829 research outputs found

    Advances and visions in large-scale hydrological modelling: findings from the 11th Workshop on Large-Scale Hydrological Modelling

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    Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future

    Apex and fuzzy model assessment of environmental benefits of agroforestry buffers for claypan soils

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    Contamination of surface waters with pollutants from agricultural land is a major threat to the environment. A field-size watershed study in Northeast Missouri showed that vegetated filter strips containing grass and grass+trees (agroforestry) buffers placed on contours reduced sediment and nutrient loadings by 11-35%. Watershed scale studies are overly expensive while computer simulated hydrologic models offer efficient and economical tools to examine environmental benefits of conservation practices. The current study used the Agricultural Policy Environmental eXtender (APEX) model and a fuzzy logic model to predict environmental benefits of buffers and grass waterways of three adjacent watersheds at the Greenley Memorial Research Center. During the second phase of the study, an automated computer technique was developed to optimize parameter sets for the APEX model for runoff, sediment, total phosphorous (TP) and total nitrogen (TN) losses. The APEX model was calibrated and validated satisfactorily for runoff from both pre- and post-buffer watersheds. The sediment, TP, and TN were calibrated only for larger events during the pre-buffer period (>50 mm). Only TP was calibrated by post-buffer models. The models simulated 13- 25% TP reduction by grass waterways, and 4-5% runoff and 13-45% TP reductions by buffers. The fuzzy model predicted runoff for the study watersheds and for watersheds 30 and 50 times larger in northern Missouri. A stepwise multi-objective, multi-variable parameter optimization technique improved calibration of sediments, TP, and TN after optimization for runoff parameters. The results of the study show that models can be used to examine environmental benefits provided long-term data are available

    Nitrous oxide emission budgets and land-use-driven hotspots for organic soils in Europe

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    Predicting spatiotemporal yield variability to aid arable precision agriculture in New Zealand : a case study of maize-grain crop production in the Waikato region : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Agriculture and Horticulture at Massey University, Palmerston North, New Zealand

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    Precision agriculture attempts to manage within-field spatial variability by applying suitable inputs at the appropriate time, place, and amount. To achieve this, delineation of field-specific management zones (MZs), representing significantly different yield potentials are required. To date, the effectiveness of utilising MZs in New Zealand has potentially been limited due to a lack of emphasis on the interactions between spatiotemporal factors such as soil texture, crop yield, and rainfall. To fill this research gap, this thesis aims to improve the process of delineating MZs by modelling spatiotemporal interactions between spatial crop yield and other complementary factors. Data was collected from five non-irrigated field sites in the Waikato region, based on the availability of several years of maize harvest data. To remove potential yield measurement errors and improve the accuracy of spatial interpolation for yield mapping, a customised filtering algorithm was developed. A supervised machine-learning approach for predicting spatial yield was then developed using several prediction models (stepwise multiple linear regression, feedforward neural network, CART decision tree, random forest, Cubist regression, and XGBoost). To provide insights into managing spatiotemporal yield variability, predictor importance analysis was conducted to identify important yield predictors. The spatial filtering method reduced the root mean squared errors of kriging interpolation for all available years (2014, 2015, 2017 and 2018) in a tested site, suggesting that the method developed in R programme was effective for improving the accuracy of the yield maps. For predicting spatial yield, random forest produced the highest prediction accuracies (R² = 0.08 - 0.50), followed by XGBoost (R² = 0.06 - 0.39). Temporal variables (solar radiation, growing degree days (GDD) and rainfall) were proven to be salient yield predictors. This research demonstrates the viability of these models to predict subfield spatial yield, using input data that is inexpensive and readily available to arable farms in New Zealand. The novel approach employed by this thesis may provide opportunities to improve arable farming input-use efficiency and reduce its environmental impact

    Site suitability assessment of spotted gum (Corymbia citriodora subspecies Variegata) forest plantation in south east Queensland for carbon sequestration

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    The inevitable development brought about by human intervention in the global natural ecosystem has led to a continuous increase in greenhouse gas (GHG) emissions into the atmosphere (IPCC 2013), thereby warming the earth. Forest and other vegetation landscapes have the potential to mitigate this warming by serving as the sinks or storages of carbon dioxide. However, land suitability for carbon sink enterprises must be identified to effect a more productive, profitable and efficient sequestration. Additionally, the impact of soil salinity in the suitability of potential forestation sites and carbon sequestration capacity of forest plantation in saline affected areas is not well understood. This research addressed the problem of site suitability by applying the most appropriate process based model particularly the 3-PG (Physiological Principle in Predicting Growth) to enhance the accuracy of estimated biomass for spotted gum. Salinity was incorporated through the mortality impact of varying salt concentrations in the spotted gum. As carbon sequestration endeavour via forestation was deemed risky in marginal areas such as those with salinity problems, the net present value (NPV) of spotted gum forest plantation was incorporated to determine its financial benefits. Site suitability of this forestation endeavour in southeast Queensland was determined and visualised using the geographical information system (GIS). Mathematical models for spotted gum mortality and soil salinity were developed and integrated with the 3-PG model. Parameterisation of the model using specific climatic and bio-physical parameters for spotted gum was conducted prior to the simulation. These provided confidence in the biomass simulation and projection of carbon sequestered until the end of the rotation period. The estimated total biomass (aboveground and belowground biomass) were converted to carbon and tabulated. The tabulated results were converted into maps using GIS techniques and the Net Present Value of spotted gum was calculated based from its potential for timber, carbon and salinity amelioration. The utilisation of spatial mapping tools, specifically GIS, generated potential suitable sites for carbon sequestration activities in the SEQ region. The study generated maps to identify potential locations suitable for Carbon Farming Initiative (CFI) eligible carbon sequestration projects. The site suitability index (SSI) map showed suitable sites in the northern part of the study area located at SEQ 1 and in the southern part at SEQ 2 and SEQ 8. The SSI map also indicated locations for potential investment in forestation projects. It also suggested that success of the carbon sequestration activities cannot be guaranteed in high rainfall areas where salinity could pose a challenge. If spotted gum plantations are established in southeast Queensland and only the conventional timber is accounted as the source of revenue, then the financial benefits are limited to high rainfall areas with a mean annual increment (MAI) of more than 18 m3 ha-1 yr-1. However, under high saline conditions the viability is questionable. When established under high saline affected areas with carbon and salt amelioration incorporated, then carbon sequestration may become profitable. However, this may only be applicable in a scenario where the carbon price was increased and a conventional timber is added with carbon and soil amelioration benefits. Though suitable sites are limited where this activity is profitable, the potential of spotted gum for soil amelioration under saline affected areas is significant even for an extended long period of time

    Book of abstracts - Metallurgy and related topics - Section D

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    Catchment Modelling Tools and Pathways Review

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    Tools for improved efficiency and control in wastewater treatment

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