity, thereby effectively simulating Tc for runoff on gravel-covered slopes (R2 = 0.94, NSE = 0.94). These findings provide a basis for modeling soil erosion on gravel-covered slopes.

Characterizing and Modeling Infiltration and Evaporation Processes in the Shallow Loess Layer: Insight from Field Monitoring Results of a Large Undisturbed Soil Column

Frequent agricultural irrigation events continuously raise the groundwater table on loess platforms, triggering numerous loess landslides and significantly contributing to soil erosion in the Chinese Loess Plateau. The movement of irrigation water within the surficial loess layer is crucial for comprehending the mechanisms of moisture penetration into thick layers. To investigate the infiltration and evaporation processes of irrigation water, a large undisturbed soil column with a 60 cm inner diameter and 100 cm height was extracted from the surficial loess layer. An irrigation simulation event was executed on the undisturbed soil column and the ponding infiltration and subsequent evaporation processes were systematically monitored. A ruler placed above the soil column recorded the ponding height during irrigation. Moisture probes and tensiometers were installed at five depths to monitor the temporal variations in volumetric water content (VWC) and matric suction. Additionally, an evaporation gauge and an automatic weighing balance measured the potential and actual evaporation. The results revealed that the initially high infiltration rate rapidly decreased to a stable value slightly below the saturated hydraulic conductivity (Ks). A fitted Mezencev model successfully replicated the ponding infiltration process with a high correlation coefficient of 0.995. The monitored VWC of the surficial 15 cm-thick loess approached a saturated state upon the advancing of the wetting front, while the matric suction sharply decreased from an initial high value of 65 kPa to nearly 0 kPa. The monitored evaporation process of the soil column was divided into an initial constant rate stage and a subsequent decreasing rate stage. During the constant rate stage, the actual evaporation closely matched or slightly exceeded the potential evaporation rate. In the decreasing rate stage, the actual evaporation rate fell below the potential evaporation rate. The critical VWC ranged from 26% to 28%, with the corresponding matric suction recovering to approximately 25 kPa as the evaporation process transitioned between stages. The complete evaporation process was effectively modeled using a fitted Rose model with a high correlation coefficient (R2 = 0.971). These findings provide valuable insights into predicting water infiltration and evaporation capacities in loess layers, thereby enhancing the understanding of water movement within thick loess deposits and the processes driving soil erosion.

Modelling current and future forest fire susceptibility in north-eastern Germany

Abstract. Preventing and fighting forest fires has been a challenge worldwide in recent decades. Forest fires alter forest structure and composition; threaten people's livelihoods; and lead to economic losses, as well as soil erosion and desertification. Climate change and related drought events, paired with anthropogenic activities, have magnified the intensity and frequency of forest fires. Consequently, we analysed forest fire susceptibility (FFS), which can be understood as the likelihood of fire occurrence in a certain area. We applied a random forest (RF) machine learning (ML) algorithm to model current and future FFS in the federal state of Brandenburg (Germany) using topographic, climatic, anthropogenic, soil, and vegetation predictors. FFS was modelled at a spatial resolution of 50 m for current (2014–2022) and future scenarios (2081–2100). Model accuracy ranged between 69 % (RFtest) and 71 % (leave one year out, LOYO), showing a moderately high model reliability for predicting FFS. The model results underscore the importance of anthropogenic parameters and vegetation parameters in modelling FFS on a regional level. This study will allow forest managers and environmental planners to identify areas which are most susceptible to forest fires, enhancing warning systems and prevention measures.

Modeling future sediment retention service in the Bagh-e-Shadi Forest protected area using InVEST and the ACCESS-ESM1-5 climate model

Assessing the impact of climate change on water-related ecosystem services (ES) in Protected Areas (PAs) is essential for developing soil and water conservation strategies that promote sustainability and restore ES. However, the application of ES research in Protected Area (PA) management remains ambiguous and has notable shortcomings. This study primarily aimed to assess the SDR-InVEST (Sediment Delivery Ratio-Integrated Valuation of Ecosystem Services and Tradeoffs) model for estimating ES, including soil loss, sediment export, and sediment retention, under various climate change scenarios from 1997 to 2100 in the data-scarce region of the Bagh-e-Shadi Forest PA. Bagh-e-Shadi Forest PA, a forest zone in Yazd Province, Iran, has the highest incidence of fire occurrences, leading to accelerated soil erosion and degradation. Our study is pioneering in the Bagh-e-Shadi Forest for employing the InVEST model, particularly the SDR model, to investigate the effects of climate change on sediment load, soil loss, and sediment retention. Additionally, this study focused on sensitivity analysis to individually assess model parameter uncertainties and highlighted the calibration process. By incorporating the latest IPCC emission scenarios, it addresses a critical research gap in the study area. Sensitivity analyses identified Borselli IC0, forest cover factor, and Borselli k (Kb) as the most influential parameters for sediment export. IC0 and kb are calibration factors that shape the sigmoid function in the SDR–IC relationship. From 1997 to 2021, our findings indicated that the study area experienced an average annual soil loss of 77.1 t ha−1 year−1. Additionally, the average sediment export was 0.08 t ha−1 year−1, while sediment retention averaged 2.2 t ha−1 year−1. The results indicated an increasing impact on ES due to climate change, primarily driven by projected increases in precipitation. Our findings showed that sediment yield export is projected to increase the most under the SSP585 scenario during the period 2041–2060, with a rise of 148.02% compared to baseline conditions. Sediment retention is expected to increase from 25,436.25 t year−1 in the baseline scenario to 63,128.63 t year−1 under SSP585 during the same period. The minimum increase in soil loss is projected to be 40.6% under the SSP126 scenario during the period 2021–2040. The quantified changes in ES provisioning will enhance future land use planning, especially for managing the Bagh-e-Shadi Forest.

Rainfed agriculture in Ethiopia: a systematic review of green water management pathways to improve water and food security

It is widely acknowledged that the world is currently experiencing an unprecedented water shortage, with agriculture being a crucial contributor. This paper presents a synthesis of available evidence, identify knowledge gaps, and make a state-of-the-art synthesis on green water management in Ethiopia. A systematic review methodology was implemented, encompassing the compilation and analysis of peer-reviewed and gray literature. The paper demonstrates that rainfed agriculture, which relies on “green water” (soil moisture from rainfall), accounts for 80% of cultivated land and 60-70% of global crop production. However, green water management has not received adequate attention in water policy and land rehabilitation programs in Ethiopia, where irrigation is limited. The analysis reveals a large yield gap and water productivity gap for major crops like maize, sorghum, and wheat in Ethiopia’s rainfed agriculture. Increasing crop yields through better soil, water, and crop management practices can significantly improve water productivity, offering “windows of opportunity” to enhance food and water security. Thus, a paradigm shift from the traditional narrow focus on soil erosion control towards an integrated green-blue water management approach in water and agricultural policies and programs is urgently required. Increased investments and expertise in green water management at the government level are crucial. Optimizing the use of green water resources in rainfed farming can also unlock Ethiopia’s export potential while improving domestic water and food security through strategic virtual water trade. In conclusion, the review highlights unlocking the potential of green water resources through targeted investments and policy support for rainfed agriculture can significantly contribute to Ethiopia’s water and food security objectives in a cost-effective and environmentally sustainable manner.

Socio-environmental changes and the local ecological knowledge of fishermen of the São Francisco River after the construction of the Sobradinho Hydroelectric Plant, BA

Between the 1950s and 1970s, the construction of hydroelectric plants in Brazil, such as the Sobradinho Hydroelectric Plant, aimed to accelerate economic growth but caused serious social and environmental impacts. The relocation of around 72,000 people resulted in issues such as lack of compensation and poor infrastructure. Environmentally, there was deforestation and soil erosion, affecting biodiversity and soil quality, which are essential for local subsistence. The ichthyofauna of the São Francisco River basin also deteriorated, with a drastic reduction in fish species, impacting artisanal fishing, which is essential for riverside communities. In response, associations and fishing colonies emerged to claim rights and improvements in living conditions. This work aims to analyze the ichthyofauna of the Sobradinho Dam lake and the socio-environmental impacts of this construction from the perspectives of local fishermen. Data were collected through participatory tools and individual interviews, using snowball sampling focused on experts from the Z-026 Fishermen’s Colony and the Association of Riverside Residents. The "Timeline" tool was used to recover the oral history of the residents. The interviews followed semi-structured scripts, addressing socioeconomic and socio-environmental aspects and using photo elicitation. The analysis of the ichthyofauna included interviews with fishermen and a species catalog, utilizing methods such as Chao 2 and Jackknife 1 for richness estimates. Multiple linear regression models were applied to evaluate the relationship between the number of recognized species and variables such as age and fishing time. The results showed that fishermen identified 94 out of the 104 cataloged species, reflecting a good understanding of the local ichthyofauna. The time of association with the Fishermen’s Colonies and the duration of fishing activity were influential in species identification, indicating that these associations can assist in the conservation of the ichthyofauna.

Long-Term Effects of Crop Treatments and Fertilization on Soil Stability and Nutrient Dynamics in the Loess Plateau: Implications for Soil Health and Productivity

Soil degradation and erosion pose significant threats to agricultural sustainability in fragile ecosystems, such as the Loess Plateau in northern China. This study examines the long-term impacts of fertilization regimes and land-use systems on soil health, focusing on soil aggregate stability, fertility, and crop productivity. Six treatment combinations were evaluated in our study, including three continuous alfalfa fields (AL-CK, AL-P, and AL-NPM) and three continuous wheat fields (WH-NPM, WH-NP, and WH-P), each representing a combination of land use and three fertilization treatments: (1) no fertilization (CK), (2) inorganic fertilization (120 kg ha−1 N, 60 kg ha−1 P-NP), and (3) a combination of organic and inorganic fertilization (75 t ha−1 cow manure-NPM). Soil samples were collected from three depths (0–10 cm, 10–20 cm, and 20–30 cm) to assess physical and chemical properties. We evaluated the long-term effects of different fertilization treatments on soil stability, fertility, and crop yield to explore the interactions among soil’s physical and chemical properties under two land-use types and to assess the effectiveness of combined organic and inorganic fertilization strategies in improving soil health and mitigating erosion in vulnerable landscapes. The study revealed significant depth-specific variations with surface layers (0–10 cm) showing the greatest improvement under NPM treatments, particularly in continuous alfalfa fields, which exhibited higher soil fertility, improved soil structure, and crop yield. In contrast, continuous wheat fields with minimal fertilization demonstrated significantly lower soil quality and productivity. Using the combination of mineral fertilizers and organic amendments, such as cow manure, proved to be the most effective strategy for significantly enhancing nutrient availability and overall soil health. Partial Least Squares Modeling (PLS-M) and Mantel analysis highlighted the critical role of fertilization management in maintaining soil quality, boosting crop productivity, and mitigating erosion in high-risk areas. This study emphasizes the importance of integrated nutrient management for sustainable land use and soil conservation in erosion-prone regions.

Soil Erosion Assessment Using the RUSLE Model and Geospatial Techniques (Remote Sensing and GIS) in Kalyani River Watershed of Uttar Pradesh, India

Soil erosion significantly impacts environmental sustainability, agriculture, and water quality. This study examines soil erosion in the Kalyani River within the Nindoora and Fatehpur blocks of Barabanki District, Uttar Pradesh, India, where seasonal fluctuations and steep banks exacerbate the issue. The region experiences severe soil degradation due to uncontrolled land use, deforestation, over-cultivation, overgrazing, and biomass exploitation driven by population growth. To address this, GIS and Remote Sensing technologies were utilized, employing the Revised Universal Soil Loss Equation (RUSLE) model to identify erosion-prone areas. The RUSLE model involves calculating parameters such as the runoff-rainfall erosivity factor (R), soil erodibility factor (K), topographic factor (LS), cropping management factor (C), and support practice factor (P). Layer-wise thematic maps of each factor were generated using a GIS platform, incorporating various data sources and preparation methods. The study's results indicate that value of K factor is found to be 0.025 indicates that the soil is relatively resistant to erosion. Higher LS factor values are scattered across the area, especially near the Kalyani River. The southeastern regions show higher C factor values, indicating less effective soil cover and management against erosion. It has also been estimated that 90% of the Kalyani River watershed faces low soil erosion risk (0–10 ton/ha/yr), while 0.20% primarily near riverbanks experiences high to very high erosion risk (10–40 ton/ha/yr). Sandy and sandy loam soils near riverbanks, exacerbated by seasonal water level fluctuations and steep slopes, are highly prone to erosion. The RUSLE-based GIS approach allowed for the precise identification of erosion hotspots, facilitating the development of targeted soil conservation strategies to mitigate soil degradation and promote sustainable land management.

A Laboratory Study of the Effects of Wildfire Severity on Grain Size Distribution and Erosion in Burned Soils

Wildfires pose a significant threat to the entire ecosystem. The impacts of these wildfires can potentially disrupt biodiversity and ecological stability on a large scale. Wildfires may alter the physical and chemical properties of burned soil, such as particle size, loss of organic matter and infiltration capacity. These alterations can lead to increased vulnerability to geohazards such as landslides, mudflows and debris flows, where soil erosion and sediment transport play a crucial role. The present study investigates the impact of wildfire on soil erosion by conducting a series of laboratory experiments. The soil samples were burned using two different methods: using firewood for different burning durations and using a muffle furnace at an accurately controlled temperature within 400∘C∼1000∘C. The burned soils were subsequently subjected to surface erosion by utilizing the constant head method to create a steady water flow to induce the erosion. In addition, empirically based theoretical models are explored to further assess the experimental results. The experimental results reveal a loss of organic matter in the burned soils that ranged from approximately 2% to 10% as the burning temperature rose from 400∘C to 1000∘C. The pattern of the grain size distribution shifted to a finer texture in the burned soil. There was also a considerable increase in soil erosion in burned soils, especially at a higher burn severity, where the erosion rate increased by more than five times. The empirical predictions are overall consistent with the experimental results and offer reasonable calibration of relevant soil erosion parameters. These findings demonstrate the importance of post-fire erosion in understanding and mitigating the long-term effects of wildfires on geo-environmental systems.

Effects of land consolidation on moisture and surface temperature regime of agricultural soil blocks using remote sensing data in the Czech Republic

Abstract The Czech Republic has experienced collectivization, transforming individual land ownership into state ownership through agricultural land consolidation after World War II. Land consolidation has led to the expansion of agricultural soil blocks as well as the disappearance of vital landscape features such as shrubs, hedges, lone trees, and wetlands, all of which serve a variety of ecological functions. The disappearance of the landscape elements causes some important problems, such as soil degradation and erosion. The Czech Ministry of Agriculture has enforced a regulation that was developed by the European Union to improve agriculture by enforcing cross-compliance requirements, which encompass the observance of Good Agricultural and Environmental Condition (GAEC) standards. The regulation disincentivizes single-crop cultivation on areas larger than 30 hectares since 2020 to reduce the negative effects of land consolidations on agriculture and soil quality. In this context, the study examines the relationship between land surface temperature (LST) and moisture of agricultural plants and soil blocks in the South Bohemia, Czech Republic, using Landsat-8 remote sensing data from 2018 to 2021. The mono-window algorithm (MWA) was used to obtain LST, and the precision of Landsat LST data was evaluated using MODIS daily LST data. The NRMSE ≤ 0.15 and RMSE ≤ 3.5 C were found with a strong positive relationship r ≥ 0.65 between datasets. Additionally, the density of vegetation and the moisture index of soil and plants were calculated using spectral remote sensing indices such as the normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), and soil moisture index (SMI). The statistical relationships among those spectral indices with LST were examined. The analyzes showed that the implementation of GAEC 7d improved the relationship between NDVI and NDMI, with the correlation increasing from r = 0.80 in 2019 to 0.92 in 2021. Meanwhile, the inverse relationship between NDMI and LST changed from − 0.71 to -0.67. These changes in correlation suggest that plant water retention in the region increased following the regulation, and the soil structure may have also improved.

Assessment of Soil Quality and Erosion Hazards Using Statistical and PCA Analysis: A Case Study of the Arjasa Subwatershed

This study aims to analyze the soil quality and erosion hazard level of each cluster in the Arjasa Subwatershed, which is the upstream part of the Bedadung Watershed, Indonesia. Land use in this area is production forest, dry land agriculture, and mixed dry land agriculture with slopes varying from 3-8% to &gt;40%. The soil types include Andic Dystrudepts, Lithic Hapludands, Typic Dystrudepts, Typic Eutrudepts, and Typic Hapludands. Soil samples were taken at 30 random sample points at a depth of 0-20 cm. Soil physical and chemical parameters were used in this study. Statistical analysis used were Anova, Duncan test, PCA, and regression-correlation. Quantitative analysis of erosion hazard level was conducted using the USLE formula developed by Wischmeier and Smith (1978). This research has identified three main problems, namely the unavailability of soil quality analysis data, the magnitude of the erosion hazard level in the sub-watershed, and the magnitude of the impact of erosion on soil quality. After assessing these issues, the soil quality index data was found to be in the medium (0.47) to high (0.65) range. Meanwhile, the amount of erosion hazard in each cluster has also been obtained, which shows a range of 4.39 tons/ha/year which is categorized as very light, covering 19.91% of the total area, to 184.81 tons/ha/year, which is included in the heavy category, amounting to 33.37%. In addition, it can be seen that there is a negative relationship at a moderate level (r = 0.56) between the level of erosion hazard and the soil quality index, which means that soil erosion can have an impact on reducing the soil quality index. Finally, it can be suggested that good soil conservation practices such as terracing and organic fertilizer application in agricultural practices are needed to prevent increased erosion so that soil quality does not further decline.

Assessment of Soil and Sediment Loss in the Ken River Basin, Central India, Using RUSLE and InVEST SDR Models

ABSTRACTAssessing soil and sediment loss are the main aims of the paper using the Revised Universal Soil Loss Equation (RUSLE) and the InVEST SDR models in the Ken River Basin (KRB). The annual soil loss varied from few‐ton/hectare/year to 1630.5. The high erosion susceptibility was prevalent in the elevated area and low soil erosion severity was seen in the low‐lying plains of the middle and lower reaches. The maximum sediment export (430.16‐ton/hectare/year) was noticed in the hills of the Vindhyans, Bundelkhand, and Deccan traps. Contrary to this the low sediment transport was observed in the flat alluvium plains. The conservation practices are slightly more effective in the KRB. Its crop cover reduces the impact of rain's kinetic energy, increase recharge, and mitigates soil erosion. These research output may be helpful to planners in minimizing soil and sediment loss and in enhancing the soil conservation and agricultural productivity.

Vegetation based climate solutions for soil management in smallholder farmlands of Kabale and Rubanda districts, Uganda

Understanding and appreciating climate solutions for soil management in smallholder farmlands are paramount. These climate solutions inform smallholder farmers’ actions, choices, decisions and priorities to tackle specific climate change problems and opportunities. The study used structured and semi structured questionnaires to collect field data to ascertain smallholder farmers’ knowledge about vegetation based climate solutions for soil management in Kabale and Rubanda districts, Uganda. A purposive sampling technique was used to collect data from 367 smallholder farmer household head respondents. Regression model, specifically linear to test multicollinearity and multinomial logistic and descriptive statistics was utilised to examine vegetation based climate solutions for soil management. Vegetation based climate solutions such as crop residues, selected trees, Napier grass and Seteria grass (dependent) and gender, age and marital status, and level of education information (independent) were determined predictor variables. The findings revealed that both genders, males (51.5%) and females (48.5%), witnessed climate change as demonstrated in Fig. 2. The chi-square test (χ2 = 376.337) indicated a significant difference between smallholder farmers’ implementing climate solutions. The study observed positive Kendall’s tau (0.357 and 0.118) and a p-value (0.002 and 0.289) of temperature and rainfall respectively. Most farmers (69.2%) relied on fellow farmers as a major source of climate information to manage soil and enhance soil fertility. Vegetation based climate solutions 33.8%, (planting Napier grass, selected tree species, and crop residues) were revealed as suitable and effective soil management interventions to control soil erosion and fertility improvement in smallholder farmlands. Climate solutions were significantly influenced by level of education (0.000) and farmland size (0.001) at 0.05. Therefore, there is a need to incorporate vegetation based climate solutions into government development programmes and agendas to enhance soil fertility and erosion management in smallholder farmers’ farmlands with a focus on livelihood improvement through increasing crop yields and hunger alleviation.

A convolutional neural network model and algorithm driven prototype for sustainable tilling and fertilizer optimization

Tilling, a common agricultural practice, is being done excessively on farms leading to about 2.35 billion tons of soil erosion from US croplands annually, in addition to causing soil infertility, carbon release, nutrient runoff, and fertilizer over-usage. This paper evaluates whether optimizing tillage intensity, timing, and fertilizer quantity using a convolutional neural network model and algorithm will address these problems. The machine learning model utilizes a camera-captured field image to determine existing tilling intensity on a 7-point scale. This machine learning output, along with soil sensor and external forecast data, flows into a 10-parameter algorithm that determines optimal tilling and fertilizer levels. A fully functional tractor prototype demonstrates the above. A 30-year simulation comparing conventionally-tilled and algorithm-tilled farms showed a reduction in carbon emission by 57%, fertilizer usage by 43%, and runoff by 86% demonstrating the transformative potential of this algorithm. Additionally, a stationary prototype was deployed in 155 farms across 5 countries.

Conservation Soil Tillage: Bridging Science and Farmer Expectations—An Overview from Southern to Northern Europe

Soil degradation and climate change are the most destructive (human- and/or naturally induced) processes, making agricultural production more challenging than ever before. Traditional tillage methods, characterized by intensive mechanical soil disturbance (dominantly using a plow), have come under question for their role in exacerbating soil erosion, depleting organic matter, and contributing to the decline in soil biodiversity and other soil devastating processes. These practices, while effective in the short term for crop production, undermine the sustainability of agricultural systems, posing a threat to food security and environmental stability. This review examines the adoption and implementation of Conservation Soil Tillage (CST) across six European countries: Croatia, Serbia, Hungary, Slovakia, Czech Republic, and Poland. The main objective is to analyze the historical development, current status, and future prospects of CST in these countries, highlighting the challenges and opportunities in transitioning from conventional tillage methods. Conservation Soil Tillage (CST) emerges as a promising alternative platform to still dominant conventional plowing tillage approach. By reducing the intensity and frequency of tillage, CST practices aim to maintain adequate soil cover, minimize erosion, and encourage biological activity and organic matter accumulation, thus, ensuring soil productivity and resilience against additional degradation and climate variation. Efforts made by scientists and the government to go over it sometimes are not sufficient. Farmers’ expectations of benefits are the final keystone for the integration of CST as a dominant sustainable practice. Analyses from six European countries pointed to a high level of diversity in readiness and willingness to accept, as well as different levels of knowledge about the adoption of CST. Our study suggested that the adoption of CST is increasing, and it represents a key strategy for soil degradation prevention and climate change mitigation

Integrating rainwater harvesting and organic soil amendment to enhance crop yield and soil nutrients in agroforestry

Abstract More than 90% of rainfed croplands in Sub-Saharan Africa (SSA) are severely affected by highly intermittent rainfall and frequent drought limiting crop productivity in the region. Besides, 27.1% of the population in SSA are currently food insecure and this is likely to increase with the current rapid population growth in the region. Soil erosion and water scarcity remain to be the core problem affecting agricultural productivity of smallholder farming. In the current study, we analysed rainwater harvesting assisted small-scale agroforestry system in order to mitigate both soil erosion and water scarcity issues simultaneously. The system included in-situ rainwater harvesting, soil organic amendment (raw poultry litter, poultry litter biochar, wood ash) and an agroforestry system (AFS) containing maize, barley- Eucalyptus globulus all intercropped in a holistic approach. The effect was evaluated on selected soil parameters and crop yield in a field experiment on a completely randomized design. The treatments were poultry litter (PWAFS), poultry litter biochar (BWAFS) wood ash (AWAFS) with supplementary irrigation (WAFS) and agroforestry system AFS (control). The first three treatments contained poultry litter, poultry litter biochar and wood ash along with rainwater harvesting respectively while the fourth treatment contained only rainwater harvesting. Besides, a control plot-AFS was assigned with neither rainwater harvesting nor soil organic resources. The result indicated that BWAFS increased the pH by 19.4% followed by AWAFS and PWAFS (9%). Maximum and minimum SOM (2.26%, 1.21%) were observed under BWAFS and the control (AFS) respectively. BWAFS significantly increased Av.P by 78.1% while WAFS increased by 40% compared to the control. Similarly, BWAFS and PWAFS had significant effect on maize yield with increase by 74% and 36% respectively. The study concluded that integrating rainwater harvesting and soil amendment with agroforestry systems can enhance crop yield and soil nutrient levels. Therefore, such agricultural practices should be adopted by smallholder farmers in areas with limited water and nutrients levels.