Assessment of Soil Loss in a Typical Ungauged Dam Catchment using RUSLE Model (Maruba Dam, Kenya)

Soil erosion is a serious land degradation problem which nations all over the world are struggling with. It has affected many river catchments most of which are very dynamic and have become quite vulnerable due to human influence. As such, the functionality of the ecosystem has been largely compromised. Soil erosion has been reported as an expensive problem to remedy and therefore numerous of efforts have shifted to its prevention. This has called for estimation of soil loss which has been adequately achieved by use erosion models over the past. One such model is the Revised Universal Soil Loss Equation (RUSLE) which has been applied at catchment level. Maruba dam catchment has become very unhealthy due to the unsustainable modifications of the terrain. This is evident at the rate at which the dam is losing its storage capacity due to sedimentation. The current situation in the dam formed the basis for this study. Information on soil loss within the catchment is missing and as such decision makers do not have a basis for initiating soil and water conservation plans. The methodological framework for this study was the use of RUSLE model integrated in a GIS framework. The parameters of the model were derived using GIS and RS tools. The study revealed that soil loss ranged between 0 and 29 t ha-1 yr-1 and this explains why the dam if silting up at a fast rate. With this set of information on soil loss, the health of the catchment would be adequately restored and this would save the dam from unwarranted sedimentation. Keywords: Soil erosion, catchment, RUSLE, sedimentation, GIS DOI: 10.7176/JEES/11-16-06 Publication date:June 30th 202

Assessing potential of biochar for increasing water-holding capacity of sandy soils

Increasing the water-holding capacity of sandy soils will help improve efficiency of water use in agricultural production, and may be critical for providing enough energy and food for an increasing global population. We hypothesized that addition of biochar will increase the water-holding capacity of a sandy loam soil, and that the depth of biochar incorporation will influence the rate of biochar surface oxidation in the amended soils. Hardwood fast pyrolysis biochar was mixed with soil (0%, 3%, and 6% w/w) and placed into columns in either the bottom 11.4 cm or the top 11.4 cm to simulate deep banding in rows (DBR) and uniform topsoil mixing (UTM) applications, respectively. Four sets of 18 columns were incubated at 30 °C and 80% RH. Every 7 days, 150 mL of 0.001 M calcium chloride solution was added to the columns to produce leaching. Sets of columns were harvested after 1, 15, 29, and 91 days. Addition of biochar increased the gravity-drained water content 23% relative to the control. Bulk density of the control soils increased with incubation time (from 1.41 to 1.45 g cm−3), whereas bulk density of biochar-treated soils was up to 9% less than the control and remained constant throughout the incubation period. Biochar did not affect the CEC of the soil. The results suggest that biochar added to sandy loam soil increases water-holding capacity and might increase water available for crop use

Microbial carbon use efficiency promotes global soil carbon storage

Soils store more carbon than other terrestrial ecosystems$^{1,2}$. How soil organic carbon (SOC) forms and persists remains uncertain$^{1,3}$, which makes it challenging to understand how it will respond to climatic change$^{3,4}$. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss$^{5–7}$. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways$^{4,6,8–11}$, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes$^{12,13}$. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved$^{7,14,15}$. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate

Can Infrared Spectroscopy Be Used to Measure Change in Potassium Nitrate Concentration as a Proxy for Soil Particle Movement?

Displacement of soil particles caused by erosion influences soil condition and fertility. To date, the cesium 137 isotope (137Cs) technique is most commonly used for soil particle tracing. However when large areas are considered, the expensive soil sampling and analysis present an obstacle. Infrared spectral measurements would provide a solution, however the small concentrations of the isotope do not influence the spectral signal sufficiently. Potassium (K) has similar electrical, chemical and physical properties as Cs. Our hypothesis is that it can be used as possible replacement in soil particle tracing. Soils differing in texture were sampled for the study. Laboratory soil chemical analyses and spectral sensitivity analyses were carried out to identify the wavelength range related to K concentration. Different concentrations of K fertilizer were added to soils with varying texture properties in order to establish spectral characteristics of the absorption feature associated with the element. Changes in position of absorption feature center were observed at wavelengths between 2,450 and 2,470 nm, depending on the amount of fertilizer applied. Other absorption feature parameters (absorption band depth, width and area) were also found to change with K concentration with coefficient of determination between 0.85 and 0.99. Tracing soil particles using K fertilizer and infrared spectral response is considered suitable for soils with sandy and sandy silt texture. It is a new approach that can potentially grow to a technique for rapid monitoring of soil particle movement over large areas

Microbial carbon use efficiency promotes global soil carbon storage

Funding Information: We thank H. Yang, M. Schrumpf, T. Wutzler, R. Zheng and H. Ma for their comments and suggestions on this study. This work was supported by the National Natural Science Foundation of China (42125503) and the National Key Research and Development Program of China (2020YFA0608000, 2020YFA0607900 and 2021YFC3101600). F.T. was financially supported by China Scholarship Council during his visit at Food and Agricultural Organization of the United Nations (201906210489) and the Max-Planck Institute for Biogeochemistry (202006210289). The contributions of Y.L. were supported through US National Science Foundation DEB 1655499 and 2242034, subcontract CW39470 from Oak Ridge National Laboratory (ORNL) to Cornell University, DOE De-SC0023514, and the USDA National Institute of Food and Agriculture. S.M. has received funding from the ERC under the European Union’s H2020 Research and Innovation Programme (101001608). The contributions of U.M. were supported through a US Department of Energy grant to the Sandia National Laboratories, which is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. We thank the WoSIS database ( https://www.isric.org/explore/wosis ) for providing the publicly available global-scale SOC database used in this study. Publisher Copyright: © 2023, The Author(s).Peer reviewedPublisher PD

Review of Soil Organic Carbon Measurement Protocols: A US and Brazil Comparison and Recommendation

Soil organic carbon (SOC) change influences the life-cycle assessment (LCA) calculations for globally traded bio-based products. Broad agreement on the importance of SOC measurement stands in contrast with inconsistent measurement methods. This paper focuses on published SOC research on lands managed for maize (Zea mays L.) in the U.S. and sugarcane (Saccharum officinarum L.) in Brazil. A literature review found that reported SOC measurement protocols reflect different sampling strategies, measurement techniques, and laboratory analysis methods. Variability in sampling techniques (pits versus core samples), depths, increments for analysis, and analytical procedures (wet oxidation versus dry combustion) can influence reported SOC values. To improve consistency and comparability in future SOC studies, the authors recommend that: (a) the methods applied for each step in SOC studies be documented; (b) a defined protocol for soil pits or coring be applied; (c) samples be analyzed at 10 cm intervals for the full rooting depth and at 20 cm intervals below rooting until reaching 100 cm; (d) stratified sampling schemes be applied where possible to reflect variability across study sites; (e) standard laboratory techniques be used to differentiate among labile and stable SOC fractions; and (f) more long-term, diachronic approaches be used to assess SOC change. We conclude with suggestions for future research to further improve the comparability of SOC measurements across sites and nations

Coastline shift analysis in data deficient regions: Exploiting the high spatio-temporal resolution Sentinel-2 products

In most developing countries, coastline shift monitoring using in-situ (ground-based) data faces challenges due, e.g., to data unreliability, inconsistency, deficiency, inaccessibility or incompleteness. Even where practically applicable, the traditional “boots on the ground” methods are labour intensive and expensive, thus imposing burden on poor countries struggling to meet other urgent pressing daily needs, i.e., food and medicine. Remote sensing (RS) techniques provide a more efficient and effective way of collecting data for coastline shift analysis. However, moderate spatio-temporal resolution RS products such as the widely used Landsat products (30 m and 16 days) may be insufficient where high accuracy is desired. In 2015, Sentinel-2 Multi-Spectral Instrument (MSI) remotely sensed products with higher spatio-temporal resolution (10 m and 5 days) and high spectral resolution (13 bands), which promises to improve coastline movement monitoring to high accuracy, was launched. Using two war-impacted countries (Liberia and Somalia) as case studies of regions with data deficiency or of poor quality, for the period 2015–2018, this contribution aims at (i) assessing the suitability of the new freely available high spatio-temporal Sentinel-2 products to monitor coastline shift, (ii) assessing the possibility of filling the missing Sentinel-2 gaps with Landsat 8 panchromatic band (15 m) products to provide alternative data source for mapping of coastline movements where Sentinel-2 data is unusable, e.g., due to cloud cover, and (iii), undertake a comparative analysis between Sentinel-2 (10 m), Landsat panchromatic (15 m), and Landsat multi-spectral (30 m). The results of the evaluation indicate 23% (on average) improvement gained by using Sentinel-2 compared to the traditional Landsat 30 m resolution data (i.e., 32% for Liberia and 14% for Somalia). A comparison of 100 check points from Google Earth Pro (i.e., surrogate in-situ reference data) show 91% agreement for Liberia and 85% for Somalia, indicating the potential of using Sentinel-2 data for future coastal shift studies, particularly for the data deficient regions. The results of comparative studies for Sentinel-2, Landsat panchromatic (PAN), and Landsat multi-spectral (MS) show that the percentages of Sentinel-2 and Landsat PAN that falls within 10 m threshold is much higher than Landsat MS by 35% and 26%, respectively, and for the 2016–2017 period, they provide more detailed mapping of the Liberian coastline compared to Landsat MS (30 m). Finally, panchromatic Landsat data with 15 m resolution are found to be capable of filling the missing Sentinel-2 gaps, i.e., where cloud cover hampers its usability