Comparison of Evapotranspiration Simulation Performance by APEX Model in Dryland and Irrigated Cropping Systems

Accurate estimation of evapotranspiration (ET) is essential to improve water use efficiency of crop production systems managed under different water regimes. The Agricultural Policy/Environmental eXtender (APEX) model was used to simulate ET using four potential ET (ET_p) methods. The objectives were to determine sensitive ET parameters in dryland and irrigated cropping systems and compare ET simulation in the two systems using multiple performance criteria. Measured ET and crop yield data from lysimeter fields located in the United States Department of Agriculture‐Agricultural Research Service Bushland, Texas were used for evaluation. The number of sensitive parameters was higher for dryland (11–14) than irrigated cropping systems (6–8). Only four input parameters: soil evaporation plant cover factor, root growth soil strength, maximum rain intercept, and rain intercept coefficient were sensitive in both cropping systems. Overall, it is possible to find a set of robust parameter values to simulate ET accurately in APEX in both cropping systems using any ET_p method. However, more computation time is required for dryland than irrigated cropping system due to a relatively larger number of sensitive input parameters. When all inputs are available, the Penman–Monteith method takes the shortest computation time to obtain one model run with robust parameter values in both cropping systems. However, in areas with limited datasets, one can still obtain reasonable ET simulations using either Priestley–Taylor or Hargreaves. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

The need for integration of drought monitoring tools for proactive food security management in sub‐Saharan Africa

Reducing the impact of drought and famine remains a challenge in sub‐Saharan Africa despite ongoing drought relief assistance in recent decades. This is because drought and famine are primarily addressed through a crisis management approach when a disaster occurs, rather than stressing preparedness and risk management. Moreover, drought planning and food security efforts have been hampered by a lack of integrated drought monitoring tools, inadequate early warning systems (EWS), and insufficient information flow within and between levels of government in many sub‐Saharan countries. The integration of existing drought monitoring tools for sub‐Saharan Africa is essential for improving food security systems to reduce the impacts of drought and famine on society in this region. A proactive approach emphasizing integration requires the collective use of multiple tools, which can be used to detect trends in food availability and provide early indicators at local, national, and regional scales on the likely occurrence of food crises. In addition, improving the ability to monitor and disseminate critical drought‐related information using available modern technologies (e.g., satellites, computers, and modern communication techniques) may help trigger timely and appropriate preventive responses and, ultimately, contribute to food security and sustainable development in sub‐Saharan Africa.     

Time-series trend analysis and farmer perceptions of rainfall and temperature in northwestern Ethiopia

Environment, Development and Sustainability - Smallholder farmers are the most vulnerable community to climate change in Ethiopia since they rely heavily on the subsistence rain-fed farming system....     

Soil carbon sequestration in tropical agroforestry systems: a feasibility appraisal

Agroforestry is recognized as a strategy for soil carbon sequestration (SCS) under the afforestation/reforestation activities, but our understanding of soil carbon (C) dynamics under agroforestry systems (AFS) is not adequate. Although some SCS estimates are available, many of them lack scientific rigor. Several interrelated and site-specific factors ranging from agroecological conditions to system management practices influence the rate and extent of SCS under AFS, so that generalizations tend to become unrealistic. Furthermore, widely and easily adoptable methodologies are not available for estimating the SCS potential under different conditions. In spite of these, there is an increasing demand for developing “best-bet estimates” based on the current level of knowledge and experience. This document presents an attempt in that direction. The appraisal validates the conjecture that AFS can contribute to SCS, and presents indicative ranges of SCS under different AFS in the major agroecological regions of the tropics. The suggested values range from 5 to 10 kg C ha^?1 in about 25 years in extensive tree-intercropping systems of arid and semiarid lands to 100–250 kg C ha^?1 in about 10 years in species-intensive multistrata shaded perennial systems and homegardens of humid tropics.     

Neural Network Based Automated Interpretation Algorithm for Combined Geophysical Soundings in Coastal Zones

The fresh water availability in coastal aquifers is an important problem faced by a major part of world’s population dwelling there. For in situ and dynamic characterization of seawater encroachment into coastal aquifers, electrical geophysical methods are better suited. However, the resolving power of such data in distinguishing saline sands from moist clays in the subsurface is very poor. To meet this aspect and also the problem of analyzing voluminous data sets, we propose a feed forward back-propagation neural network (BPNN) based approach for the analysis of combined vertical electrical and induced polarization soundings. Our method is tested on synthetic data computed from available geo-electric sections and prevailing subsurface geological information of coastal aquifers of East Coast of India.The synthetic data are comprised of 18 combined soundings spread over five profiles. 15 out of 18 are used for training the BPNN, while 3 are used for testing. The trained BPNN (one node each in each of the input and output layers and 18 hidden nodes) showed 84.85% accuracy in testing phase for distinguishing clays from saline sands.Our method is also tested on real data concerning a shaly aquifer in Bahia, Brazil yielding an overall accuracy of 84.9%, comparable to that of synthetic case; thereby validating our approach.     

Impact of Length of Dataset on Streamflow Calibration Parameters and Performance of APEX Model

Due to resource constraints, long‐term monitoring data for calibration and validation of hydrologic and water quality models are rare. As a result, most models are calibrated and, if possible, validated using limited measured data. However, little research has been done to determine the impact of length of available calibration data on model parameterization and performance. The main objective of this study was to evaluate the impact of length of calibration data (LCD) on parameterization and performance of the Agricultural Policy Environmental eXtender model for predicting daily, monthly, and annual streamflow. Long‐term (1984‐2015) measured daily streamflow data from Rock Creek watershed, an agricultural watershed in northern Ohio, were used for this study. Data were divided into five Short (5‐year), two Medium (15‐year), and one Long (25‐year) streamflow calibration data scenarios. All LCD scenarios were calibrated and validated at three time steps: daily, monthly, and annual. Results showed LCD affected the ability of the model to accurately capture temporal variability in simulated streamflow. However, overall average streamflow, water budgets, and crop yields were simulated reasonably well for all LCD scenarios.     

Nutrients and bacteria in common contiguous Mississippi soils with and without broiler litter fertilization

In Mississippi, spent poultry litter is used as fertilizer. Nutrient and bacterial levels in litter and nutrient levels in litter-fertilized (L+) soil are known, but less is known of bacterial levels in L+ soil. This study compared contiguous L+ and non-litter-fertilized (L-) soils comprising 15 soil types on five farms in April through May 2009. Levels of pH; NO-N; and Mehlich-3-extractable (M3) and water-extractable (WE) P, Ca, K, and Cu were higher in L+ than in L- soil. Total C; total N; NH-N; and M3 and WE Na, Fe, and Zn did not differ in L+ and L- soil. Bacterial levels were higher in 0- to 5-cm than in 5- to 10-cm cores. Levels were higher in L+ than in L- soil for culturally determined heterotrophic plate counts and staphylococci and were lower for total bacteria estimated by quantitative polymerase chain reaction (qPCR) of 16S rRNA, but cultural levels of thermotolerant coliforms, , , and enterococci were not different. Cultural presence/absence (CPA) tests and qPCR for spp., spp., and spp. detected only spp., which did not differ in L+ (CPA = 77% positive samples; mean qPCR = 0.65 log genomic units [gu] g) and L- (CPA = 70% positive samples; mean qPCR = 0 log gu g) soils. Litter applications were associated with higher levels of pH, P, Cu, heterotrophic plate counts, and staphylococci. Fecal indicator and enteric pathogen levels were not affected. We conclude that, although some litter-derived nutrients and bacteria persisted between growing seasons in L+ soils, enteric pathogens did not.     

A Parallel Computation Tool to Enable Dynamic Sensitivity and Model Performance Analysis of APEX: Evapotranspiration Modeling

Global sensitivity analysis can be used for assessing the relative importance of model parameters on model outputs. The sensitivity of parameters usually indicates a temporal variation due to variation in the environmental conditions (e.g., variation in weather or plant growth). In addition, the size of averaging window by which the outputs of a model are aggregated or averaged may impact parameter sensitivities. In this study, temporal variation of parameters sensitives, model performance, as well as the impact of the size of time‐averaging window on evapotranspiration (ET) prediction using the Agricultural Policy/Environmental eXtender (APEX) model are investigated. To achieve these goals, an open‐source package named PARAPEX was developed in R and used to perform dynamic sensitivity and model performance analysis of APEX using parallel computation. PARAPEX reduced the computation time from 5,939 to 379 s (using 20 and 1 computation nodes, respectively). The sensitivity analysis results indicated the parameters accounting for the reducing effect of plant cover on evaporation from the soil surface, the effect of soil on the plant root growth, and the effect of cycling and transformation dynamics of organic matter at the top soil layer as the top sensitive parameters based on the mean daily simulated ET and the Nash–Sutcliffe model performance measure. The dynamic performance analysis indicated poor ET predictions by APEX during the growing seasons. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Utilization of high-volume mine tailing and by-products in composite binder production: hardened properties and sustainable development

Journal of Material Cycles and Waste Management - This study was designed to investigate the hardened performance of the paste specimens produced using a composite binder with high volumes of mine...     

Carbon storage of different soil-size fractions in Florida silvopastoral systems

Compared with open (treeless) pasture systems, silvopastoral agroforestry systems that integrate trees into pasture production systems are likely to enhance soil carbon (C) sequestration in deeper soil layers. To test this hypothesis, total soil C contents at six soil depths (0-5, 5-15, 15-30, 30-50, 50-75, and 75-125 cm) were determined in silvopastoral systems with slash pine (Pinus elliottii) + bahiagrass (Paspalum notatum) and an adjacent open pasture (OP) with bahiagrass at four sites, representing Spodosols and Ultisols, in Florida. Soil samples from each layer were fractionated into three classes (250-2000, 53-250, and <53 microm), and the C contents in each were determined. Averaged across four sites and all depths, the total soil organic carbon (SOC) content was higher by 33% in silvopastures near trees (SP-T) and by 28% in the alleys between tree rows (SP-A) than in adjacent open pastures. It was higher by 39% in SP-A and 20% in SP-T than in open pastures in the largest fraction size (250-2000 microm) and by 12.3 and 18.8%, respectively, in the intermediate size fraction (53-250 microm). The highest SOC increase (up to 45 kg m(-2)) in whole soil of silvopasture compared with OP was at the 75- to 125-cm depth at the Spodosol sites. The results support the hypothesis that, compared with open pastures, silvopastures contain more C in deeper soil layers under similar ecological settings, possibly as a consequence of a major input to soil organic matter from decomposition of dead tree-roots.