Effects of soil sample pretreatments and standardised rewetting as interacted with sand classes on Vis-NIR predictions of clay and soil organic carbon

Numerous studies have examined the soil analytical potential of diffuse reflectance spectroscopy in the near infrared range, alone or combined with the visible range (Vis-NIR). Soil organic matter (SOM), soil organic carbon (SOC) and clay content are the most commonly and successfully predicted parameters, but predictions are quite variable due e.g. to the range of soil types covered by the calibrations. Especially organic matter predictions are also suggested to be influenced by for example soil moisture content and inclusion of the visible range in the calibration. Excess quartz sand is also suggested to have a negative influence. This study was undertaken to examine the effect of a selection of standardised sample pretreatment procedures, including rewetting, on predictions of clay and SOC content. A subset of 400 samples was selected from a dataset of 3000 Swedish agricultural soils to cover clay and organic matter contents without co-variation. The selected samples were analysed by NIR and Vis-NIR on air-dry samples, either carefully mixed to avoid stratification of particle size classes or shaken to promote separation, resulting in predominantly larger particles being analysed. Unshaken samples were also analysed immediately after standardised additional drying at 35°C for 12 hours and stepwise volumetric rewetting up to 30%. Shaking and additional drying had small negative effects on clay predictions, while drying only had small positive effects on SOC predictions. Volumetric rewetting to 20 or 30% before scanning reduced clay prediction errors by up to 15%, RMSEP reduced from 5.4 % clay to 4.5 % clay, and SOC prediction errors by up to 30%, from 0.9 % SOC to 0.6 % SOC, indicating that standardised rewetting should be considered. The mechanisms concerned could not be specifically identified, but known bands for water, hydroxyl and clay mineral-dependent absorption near 1400, 1900 and 2200 nm were involved in the improved clay calibrations and bands near 1700, 2000, 2300 and 2350 nm in the improved SOC calibrations. The SOC predictions were most inaccurate for soils with a high sand content. For these samples the average prediction error was more than twice as high as those for less sandy samples. Rewetting eliminated this bias, largely explaining the positive effects of rewetting

Reservoir-scale transdimensional fracture network inversion

The Waiwera aquifer hosts a structurally complex geothermal groundwater system, where a localized thermal anomaly feeds the thermal reservoir. The temperature anomaly is formed by the mixing of waters from three different sources: fresh cold groundwater, cold seawater and warm geothermal water. The stratified reservoir rock has been tilted, folded, faulted, and fractured by tectonic movement, providing the pathways for the groundwater. Characterization of such systems is challenging, due to the resulting complex hydraulic and thermal conditions which cannot be represented by a continuous porous matrix. By using discrete fracture network models (DFNs) the discrete aquifer features can be modelled, and the main geological structures can be identified. A major limitation of this modelling approach is that the results are strongly dependent on the parametrization of the chosen initial solution. Classic inversion techniques require to define the number of fractures before any interpretation is done. In this research we apply the transdimensional DFN inversion methodology that overcome this limitation by keeping fracture numbers flexible and gives a good estimation on fracture locations. This stochastic inversion method uses the reversible-jump Markov chain Monte Carlo algorithm and was originally developed for tomographic experiments. In contrast to such applications, this study is limited to the use of steady-state borehole temperature profiles – with significantly less data. This is mitigated by using a strongly simplified DFN model of the reservoir, constructed according to available geological information. We present a synthetic example to prove the viability of the concept, then use the algorithm on field observations for the first time. The fit of the reconstructed temperature fields cannot compete yet with complex three-dimensional continuum models, but indicate areas of the aquifer where fracturing plays a big role. This could not be resolved before with continuum modelling. It is for the first time that the transdimensional DFN inversion was used on field data and on borehole temperature logs as input.DFG, 318763901, SFB 1294, Data Assimilation - The seamless integration of data and models, Assimilating data with different degrees of uncertainty into statistical models for earthquake occurrence (B04)TU Berlin, Open-Access-Mittel - 201

A Primary Ecological Survey of Dardanelle Reservoir Prior to Nuclear Facility Effluent Discharge

A preliminary ecological survey of Dardanelle Reservoir during the construction phase of Arkansas Power and Light Company\u27s nuclear generating facility was conducted from January 1970 through June 1974. The reservoir is characterized by relatively shallow depths and a high flow-thru rate. A number of features were associated with these characteristics. The reservoir carried a great deal of suspended material and exhibited high turbidities throughout most of the year. Typical thermal stratification and oxygen depletion were only rarely observed. Many of the physico-chemical parameters exhibited relatively high values in comparison to other Arkansas lakes and reservoirs, but due to absence of prolonged periods of stratification and stagnation, they did not undergo the extreme fluctuations sometimes observed in other reservoirs. Plankton and benthic samples were collected at least nine times per year from ten stations. These stations were selected to include both shallow and deep locations and to include points both within and outside the projected area of thermal influence when the plant became operational. There were a great variety of forms in the phytoplankton with the diatoms making up a considerable portion. The level of turbidity appeared to dampen somewhat the extreme fluctuations sometimes found in bloom periods. In the zooplankton the rotifers Brachionus, Keratella, and Polyarthra predominated followed by the microcrustaceans Cyclops and Bosmina. Both the plankton and the benthic fauna showed great seasonal variation. The benthic fauna consisted primarily of Chironomidae, Oligochaeta, and Hexagenia with the Chironomidae predominating in the shallower depths and the Oligochaeta exhibiting increased abundance and importance in the deeper stations

The arable farmer as the assessor of within-field soil variation

Feasible, fast and reliable methods of mapping within-field variation are required for precision agriculture. Within precision agriculture research much emphasis has been put on technology, whereas the knowledge that farmers have and ways to explore it have received little attention. This research characterizes and examines the spatial knowledge arable farmers have of their fields and explores whether it is a suitable starting point to map the within-field variation of soil properties. A case study was performed in the Hoeksche Waard, the Netherlands, at four arable farms. A combination of semi-structured interviews and fieldwork was used to map spatially explicit knowledge of within-field variation. At each farm, a field was divided into internally homogeneous units as directed by the farmer, the soil of the units was sampled and the data were analysed statistically. The results show that the farmers have considerable spatial knowledge of their fields. Furthermore, they apply this knowledge intuitively during various field management activities such as fertilizer application, soil tillage and herbicide application. The sample data on soil organic matter content, clay content and fertility show that in general the farmers’ knowledge formed a suitable starting point for mapping within-field variation in the soil. Therefore, it should also be considered as an important information source for highly automated precision agriculture systems

Effect of Conservation Agriculture on Organic Matter Stratification and Hydro-Physical Properties of Soil Under Intensive Cereal-based Cropping Systems

Although, the potential of management induced changes of soil organic matter, soil hydraulic properties (SHPs) and soil physical quality has been studied particularly in relation to tillage, few studies have evaluated combined effect of tillage, crop residue retention and cropping sequence, which are essential components of conservation agriculture (CA), on stratification and storage of soil organic matter, its effect on near-saturated soil hydraulic properties and soil physical quality in intensive cereal based irrigated cropping systems. Hence, the present study critically analyses the effects of CA on organic matter and hydro-physical properties of soil in a long-term CA field trial in NWIGP, India, which is one of the most fragile agro-ecosystems in the world. The objectives were (I) to investigate the stratification of soil organic carbon (SOC), total nitrogen (TN), C/N ratio and evaluate SR as an indicator of storage of SOC and TN and soil quality for different CA practices, (II) to assess the long-term effect of CA practices and short-term effect of crops on near-saturated soil hydraulic conductivity and water transmission properties, and (III) to assess the effect of CA practices on soil physical quality using capacitive and dynamic indicators. There were four treatments: (1) conventionally tilled rice-wheat cropping system (CT-RW), (2) reduced till CA-based rice-wheat-mungbean system (RT-RWMB), (3) no-till CA-based rice-wheat-mungbean system (NT-RWMB), and (4) no-till CA-based maize-wheat-mungbean system (NT-MWMB). To achieve these objectives, soil bulk density, SOC and TN were measured in an increment of 5 cm up to 30 cm soil depth. Furthermore, the effects of CA were also evaluated in terms of soil hydro-physical properties. Soil physical properties such as bulk density and soil aggregate distribution were evaluated in two cropping seasons along with near saturated hydraulic properties. Steady state infiltration rates were obtained at four pressure heads by hood infiltrometer consecutively over two cropping seasons, i.e. during harvest season of rice/maize (October 2017) and maximum crop growth stage of wheat (February 2018). Data were analysed in terms of soil hydraulic conductivity, k(h), flow weighted mean pore radius (r0), hydraulically active porosity (ε) and threshold pore radius (rbp), a new pore measure indicative of macropore stability derived by substituting soil’s bubble pressure in the capillary equation. Finally, the effects of CA on soil physical quality in terms of both capacitive and dynamic indicators, derived from soil moisture retention curve and field measured hydraulic conductivity, respectively, were assessed and related with crop yield to infer which indicator better represented the soil physical quality and its effect on crop yield under irrigated intensive cereal based cropping systems. Results showed that CA had profound impacts on distribution of SOC and TN in the soil profile. Significantly higher proportion of both SOC and TN were observed in the top soil in the CA-based treatments as compared with conventional intensive tillage-based treatment. The mean stratification ratio of both SOC and TN were found > 2 in CA-based treatments whereas the same was < 2 in intensive tillage-based treatment. Storage of SOC and TN in the 0-30 cm were found higher in CA-based treatments as compared with the intensive tillage-based treatment. These results on vertical distribution and storage of SOC and TN indicated a relatively better soil carbon sequestration and soil quality in CA-based treatment. The higher concentrations and storage of soil organic matter in CA-based treatments were, however, not translated into significantly (p < 0.05) lower bulk density due to probable compaction effect of no-tillage and harvest machinery and hydraulic pressure exerted by the flooded irrigation water. However, the increased soil organic matter in the top soil in CA-based treatments improved the soil aggregation significantly which helped in enhancing soil structural quality. Improvement in soil structure was reflected in relatively higher near saturated hydraulic conductivity in CA-based treatments. Irrespective of crop seasons, higher k(h) was observed under CA due to formation of macropores with better continuity, greater size and numbers as compared with conventional intensive tillage treatment. Moreover, higher r0 values were observed for a given k(h) for CA treatments suggesting that interaggregate pores are the dominant pathways of infiltration in CA. A relatively smaller temporal variation of rbp was indicative of a more stable macropore system established by rice-based CA as compared with maize-based CA. CA also enhanced hydraulically active macropores as compared with intensive tillage based conventional agriculture. Results also indicated that crops play an important role in relative distribution of the hydraulically active macropores in the root zone. The impact of CA on soil organic matter stratification and soil hydraulic properties were found to be expressed in terms of changes in soil physical quality. Soil moisture retention curves and pore size distributions under different treatments suggested higher soil water storage in structural pores in CA as compared with intensive tillage-based conventional agriculture. The impact of CA on soil physical quality and consequent effect on crop yield was found to be more expressed through dynamic indicators such as hydraulically active porosity rather than capacitive indicators derived from soil moisture retention curve. Overall, this study reveals that conservation agriculture has great potentials to reverse the intensive tillage induced degradation of soil resources in Indo-Gangetic Plains of India by improving the soil hydro-physical properties and soil physical quality.:Table of Contents Declaration i Declaration of Conformity ii Acknowledgements iii Table of Contents v List of Figures vii List of Tables xi List of Symbols, Abbreviations and Acronyms xiv Abstract xvii 1 Introduction and Background 1 1.1 General Overview 1 1.2 Statement of the Research Problem 5 1.3 Objectives 6 1.4 Research Flow and Chapter Description 7 2 Materials and Methods 9 2.1 Study Area Description 9 2.1.1 Study site 9 2.1.2 Climate 9 2.1.3 Soil 10 2.1.4 Treatments 10 2.1.5 Field Campaigns and Measurement/Analysis 14 2.2 Methods and Theoretical Considerations 14 2.2.1 Soil Sampling and Analysis 14 2.2.1.1 Calculation of Stratification Ratio 15 2.2.1.2 Calculation of SOC and TN Storage 15 2.2.1.3 Aggregate Size Distribution 16 2.2.2 Infiltration Measurements 16 2.2.3 Soil Moisture Retention Experiments 17 2.2.4 Derivation of Hydraulic Properties from Steady State Infiltration Rates 18 2.2.4.1 Near-Saturated Hydraulic Conductivity 18 2.2.4.2 Flow Weighted Mean Pore Radius 20 2.2.4.3 Equivalent Threshold pore Radius 21 2.2.4.4 Hydraulically Active Porosity 21 2.2.5 Determiation of Soil Moisture Charachtristics and Pore Size Distribution 22 2.2.6 Derivation of Soil Physical Quality Indicators 23 2.3 Statistics 25 3 Results and Discussion 26 3.1 Stratification and Storage of Soil Organic Matter 26 3.1.1 Bulk Density 26 3.1.2 Concenrations of SOC 27 3.1.3 Concentrations of TN 28 3.1.4 C/N Ratio 29 3.1.5 Stratification Ratio of SOC, TN and C/N Ratio 30 3.1.6 Storage of SOC and TN 33 3.1.7 Discussion 34 3.1.8 Summary of Results 39 3.2 Soil Hydro-Physical Properties 40 3.2.1 Soil Physical Properties 40 3.2.2 Near-Saturated Hydraulic Conductivity 43 3.2.3 Soil Pore Characteristics-Conductivity Relationship 47 3.2.4 Hydrailically active Porosity 51 3.2.5 Summary of Results 54 3.3 Soil Physical Quality (SPQ) 56 3.3.1 Soil Moisture Retention Curve (SMRC) 56 3.3.2 Soil Pore Size Distribution (SPSD) 58 3.3.3 Capacitive Indicators 59 3.3.4 Dynamic Indicators 60 3.3.5 Relationship between capacitive indicators of SPQ with dynamic indicators of SPQ and long-term crop yield 60 3.3.6 Relationship between dynamic indicator of SPQ (hydraulically active porosity) and Long-term Crop Yield 62 3.3.7 Summary of Results 64 4 Synthesis and Conclusions 65 5 Implications and Outlook 69 References 7