S.J. Jacquemin, M.C. Grunden, A. Clayton, T.A. Dirksen
Saturated buffers are an edge-of-field best management practice designed to reduce nutrient loading into streams. Acting as an extension to drainage water management, these systems use a multichamber control box to raise the water table in the field (i.e., controlled drainage) and then route a portion of the subsurface drainage that does leave the field along the riparian zone using distribution tiles (i.e., saturated buffer), providing an opportunity for biological and chemical processes to reduce nitrogen (N) and phosphorus (P). Saturated buffers are inexpensive and suitable on a wide spatial scale, yet monitoring studies are lacking for many areas of the United States. This study outlines the monitoring of the first saturated buffer in Grand Lake St. Marys Watershed, Ohio. A combination of water samples from groundwater wells, depth loggers in the control box, and area velocity sensors on a comparably sized free-flowing reference site facilitated a complete hydrologic and nutrient budget for the saturated buffer study site’s subsurface drainage over two years. Using data from the free-flowing reference site as a comparison point, controlled drainage was found to have reduced runoff by ~48%. Of the water that did leave the field, ~57% of this was intercepted by the buffer where nutrient concentration reductions of ~85% soluble reactive phosphorus (SRP) and ~59% nitrate (NO3–) were noted comparing field tile to monitoring wells. Routing water through the buffer resulted in annual load reductions of 34.2 kg of N (34%) and 1.27 kg of P (52%) from the 11 ha subwatershed. Compared to previous studies, NO3– load reductions were on the lower end, likely due to the buffer tile only running an average of 35 days (buffer subwatershed) versus 245 days (free-flowing subwatershed) a year; however, SRP load reductions were higher than in previous studies. Evidence of denitrification, chemical adsorption of nutrients to sediment, as well as biological uptake in plants caused these reductions. This saturated buffer study is one of the first in Ohio and suggests additional utilization could reduce nutrient loading in the Great Lakes and Ohio River watersheds.
{"title":"Water quality improvements in Grand Lake St. Marys watershed with the region’s first saturated buffer","authors":"S.J. Jacquemin, M.C. Grunden, A. Clayton, T.A. Dirksen","doi":"10.2489/jswc.2024.00051","DOIUrl":"https://doi.org/10.2489/jswc.2024.00051","url":null,"abstract":"Saturated buffers are an edge-of-field best management practice designed to reduce nutrient loading into streams. Acting as an extension to drainage water management, these systems use a multichamber control box to raise the water table in the field (i.e., controlled drainage) and then route a portion of the subsurface drainage that does leave the field along the riparian zone using distribution tiles (i.e., saturated buffer), providing an opportunity for biological and chemical processes to reduce nitrogen (N) and phosphorus (P). Saturated buffers are inexpensive and suitable on a wide spatial scale, yet monitoring studies are lacking for many areas of the United States. This study outlines the monitoring of the first saturated buffer in Grand Lake St. Marys Watershed, Ohio. A combination of water samples from groundwater wells, depth loggers in the control box, and area velocity sensors on a comparably sized free-flowing reference site facilitated a complete hydrologic and nutrient budget for the saturated buffer study site’s subsurface drainage over two years. Using data from the free-flowing reference site as a comparison point, controlled drainage was found to have reduced runoff by ~48%. Of the water that did leave the field, ~57% of this was intercepted by the buffer where nutrient concentration reductions of ~85% soluble reactive phosphorus (SRP) and ~59% nitrate (NO3–) were noted comparing field tile to monitoring wells. Routing water through the buffer resulted in annual load reductions of 34.2 kg of N (34%) and 1.27 kg of P (52%) from the 11 ha subwatershed. Compared to previous studies, NO3– load reductions were on the lower end, likely due to the buffer tile only running an average of 35 days (buffer subwatershed) versus 245 days (free-flowing subwatershed) a year; however, SRP load reductions were higher than in previous studies. Evidence of denitrification, chemical adsorption of nutrients to sediment, as well as biological uptake in plants caused these reductions. This saturated buffer study is one of the first in Ohio and suggests additional utilization could reduce nutrient loading in the Great Lakes and Ohio River watersheds.","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"86 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141552594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Erratum for Martinez et al., Leveraging ecological monitoring programs to collect soil and geomorphology data across the western United States","authors":"","doi":"10.2489/jswc.2024.00268","DOIUrl":"https://doi.org/10.2489/jswc.2024.00268","url":null,"abstract":"Volume 79(3), p. 135: The legend …","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"24 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Understanding soil carbon (C) balance within agroecosystems is an important piece of reducing agriculture-related climate impacts and improving soil quality. The web-based Nutrient Tracking Tool (NTT) has been widely applied for estimating nutrient fate and transport, erosion potential, and crop yield using the Agricultural Policy Environmental eXtender (APEX) model. NTT simulates a variety of agricultural systems and is in the process of being improved to provide a more holistic understanding of the impact of management practices on agricultural sustainability as it is adopted in various parts of the United States. One improvement in NTT is the incorporation of APEX’s soil organic C (SOC) estimation into NTT to allow decision-makers the ability to estimate how management practices impact C balance on a free and user-friendly platform. In order to test this additional outcome, NTT was used to estimate SOC in a series of simulations using recorded SOC change from a literature review. Nine studies with SOC measurements at least five years apart that took place in the contiguous United States and had sufficient management data to reliably run NTT were selected. The selected studies consisted of 131 paired SOC measurements (initial and final) across a wide range of cropping systems, including no-till, conventional tillage, cover crops, nutrient management systems, and crop rotations. Details from each study location were input into NTT (location, slope, planting date, tillage practice, fertilization rate, and soil properties—texture and initial SOC) and run using modified NTT/APEX 806. Measured SOC and SOC change were then compared with those of predicted values. Overall, the correlation between measured and predicted final SOC was r 2 = 0.57. The average deviation between simulated and measured soil C change was −0.39 ± 0.03 Mg ha−1 (12.5% difference). This corresponds to an average percentage change of 0.27% with the simulation and −0.68% with measured values across all sites; the percentage change is relatively low because of averaging sites with opposing change directions. Sites were also grouped by management practice to determine how NTT functions in varying management practices; the practices with the lowest deviation were continuous corn (0.12 Mg ha−1 error; 39.55% difference) and intensive tillage (−0.16 Mg ha−1 error; −35.33% difference) and the practices with the highest deviation were zero fertilizer systems (3.75 Mg ha−1 error; 146.27% difference). Considering the fact all weather information was obtained from NTT databases (PRISM database) and few parameters were modified in APEX, the results obtained from this comparison study are promising. One major limitation with this study is that most of the measured values for verification came from the Midwest and north central United States with few from the southern or western states. Nevertheless, this initial look is a good first step toward a robust C decision-making tool. In future work w
{"title":"Estimating soil carbon change using the web-based Nutrient Tracking Tool (NTT) with APEX","authors":"D. Menefee, A. Saleh, O. Gallego","doi":"10.2489/jswc.2024.00042","DOIUrl":"https://doi.org/10.2489/jswc.2024.00042","url":null,"abstract":"Understanding soil carbon (C) balance within agroecosystems is an important piece of reducing agriculture-related climate impacts and improving soil quality. The web-based Nutrient Tracking Tool (NTT) has been widely applied for estimating nutrient fate and transport, erosion potential, and crop yield using the Agricultural Policy Environmental eXtender (APEX) model. NTT simulates a variety of agricultural systems and is in the process of being improved to provide a more holistic understanding of the impact of management practices on agricultural sustainability as it is adopted in various parts of the United States. One improvement in NTT is the incorporation of APEX’s soil organic C (SOC) estimation into NTT to allow decision-makers the ability to estimate how management practices impact C balance on a free and user-friendly platform. In order to test this additional outcome, NTT was used to estimate SOC in a series of simulations using recorded SOC change from a literature review. Nine studies with SOC measurements at least five years apart that took place in the contiguous United States and had sufficient management data to reliably run NTT were selected. The selected studies consisted of 131 paired SOC measurements (initial and final) across a wide range of cropping systems, including no-till, conventional tillage, cover crops, nutrient management systems, and crop rotations. Details from each study location were input into NTT (location, slope, planting date, tillage practice, fertilization rate, and soil properties—texture and initial SOC) and run using modified NTT/APEX 806. Measured SOC and SOC change were then compared with those of predicted values. Overall, the correlation between measured and predicted final SOC was r 2 = 0.57. The average deviation between simulated and measured soil C change was −0.39 ± 0.03 Mg ha−1 (12.5% difference). This corresponds to an average percentage change of 0.27% with the simulation and −0.68% with measured values across all sites; the percentage change is relatively low because of averaging sites with opposing change directions. Sites were also grouped by management practice to determine how NTT functions in varying management practices; the practices with the lowest deviation were continuous corn (0.12 Mg ha−1 error; 39.55% difference) and intensive tillage (−0.16 Mg ha−1 error; −35.33% difference) and the practices with the highest deviation were zero fertilizer systems (3.75 Mg ha−1 error; 146.27% difference). Considering the fact all weather information was obtained from NTT databases (PRISM database) and few parameters were modified in APEX, the results obtained from this comparison study are promising. One major limitation with this study is that most of the measured values for verification came from the Midwest and north central United States with few from the southern or western states. Nevertheless, this initial look is a good first step toward a robust C decision-making tool. In future work w","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"1 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141552593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E.O. Ayito, K. John, O.B. Iren, N.M. John, S. Mngadi, R. Moodley, B. Heung
This study hypothesized that biochar produced from different feedstock contains varied nutrient compositions and may ameliorate acidic soil and improve yield parameters of cucumber ( Cucumis sativus ) via an interrelated structure. We aimed to evaluate biochar nutrient composition from different feedstock and inspect the interrelationship between soil pH and yield parameters of cucumber using structural equation modeling (SEM). Eleven treatments consisting of the sole application of biochar (B) from different feedstocks at the rate of 20 t ha−1 and their combinations with poultry manure (i.e., 10 t ha−1 biochar +10 t ha−1 poultry manure) were used. The highest pH value of 5.89 was obtained in fields amended with 20 t ha−1 plantain peel biochar (PPB). We used SEM to find that soil pH produced a negative but significant relationship with fruit weight and length. Combining biochar with poultry manure is recommended for sustainable cucumber production in the tropical region of Nigeria or elsewhere.
{"title":"Effect of biochar treatment on soil pH and cucumber fruit: A demonstration of the importance of biochar amendment on the tropical soils of Nigeria","authors":"E.O. Ayito, K. John, O.B. Iren, N.M. John, S. Mngadi, R. Moodley, B. Heung","doi":"10.2489/jswc.2024.00059","DOIUrl":"https://doi.org/10.2489/jswc.2024.00059","url":null,"abstract":"This study hypothesized that biochar produced from different feedstock contains varied nutrient compositions and may ameliorate acidic soil and improve yield parameters of cucumber ( Cucumis sativus ) via an interrelated structure. We aimed to evaluate biochar nutrient composition from different feedstock and inspect the interrelationship between soil pH and yield parameters of cucumber using structural equation modeling (SEM). Eleven treatments consisting of the sole application of biochar (B) from different feedstocks at the rate of 20 t ha−1 and their combinations with poultry manure (i.e., 10 t ha−1 biochar +10 t ha−1 poultry manure) were used. The highest pH value of 5.89 was obtained in fields amended with 20 t ha−1 plantain peel biochar (PPB). We used SEM to find that soil pH produced a negative but significant relationship with fruit weight and length. Combining biochar with poultry manure is recommended for sustainable cucumber production in the tropical region of Nigeria or elsewhere.","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"40 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ravi Teja Neelipally, Debasish Saha, Sindhu Jagadamma
Agricultural systems have significantly evolved, transitioning from preindustrial organic management to highly mechanized, chemically intensive, and genetically engineered conventional crop production methods. This transformation has led to negative ecological consequences, such as soil degradation, nutrient pollution, and biodiversity loss. In response, the agricultural sector is now pivoting toward restorative and sustainable practices. The pursuit of achieving a balance between production goals and environmental preservation has led to the adoption of various agricultural systems, each having distinct principles, practices, standards, and outcomes. Current agricultural systems encompass a wide range of approaches, such as conventional, conservative, bio-dynamic, agro-ecological, precision, climate-smart, regenerative, organic, regenerative-organic, and sustainable agriculture (Muhie 2022). Conventional farming strategies focus primarily on enhancing productivity, while other specialized strategies have been implemented to address additional challenges like climatic change, soil degradation, and water scarcity. While this diversity can be beneficial, it also creates challenges in comprehension and application due to ambiguous standards and overlapping terms, impacting stakeholders such as consumers, producers, policymakers, agricultural experts, and financial institutions. For example, while regenerative agriculture (RA) is known for soil health benefits, a fiscal assessment of regenerative against traditional livestock farming in New Zealand revealed a decline in productivity and a rise in carbon dioxide (CO2) emissions (Howarth et al. 2022). Similarly, expansion of organic certification to hydroponic and aquaponic farms broadens the concept of organic farming, raising questions about soil-centric organic principles (Legal Information Institute n.d.; Di Gioia and Rosskopf 2021). Furthermore, the adoption of government-endorsed climate-smart agriculture (CSA) philosophies, when backed by multinational corporations, have raised concerns among farmers about the potential misalignment …
{"title":"Defining boundaries and conceptual frameworks for ecologically focused agricultural systems","authors":"Ravi Teja Neelipally, Debasish Saha, Sindhu Jagadamma","doi":"10.2489/jswc.2024.0416a","DOIUrl":"https://doi.org/10.2489/jswc.2024.0416a","url":null,"abstract":"Agricultural systems have significantly evolved, transitioning from preindustrial organic management to highly mechanized, chemically intensive, and genetically engineered conventional crop production methods. This transformation has led to negative ecological consequences, such as soil degradation, nutrient pollution, and biodiversity loss. In response, the agricultural sector is now pivoting toward restorative and sustainable practices. The pursuit of achieving a balance between production goals and environmental preservation has led to the adoption of various agricultural systems, each having distinct principles, practices, standards, and outcomes. Current agricultural systems encompass a wide range of approaches, such as conventional, conservative, bio-dynamic, agro-ecological, precision, climate-smart, regenerative, organic, regenerative-organic, and sustainable agriculture (Muhie 2022). Conventional farming strategies focus primarily on enhancing productivity, while other specialized strategies have been implemented to address additional challenges like climatic change, soil degradation, and water scarcity. While this diversity can be beneficial, it also creates challenges in comprehension and application due to ambiguous standards and overlapping terms, impacting stakeholders such as consumers, producers, policymakers, agricultural experts, and financial institutions. For example, while regenerative agriculture (RA) is known for soil health benefits, a fiscal assessment of regenerative against traditional livestock farming in New Zealand revealed a decline in productivity and a rise in carbon dioxide (CO2) emissions (Howarth et al. 2022). Similarly, expansion of organic certification to hydroponic and aquaponic farms broadens the concept of organic farming, raising questions about soil-centric organic principles (Legal Information Institute n.d.; Di Gioia and Rosskopf 2021). Furthermore, the adoption of government-endorsed climate-smart agriculture (CSA) philosophies, when backed by multinational corporations, have raised concerns among farmers about the potential misalignment …","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"77 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Urban land use, characterized by intense soil disturbance for site development, is rapidly expanding across the globe. This disturbance can have long-lasting effects on urban soil ecosystem service performance (e.g., water infiltration, turfgrass growth, and carbon [C] sequestration). We established a unique, multistakeholder collaboration with a private land-development company, environmental advisory nonprofit organization, and research university to study residential development effects on soil health and the effectiveness of rehabilitation practices. More specifically, we tested the impact of five current, locally recommended soil rehabilitation practices implemented at early stages of urban, residential development. In a controlled, real-world setting, we tested five treatments—a combination of decompaction and organic amendment additions—after major soil disturbances of mass and fine grading (part of subdivision development). Specific treatments included (1) a business-as-usual (or control) with compacted subsoil and 10 cm loosened topsoil, (2) mechanically decompacted subsoil and 10 cm loosened topsoil, (3) biologically decompacted subsoil using a green manure (with tillage radish [ Raphanus sativus ]) and 10 cm loosened topsoil, (4) mechanically decompacted subsoil with 2.5 cm of loosened topsoil mixed with 2.5 cm compost, and (5) mechanically decompacted subsoil mixed with 2.5 cm compost and 2.5 cm loosened topsoil. After turfgrass was established in all plots, per typical practice for erosion control, we measured physical, chemical, and biological soil health properties at 0 to 15 and 15 to 30 cm depths. The tillage radish had little-to-no effect on any soil properties, likely due to poor establishment. Compost amendments increased soil organic matter (+43%), soil test phosphorus (+79%), and soil test potassium (+60%) mostly in the top 0 to 15 cm. Compost amendments had little effect on soil microbial biomass and activity (measured as decomposition); however, they did increase salt-extractable organic C in the top 0 to 15 cm (+220%). We found even stronger effects of mechanical subsoil decompaction, which increased infiltration rate by over 2,000% and time-to-runoff by 463%, on average, providing evidence that deep ripping subsoils improves water influx and reduces runoff from residential lawns. Decompacting subsoil and adding compost had clear benefits to physical and chemical soil health early in urban, residential development. We would recommend land developers use both practices for improving soil ecosystem services in the short term, and there may be longer-term benefits too.
{"title":"Decompaction and organic amendments provide short-term improvements in soil health during urban, residential development","authors":"M.D. McDaniel, G.L. Thompson, P. Sauer","doi":"10.2489/jswc.2024.00111","DOIUrl":"https://doi.org/10.2489/jswc.2024.00111","url":null,"abstract":"Urban land use, characterized by intense soil disturbance for site development, is rapidly expanding across the globe. This disturbance can have long-lasting effects on urban soil ecosystem service performance (e.g., water infiltration, turfgrass growth, and carbon [C] sequestration). We established a unique, multistakeholder collaboration with a private land-development company, environmental advisory nonprofit organization, and research university to study residential development effects on soil health and the effectiveness of rehabilitation practices. More specifically, we tested the impact of five current, locally recommended soil rehabilitation practices implemented at early stages of urban, residential development. In a controlled, real-world setting, we tested five treatments—a combination of decompaction and organic amendment additions—after major soil disturbances of mass and fine grading (part of subdivision development). Specific treatments included (1) a business-as-usual (or control) with compacted subsoil and 10 cm loosened topsoil, (2) mechanically decompacted subsoil and 10 cm loosened topsoil, (3) biologically decompacted subsoil using a green manure (with tillage radish [ Raphanus sativus ]) and 10 cm loosened topsoil, (4) mechanically decompacted subsoil with 2.5 cm of loosened topsoil mixed with 2.5 cm compost, and (5) mechanically decompacted subsoil mixed with 2.5 cm compost and 2.5 cm loosened topsoil. After turfgrass was established in all plots, per typical practice for erosion control, we measured physical, chemical, and biological soil health properties at 0 to 15 and 15 to 30 cm depths. The tillage radish had little-to-no effect on any soil properties, likely due to poor establishment. Compost amendments increased soil organic matter (+43%), soil test phosphorus (+79%), and soil test potassium (+60%) mostly in the top 0 to 15 cm. Compost amendments had little effect on soil microbial biomass and activity (measured as decomposition); however, they did increase salt-extractable organic C in the top 0 to 15 cm (+220%). We found even stronger effects of mechanical subsoil decompaction, which increased infiltration rate by over 2,000% and time-to-runoff by 463%, on average, providing evidence that deep ripping subsoils improves water influx and reduces runoff from residential lawns. Decompacting subsoil and adding compost had clear benefits to physical and chemical soil health early in urban, residential development. We would recommend land developers use both practices for improving soil ecosystem services in the short term, and there may be longer-term benefits too.","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"9 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Settled farming or agriculture has undergone several revolutionary periods ever since its start about 10 millennia ago (Jellason et al. 2021; Akinkuotu 2023). The first Agricultural Revolution was the transition from hunter-gatherer to the settled agriculture about 8,000 BC. The second Agricultural Revolution occurred between the seventeenth and nineteenth centuries when farm size increased, farm mechanization occured, and agricultural products were commercialized and traded. The third, or “Green Revolution,” began in the early twentieth century when genetically improved and dwarf varieties of cereals (rice [ Oryza sativa L.], wheat [ Triticum aestivum L.], and corn [ Zea mays L.]) were grown with heavy inputs of agro-chemicals (fertilizers and pesticides), leading to drastic increases in crop yield (Chakravarti 1973; Borlaug 2001; Hardin 2009), but severe adverse effects on the environment (John and Babu 2021). The Green Revolution had two interrelated stages: from 1960 to 2000 it was based on seed-centric technologies (Borlaug 2001), and 2000 to 2020s it was based on soil-centric technologies with focus on soil carbon (C) sequestration (Lal 2004), eco-intensification (Martin-Guay et al. 2018), impact (Evenson and Gollin 2003), and adaptation to and mitigation of anthropogenic climate change (Lal 2013; Lal et al. 2011; Muñoz and Zornoza 2018; Hou 2021). The soil-centric Green Revolution, based on judicious management of soil, crops, water, climate change, etc., paved the way for the use of artificial intelligence (AI), and thus transformation into a fourth Agricultural Revolution. The fourth revolution involves the use of AI during the early twenty-first century to address the challenges of agriculture. It is called …
{"title":"Artificial intelligence for assessing organic matter content and related soil properties","authors":"Rattan Lal","doi":"10.2489/jswc.2024.0403a","DOIUrl":"https://doi.org/10.2489/jswc.2024.0403a","url":null,"abstract":"Settled farming or agriculture has undergone several revolutionary periods ever since its start about 10 millennia ago (Jellason et al. 2021; Akinkuotu 2023). The first Agricultural Revolution was the transition from hunter-gatherer to the settled agriculture about 8,000 BC. The second Agricultural Revolution occurred between the seventeenth and nineteenth centuries when farm size increased, farm mechanization occured, and agricultural products were commercialized and traded. The third, or “Green Revolution,” began in the early twentieth century when genetically improved and dwarf varieties of cereals (rice [ Oryza sativa L.], wheat [ Triticum aestivum L.], and corn [ Zea mays L.]) were grown with heavy inputs of agro-chemicals (fertilizers and pesticides), leading to drastic increases in crop yield (Chakravarti 1973; Borlaug 2001; Hardin 2009), but severe adverse effects on the environment (John and Babu 2021). The Green Revolution had two interrelated stages: from 1960 to 2000 it was based on seed-centric technologies (Borlaug 2001), and 2000 to 2020s it was based on soil-centric technologies with focus on soil carbon (C) sequestration (Lal 2004), eco-intensification (Martin-Guay et al. 2018), impact (Evenson and Gollin 2003), and adaptation to and mitigation of anthropogenic climate change (Lal 2013; Lal et al. 2011; Muñoz and Zornoza 2018; Hou 2021). The soil-centric Green Revolution, based on judicious management of soil, crops, water, climate change, etc., paved the way for the use of artificial intelligence (AI), and thus transformation into a fourth Agricultural Revolution. The fourth revolution involves the use of AI during the early twenty-first century to address the challenges of agriculture. It is called …","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"39 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C.T. Nietch, R.J. Hawley, A. Safwat, J.R. Christensen, M.T. Heberling, J. McManus, R. McClatchey, H. Lubbers, N.J. Smucker, E. Onderak, S. Macy
The negative effects of nutrient pollution in streams, rivers, and downstream waterbodies remain widespread global problems. Understanding the cost-effectiveness of different strategies for mitigating nutrient pollution is critical to making informed decisions and defining expectations that best utilize limited resources, which is a research priority for the US Environmental Protection Agency. To this end, we modeled nutrient management practices including residue management, cover crops, filter strips, grassed waterways, constructed wetlands, and reducing fertilizer in the upper East Fork of the Little Miami River, an 892 km2 watershed in southwestern Ohio, United States. The watershed is 64% agriculture with 422 km2 of row crops contributing an estimated 71% of the system’s nutrient load. The six practices were modeled to treat row crop area, and among them, constructed wetlands ranked highest for their low costs per kilogram of nutrient removed. To meet a 42% phosphorus (P) reduction target for row crops, the model results suggested that the runoff from 85.5% of the row crop area would need to be treated by the equivalent of 3.61 km2 of constructed wetlands at an estimated cost of US$2.4 million annually (or US$48.5 million over a 20-year life cycle). This prompted a series of projects designed to understand the feasibility (defined in terms of build, treatment, and cost potential) of retrofitting the system with the necessary extent of constructed wetlands. The practicalities of building this wetland coverage into the system, while leading to innovation in unit-level design, has highlighted the difficulty of achieving the nutrient reduction target with wetlands alone. Approximately US$1.2 million have been spent on constructing 0.032 km2 of wetlands thus far and a feasibility analysis suggests a cost of US$38 million for an additional 0.409 km2. However, the combined expenditures would only achieve an estimated 13% of the required treatment. The results highlight the potential effectiveness of innovative design strategies for nutrient reduction and the importance of considering realistic field-scale build opportunities, which include accounting for acceptance among landowners, in watershed-scale nutrient reduction simulations using constructed wetlands.
{"title":"Implementing constructed wetlands for nutrient reduction at watershed scale: Opportunity to link models and real-world execution","authors":"C.T. Nietch, R.J. Hawley, A. Safwat, J.R. Christensen, M.T. Heberling, J. McManus, R. McClatchey, H. Lubbers, N.J. Smucker, E. Onderak, S. Macy","doi":"10.2489/jswc.2024.00077","DOIUrl":"https://doi.org/10.2489/jswc.2024.00077","url":null,"abstract":"The negative effects of nutrient pollution in streams, rivers, and downstream waterbodies remain widespread global problems. Understanding the cost-effectiveness of different strategies for mitigating nutrient pollution is critical to making informed decisions and defining expectations that best utilize limited resources, which is a research priority for the US Environmental Protection Agency. To this end, we modeled nutrient management practices including residue management, cover crops, filter strips, grassed waterways, constructed wetlands, and reducing fertilizer in the upper East Fork of the Little Miami River, an 892 km2 watershed in southwestern Ohio, United States. The watershed is 64% agriculture with 422 km2 of row crops contributing an estimated 71% of the system’s nutrient load. The six practices were modeled to treat row crop area, and among them, constructed wetlands ranked highest for their low costs per kilogram of nutrient removed. To meet a 42% phosphorus (P) reduction target for row crops, the model results suggested that the runoff from 85.5% of the row crop area would need to be treated by the equivalent of 3.61 km2 of constructed wetlands at an estimated cost of US$2.4 million annually (or US$48.5 million over a 20-year life cycle). This prompted a series of projects designed to understand the feasibility (defined in terms of build, treatment, and cost potential) of retrofitting the system with the necessary extent of constructed wetlands. The practicalities of building this wetland coverage into the system, while leading to innovation in unit-level design, has highlighted the difficulty of achieving the nutrient reduction target with wetlands alone. Approximately US$1.2 million have been spent on constructing 0.032 km2 of wetlands thus far and a feasibility analysis suggests a cost of US$38 million for an additional 0.409 km2. However, the combined expenditures would only achieve an estimated 13% of the required treatment. The results highlight the potential effectiveness of innovative design strategies for nutrient reduction and the importance of considering realistic field-scale build opportunities, which include accounting for acceptance among landowners, in watershed-scale nutrient reduction simulations using constructed wetlands.","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"48 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141152698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Productions of corn ( Zea mays L.) and soybean ( Glycine max L.) in the midwestern United States are the primary source of nitrogen (N) degrading local and downstream surface waters. Conservation crop rotation involves growing a series of crop phases in a field, reducing fallow periods and enhancing N demand. The objective of this study was to contrast conventional rotations of corn–soybean (CS) with conservation rotations of corn–soybean–winter wheat ( Triticum aestivum L.; CSW) as N management tools using a mass balance approach. We calculated N balances (∑Inputs – ∑Outputs) and loads, as both nitrate-N (NO3−-N) and total N (TN), for fields with CS ( n = 18) and CSW ( n = 12) rotations to examine crop- and rotation-specific patterns of N surplus, deficit, and loss. Using data from all individual years ( n = 169), we found median N balance indicated surplus N in corn phases (CSW-corn: 112 kg N ha−1; CS-corn: 51 kg N ha−1) compared to N deficits in wheat (−1.3 kg N ha−1) and soybean (CS-soybean: −110 kg N ha−1; CSW-soybean: −92 kg N ha−1) phases. Median N loss was least in wheat (8 kg NO3−-N ha−1; 11 kg TN ha−1) and soybean phases (CS-soybean: 18 kg NO3−-N ha−1, 21 kg TN ha−1; CSW-soybean: 17 kg NO3−-N ha−1, 23 kg TN ha−1) and greatest in corn phases (CS-corn: 31 kg NO3−-N ha−1, 35 kg TN ha−1; CSW-corn: 27 kg NO3−-N ha−1, 34 kg TN ha−1). The median of average annual N balance was greater in CSW (14 kg N ha−1) than CS fields (−29 kg N ha−1), yet the medians of average annual N loss were similar (e.g., CSW: 19 kg NO3−-N ha−1; CS: 22 kg NO3−-N ha−1). These results suggest that including winter wheat into the CS rotation may have the potential to address N surplus pools and reduce N loss to downstream waters.
{"title":"Nitrogen balances and losses in conservation cropping systems across a tile-drained landscape in Ohio, United States","authors":"B.R. Hanrahan, K.W. King, K.R. Rumora, J.H. Stinner","doi":"10.2489/jswc.2024.00055","DOIUrl":"https://doi.org/10.2489/jswc.2024.00055","url":null,"abstract":"Productions of corn ( Zea mays L.) and soybean ( Glycine max L.) in the midwestern United States are the primary source of nitrogen (N) degrading local and downstream surface waters. Conservation crop rotation involves growing a series of crop phases in a field, reducing fallow periods and enhancing N demand. The objective of this study was to contrast conventional rotations of corn–soybean (CS) with conservation rotations of corn–soybean–winter wheat ( Triticum aestivum L.; CSW) as N management tools using a mass balance approach. We calculated N balances (∑Inputs – ∑Outputs) and loads, as both nitrate-N (NO3−-N) and total N (TN), for fields with CS ( n = 18) and CSW ( n = 12) rotations to examine crop- and rotation-specific patterns of N surplus, deficit, and loss. Using data from all individual years ( n = 169), we found median N balance indicated surplus N in corn phases (CSW-corn: 112 kg N ha−1; CS-corn: 51 kg N ha−1) compared to N deficits in wheat (−1.3 kg N ha−1) and soybean (CS-soybean: −110 kg N ha−1; CSW-soybean: −92 kg N ha−1) phases. Median N loss was least in wheat (8 kg NO3−-N ha−1; 11 kg TN ha−1) and soybean phases (CS-soybean: 18 kg NO3−-N ha−1, 21 kg TN ha−1; CSW-soybean: 17 kg NO3−-N ha−1, 23 kg TN ha−1) and greatest in corn phases (CS-corn: 31 kg NO3−-N ha−1, 35 kg TN ha−1; CSW-corn: 27 kg NO3−-N ha−1, 34 kg TN ha−1). The median of average annual N balance was greater in CSW (14 kg N ha−1) than CS fields (−29 kg N ha−1), yet the medians of average annual N loss were similar (e.g., CSW: 19 kg NO3−-N ha−1; CS: 22 kg NO3−-N ha−1). These results suggest that including winter wheat into the CS rotation may have the potential to address N surplus pools and reduce N loss to downstream waters.","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"96 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141152714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In an attempt to restore degraded rangelands in the western United States, thousands of water and erosion control structures such as earthen water spreaders and contour berms were built in the mid 1900s to control runoff and sediment. Although many were installed by the newly formed USDA Soil Conservation Service, many others were designed without the benefit of local hydrologic data or technical design guidance. As a result, there is a wide range in the efficacy of these structures, and in many cases, the current status of hydrologic process interactions is unknown. In addition, structurally compromised, abandoned, and unmaintained structures are now interacting with runoff and sediment contrary to their intended purpose, in some cases exacerbating erosion. Because these structures are typically small relative to the resolution of available topographic data, they are not generally accounted for in runoff simulation models. Recent years have marked the increasing availability of LiDAR-based topographic data of sufficiently high resolution to incorporate water and erosion control structures in the digital elevation models underpinning hydrologic models. However, beyond the challenges of data acquisition, modeling tools capable of resolving berm topographies and characterizing their hydrologic impacts are needed. Here, the potential hydrologic impacts of water spreader berms are simulated in virtual experiments using a rainfall-runoff model (specifically, the Saint Venant Equations). The model simulations characterize the local and hillslope-scale effects of berms across a range of storm intensities, landscape attributes, and berm shapes while accounting for berm topography and elevated soil permeability upslope of berms in response to vegetation growth. We demonstrate how berms alter surface runoff and create spatially varied runoff patterns, and describe the impact of berm removal on re-establishing connectivity patterns.
为了恢复美国西部退化的牧场，人们在 20 世纪中期建造了数以千计的水和侵蚀控制结构，如土制扩水器和等高线护堤，以控制径流和沉积物。尽管其中许多是由新成立的美国农业部水土保持局安装的，但还有许多是在没有当地水文数据或技术设计指导的情况下设计的。因此，这些结构的功效差别很大，而且在许多情况下，水文过程相互作用的现状也不得而知。此外，结构受损、废弃和未维护的结构目前与径流和沉积物的相互作用与其预期目的背道而驰，在某些情况下会加剧侵蚀。由于相对于现有地形数据的分辨率而言，这些结构通常较小，因此径流模拟模型通常不会考虑它们。近年来，基于激光雷达的高分辨率地形数据越来越多，可以将水和侵蚀控制结构纳入水文模型所需的数字高程模型中。然而，除了数据采集方面的挑战之外，还需要能够解析护堤地形并描述其水文影响的建模工具。在此，我们使用降雨-径流模型（特别是 Saint Venant 方程）在虚拟实验中模拟了扩水护堤对水文的潜在影响。模型模拟描述了护堤在各种暴雨强度、景观属性和护堤形状下对当地和山坡的影响，同时考虑了护堤地形和护堤上坡土壤渗透性因植被生长而提高的情况。我们展示了护堤如何改变地表径流并形成空间上不同的径流模式，并描述了移除护堤对重建连通性模式的影响。
{"title":"Resolving the hydrologic signature of water spreader berms in the US Southwest","authors":"O. Crompton, M. Nichols, D. Lapides, H. Xu","doi":"10.2489/jswc.2024.00086","DOIUrl":"https://doi.org/10.2489/jswc.2024.00086","url":null,"abstract":"In an attempt to restore degraded rangelands in the western United States, thousands of water and erosion control structures such as earthen water spreaders and contour berms were built in the mid 1900s to control runoff and sediment. Although many were installed by the newly formed USDA Soil Conservation Service, many others were designed without the benefit of local hydrologic data or technical design guidance. As a result, there is a wide range in the efficacy of these structures, and in many cases, the current status of hydrologic process interactions is unknown. In addition, structurally compromised, abandoned, and unmaintained structures are now interacting with runoff and sediment contrary to their intended purpose, in some cases exacerbating erosion. Because these structures are typically small relative to the resolution of available topographic data, they are not generally accounted for in runoff simulation models. Recent years have marked the increasing availability of LiDAR-based topographic data of sufficiently high resolution to incorporate water and erosion control structures in the digital elevation models underpinning hydrologic models. However, beyond the challenges of data acquisition, modeling tools capable of resolving berm topographies and characterizing their hydrologic impacts are needed. Here, the potential hydrologic impacts of water spreader berms are simulated in virtual experiments using a rainfall-runoff model (specifically, the Saint Venant Equations). The model simulations characterize the local and hillslope-scale effects of berms across a range of storm intensities, landscape attributes, and berm shapes while accounting for berm topography and elevated soil permeability upslope of berms in response to vegetation growth. We demonstrate how berms alter surface runoff and create spatially varied runoff patterns, and describe the impact of berm removal on re-establishing connectivity patterns.","PeriodicalId":50049,"journal":{"name":"Journal of Soil and Water Conservation","volume":"17 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141152707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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