Infrastructure Engineering - Research Publications
Now showing items 1-12 of 1492
Dependence of CWSI-Based Plant Water Stress Estimation with Diurnal Acquisition Times in a Nectarine Orchard
Unmanned aerial vehicle (UAV) remote sensing has become a readily usable tool for agricultural water management with high temporal and spatial resolutions. UAV-borne thermography can monitor crop water status near real-time, which enables precise irrigation scheduling based on an accurate decision-making strategy. The crop water stress index (CWSI) is a widely adopted indicator of plant water stress for irrigation management practices; however, dependence of its efficacy on data acquisition time during the daytime is yet to be investigated rigorously. In this paper, plant water stress captured by a series of UAV remote sensing campaigns at different times of the day (9h, 12h and 15h) in a nectarine orchard were analyzed to examine the diurnal behavior of plant water stress represented by the CWSI against measured plant physiological parameters. CWSI values were derived using a probability modelling, named ‘Adaptive CWSI’, proposed by our earlier research. The plant physiological parameters, such as stem water potential (ψstem) and stomatal conductance (gs), were measured on plants for validation concurrently with the flights under different irrigation regimes (0, 20, 40 and 100 % of ETc). Estimated diurnal CWSIs were compared with plant-based parameters at different data acquisition times of the day. Results showed a strong relationship between ψstem measurements and the CWSIs at midday (12 h) with a high coefficient of determination (R2 = 0.83). Diurnal CWSIs showed a significant R2 to gs over different levels of irrigation at three different times of the day with R2 = 0.92 (9h), 0.77 (12h) and 0.86 (15h), respectively. The adaptive CWSI method used showed a robust capability to estimate plant water stress levels even with the small range of changes presented in the morning. Results of this work indicate that CWSI values collected by UAV-borne thermography between mid-morning and mid-afternoon can be used to map plant water stress with a consistent efficacy. This has important implications for extending the time-window of UAV-borne thermography (and subsequent areal coverage) for accurate plant water stress mapping beyond midday.
Continuously Vegetation Greening over Inner Mongolia for the Past Three Decades
The warming climate has rapidly altered vegetation growth in drylands, and consequently, has put great pressure on sustainable livelihoods. Various datasets have been applied from local to global scale to study vegetation dynamics and there is a lack of solid comparison among multiple datasets. Note that vegetation growth might shift over time and the greening and browning components over a long-time span might be masked by a linear trend. Here, we aim to monitor the long-term and nonlinear dynamics in vegetation greenness for Inner Mongolia (an important part of dryland Asia). As a useful tool that indicates vegetation greenness, NDVI (Normalized Difference Vegetation Index) and LAI (Leaf Area Index) integrals derived from the GIMMS (Global Inventory Modelling and Mapping Studies) NDVI3g and the GIMMS LAI3g products are applied. During the period of 1982-2016, NDVI/LAI integrals have an overall acceptable consistency in characterizing the trends of vegetation greenness, with NDVI large/small integrals and LAI large/small integrals increase at a rate of 0.96, 1.72, 2.23, and 3.13 per decade, respectively. Inner Mongolia experienced a noticeable greening process (71% and 82% greening area in NDVI large/small integrals, 67% and 73% greening area in LAI large/small integrals), despite the fragmentally distributed browning trends in eastern and partial northern Inner Mongolia. As inferred from nonlinear trend analysis, we found the greening process is still prevalent. The browning of eastern Inner Mongolia under the linear analysis was actually transferring from browning to greening, while the greening trend in northern Inner Mongolia was changing to browning. Increased occurrences in the frequency of breakpoints after 1999 suggest that previously stable vegetation ecology is more sensitive to external disturbances such as altered climatic impact and anthropogenic intervention.
Modeling the Compaction Characteristics of Fine-Grained Soils Blended with Tire-Derived Aggregates
This study aims at modeling the compaction characteristics of fine-grained soils blended with sand-sized (0.075–4.75 mm) recycled tire-derived aggregates (TDAs). Model development and calibration were performed using a large and diverse database of 100 soil–TDA compaction tests (with the TDA-to-soil dry mass ratio ≤ 30%) assembled from the literature. Following a comprehensive statistical analysis, it is demonstrated that the optimum moisture content (OMC) and maximum dry unit weight (MDUW) for soil–TDA blends (across different soil types, TDA particle sizes and compaction energy levels) can be expressed as universal power functions of the OMC and MDUW of the unamended soil, along with the soil to soil–TDA specific gravity ratio. Employing the Bland–Altman analysis, the 95% upper and lower (water content) agreement limits between the predicted and measured OMC values were, respectively, obtained as +1.09% and −1.23%, both of which can be considered negligible for practical applications. For the MDUW predictions, these limits were calculated as +0.67 and −0.71 kN/m3, which (like the OMC) can be deemed acceptable for prediction purposes. Having established the OMC and MDUW of the unamended fine-grained soil, the empirical models proposed in this study offer a practical procedure towards predicting the compaction characteristics of the soil–TDA blends without the hurdles of performing separate laboratory compaction tests, and thus can be employed in practice for preliminary design assessments and/or soil–TDA optimization studies.
Production and application of manure nitrogen and phosphorus in the United States since 1860
(COPERNICUS GESELLSCHAFT MBH, 2021-02-18)
Abstract. Livestock manure nitrogen (N) and phosphorus (P) play an important role in biogeochemical cycling. Accurate estimation of manure nutrient is important for assessing regional nutrient balance, greenhouse gas emission, and water environmental risk. Currently, spatially explicit manure nutrient datasets over a century-long period are scarce in the United States (US). Here, we developed four datasets of annual animal manure N and P production and application in the contiguous US at a 30 arcsec resolution over the period of 1860–2017. The dataset combined multiple data sources including county-level inventory data as well as high-resolution livestock and crop maps. The total production of manure N and P increased from 1.4 Tg N yr−1 and 0.3 Tg P yr−1 in 1860 to 7.4 Tg N yr−1 and 2.3 Tg P yr−1 in 2017, respectively. The increasing manure nutrient production was associated with increased livestock numbers before the 1980s and enhanced livestock weights after the 1980s. The manure application amount was primarily dominated by production, and its spatial pattern was impacted by the nutrient demand of crops. The intense-application region mainly enlarged from the Midwest toward the southern US and became more concentrated in numerous hot spots after the 1980s. The South Atlantic–Gulf and Mid-Atlantic basins were exposed to high environmental risks due to the enrichment of manure nutrient production and application from the 1970s to the period of 2000–2017. Our long-term manure N and P datasets provide detailed information for national and regional assessments of nutrient budgets. Additionally, the datasets can serve as the input data for ecosystem and hydrological models to examine biogeochemical cycles in terrestrial and aquatic ecosystems. Datasets are available at https://doi.org/10.1594/PANGAEA.919937 (Bian et al., 2020).
Fly Ash-Based Eco-Efficient Concretes: A Comprehensive Review of the Short-Term Properties
Development of sustainable concrete as an alternative to conventional concrete helps in reducing carbon dioxide footprint associated with the use of cement and disposal of waste materials in landfill. One way to achieve that is the use of fly ash (FA) as an alternative to ordinary Portland cement (OPC) because FA is a pozzolanic material and has a high amount of alumina and silica content. Because of its excellent mechanical properties, several studies have been conducted to investigate the use of alkali-activated FA-based concrete as an alternative to conventional concrete. FA, as an industrial by-product, occupies land, thereby causing environmental pollution and health problems. FA-based concrete has numerous advantages, such as it has early strength gaining, it uses low natural resources, and it can be configurated into different structural elements. This study initially presents a review of the classifications, sources, chemical composition, curing regimes and clean production of FA. Then, physical, fresh, and mechanical properties of FA-based concretes are studied. This review helps in better understanding of the behavior of FA-based concrete as a sustainable and eco-friendly material used in construction and building industries.
Calculation model and bearing capacity optimization method for the soil settlement between piles in geosynthetic-reinforced pile-supported embankments based on the membrane effect
(PUBLIC LIBRARY SCIENCE, 2021-01-01)
The geosynthetic-reinforced pile-supported embankment (GRPSE) system has been widely used in road construction on soft soil. However, the application of the GRPSE system is often restricted by its high-cost. The reason is that they are designed for bearing control as defined in the past. During the construction process, the pile spacing is reduced to meet the requirements for the embankment bearing capacity and settlement. These factors cause the membrane effect to not be exploited. As a result, the utilization efficiency of the bearing capacity of the soil between the piles is low and the project cost is high. Therefore, in order to solve the problem of insufficient bearing capacity of soil between piles, we established a settlement calculation model of soil between piles based on membrane effect. The model considers the relationship between the geosynthetic reinforcement (GR) and the pile spacing. Based on the obtained model, a method for optimizing the soil bearing capacity of GRPSEs is proposed. By controlling the settlement of soil between piles, the bearing capacity of soil between piles and the membrane effect of embankment can be fully utilized. Therefore, the project cost can be reduced. Finally, the method is applied to field tests for comparison. The results show that the method is reasonable and applicable. This method can effectively exploit the membrane effect and improve the utilization efficiency of the bearing capacity of the soil between piles. An economical and reasonable arrangement scheme for the piles and GR was obtained. This scheme can not only ensure the safety of the project, but also fully utilize the bearing capacity of the soil between the piles and provide a new method for engineering design.
AWAPer: An R package for area weighted catchment daily meteorological data anywhere within Australia
(John Wiley & Sons Ltd., 2020-02-28)
Meteorological time‐series data are a fundamental input to hydrological investigations. But sourcing data is often laborious and plagued with difficulties. In an effort to improve efficiency and rigor we present an R‐package, named AWAPer (https://github.com/peterson-tim-j/AWAPer), for the efficient estimation of daily area weighted catchment average and spatial variance of meteorological variables, including evapotranspiration. The package allows creation and updating of a data‐cube of gridded daily data from 1900 onwards. Once created, point and area weighted estimates can be extracted at user‐defined locations and time periods for anywhere within Australia. Examples of point and catchment average extraction are presented.
Joint Estimation of Gross Recharge, Groundwater Usage, and Hydraulic Properties within HydroSight
Groundwater management decisions are often founded upon estimates of aquifer hydraulic properties, recharge and the rate of groundwater usage. Too often hydraulic properties are unavailable, recharge estimates are very uncertain, and usage is unmetered or infrequently metered over only recent years or estimated using numerical groundwater models decoupled from the drivers of drawdown. This paper extends the HydroSight groundwater time‐series package ( http://peterson‐tim‐j.github.io/HydroSight/) to allow the joint estimation of gross recharge, transmissivity, storativity, and daily usage at multiple production bores. A genetic evolutionary scheme was extended from estimating time‐series model parameters to also estimating time series of usage that honor metered volumes at each production bore and produces (1) the best fit with the observed hydrograph and (2) plausible estimates of actual evapotranspiration and hence recharge. The reliability of the approach was rigorously tested. Repeated calibration of models for four bores produced estimates of transmissivity, storativity, and mean recharge that varied by a factor of 0.22‐0.32, 0.13‐0.2, and 0.03‐0.48, respectively, when recharge boundary effects were low and the error in monthly, quarterly, and biannual metered usage was generally <10%. Application to the 30 observation bores within the Warrion groundwater management area (Australia), produced a coefficient of efficiency of ≥0.80 at 22 bores and ≥0.90 at 12 bores. The aquifer transmissivity and storativity were reasonably estimated, and were consistent with independent estimates, while mean gross recharge may be slightly overestimated. Overall, the approach allows greater insights from the available data and provides opportunity for the exploration of usage and climatic scenarios.