Soil Management Plan Research Articles

Estimation of soil loss using RUSLE model and GIS tools: Case study in the Jucusbamba Micro-Watershed (Amazonas, NW Peru)

Human activities have intensified soil erosion globally, negatively impacting the physical, chemical, and microbiological quality of water and soil. This study estimated soil loss in the Jucusbamba Micro-Watershed (Amazonas, northwestern Peru) using the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information Systems (GIS) and remote sensing (RS) data. Meteorological data, soil maps, digital elevation models, and land cover and use maps were integrated into a GIS environment to predict the spatial distribution of erosion. The results showed five classes of soil loss severity: slight (93.34%), moderate (3.94%), high (1.82%), very high (0.61%), and severe (0.29%). Areas with high, very high, and severe erosion levels were mainly located in the middle and lower parts of the micro-watershed. The average annual soil loss was estimated at 23.24 t/ha/year. The information obtained is crucial for the formulation of soil management plans and programs to address erosion problems in the Jucusbamba River Micro-Watershed. Future research should focus on validating these models through field studies and implementing soil conservation practices based on these findings. Keywords: Amazonas, hydrology, RUSLE model, water erosion map, watershed.

CA-Markov prediction modeling for the assessment of land use/land cover change in two sub-basins of the Tocantins-Araguaia River Basin.

Due to the anthropogenic pressures of expansion areas for livestock and agricultural production in the Brazilian Cerrado, it is of paramount importance to understand the dynamics of land use/land cover (LULC) changes in this region. Thus, we investigated LULC changes in two sub-basins of the Tocantins-Araguaia River basin from 1997 to 2015 and consequently projected future changes for the timespan between 2030 and 2050. The Formoso sub-basin experienced significant expansion of agricultural and pasture areas, whereas the Sono sub-basin limited farmland expansion (more stable native vegetation) due to substantial protected areas, trends that were also observed for future projections (2030 and 2050). Pastureland in the Formoso sub-basin increased by 5.8%, while the Sono sub-basin saw significant gains in cultivated land, according to change detection analyses during the 1997-2015 period. High stability probabilities of no change (> 70%) for grassland areas in the Sono River sub-basin and pasturelands in the Formoso River sub-basin were computed. The CA-Markov model demonstrated a high consistency level with actual LULC classes for both sub-basins, as indicated by an overall Kappa coefficient above 0.8. Future projections for 2030 and 2050 show a substantial expansion of agriculture and pasture in both sub-basins, driven by specific factors such as soil organic carbon stocks, distance from rural settlements, and proximity to rivers. Short- and mid-term simulations indicate substantial expansion of agriculture and pasture in both basins, with potential adverse impacts on water erosion. Consequently, developing policies for soil management and sustainable land use planning is essential for agroecosystem sustainability, promoting a balanced approach to economic development while addressing climate change and anthropogenic challenges.

Estimation of Soil Loss in the Nanoi River Basin using Geospatial Techniques

Objectives: The main purpose of this research is to identify severe soil loss areas in the Nanoi river basin of Assam, India to suggest appropriate soil management planning in the river basin. Methods: The Revised Universal Soil Loss Equation (RUSLE) integrates geospatial technologies to assess overall soil loss in the Nanoi river basin which provides a faster and more accurate estimation. It is possible to understand soil erosion patterns more thoroughly using RUSLE which makes sustainable soil management easier. Findings: According to the RUSLE equation, the Nanoi river basin experiences an estimated total soil loss of 18,562.5 tons per year, with an average annual soil loss of 0.32 t/h/y. This suggests that approximately 0.64 km2 of the area falls into the Moderate, high and Extreme soil erosion sensitivity zones. Furthermore, a final map is generated to display different areas with varying levels of soil loss rates. Novelty: The geospatial approaches used produce precise findings at a reasonable price and demonstrate the severity of soil loss in the river basin. If soil loss continues at the current rate, there is a high likelihood that certain areas on both sides of the river, particularly in the downstream region of the basin, will experience fluvial hazards, such as drainage congestion and floods. Hence, the results generated will be helpful in the management practices of the river basin. Keywords: Soil loss, Soil erosion, Geospatial, Revised universal soil loss equation, River basin

Reference soil groups map of Ethiopia based on legacy data and machine learning-technique: EthioSoilGrids 1.0

Abstract. Up-to-date digital soil resource information and its comprehensive understanding are crucial to supporting crop production and sustainable agricultural development. Generating such information through conventional approaches consumes time and resources, and is difficult for developing countries. In Ethiopia, the soil resource map that was in use is qualitative, dated (since 1984), and small scaled (1 : 2 M), which limit its practical applicability. Yet, a large legacy soil profile dataset accumulated over time and the emerging machine-learning modeling approaches can help in generating a high-quality quantitative digital soil map that can provide better soil information. Thus, a group of researchers formed a Coalition of the Willing for soil and agronomy data-sharing and collated about 20 000 soil profile data and stored them in a central database. The data were cleaned and harmonized using the latest soil profile data template and 14 681 profile data were prepared for modeling. Random forest was used to develop a continuous quantitative digital map of 18 World Reference Base (WRB) soil groups at 250 m resolution by integrating environmental covariates representing major soil-forming factors. The map was validated by experts through a rigorous process involving senior soil specialists or pedologists checking the map based on purposely selected district-level geographic windows across Ethiopia. The map is expected to be of tremendous value for soil management and other land-based development planning, given its improved spatial resolution and quantitative digital representation.

Assessment of potential soil erosion in Mongolia based on the RUSLE model and RCP 8.5 scenario

AbstractDue to its relatively high altitude and a continental climate, environmental issues related to soil erosion and land degradation more seriously affect the ecosystem and crop production in Mongolia. As detailed soil erosion and land degradation assessments have only been performed in some regions of Mongolia, the purpose of this study is to evaluate the soil vulnerability on a national scale and predict future soil erosion under climate change prior to establishing an appropriate management plan. The revised universal soil loss equation model was chosen for this study, which reflects geographic and climatic characteristics in a vast area as the Mongolian territory. We evaluated soil erosion using historical data from 1993 and 2013 and generated predictions in the near (2041–2060) and far future (2061–2080) periods under the representative concentration pathway 8.5 scenario. The soil erosion rates were divided into six classes: very low, low, medium, high, very high and extreme. The total of 46,039 km2 of the Mongolian territory was classified as very high and extreme risk, which is predicted to increase up to 48,961 and 51,769 km2, in the near and far future periods, respectively. At the national scale, most of the soil erosion appeared in bare area, as it covers more than 60% of the total area. Meanwhile, the highest soil erosion risk was expected in high mountain ranges and ecologically vulnerable regions of the Gobi Desert and steppe area. This study identifies three land cover types with high priority for management and areas that should be considered first in the sustainable national land use and soil management plans considering regional characteristics.

Agricultural soil legacy influences multitrophic interactions between crops, their pathogens and pollinators.

Soil legacy influences plant interactions with antagonists and below-ground mutualists. Plant-antagonist interactions can jeopardize plant-pollinator interactions, while soil mutualists can enhance plant-pollinator interactions. This suggests that soil legacy, either directly or mediated through plant symbionts, affects pollinators. Despite the importance of pollinators to natural and managed ecosystems, information on how soil legacy affects plant-pollinator interactions is limited. We assessed effects of soil management legacy (organic versus conventional) on floral rewards and plant interactions with wild pollinators, herbivores, beneficial fungi and pathogens. We used an observational dataset and structural equation models to evaluate hypothesized relationships between soil and pollinators, then tested observed correlations in a manipulative experiment. Organic legacy increased mycorrhizal fungal colonization and improved resistance to powdery mildew, which promoted pollinator visitation. Further, soil legacy and powdery mildew independently and interactively impacted floral traits and floral reward nutrients, which are important to pollinators. Our results indicate that pollination could be an overlooked consequence of soil legacy and suggests opportunity to develop long-term soil management plans that benefit pollinators and pollination.

Surveying and localized screening of soil contamination with the growth of urban community agriculture in Northern Utah

AbstractUrban soil contamination has become an increasing concern within residential developments and with the expansion of urban agriculture, which has grown across the United States. In Salt Lake County, Utah, there are 39 community gardens and urban farms, with more in development. Only limited data exist to determine whether these soils may be considered contaminated. The purpose of this study was to conduct an urban soil survey in Salt Lake County for initial screening of soils in community gardens and urban farms for common contaminants, including the trace elements lead and arsenic (total concentrations), along with organic contaminant benzo (A) pyrene (BAP). Site selection included an emphasis on sites serving at least nine families and those with greater potential for soil contamination based on identified risk factors. Measured soil test concentrations were compared to US EPA regional screening levels (RSLs) and other US background levels. Lead concentrations ranged from 14.8 to 516 mg kg−1, with a mean concentration of 91.8 mg kg−1. Measured arsenic ranged from 2.83 to 39.3 mg kg−1 with a mean of 11.8 mg kg−1. All measured arsenic concentrations exceeded the US EPA RSL of 0.68 mg kg−1. BAP was the primary hydrocarbon of concern, and concentrations above detectable limits ranged from 0.01 to 0.44 mg kg−1, with a mean concentration of 0.09 mg kg−1. By determining the baseline degree of soil contamination in key urban agricultural sites in Utah's most populated county, local screening levels were developed into soil management plans for producers.

Nutrient-Rich Organic Soil Management Patterns in Light of Climate Change Policy

Nutrient-rich organic soil management in agriculture is among the critical sources of greenhouse gas (GHG) emissions globally and at the European level, where the most significant effects are observed in Northern, Eastern, and Central Europe. Growing climate change mitigation targets urge the need to assess and analyze current organic soil management patterns and policy planning and look for appropriate future management strategies. The objectives of this research were to assess the nutrient-rich organic soil management patterns in Latvia during the last decade and to conclude whether organic soil management in agriculture has been climate change mitigation targeted and driven by agriculture support policy. We analyzed the complex, two state-level databases based organic soil data set by using the multidimensional approach of the research methods, including graphical, spatial, correlation, factor, and cluster analysis. Our results revealed the lack of purposeful organic soil management planning in light of the climate change policy in Latvia during the research period and the inexpediency of the agriculture support policy in this regard. The research introduced an innovative methodological approach for the analysis of organic soil management patterns and policy impacts, as well as opened the necessity for a revision of the nutrient-rich organic soil management perspective in light of climate change mitigation targets. Doi: 10.28991/CEJ-2022-08-10-017 Full Text: PDF

Land Use Capability and Suitability Classifications of a Plinthic Alfisol of a Derived Savannah Ecology of Nigeria

Background: In derived savanna ecology, the evaluation of soil characteristics for the current and future capability and suitability for crop production is crucial. Therefore, studies were conducted to evaluate the capability and suitability of plinthic soil of a derived savannah ecology of Nigeria for sustainable crop production. Methods: The methodology was essentially Grid using hand-held GPS to determine the coordinates of sampling points for the collection of soil samples. In all, 18 profile pit samples were collected. The profile pits were described morphologically on the field using the FAO guideline on soil profile description. From the various horizons of these profile pits, soil samples were collected. Results: Land assessment indicates that the soils of the area are very fragile and inherently low in nutrients. Mapping unit A is moderately suitable for arable crop production while Units B and C are fairly suitable. For agricultural activities, mapping unit D is marginal for arable crop production. Stoniness, steep slope, and shallow soil depth are the major limitations. Mapping unit E is the most suitable for lowland rice production. Soil fertility management ought to be integrated (organic and inorganic). The land evaluation shows that the soils of the project site are very fragile and poor in native fertility. Also, the soils are generally defined by the plinthite content. Apart from the traditional crops grown in the area, some other crops like sweet potato and cowpea will do well on the soil of the area. Crop residue has to be well managed and adopted. Crop rotation and intercropping should be encouraged and included in the soil management plan. Also, due to the low level of organic carbon in the soils, the soils will benefit optimally from the application of manure. This will improve the soil aggregation, water, and nutrient-holding capacities as well as improve the pH status of the soil. Conclusion: Soil fertility assessments should be undertaken every two years after continuous cropping. ’High-Intensity Detailed Soil Survey’ of this nature should be carried out every ten years.

Back to the Future: Farming Systems in Transition

National policy levers play a central role in shaping agricultural systems. In his timely book Land Renewed: reworking the Countryside Peter Hetherington (2021) challenges British policy makers to form a far more coherent approach for land use supporting the transition towards improved national food security, seen through a lens of climate change and biodiversity loss. In the UK there are currently three separate government departments responsible for land, the environment, farming and climate change complicating policy alignment. He points out that without subsidies, in the form of area payments, over 60% of all British farms would be running at a loss. The challenge is to improve domestic crop production which currently provides just 60% of the nation's food (Lang, 2020) and hence make the food system more resilient to shocks in international food supply chains while addressing the climate emergency. Hetherington documents a number of cases where farmers, collaborating in organisations such as the Nature Friendly Farming Network, are successfully encouraging a resurgence of bird-life through reduced tillage, renewing and planting hedgerows and using lower doses of fertilisers, including on larger holdings with over 500 ha. This is perhaps the other side of the coin of the bleak future for biodiversity associated with major broad-acre crops outlined by Dewar (2021) in these pages. However, Hetherington (2021) points out that just under half of England's farms produce 2% of total agricultural output, while 8% of them account for over half of it. This implies room for landscape scale nature-friendly farming and even re-wilding, particularly in the uplands, with the caveat that local communities play a central role in plans and implementation. With heightened public interest in the climate emergency and biodiversity loss there is increasing desire for food which is local and particularly in food traceability. This is leading to increasingly sophisticated methods to track and publish farming and animal welfare standards with supermarket chains requiring producers to adhere to these (e.g., Waitrose and Partners, 2022 one of many examples). Underpinning such standards, methods of carbon accounting which may be applied to soil, whole farms or individual enterprises within the farm have been a focus of research for some time (e.g. Goglio et. al. 2015; Abram, 2020). At the most basic level regular soil organic matter tests and a soil management plan will allow British farmers signed up to the entry level of the recently announced Sustainable Farming Incentive (DEFRA, 2022) to be "paid with public funds for providing public goods". To receive payment, they will also be required to ensure 70% of the farm has a green cover through the winter from December to February and add organic matter, which can be via a green cover crop, on one third of the land each year. Currently there is no requirement to demonstrate that soil organic matter is increasing over time – this is assumed. As time goes on however it is possible to envisage more nuanced payments for increasing stored soil carbon, and even a "market" developing as is the case with woodland creation (Forestry Commission, 2022) as producers become the "carbon farmers" of tomorrow as suggested by Korres & Dayan (2020). External inputs including crop protection products will all be included in farm or enterprise carbon budgets. Policy levers are also a focus to regulate the quantity of agrochemicals used for crop protection. The European Union's "Farm to Fork" and Biodiversity strategies, aim reduce by 50% the use and potential risk of chemical pesticides by 2030 and reduce by 50% the use of the more hazardous pesticides also by 2030, although a recent assessment indicates slow and uneven progress towards targets and adoption of IPM measures (European Commission, 2020). Individual countries also take unilateral measures as seen with restrictions on use and in some cases phasing out of the use of glyphosate e.g. by 2024 in Germany (Sustainable Pulse, 2022). Glyphosate is a widely used tool for the destruction of green cover crops (e.g. Fogliato, 2020) so alternative approaches will be needed where these are used at scale as part of interventions to build soil health and store carbon.

芝生の収容限界と土壌構造・管理計画 日本芝草学会2010年度春季大会 校庭芝生部会記録

芝生の収容限界と土壌構造・管理計画 日本芝草学会2010年度春季大会 校庭芝生部会記録

Susceptibility to Gully Erosion: Applying Random Forest (RF) and Frequency Ratio (FR) Approaches to a Small Catchment in Ethiopia

Soil erosion by gullies in Ethiopia is causing environmental and socioeconomic problems. A sound soil and water management plan requires accurately predicted gully erosion hotspot areas. Hence, this study develops a gully erosion susceptibility map (GESM) using frequency ratio (FR) and random forest (RF) algorithms. A total of 56 gullies were surveyed, and their extents were derived by digitizing Google Earth imagery. Literature review and a multicollinearity test resulted in 14 environmental variables for the final analysis. Model prediction potential was evaluated using the area under the curve (AUC) method. Results showed that the best prediction accuracy using the FR and RF models was obtained by using the top four most important gully predictor factors: drainage density, elevation, land use, and groundwater table. The notion that the groundwater table is one of the most important gully predictor factors in Ethiopia is a novel and significant quantifiable finding and is critical to the design of effective watershed management plans. Results from separate variable importance analyses showed land cover for Nitisols and drainage density for Vertisols as leading factors determining gully locations. Factors such as texture, stream power index, convergence index, slope length, and plan and profile curvatures were found to have little significance for gully formation in the studied catchment.

Predicting Soil Cation Exchange Capacity in Entisols with Divergent Textural Classes: The Case of Northern Sudan Soils

Cation exchange capacity (CEC) is an important soil property because it affects the assimilation of nutrients and buffers against soil acidification. Thus, knowledge of CEC is considered key to developing agricultural and environmental models for land management planning. However, in developing countries such as Sudan, there is a lack of soil CEC data due to the absence of research projects and funding to develop this information. Therefore, this research was conducted to predict CEC for large areas using specific soil physical characteristics, including soil texture and saturation percentage (SP), for which there is potentially available data. To achieve this goal, the properties of 430 soil samples (301 for training and 129 for validation) were obtained from the soil database of the Soil Survey Administration, Ministry of Agriculture, Sudan, which had different soil depth intervals (0–0.3 m, 0.3–0.6 m, 0.6–0.9 m, 0.9–1.5 m, and >1.5 m) from Entisols in the Northern State of Sudan. The data were stratified into homogeneous groups based on the textural classes of the main soil order. Then, regression models were performed and evaluated using the coefficient of determination ( R2), standard error of the estimate (SEE), and root mean square error (RMSE). The results indicated that in individual Entisols and textural classes, the combined soil covariates silt, clay, and SP were the best properties to predict CEC values ( R2 ranged from 0.86 to 0.99). The regression models did not provide statistically significant results for the silty clay loam textural class ( R2 ranged from 0.01 and 0.35). The findings of this modeling study could be applied to other Entisols worldwide with divergent textural classes, which could be used to verify the suggested CEC pedotransfer functions and/or improve them. This would help farmers correctly design soil management plans and prevent acidification issues if combined with other soil properties data.

Applied research on the numerical simulation of Cu and Cd transport laws in a metal mining area

China is paying increasing attention to the ecological environment, and heavy metal pollutants produced during mining and smelting in metal mines have caused serious environmental problems to the soil in mining areas. Heavy metal pollution by Cd and Cu in the soil of a metal mining area in Leiyang City, Hunan Province, China, is used here as an example. The total content of heavy metals and the contents of various forms were determined. High Cd and Cu contents were found, and the main forms of the two heavy metals were in the residual state. Then, using the COMSOL software, the migration and evolution of Cu and Cd in the soil were predicted by real simulations. On this basis, a soil management plan was explored. The migration model shows that within 30 days, the pollutant concentration gradually decreases with increasing depth, and most of the heavy metals are concentrated in the surface layer of the soil; after migration, Cd and Cu have different concentrations at various depth levels in the soil. Among them, the soil concentration is the highest in the range of 0 cm–10 cm depth. As the depth reaches 30 cm, the concentration gradually stabilizes. The conclusions of the study provide a scientific basis for the rational use and ecological restoration of mining areas and the prevention and control of soil pollution in mining areas.

Legacy data-based national-scale digital mapping of key soil properties in India

Mapping soil resources at a national scale in large countries such as India is a challenge because of limited soil data available and efforts to collect them. Legacy soil information shows promise; but, there are still challenges that need to be addressed. In this study, we deliver the first digital maps of key soil properties down to 2 m depth across India using legacy data and quantified the relationships between mapped soil properties and bioclimatic and terrain attributes. A legacy database containing analytical data for 1,707 soil profiles with 7,337 soil horizons was collated from reports published by the National Bureau of Soil Survey and Land Use Planning and other Indian organizations. 3D regression kriging based on the random forest model was used to map sand and clay contents, pH and soil organic carbon (SOC) contents at depths as per the GlobalSoilMap specifications. Important covariates included mean monthly temperature and precipitation data from the World Climatic Centre and terrain attributes derived from the NASA’s Shuttle Radar Topography Mission (SRTM) digital elevation model. The uncertainty of the model was quantified as the coefficient of variation of the predicted soil properties by repeated random sampling of the profile dataset into calibration and validation samples at a ratio of 75:25. The performance statistics for the surface soil properties were superior to subsurface soils with the highest Lin’s concordance coefficient (LCC) recorded for soil pH. Estimated LCC values in validation datasets ranged from 0.81 to 0.84 for pH, 0.30 to 0.59 for SOC, 0.48 to 0.56 for clay content, and 0.34 to 0.44 for sand content. Elevation, topographic wetness index, high rainfall, and temperature were observed to be the major drivers for the variability of selected soil properties. Prepared digital soil maps across different agroecological regions showed that sandy soils dominated Western Plains while clayey soils were dominant in the central Deccan Plateau. Soils of the North-Eastern hills were acidic in nature while the Western Ghats and Coastal Plains showed high SOC accumulation. Although finer soil fractions are considered as major drivers of SOC stabilization, rainfall during June (onset of monsoon) was a major climatic driver for SOC in Indian soils. The national maps of soil properties may be linked to soil productivity and provisioning of ecosystem services to guide policy makers for creating region-specific soil management plans.

EVALUACIÓN DE LA CALIDAD DEL SUELO DE UN HUERTO URBANO EN XALAPA, MÉXICO.

Los suelos de las ciudades tienen una historia de formación particular, lo que hace que tengan propiedades variables que deben ser ajustadas cuando se tiene la intención de darles un uso agrícola. En este trabajo evaluamos la calidad del suelo de un área verde urbana en Xalapa, Veracruz (México), previo a la implementación de un huerto universitario, a través de la determinación rápida de algunas propiedades físicas, químicas y biológicas. Se tomaron muestras de suelo mediante la técnica descrita por la NOM-021 RECNAT-2000 y el método de TSBF. Los resultados obtenidos mostraron que el suelo evaluado es de color café y de textura franco arenosa, con agregados de pobre estabilidad, la densidad aparente (DA) fue de (2.52 g/cm3), la capacidad de campo (CC) fue de 49.04 %, su pH es óptimo para el cultivo de hortalizas (6.58) y la materia orgánica (MO) es de clase media (6.45 %). A nivel biológico, la densidad de lombrices fue de 67.2 ind/m2 y el número grupos edáficos (5) por metro cuadrado resultó ser pobre. La cantidad de hojarasca en el mantillo (118.4 g/m2) y la profundidad de las raíces (30.3 cm) fue moderadamente buena; además, la respiración microbiana y los miligramos de glomalina mostraron indicios de que los procesos enzimáticos se están desarrollando eficientemente. La calidad del suelo evaluado fue de condición moderada; sin embargo, es necesario establecer un plan de manejo integral del suelo para mejorar algunas propiedades y fortalecer otras de forma sinérgica

Spatial Distribution of Soil Hydrological Properties in the Kilombero Floodplain, Tanzania

Analysis and interpretation of soil properties dynamics is a keystone in understanding the hydrologic responses and yield potential of floodplain wetlands. This study characterizes the distribution and spatial trends of selected soil physical properties in the Kilombero floodplain, Tanzania. A total of 76 composite soil samples were taken from 0 to 20 cm and 20 to 40 cm depth in a regular grid design across three hydrological zones, related to flooding intensity defined as fringe, middle, and riparian during the rainy season of 2015. The samples were analyzed for soil texture, bulk density, organic carbon, and saturated hydraulic conductivity. Seasonal soil moisture content was monitored at depths of 10, 20, 30, and 40 cm, using 17 frequency domain reflectometry profile probes type PR2, installed at each hydrological zone for 18 months (March 2015–August 2016). Data were subjected to classical statistical and geostatistical analyses. Results showed significant (p < 0.05) differences in bulk density, texture, soil organic carbon (SOC), and saturated hydraulic conductivity (Ksat) across the hydrological zones. Bulk density showed a clear increasing trend towards the fringe zone. Mean Ksat was highest at the riparian zone (69.15 cm·d−1), and clay was higher in the riparian (20.3%) and middle (28.7%) zones, whereas fringe had the highest percentage of sand (33.7–35.9%). Geostatistical spatial results indicated that bulk density, silt, and SOC at 0–20 cm had intermediate dependence, whereas other soil properties at both depths had high spatial dependence. Soil moisture content showed a significant (p < 0.05) difference across the hydrological zones. The riparian zone retained the highest soil moisture content compared to the middle and fringe zone. The temporal soil moisture pattern corresponded to rainfall seasonality and at the riparian zone, soil moisture exhibited a convex shape of sloping curve, whereas a concave sloping curve for topsoil and for the middle zone at the subsoil was observed during the start of the dry season. Our results are seen to contribute to a better understanding of the spatial distribution of soil properties and as a reference for soil and water management planning in the floodplain.

Spatial analysis of soil resources in the Mewat district in the semiarid regions of Haryana, India

The soil characteristics are critical for crop health and its yield and therefore for agriculture. The soil properties are spatially variable and therefore soil resources should be managed as per location-specific requirements. An integrated spatial analysis of the soil resources of Mewat district was conducted to identify the soil resource management zones to develop site-specific soil management plan which might lead to sustained and enhanced crop yield. Spatial analysis of soil resources was conducted by modeling soil fertility and erosion which determines the crop productivity in the region. Soil fertility of the region was modeled using weighted overlay approach using 10 soil parameters, namely nitrogen, phosphorus, potassium, sulfur, iron, zinc, manganese, organic carbon, electrical conductivity, and pH. Each parameter was assigned weights based on their relative importance to agricultural productivity. The modeled soil fertility was classified into three fertility zones, low, medium, and high. Soil fertility was found to be low to moderate in 65% of the area, largely because of the low nitrogen, soil organic carbon, phosphorus concentration, and excessive salinity. Soil erosion was modeled using the universal soil loss equation (USLE) model by estimating rainfall erosivity factor (R), the soil erodibility factor (K), the topographic factors (L and S), cropping factor (C), and the conservation practice factor (P). Soil erosion problems were limited to areas having high elevation with barren land and areas with minimal management practices. The severity of soil erosion was found high in 15% of the region, while the remaining 85% showed low to moderate erosion. Soil fertility and erosion were integrated using the multivariate clustering method to identify soil management zones. The region was delineated into three soil management zones. Zone I (29%) which covers majorly Tarou block, was characterized by high soil fertility and low soil erosion. Zone II (18%) with medium soil fertility and high erosion covers villages of Taoru, Nuh, Nagina, FP Jhirka, and Punhana, which are located in the foothills of Aravalli ranges. Zone III represents the major part of the region, covering Nuh, Nagina, and FP Jhirka blocks (54%) with low soil fertility and erosion conditions. Thus, within the study area, the soil management domains are spatially variable in terms of fertility and soil erosion, and thus zone-specific soil management measures are required to improve the soil condition in order to sustain and improve agriculture production. The study would help the policy makers to design site-specific planning for identified soil resource management zones.

Three-decade long fertilization-induced soil organic carbon sequestration depends on edaphic characteristics in six typical croplands.

Fertilizations affect soil organic carbon (SOC) content but the relative influences of the edaphic and climate factors on SOC storage are rarely studied across wide spatiotemporal scales. This study synthesized long-term datasets of fertilization experiments in six typical Chinese croplands, and calculated annual C input from crops and manure amendments, changes in SOC storage (ΔSOC) and C sequestration efficiency (i.e. the percentage of soil C change per unit of C input, hereafter referred as CSE) in 0–20 cm soil over three decades. Three fertilization treatments include no fertilization (CK), chemical nitrogen, phosphorus and potassium fertilizers (NPK) and combined chemical fertilizers and manure (NPKM). Results showed significant fertilization effects on C input and ΔSOC (NPKM>NPK>CK), and significantly higher CSE in Qiyang at Hunan than Zhengzhou at Henan and Heihe at Heilongjiang. The variance partitioning analysis (VPA) showed more variance of CSE can be explained by edaphic factors (up to 39.7%) than other factors. Furthermore, soil available N content and pH were identified as the major soil properties explaining CSE variance. This study demonstrated key controls of soil fertility factors on SOC sequestration and informs the need to develop strategic soil management plan to promote soil carbon sequestration under long-term intensive fertilization.

Linking climate change perceptions to adaptation and mitigation action

One of the main contributors to anthropogenic climate change is agriculture, although, paradoxically, the sector is also very vulnerable to climate change effects, in particular extreme weather events. The agricultural sector can however make a significant contribution to climate change mitigation through increasing or sustaining soil carbon levels. The perception and action of farmers to anticipated climate change may be a significant determinant of both climate change impacts and mitigation efforts in agriculture. This is the first national-scale study of the perception of climate change by farmers and their associated farming practices regarding mitigation and adaptation. We find that Danish farmers realise that climate change will affect them in the future, and that many are already affected and are taking action to prevent future losses. Almost one fourth of the farmers surveyed stated that they include climate change mitigation in soil management planning. The majority of Danish farmers are already adapting to the effects of climate change, especially through maintaining or expanding drainage areas to reduce the impact of heavy rain, but also by changing soil management practices to increase water infiltration capacity. The study reveals the paradoxical finding that farmers, although believing that climate change is real, and having experienced losses due to adverse climatic events, do not tend to connect the two phenomena. Also there seems to be no link between perceptions of climate change and adaptation/mitigation action. Knowledge gained from this study can be useful for future policymaking on the effect of farm management practices in relation to climate change. Acknowledging farmers’ attitudes and beliefs may be an important component in understanding the responsiveness of the agricultural sector to initiatives to reduce emissions from farming and to improve the robustness of agricultural systems to climate change.