Agricultural Best Management Practices Research Articles

Identification of critical areas and evaluation of best management practices using SWAT for sustainable watershed management

Identification of critical erosion-prone areas and selection of best management practices (BMPs) for watersheds are necessary to control their degradation by reducing sediment yields. The current research assesses and proposes a combination of potential BMPs for the Baitarani catchment in India using the Soil and Water Assessment Tool (SWAT). After the successful calibration and validation of the SWAT model developed for this catchment, the model was applied to evaluate the efficacy of eight agricultural and structural management practices and their combinations (three scenarios) for controlling sediment yields at watershed and sub-watershed levels as well as to assess the impacts of combined BMPs on water balance components. A combination of BMPs was found more effective in reducing sediment yields than individual BMPs. Comparative evaluation revealed that structural BMPs (0.66–70%) are better than agricultural BMPs (2–7%) in minimizing sediment yields at watershed level. The costly measures like grade and streambank stabilization structures can reduce the sediment yield up to 70% at the watershed level. The modeling results of the impacts of different combinations of BMPs (three scenarios) indicated that if all the eight BMPs are implemented, the reduction of sediment yields is increased by 76% and 80% at sub-watershed and watershed levels, respectively compared to the Base Scenario. Based on funds availability, a suitable combination of BMPs can be adopted by the concerned decision-makers to effectively reduce sediment yields in the study area. Further, the simulation results of BMPs impacts on water balance components revealed that the annual average surface runoff reduces by 4–14% in the three scenarios, while aquifer recharge (6.8–8.7%), baseflow (8–10.5%), and percolation (1.2–3.9%) increase due to implementation of BMPs. Overall, the findings of this study are very useful for ensuring sustainable management of land and other resources at a catchment scale.

Evaluation of best management practices with greenhouse gas benefits for salt-affected paddy soils in South Asia

Anthropogenic climate change has caused increased soil salinity in South Asia due to saltwater intrusion caused by sea level rise, input of fertilizers with high salt index, and irrigation malpractices, etc. Salinity has a multitude of impacts on plant and soil processes, leading to alterations in gas fluxes and rice productivity. The remedial measures adopted on salt-affected soils to reduce the salinity effect could enhance future climate change if they cause an increase in greenhouse gas (GHG) emissions. This study was conducted to find the best agricultural management practices (BMPs) for salt-affected soils in rice cropping systems (i.e. the major cropping system in Asia) in four South Asian countries (Sri Lanka, India, Bangladesh and Pakistan) considering net GHG emissions and other socioeconomic benefits associated with the adopted measures. The salinity-affected sites were selected based on available information (e.g. agricultural statistics and maps). Site-level measurements on soil parameters and GHG emissions were made in control- and managed plots and farmer surveys were conducted. Although organic amendments ameliorated salinity, it could cause a net increase in carbon dioxide or methane emissions depending on the soil conditions, particularly during the initial stages. This impact could be ameliorated by combining organic amendments with other management practices. In the Indo-Gangetic region, poor soil drainage causing anaerobic conditions favoured nitrous oxide emission under low to medium salinity. Yield losses and emissions in high salinity sites were controlled through organic amendment, irrigation and rice-fallow cropping sequence. The combination of transplanting of rice seedlings, the addition of organic matter, and intermittent irrigated water levels was identified as the BMP for Sri Lankan farmers. The outcome of this project will be used to raise awareness among farmers and policymakers.

Spatio-temporal critical source area patterns of runoff pollution from agricultural practices in the Colombian Andes

Lake Riogrande II, located in the central region of the Colombian Andes, has eutrophication due to a progressive increase of runoff pollution from upstream intensive dairy cattle and agricultural activities in the watershed. Public and private entities have invested in programs aimed at adopting the best agricultural management practices (BMP). BMP is a general formulation of recommended criteria and, therefore, not universally fit all problems. For example, the corrective measures taken so far demonstrate difficulties in selecting and allocating BMPs aligned to the space-time hydrological variability within the watershed. This research analyses the spatio-temporal dynamics of BMP pollution patterns. The study is built on the concept of critical source areas of runoff pollution from agricultural practices in the Colombia Andes. Fieldwork was conducted with the participation of farmers to collect spatial data of the current management operations for potato (Solanum tuberosum), tree tomato (Solanum betaceum), and dairy agriculture. A Soil Water Assessment model is used to simulate agricultural and hydrological processes. The model was calibrated using observed discharge, nitrate-N (NO3—N), and soluble phosphorus (P) concentrations at a monthly scale. The origin of pollution at the catchment scale was used applying the critical source areas (CSAs) method. This paper proposes for this analysis a new spatio-temporal CSA index (ST-CSA) to represent the behavior of the CSAs simultaneously in space and time. For this, several aggregated CSA in time were analyzed for monthly and annual time steps. Results indicate that there is an essential difference in the aggregation of CSA in time, and pollution location changes significantly using the ST-CSA. As expected, the highest number of CSAs occurs during the rainy months. However, these CSAs are located in the region with the lowest precipitation levels in the agricultural areas dominated by potato, tree tomato, and dairy agriculture located within the watershed. These areas vary significantly from 24.07% of the entire area of the basin (1034.348 km2), and it could reach a maximum value of 61.78%. Despite the model uncertainties, the results highlight the importance of identifying spatio-temporal CSAs to select BMPs with the highest potential of nitrogen and phosphorus losses reduction - such as the adaptation of fertilization schedules - applicable to the study watershed.

Multi-Variable Sensitivity Analysis, Calibration, and Validation of a Field-Scale SWAT Model: Building Stakeholder Trust in Hydrologic and Water Quality Modeling

HighlightsSWAT can adequately simulate runoff, soil moisture, cotton and peanut yields, and nitrate at field scale.Muskingum routing and adjusting DIS_STREAM are important to simulate fields as watersheds rather than HRUs.Crop yield calibration is critical for improving SWAT model robustness in nutrient transport simulations and for building stakeholder trust.SWAT can quantify the impacts of different management scenarios at the field scale.Abstract. Multi-variable calibration of a field-scale Soil and Water Assessment (SWAT) model is critical for understanding the true impacts of irrigation and nutrient best management practices (BMPs) on hydrology, water quality, and agricultural productivity and for building stakeholder trust for eventual BMP implementation at the watershed scale. This study evaluated the ability of SWAT to simulate runoff, soil moisture, cotton and peanut yields, and nitrate in conventionally tilled and strip-tilled plots while also evaluating the differences in hydrological and nutrient simulation parameters for the two tillage practices. Modeling results showed that SWAT adequately simulated runoff, soil moisture, cotton and peanut yields, and nitrate at the field scale and that calibrated values for the curve number of operation (CNOP) were different for the conventionally tilled and strip-tilled plots and critical to runoff calibration. It was also important to change the routing method from variable storage to Muskingum and to adjust DIS_STREAM for runoff simulation if the field was to be simulated as a watershed rather than as an HRU. Sequential calibration of surface runoff, soil moisture, crop yield, and nitrate showed that crop yield can be an important consideration for improving SWAT model robustness in nutrient transport simulations. Soil moisture calibration did not have a significant effect on runoff simulations. Evaluation of the impacts of different management scenarios showed that soil moisture sensor-based irrigation, cover crop, and strip tillage had the highest potential for reducing nutrient loss and conserving water while maintaining agricultural productivity in southern Georgia. This study also demonstrated to stakeholders that the SWAT model can successfully quantify the impacts of different management scenarios on their farm fields. Keywords: Agricultural BMPs, Field-scale SWAT, Multi-variable calibration, SWAT, SWAT-CUP.

Multi-site watershed model calibration for evaluating best management practice effectiveness in reducing fecal pollution

In this study, the Soil and Water Assessment Tool (SWAT) is coupled with the Bacteria Source Load Calculator (BSLC) to develop alternative scenarios of agricultural best management practice (BMP) implementation and septic system repair to achieve total maximum daily load (TMDL) targets for Escherichia coli (E. coli) in a small agricultural watershed located in Michigan, USA. Due to the uncertainty involved in bacterial source estimation from wildlife and failing septic systems in agricultural watersheds, we propose a method for estimating their respective bacteria loading during SWAT calibration, which was performed at eight sampling locations and validated at a ninth. BMP implementation scenarios were prioritized based on their ability to meet TMDL targets at the lowest cost using a spatially targeted subwatershed ranking identifying the greatest E. coli source contribution. BMP effectiveness is driven by E. coli source locations defined in the BSLC-SWAT linkage. The framework developed here, from linking BSLC to SWAT to ranking subwatersheds, was effective in meeting the TMDL targets and is readily transferable to other watersheds. Agricultural BMPs were unsuccessful in meeting TMDL targets, but the target can be met by repairing about 60 of 110 estimated failing septic tanks.

Evaluating efficiencies and cost-effectiveness of best management practices in improving agricultural water quality using integrated SWAT and cost evaluation tool

Agricultural conservation practices, or agricultural best management practices (BMPs), can reduce nutrient loading and help address harmful algal blooms (HABs). HABs in the western basin of Lake Erie, which are largely caused by phosphorus losses from the Maumee River watershed, are critical in the recent years. In this study, a new BMP cost tool was developed. Then the Soil and Water Assessment Tool (SWAT) and the new BMP cost tool were integrated to explore efficiencies and cost-effectiveness of BMPs in an agricultural catchment of the Maumee River watershed with various scenarios. The scenarios included individual BMPs applied in 100% of suitable areas, individual BMPs targeting Dissolved Reactive Phosphorus (DRP) and Total Phosphorus (TP) critical areas, and BMPs implemented in series. In addition, a cost-effective approach for the selections and placements of BMPs in agricultural watersheds was developed as an alternative to running complex optimization tools that are not applicable to large watersheds. The cost-effective approach applied BMPs based on cost-effectiveness rankings starting from the most cost-effective one. Results showed that: (1) BMPs implemented in series, which reduced pollutant loads more than individual BMPs, were not as cost-effective as some individual BMPs; (2) among all scenarios, filter strips targeting DRP/TP critical areas were the most cost-effective in reducing yearly/spring DRP/TP losses; (3) to obtain the watershed management plan goal of reducing March-July DRP/TP losses by 40%, implementing BMPs one by one in critical areas based on the cost-effectiveness rankings of individual BMPs in DRP/TP critical areas was the most cost-effective; and (4) the simulation results, modeling tools, and cost-effective approach can help create agricultural BMP strategies to cost-efficiently improve water quality.

A SWAT-based optimization tool for obtaining cost-effective strategies for agricultural conservation practice implementation at watershed scales.

To address the harmful algal blooms problem in Lake Erie, one solution is to determine the most cost-effective strategies for implementing agricultural best management practices (BMPs) in the Maumee River watershed. An optimization tool, which combines multi-objective optimization algorithms, SWAT (Soil and Water Assessment Tool), and a computational efficient framework, was created to optimally identify agricultural BMPs at watershed scales. The optimization tool was demonstrated in the Matson Ditch watershed, an agricultural watershed in the Maumee River basin considering critical areas (25% of the watershed with the greatest pollutant loadings per area) and the entire watershed. The initial implementation of BMPs with low expenditures greatly reduced pollutant loadings; beyond certain levels of pollutant reductions, additional expenditures resulted in less significant reductions in pollutant loadings. Compared to optimization for the entire watershed, optimization in critical areas can greatly reduce computational time and obtain similar optimization results for initial reductions in pollutant loadings, which were 10% for Dissolved Reactive Phosphorus (DRP) and 38% for Total Phosphorus (TP); however, for greater reductions in pollutant loadings, critical area optimization was less cost-effective. With the target of simultaneously reducing March-July DRP/TP losses by 40%, the optimized scenario that reduced DRP losses by 40% was found to reduce 51.1% of TP; however, the optimized scenario that reduced TP losses by 40% can only decrease 11.3% of DRP. The optimization tool can help stakeholders identify optimal types, quantities, and spatial locations of BMPs that can maximize reductions in pollutant loadings with the lowest BMP costs.

Modeling the impacts of agricultural best management practices on runoff, sediment, and crop yield in an agriculture-pasture intensive watershed.

Best management practices (BMPs) are commonly used to reduce sediment loadings. In this study, we modeled the Fort Cobb Reservoir watershed located in southwestern Oklahoma, USA using the Soil and Water Assessment Tool (SWAT) and evaluated the impacts of five agricultural BMP scenarios on surface runoff, sediment yield, and crop yield. The hydrological model, with 43 sub-basins and 15,217 hydrological response units, was calibrated (1991–2000) and validated (2001–2010) against the monthly observations of streamflow, sediment grab samples, and crop-yields. The coefficient of determination (R2), Nash-Sutcliffe efficiency (NS) and percentage bias (PB) were used to determine model performance with satisfactory values of R2 (0.64 and 0.79) and NS (0.61 and 0.62) in the calibration and validation period respectively for streamflow. We found that contouring practice reduced surface runoff by more than 18% in both conservation tillage and no-till practices for all crops used in this modeling study. In addition, contour farming with either conservation tillage or no-till practice reduced sediment yield by almost half. Compared to the conservation tillage practice, no-till practice decreased sediment yield by 25.3% and 9.0% for cotton and grain sorghum, respectively. Using wheat as cover crop for grain sorghum generated the lowest runoff followed by its rotation with canola and cotton regardless of contouring. Converting all the crops in the watershed into Bermuda grass resulted in significant reduction in sediment yield (72.5–96.3%) and surface runoff (6.8–38.5%). The model can be used to provide useful information for stakeholders to prioritize ecologically sound and feasible BMPs at fields that are capable of reducing sediment yield while increasing crop yield.

Sensitivity analysis of C and N modules in biogeochemical crop and grassland models following manure addition to soil

Process‐based crop and grassland models estimating carbon (C) and nitrogen (N) dynamics are widely used to investigate best management practices in agriculture. They integrate several processes in a complex structure, but studies where modules corresponding to specific processes extracted from the whole model structure are assessed independently are uncommon. With the support of documented aerobic incubation trials in manure‐amended soils, a sensitivity analysis was performed on the C–N cycling processes of four modules (MOD1–4), corresponding to the models APSIM, EPIC, FASSET and STICS. The results showed that the parameter ‘substrate use efficiency’ had the most effect on the predicted values of net CO2 emissions and net N mineralization, together with the C/N ratio of the soil microbial biomass. They explained 74–75% on average of both output variances, whereas parameters determining manure C and N partitioning and first‐order decomposition constants of manure pools explained, on average, an additional 17–19%. Efforts should be focused on calibrating these parameters for more accurate simulations. The greater sensitivity of both outputs to parameters related to manure pools in more complex modules (MOD2–4) facilitates their adaptation to specific contexts, whereas MOD1 probably requires that parameters related to soil pools are also adapted to specific applications. Parameter interactions were limited, becoming noticeable only in situations of N‐limited soil organic matter decomposition. Models MOD1 and MOD3 allowed the C/N ratio of the soil microbial biomass to vary temporarily; therefore, they were less sensitive to mineral N availability and more easily adapted to a wide range of situations. This study provides essential information to support the development of state‐of‐the‐art biogeochemical models.Highlights We compared four C–N modules embedded in process‐based biogeochemical models. We used sensitivity analysis to assess the simulation of manure decomposition in soil. We identified a few parameters that influenced CO2 emissions and N mineralization. We found that substrate use efficiency explained most of the output variance for all models.

A Review of Studies Documenting the Effects of Agricultural Best Management Practices on Physiochemical and Biological Measures of Stream Ecosystem Integrity

After decades of efforts by the agricultural and scientific communities to manage the impacts of farming through Best Management Practice (BMP) implementation, there is a need to communicate to program managers and policy makers how effective these practices actually are via their expected effects on aquatic ecosystems. Land managers, biologists, funders, and policy makers could all greatly benefit from how to account for factors that influence reductions in compounds accomplished by BMP projects, to set expectations for physiochemical and biological community responses. To date there have been a great deal of studies on how BMPs may relate to nutrients and sediment in streams, and there is some professional consensus on expected outcomes on water chemistry. Studies based on observational and/ or modelled data have yielded very broad ranges of 0–92% reductions in nitrogen compounds, 0–91% in phosphorus compounds, and 0–90% in total suspended sediments; these ranges make it difficult to choose values for reliable models and predictions. Uncertainty in expected abiotic responses to BMP implementation also implies a potentially broad range of biotic responses. In this review, we synthesize results from studies investigating how the application of agricultural BMPs affect the water quality and ecological integrity of nearby water bodies and provide suggestions for monitoring BMP projects to better understand the effects of these practices. The objective of this review is to compare study results on BMP effectiveness as well as to contribute information for decision-making on BMP implementation. Our synthesis highlights the high variability in reported BMP impacts and, subsequently, the need for single studies to be interpreted with caution. We conclude with recommendations for land management and further studies of BMP effectiveness.

Use of a calibrated SWAT model to evaluate the effects of agricultural BMPs on sediments of the Kalaya river basin (North of Morocco)

Soil erosion from agricultural fields is a worldwide problem, to influence water quality, soil fertility and reservoir sedimentation especially in Mediterranean countries such as Morocco. In fact, this work assesses the effects of Best Management Practices (BMPs) on sediments using the Soil and Water Assessment Tool (SWAT) model in the Kalaya watershed in Northern Morocco, to recommend the most appropriate practice. This study is based on the use of three most usable practices: contouring, strip-cropping and terracing, by the calibrated SWAT model. The general parameters of the model have been modified to reflect the implementation of different agricultural BMPs used. Resulting sediment yield were compared with the baseline scenario, for validation. However, the effective measures to reduce sediment losses at the watershed level are organized according to their effectiveness, and these are terracing (28% reduction and the value is 15t/ha/yr) followed by strip-cropping (9% reduction and the value is 5t/ha/yr). In contrast, measurements performed by the contouring are inappropriate for the study area because they have contributed to increasing the soil erosion (more than 31% of losses and the value is 17t/ha/yr more than existing conditions). Therefore, the model illustrates that the terrace is effective for reducing sediment losses and limiting soil erosion especially on steep slopes. Thus, the results provide useful information for targeted management in order to implement the most effective agricultural BMPs in the watershed.

Sustainability Assessment of Annual and Permanent Crops: The Inspia Model

The Initiative for Sustainable Productive Agriculture (INSPIA) project promotes best management practices for agriculture, to enhance the provision of ecosystem services through better stewardship of soil and water resources while ensuring high levels of productivity. This paper presents the INSPIA methodology for the assessment of sustainability and for guiding farmers on strategic decision-making at farm level, applicable to any kind of cropland. The methodology is based on the application of 15 best management practices, which are assessed through a set of 31 basic sustainability indicators that cover the economic, social and environmental dimensions both agreed by a panel of experts. Basic indicators are then grouped into 12 aggregated indicators, to build the final INSPIA composite index. The INSPIA methodology provides farmers and advisers with a tool to understand sustainability and which, to a certain extent, serves to improve performance toward sustainability. Results are presented in three different ways: a bar diagram with the whole set of basic indicator-values; a pie chart representing the sustainability split in the aggregated indicators; and a final sustainability index. In the medium and long term, the INSPIA methodology can help to monitor and assess agricultural and environmental policy implementation, as well as help improve its decision-making processes in the future.

Evaluating Agricultural BMP Effectiveness in Improving Freshwater Provisioning Under Changing Climate

Freshwater provisioning (FWP) is a critical ecosystem service that is highly affected by climate change/variability as well as land use/land management. Agricultural best management practices (BMPs) are implemented to mitigate the adverse impacts of intensive agricultural production on flow and water quality, thus can potentially protect and improve FWP services. Many studies have assessed BMP effectiveness for improving hydrology/water quality, however the impact of climate changes on BMP effectiveness for protecting FWP is poorly understood. In this study, changes in FWP under 5 BMPs and 6 projected climate change/variability scenarios, were quantified. The Soil and Water Assessment Tool was used to quantify FWP services for baseline (1975–2004) and future climates (2021–2050). We then assessed the climate change impacts on BMP effectiveness for 13 watersheds in the Upper Mississippi River Basin. The results indicated that all 5 BMP scenarios behaved similarly under the historical and future climates, generally resulting in improved FWP services compared to the baseline agricultural management. The combined BMPs was the most effective way to enhance FWP. No-tillage and cover crops performed well in improving FWP in agriculturally-dominated watersheds, while filter strips and grassed waterways had high effectiveness in non-agriculturally dominated watersheds. Results for the climate scenarios indicate that 5 BMPs under future climate were still effective compared to baseline. The increased precipitation and rising temperatures generally improved BMP effectiveness in maintaining and improving FWP services, due to increased freshwater availability under the projected future climate.

Modeling framework for representing long-term effectiveness of best management practices in addressing hydrology and water quality problems: Framework development and demonstration using a Bayesian method

Best management practices (BMPs) are popular approaches used to improve hydrology and water quality. Uncertainties in BMP effectiveness over time may result in overestimating long-term efficiency in watershed planning strategies. To represent varying long-term BMP effectiveness in hydrologic/water quality models, a high level and forward-looking modeling framework was developed. The components in the framework consist of establishment period efficiency, starting efficiency, efficiency for each storm event, efficiency between maintenance, and efficiency over the life cycle. Combined, they represent long-term efficiency for a specific type of practice and specific environmental concern (runoff/pollutant). An approach for possible implementation of the framework was discussed. The long-term impacts of grass buffer strips (agricultural BMP) and bioretention systems (urban BMP) in reducing total phosphorus were simulated to demonstrate the framework. Data gaps were captured in estimating the long-term performance of the BMPs. A Bayesian method was used to match the simulated distribution of long-term BMP efficiencies with the observed distribution with the assumption that the observed data represented long-term BMP efficiencies. The simulated distribution matched the observed distribution well with only small total predictive uncertainties. With additional data, the same method can be used to further improve the simulation results. The modeling framework and results of this study, which can be adopted in hydrologic/water quality models to better represent long-term BMP effectiveness, can help improve decision support systems for creating long-term stormwater management strategies for watershed management projects.

Sustainable Agricultural Practices for Improving Soil Carbon and Nitrogen Content in Relation to Water Availability – An Adapted Approach to Mediterranean Olive Groves

ABSTRACTA field experiment was conducted in an irrigated olive orchard to determine the effects of an orchard management system consisting of increased carbon input management on spatial distribution (tree inter-row/in-row, soil depth 0–10/10–20 cm) of nitrogen and carbon in the soil as well as on some microbial properties in relation to water availability. The experiment consisted of 12 blocks (each with 4 trees covering 200 m2 of land), uniform olive tree canopy size and natural vegetation, used as replications (three per treatment) in a split plot design for the following four treatments: a) spreading of olive mill compost on the soil without soil tillage, b) spreading of chopped pruning residue on the soil without soil tillage, c) combination of b + c, and d) control which received no organic materials and soil was kept free of weeds with frequent tillage and herbicide sprays. Increased soil organic matter content (SOM) (up to +80%), NO3 N (up to +194%), and NH4 N (up to +37%) by carbon inputs were observed in soil layer 0–10 cm. Irrigation enhanced SOM, NH4 N, and electrical conductivity (EC) while it favored NO3 N increase by carbon inputs. All microbial properties (Soil Basal Microbial Respiration, Soil Microbial Biomass Carbon, and Metabolic quotient) were significantly higher at 0–10 cm in comparison to 10–20 cm depth. This study suggests good agricultural management practices for optimized soil organic carbon (SOC) storage adapted to the typical Mediterranean agroecosystems.

Impact of anthropogenic inputs on water quality in Chincholi industrial area of Solapur, Maharashtra, India

A comprehensive hydrochemical study has been carried out to evaluate the impact of anthropogenic activities like industrial effluents, open defecation and untreated sewerage disposal on groundwater and surface water in Chincholi industrial area. The study area comprises of 3 sites viz. Kondi, Pakni and Chincholi with approximate 7000 population and out of that 81% defecates openly. Many industries release effluent in simple pits and surface water tanks without any prior treatment and people harness water from contaminated aquifers. A total 55 water samples have been collected during pre and post monsoon seasons of 2015. According to the BIS, at many sample locations the contents of TH, Ca, Na, Cl, NO3 and TDS exceeded the desirable limit. The piper plot suggests that, alkaline earth exceeds the alkalis and strong acid dominate over weak acid in pre and post monsoon. However, elevated contents of nitrate and chloride in post monsoon season are owed to increased percolation of effluent and agricultural waste along with the recharging water. The strong positive correlation between Cl, NO3 and TDS represents the contamination is of anthropogenic origin supported by the cluster analysis by forming three different clusters. All the parameters exceed the safe limits of the BIS in surface water samples from industrial area due to the mixing of untreated effluents while the samples from non industrial area remain unpolluted. The study concludes that the anthropogenic activities like sewerage disposal, open defecation and discharged effluent disposal threatening the groundwater and surface water quality. Few aquifers from Chincholi and Pakni site are affected most due to industrial effluent and agricultural waste while few samples from Kondi site are polluted due to unlined drainage. To overcome the problem; discharged waste water should be treated and enhancement of sanitation systems along with best management practices in agriculture is essential.

BMP Optimization to Improve the Economic Viability of Farms in the Upper Watershed of Miyun Reservoir, Beijing, China

Best management practices (BMPs) are being implemented to reduce non-point sources pollution in China and worldwide. There are many types of agricultural BMPs, but their effectiveness differs from farm to farm, depending on where they are applied, how they are applied, and how they are impacted by weather. Two farms (village Nan Wayao, VNWY and village Liu Jianfang, VLJF) with differing farm systems (crop-based mixed farm and dairy-based farms) located in the upper watershed of Miyun reservoir, Beijing, China were selected. We used the Integrated Farming System Model (IFSM) based on these two farms information to estimate total phosphorus (TP) and total nitrogen (TN) loss from 2000 to 2014, to identify (1) causes of farm nutrient imbalances, (2) key factors causing the imbalances, and (3) viable BMPs to reduce source and TN runoff at the farm scale. Results indicated that these farms had TP losses ranging from 8.2 to 160 kg/ha/year and TN losses from 73.7 to 1391.6 kg/ha/year. Using IFSM, physical (i.e., soil bulk density, available water content, and soil-P) and economic (i.e., diesel and farm loan interest rates) factors are more influential in determining nutrient loss from VNWY than VLJF. Rainfall patterns had a little effect on nutrient use and loss on the dairy farm in VLJF. Changes in available water content and soil bulk density had greater impact on the return for VNWY than VLJF, while changes in loan interest rates were more influential on VLJF. Maximum reductions in nutrient loss were obtained with implementation of the BMPs conservation tillage, reduced fertilizer and manure applications, buffer strips, and storage of poultry manure.

Evaluation of nutrient retention in vegetated filter strips using the SWAT model.

Nutrient fluxes in stream basins need to be controlled to achieve good water quality status. In stream basins with intensive agricultural activities, nutrients predominantly come from diffuse sources. Therefore, best management practices (BMPs) are increasingly implemented to reduce nutrient input to streams. The objective of this study is to evaluate the impact of vegetated filter strip (VFS) application as an agricultural BMP. For this purpose, SWAT is chosen, a semi-distributed water quality assessment model that works at the watershed scale, and applied on the Nif stream basin, a small-sized basin in Western Turkey. The model is calibrated with an automated procedure against measured monthly discharge data. Nutrient loads for each sub-basin are estimated considering basin-wide data on chemical fertilizer and manure usage, population data for septic tank effluents and information about the land cover. Nutrient loads for 19 sub-basins are predicted on an annual basis. Average total nitrogen and total phosphorus loads are estimated as 47.85 t/yr and 13.36 t/yr for the entire basin. Results show that VFS application in one sub-basin offers limited retention of nutrients and that a selection of 20-m filter width is most effective from a cost-benefit perspective.

David Stewart Jenkinson. 25 February 1928 — 16 February 2011

David Jenkinson was one of the most influential soil scientists of his generation, bringing new insights into the transformations of organic matter and nitrogen in soil. He spent the majority of his career at Rothamsted Research, Harpenden, UK. His studies were influential regarding the role of soil carbon stocks in the context of climate change and the role of nitrogen fertilizer in delivering adequate supplies of food for a growing world population. His research encompassed both fundamental studies on soil processes and immensely practical applications of this knowledge, often utilizing the Rothamsted long-term experiments that have run for over 170 years. He is particularly well known for his development of a method for determining the quantity of organic carbon held in the cells of living micro-organisms in soil, termed the ‘soil microbial biomass’. This breakthrough opened the way for a new wave of soil biological research. David developed one of the earliest computer models for the turnover of organic carbon in soil, known as the Rothamsted Carbon Model, RothC. This model, conceptually very simple, has proved highly successful in simulating and predicting changes in soil organic carbon (SOC) content under different management practices worldwide, being used by over 2600 people in 115 countries. His research using the stable isotope of nitrogen, 15 N, in large-scale field experiments drew attention to the factors leading to inefficiencies in the use of nitrogen fertilizer but also demonstrated that it is possible to achieve high efficiency if good agricultural management practices are followed. It also demonstrated, more clearly than previously, the great importance of soil organic matter as a source of nitrogen for crops and the role of the soil microbial biomass both in immobilizing a proportion of applied fertilizer nitrogen and also in causing confusion in the interpretation of such experiments. By calculating nitrogen budgets for the Rothamsted long-term experiments he quantified the deposition of nitrogen compounds from atmosphere to land, laying foundations for later studies concerning the ecological and agricultural impacts of this significant input of nitrogen.

Do Varying Aquatic Plant Species Affect Phytoplankton and Crustacean Responses to a Nitrogen-Permethrin Mixture?

Hydraulically connected wetland microcosms vegetated with either Typha latifolia or Myriophyllum aquaticum were amended with an NH4NO3 and permethrin mixture to assess the effectiveness of both plant species in mitigating effects of the pollutant mixture on phytoplankton (as chlorophyll a) and Hyalella azteca. Phytoplankton grew in response to increased NH4NO3 in the presence of all plant species, but was unaffected by exposure to permethrin. H. azteca responses occurred rapidly (0.17days), was mitigated within 1-2days, and aqueous toxicity was unaffected by plant species type. A toxic unit model approach ascertained primary toxicity was permethrin with minimal additional toxicity from NH4NO3. Varying aquatic plant species had only modest influences on phytoplankton responses and no observable influence on animal responses during nitrogen-permethrin mixture exposures. As a result, both T. latifolia and M. aquaticum can be used as part of an effective agricultural best-management practice system for mitigating pollutant impacts of agricultural run-off.