Simulation of groundwater dynamics in the North China Plain by coupled hydrology and agricultural models

We simulated the effects of irrigation on groundwater flow dynamics in the North China Plain by coupling the NIES Integrated Catchment‐based Ecohydrology (NICE) model with DSSAT‐wheat and DSSAT‐maize, two agricultural models. This combined model (NICE‐AGR) was applied to the Hai River catchment and the lower reach of the Yellow River (530 km wide by 840 km long) at a resolution of 5 km. It reproduced excellently the soil moisture, evapotranspiration and crop production of summer maize and winter wheat, correctly estimating crop water use. So, the spatial distribution of crop water use was reasonably estimated at daily steps in the simulation area. In particular, NICE‐AGR reproduced groundwater levels better than the use of statistical water use data. This indicates that NICE‐AGR does not need detailed statistical data on water use, making it very powerful for evaluating and estimating the water dynamics of catchments with little statistical data on seasonal water use. Furthermore, the simulation reproduced the spatial distribution of groundwater level in 1987 and 1988 in the Hebei Plain, showing a major reduction of groundwater level due mainly to overpumping for irrigation. Copyright © 2006 John Wiley & Sons, Ltd.     

Nonlinear regional economic dynamics: continuous-time specification,estimation and stability analysis

This paper presents an innovative approach to the study of regional economic dynamics within a nonlinear continuous-time econometric framework—a generalized specification of the Lotka–Volterra system of equations. This specification, which accounts for interdependent behavior of three industrial sectors and spillover effects of activities in neighboring regions, is employed in an analysis of five Italian regions between 1980 and 2003. For these regions, we report estimation results, characterize the varying systems dynamics, analyze the models’ local and global stability properties, and determine via sensitivity analyses which structural features appear to exert the greatest influence on these properties.

Phase Equilibria Constraints on the Chemical and Physical Evolution of the Campanian Ignimbrite

The Campanian Ignimbrite is a > 200 km³ trachyte–phonolitepyroclastic deposit that erupted at 39·3 ± 0·1ka within the Campi Flegrei west of Naples, Italy. Here we testthe hypothesis that Campanian Ignimbrite magma was derived byisobaric crystal fractionation of a parental basaltic trachyandesiticmelt that reacted and came into local equilibrium with smallamounts (5–10 wt%) of crustal rock (skarns and foid-syenites)during crystallization. Comparison of observed crystal and magmacompositions with results of phase equilibria assimilation–fractionationsimulations (MELTS) is generally very good. Oxygen fugacitywas approximately buffered along QFM + 1 (where QFM is the quartz–fayalite–magnetitebuffer) during isobaric fractionation at 0·15 GPa ( 6km depth). The parental melt, reconstructed from melt inclusionand host clinopyroxene compositions, is found to be basaltictrachyandesite liquid (51·1 wt% SiO₂, 9·3 wt%MgO, 3 wt% H₂O). A significant feature of phase equilibria simulationsis the existence of a pseudo-invariant temperature, 883 °C,at which the fraction of melt remaining in the system decreasesabruptly from 0·5 to < 0·1. Crystallizationat the pseudo-invariant point leads to abrupt changes in thecomposition, properties (density, dissolved water content),and physical state (viscosity, volume fraction fluid) of meltand magma. A dramatic decrease in melt viscosity (from 1700Pa s to 200 Pa s), coupled with a change in the volume fractionof water in magma (from 0·1 to 0·8) and a dramaticdecrease in melt and magma density acted as a destabilizingeruption trigger. Thermal models suggest a timescale of 200kyr from the beginning of fractionation until eruption, leadingto an apparent rate of evolved magma generation of about 10^–3km³/year. In situ crystallization and crystal settling in density-stratifiedregions, as well as in convectively mixed, less evolved subjacentmagma, operate rapidly enough to match this apparent volumetricrate of evolved magma production. KEY WORDS: assimilation; Campanian Ignimbrite; fractional crystallization; magma dynamics; phase equilibria     

Generating soil thickness maps by means of geomorphological-empirical approach and random forest algorithm in Wanzhou County,Three Gorges Reservoir

Soil thickness, intended as depth to bedrock, is a key input parameter for many environmental models. Nevertheless, it is often difficult to obtain a reliable spatially exhaustive soil thickness map in wide-area applications, and existing prediction models have been extensively applied only to test sites with shallow soil depths. This study addresses this limitation by showing the results of an application to a section of Wanzhou County (Three Gorges Reservoir Area, China), where soil thickness varies from 0 to ～40 m. Two different approaches were used to derive soil thickness maps: a modified version of the geomorphologically indexed soil thickness (GIST) model, purposely customized to better account for the peculiar setting of the test site, and a regression performed with a machine learning algorithm, i.e., the random forest, combined with the geomorphological parameters of GIST (GIST-RF). Additionally, the errors of the two models were quantified, and validation with geophysical data was carried out. The results showed that the GIST model could not fully contend with the high spatial variability of soil thickness in the study area: the mean absolute error was 10.68 m with the root-mean-square error (RMSE) of 12.61 m, and the frequency distribution residuals showed a tendency toward underestimation. In contrast, GIST-RF returned a better performance with the mean absolute error of 3.52 m and RMSE of 4.56 m. The derived soil thickness map could be considered a critical fundamental input parameter for further analyses.     

Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India

Drought is a natural phenomenon posing severe implications for soil, groundwater and agricultural yield. It has been recognized as one of the most pervasive global change drivers to affect the soil. Soil being a weakly renewable resource takes a long time to form, but it takes no time to degrade. However, the response of soil to drought conditions as soil loss is not manifested in the existing literature. Thus, this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India. MODIS remote sensing data was utilized for driving drought indices during 2000–2019. Firstly, we constricted Temperature condition index (TCI) and Vegetation Condition Index (VCI) from Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) derived from MODIS data. TCI and VCI were then integrated to determine the Vegetation Health Index (VHI). Revised Universal Soil Loss Equation (RUSLE) was utilized for estimating soil loss. The relationship between drought condition and vegetation was ascertained using the Pearson correlation. Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during 2000–2019. The mean frequency of the drought occurrence was 7.95 months. The average soil erosion in the sub-basin was estimated to be 9.88 t ha^?1 year^?1. A positive relationship was observed between drought indices and soil erosion values (r value being 0.35). However, wide variations were observed in the distribution of spatial correlation. Among various factors, the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin. Thus, the study calls for policy measures to lessen the impact of drought and soil erosion.     

山地冰川演化与冰湖发育相互作用机制北大核心CSCD

冰川-冰湖耦合过程是冰冻圈物质与能量循环的重要组成部分,系统刻画冰川演化与冰湖发育过程的相互作用机制,对于完善冰冻圈科学理论体系和认知冰川作用区变化规律、水循环模式和灾害效应具有重要意义。本文立足山地冰川演化和冰湖发育过程,系统归纳了冰川-冰湖相互作用研究进展,剖析了冰川作用与冰湖发育耦合机制及相关模型的应用,并对现有冰川演化与冰湖发育过程耦合机制研究存在的不足与挑战进行解析和总结。冰川-冰湖耦合过程的深入研究有助于提高数值模拟的可信度与精度,为评估冰川-冰湖耦合过程影响、建立灾害监测预警体系和采取适应性措施提供数据与理论基础。     

地壳内的岩浆动力学过程及其资源与环境效应SCIEI北大核心CSCD

岩浆是将地球内部物质传送到表层系统的主要载体,并造成显著的资源聚集和环境效应。岩浆动力学是研究岩浆的迁移、储存、演化、就位以及喷发过程,侧重物理机制。这些岩浆过程主要发生在岩浆通道系统中,包括岩浆储库和岩浆管道。本文对目前国际岩浆动力学领域一些热点和前沿进行了介绍,这包括从岩浆房到岩浆储库概念的转变、岩浆储库的生长和动力学演化过程、岩浆过程的时间尺度以及岩浆中晶体的生长。然后阐述了岩浆中挥发分的种类和溶解度、获取天然岩浆挥发分含量的方法、一些典型镁铁质岩浆中的挥发分含量、岩浆去气的化学和物理机制,并简要梳理了热液金属矿床的形成过程和岩浆挥发分进入地表圈层系统引发的环境气候效应。最后列举了一些岩浆动力学有关的重要科学问题并建议了进一步的研究方向。     

The Energy Relationship between Ions and Soil Particles based on Wien Effect and Its Application in Soil Science

The interaction between ions and soil particles plays an important role in the mobilization and bioavailability of ions in soils, which is one of the main research areas of soil chemistry. The new method based on suspension Wien effect has been developed recently to determine the binding energy and adsorption energy between ions and soil particles. Compared with other methods on the basis of adsorption isotherm or ions activity, Wien effect method has more advantages including convenience and direct measurement. The term suspension Wien effect refers to the increase of electrical conductivity of suspension with increasing applied electrical field. In this review paper, we introduced the fundamentals of suspension Wien effect, the apparatus about the Wien effect measurement, and along with demonstrating their application to quantifying the particles-ions interactions for several systems of soils. Our studies indicated that divalent cations have larger binding energies and adsorption energies on soil particles than monovalent because of the electrostatic interaction. However, few studies about the interaction between Cr³⁺ and La³⁺ on soil particles showed that the binding energy and adsorption energy of trivalent cations are lower than those of divalent cations because of hydrolysis. Soil properties such as soil organic matter, soil pH, and iron oxides significantly affected the binding energy and adsorption energy of ions. Our results deepened our understanding about the non specific adsorption of ions in soil chemistry, and enlarged the research area of soil chemistry in fundamental and methodology.     

Prediction of soil properties using imaging spectroscopy: Considering fractional vegetation cover to improve accuracy

Spectroscopic techniques have become attractive to assess soil properties because they are fast, require little labor and may reduce the amount of laboratory waste produced when compared to conventional methods. Imaging spectroscopy (IS) can have further advantages compared to laboratory or field proximal spectroscopic approaches such as providing spatially continuous information with a high density. However, the accuracy of IS derived predictions decreases when the spectral mixture of soil with other targets occurs. This paper evaluates the use of spectral data obtained by an airborne hyperspectral sensor (ProSpecTIR-VS – Aisa dual sensor) for prediction of physical and chemical properties of Brazilian highly weathered soils (i.e., Oxisols). A methodology to assess the soil spectral mixture is adapted and a progressive spectral dataset selection procedure, based on bare soil fractional cover, is proposed and tested. Satisfactory performances are obtained specially for the quantification of clay, sand and CEC using airborne sensor data (R² of 0.77, 0.79 and 0.54; RPD of 2.14, 2.22 and 1.50, respectively), after spectral data selection is performed; although results obtained for laboratory data are more accurate (R² of 0.92, 0.85 and 0.75; RPD of 3.52, 2.62 and 2.04, for clay, sand and CEC, respectively). Most importantly, predictions based on airborne-derived spectra for which the bare soil fractional cover is not taken into account show considerable lower accuracy, for example for clay, sand and CEC (RPD of 1.52, 1.64 and 1.16, respectively). Therefore, hyperspectral remotely sensed data can be used to predict topsoil properties of highly weathered soils, although spectral mixture of bare soil with vegetation must be considered in order to achieve an improved prediction accuracy.     

(Re-)sources of innovation: Understanding and comparing time-spatial innovation dynamics through the lens of communities of practice

Communities of practice play an important role in innovation processes. It is, however, still unclear what their particular function is. In this article the authors seek first to develop further systematic differentiations between different types of knowing in practice to provide the conceptual ground for studying the influences of knowing in practice on innovation in a comparative way. Therefore, existing inductive approaches are complemented with deductive elements that highlight different impulses of reflexivity (push vs. pull) and different internal logics of reflexivity (rationalist vs. aesthetic). Second, in this article the authors introduce a dynamic approach which focuses on core ideas of innovation processes from a spatial perspective. In such a dynamic view types of knowing in practice have an impact as sources and resources of innovation. As sources of innovation they form a particular locus in which novel ideas emerge and subsequently take particular trajectories. As resources of innovation they intervene at subsequent stages of the process and propel further the translation process of a novel idea becoming eventually a valuable and practicable solution.