Shelf water entrainment by Gulf Stream warm-core rings between 75°W and 50°W during 1978–1999

Previous work concerning Gulf Stream warm-core rings (WCRs) and their associated shelf water entrainments have been based upon single surveys or time series from individual WCRs. To date, estimates of annual shelf water volume entrained into the Slope Sea by WCRs and its interannual variability have not been made. Using a long time series of satellite-derived sea surface temperature (SST) observations of Slope Sea WCRs, we have completed an analysis of 22 years of WCR data (1978–1999) between 75°W and 50°W to understand the interannual variability of WCRs and their role in entraining shelf water. Satellite-derived SST data digitized at Bedford Institute of Oceanography are analyzed using an ellipse-fitting feature model to determine key WCR characteristics including WCR center position, radius and orientation. Key characteristics are then used to compute WCR swirl velocity by finite-differencing WCR orientations (θ) obtained from the feature model time series. Global mean WCR-edge swirl velocity calculated from all observations is 105.72±10.7 km day⁻¹ (122.36±12.4 cm s⁻¹), and global mean WCR radius is 64.8±6.2 km. Primary and derived WCR data are incorporated into a two-dimensional ring entrainment model (RM) using the quasi-geostrophic approximation of the potential vorticity equation. The RM defines ambient water as entrained by a WCR only if the gradient of relative vorticity term (horizontal shear) dominates the potential vorticity. Proximity of a WCR to the position of the shelf-slope front (SSF) is then used to determine whether the ambient water is entrained from the outer continental shelf. WCR-induced shelf entrainment derived from the RM displays considerable spatial variability, with maximum entrainment occurring offshore of Georges Bank, advecting a mean total annual shelf water volume of 7500 km³ year⁻¹ from the region. Estimates of shelf water fluxes display significant interannual variability, which may be in part due to the observed covariance between WCR occurrences and the state of the North Atlantic Oscillation (NAO). Increased (decreased) occurrences of WCRs are evidenced during positive (negative) phases of the NAO. The total mean annual shelf-wide WCR-induced shelf water transport is estimated to be 23,700 km³ year⁻¹ (0.75 Sv), accounting for nearly 25% of the total transport in the Slope Sea region neighboring the outer continental shelf.     

Plutonium and210Pb distributions in northeast Atlantic sediments: subsurface anomalies caused by non-local mixing

The depth distributions of²¹⁰Pb and^239,240Pu measured in a suite of box cores collected from water depths of 4000–5000 m in the northeast Atlantic Ocean exhibit pronounced subsurface maxima caused by sediment reworking by benthic infauna. Small-scale spatial heterogeneity in bioturbation rates is indicated by large differences in tracer profiles from duplicate cores separated only by a few centimeters.²¹⁰Pb and^239,240Pu activity distributions from each subcore exhibit a high degree of correlation, and most tracer profiles exhibit one or more subsurface maxima.One-dimensional, “biodiffusion” analogue models do not adequately simulate the principal features of this data set. However, an inverse “conveyer belt” mixing model which simulates subsurface egestion (or a functionally equivalent process) of surficial material which is enriched both in organic debris and radioactive tracers can reproduce the subsurface tracer maxima. Single-event and continuous subsurface egestion models have been formulated and solved for different “feeding rates” and background biodiffusive fields. The single-event model provides a better fit to the data and, in particular, ensures the observed, high degree of correlation between the²¹⁰Pb and^239,240Pu activity profiles, regardless of the different tracer input functions. The most likely candidate responsible for subsurface tracer egestion is a large infaunal worm of the phylum Sipunculida which dominates the biomass below a depth of 3 cm.     

Controls on deep critical zone architecture: a historical review and four testable hypotheses

The base of Earth's critical zone (CZ) is commonly shielded from study by many meters of overlying rock and regolith. Though deep CZ processes may seem far removed from the surface, they are vital in shaping it, preparing rock for infusion into the biosphere and breaking Earth materials down for transport across landscapes. This special issue highlights outstanding challenges and recent advances of deep CZ research in a series of articles that we introduce here in the context of relevant literature dating back to the 1500s. Building on several contributions to the special issue, we highlight four exciting new hypotheses about factors that drive deep CZ weathering and thus influence the evolution of life‐sustaining CZ architecture. These hypotheses have emerged from recently developed process‐based models of subsurface phenomena including: fracturing related to subsurface stress fields; weathering related to drainage of bedrock under hydraulic head gradients; rock damage from frost cracking due to subsurface temperature gradients; and mineral reactions with reactive fluids in subsurface chemical potential gradients. The models predict distinct patterns of subsurface weathering and CZ thickness that can be compared with observations from drilling, sampling and geophysical imaging. We synthesize the four hypotheses into an overarching conceptual model of fracturing and weathering that occurs as Earth materials are exhumed to the surface across subsurface gradients in stress, hydraulic head, temperature, and chemical potential. We conclude with a call for a coordinated measurement campaign designed to comprehensively test the four hypotheses across a range of climatic, tectonic and geologic conditions. Copyright © 2016 John Wiley & Sons, Ltd.     

How Does Subsurface Characterization Affect Simulations of Hyporheic Exchange?

We investigated the role of increasingly well‐constrained geologic structures in the subsurface (i.e., subsurface architecture) in predicting streambed flux and hyporheic residence time distribution (RTD) for a headwater stream. Five subsurface realizations with increasingly resolved lithological boundaries were simulated in which model geometries were based on increasing information about flow and transport using soil and geologic maps, surface observations, probing to depth to refusal, seismic refraction, electrical resistivity (ER) imaging of subsurface architecture, and time‐lapse ER imaging during a solute tracer study. Particle tracking was used to generate RTDs for each model run. We demonstrate how improved characterization of complex lithological boundaries and calibration of porosity and hydraulic conductivity affect model prediction of hyporheic flow and transport. Models using hydraulic conductivity calibrated using transient ER data yield estimates of streambed flux that are three orders of magnitude larger than uncalibrated models using estimated values for hydraulic conductivity based on values published for nearby hillslopes (10^?4 vs. 10^?7 m²/s, respectively). Median residence times for uncalibrated and calibrated models are 10³ and 10⁰ h, respectively. Increasingly well‐resolved subsurface architectures yield wider hyporheic RTDs, indicative of more complex hyporheic flowpath networks and potentially important to biogeochemical cycling. The use of ER imaging to monitor solute tracers informs subsurface structure not apparent from other techniques, and helps to define transport properties of the subsurface (i.e., hydraulic conductivity). Results of this study demonstrate the value of geophysical measurements to more realistically simulate flow and transport along hyporheic flowpaths.     

Assessing titanium dioxide nanoparticles transport models by Bayesian uncertainty analysis

With the rapid growth of nanotechnology industry, nanomaterials as an emerging pollutant are gradually released into subsurface environments and become great concerns. Simulating the transport of nanomaterials in groundwater is an important approach to investigate and predict the impact of nanomaterials on subsurface environments. Currently, a number of transport models are used to simulate this process, and the outputs of these models could be inconsistent with each other due to conceptual model uncertainty. However, the performances of different models on simulating nanoparticles transport in groundwater are rarely assessed in Bayesian framework in previous researches, and these will be the primary objective of this study. A porous media column experiment is conducted to observe the transport of Titanium Dioxide Nanoparticles (nano-TiO₂). Ten typical transport models which consider different chemical reaction processes are used to simulate the transport of nano-TiO₂, and the observed nano-TiO₂ breakthrough curves data are used to calibrate these models. For each transport model, the parameter uncertainty is evaluated using Markov Chain Monte Carlo, and the DREAM_(ZS) algorithm is used to sample parameter probability space. Moreover, the Bayesian model averaging (BMA) method is used to incorporate the conceptual model uncertainty arising from different chemical reaction based transport models. The results indicate that both two-sites and nonequilibrium sorption models can well reproduce the retention of nano-TiO₂ transport in porous media. The linear equilibrium sorption isotherm, first-order degradation, and mobile-immobile models fail to describe the nano-TiO₂ retention and transport. The BMA method could instead provide more reliable estimations of the predictive uncertainty compared to that using a single model.     

Elastic full waveform inversion with probabilistic petrophysical clustering

Full waveform inversion aims to use all information provided by seismic data to deliver high-resolution models of subsurface parameters. However, multiparameter full waveform inversion suffers from an inherent trade-off between parameters and from ill-posedness due to the highly non-linear nature of full waveform inversion. Also, the models recovered using elastic full waveform inversion are subject to local minima if the initial models are far from the optimal solution. In addition, an objective function purely based on the misfit between recorded and modelled data may honour the seismic data, but disregard the geological context. Hence, the inverted models may be geologically inconsistent, and not represent feasible lithological units. We propose that all the aforementioned difficulties can be alleviated by explicitly incorporating petrophysical information into the inversion through a penalty function based on multiple probability density functions, where each probability density function represents a different lithology with distinct properties. We treat lithological units as clusters and use unsupervised K-means clustering to separate the petrophysical information into different units of distinct lithologies that are not easily distinguishable. Through several synthetic examples, we demonstrate that the proposed framework leads full waveform inversion to elastic models that are superior to models obtained either without incorporating petrophysical information, or with a probabilistic penalty function based on a single probability density function.     

Fusion of multi‐resolution surface (terrestrial laser scanning) and subsurface geodata (ERT,SRT) for karst landform investigation and geomorphometric quantification

A multi‐method research design based on terrestrial laser scanning, GIS, geophysical prospecting (electrical resistivity tomography, refraction seismics) and sedimentology is applied for the first time to investigate enclosed karst depressions in an integrated way. Fusing multi‐resolution surface and subsurface geodata provides profound insights into the formation, geometry and geomorphologic processes of dolines. The studied landforms, which are located in the Dikti Mountains of East Crete, are shown to be filled by loose sediments of thicknesses of up to 30 m that mainly consist of fine‐grained material overlying solid bedrock at depths below 35 to 45 m. By combining subsurface observations with geomorphometric calculations, local doline genesis can be traced back to initial collapse of fractured bedrock followed by subsequent infilling with colluvials. In order to define crucial methodological requirements and guidelines for data fusion, both the impact of different elevation models and the influence of data resolution are assessed. Surface volumes of depressions derived by the digital surface model are 7–21% higher than the results obtained from the terrain model due to vegetation. Similarly, estimates of infill volume calculated on the basis of geophysical outcomes and elevation data differ by up to 13%. Calculations of the landforms' current volumes (i.e. total surface and subsurface volume), however, are fairly insensitive to raster resolution. Hence, the distinct geomorphologic properties of landforms (e.g. shape, terrain roughness, slope inclination) substantially determine the geomorphometric analysis of both surface and subsurface data. As shown by the findings, data fusion to integrate digital terrain, geophysical and sedimentological datasets of varied resolutions benefits geomorphologic studies and helps provide a comprehensive image of landforms. Copyright © 2013 John Wiley & Sons, Ltd.     

Site Response from Ambient Vibrations in the Towns of Lod and Ramle (Israel) and Earthquake Hazard Assessment

Throughout their long history, the towns of Lod and Ramle have been severely affected by strong earthquakes. The last destructive earthquake occurred on July 11, 1927 and caused the destruction of large parts of these cities, reaching a seismic intensity of VIII–IX on the MSK scale. Such a high intensity from a relatively distant earthquake (about 70 km) of magnitude 6.2 is likely to be the result of local site effects of the sedimentary layers that may have significantly enhanced earthquake ground motions. This study is focused on estimating the seismic hazard to Lod and Ramle by implementing a three-step process (1) detailed mapping of the characteristics of the H/V spectral ratios from ambient noise, (2) incorporating geological information and well data to construct subsurface models for different sites within the investigated area and (3) estimating the seismic hazard in terms of uniform hazard site-specific accelerations. The horizontal-to-vertical spectral ratios of ambient noise were used to approximate the fundamental resonance frequencies of the subsurface and their associated amplitudes. About 360 sites in Lod and Ramle were instrumented for varying periods. The soil sites exhibits H/V peak amplitudes ranging from 4 to 6 in the frequency range 0.5–2.5 Hz. These data were used to constrain 1-D subsurface models that were developed using geological data and borehole information. H/V spectral ratio observations were checked against theoretical subsurface transfer functions at locations where borehole information is available farther constraint the range of possible V_s velocities of the different layers and thus, by means of trial an error it was possible to conclude a systematic spatial distribution of the V_s velocity and thickness in the substrata that are also consistent with the spatial distribution of the fundamental resonance frequencies of the soft sediments obtained by means of the H/V spectral ratios, and other geological and geophysical information available at different locations in the study area. The evaluated subsurface models are introduced using the SEEH procedure of Shapira and van~Eck [(1993) Natural Hazards 8, 201–205] to assess Uniform Hazard Site-Specific Acceleration Spectra for different zones within the towns of Lod and Ramle. These evaluations are very important for realistic assessment of the vulnerabilities of all types of existing and newly designed structures and for urban and land use planning.     

Initial velocity model construction of seismic tomography in near-surface applications

The impact of initial velocity models on final image reconstruction results and how to construct a proper initial velocity model in near-surface tomography studies are investigated on a two-layer synthetic model with gradually increasing velocity with depth. Refraction initial velocity models and linear velocity function models are tested on both synthetic and field data to obtain images close to reality. It is concluded that velocity function type initial models should be preferred in soft alluvial deposits that exist within the investigated depths, whereas refraction initial models should be preferred in the groundwater table or with strong refractors' existence within the investigated depths to obtain optimum subsurface images in refraction–diving wave seismic tomography.     

Water balance estimation under the challenge of data scarcity in a hyperarid to Mediterranean region

Water budget analyses are important for the evaluation of the water resources in semiarid and arid regions. The lack of observed data is the major obstacle for hydrological modelling in arid regions. The aim of this study is the analysis and calculation of the natural water resources of the Western Dead Sea subsurface catchment, one which is highly sensitive to rainfall resulting in highly variable temporal and spatial groundwater recharge. We focus on the subsurface catchment and subsequently apply the findings to a large‐scale groundwater flow model to estimate the groundwater discharge to the Dead Sea. We apply a semidistributed hydrological model (J2000g), originally developed for the Mediterranean, to the hyperarid region of the Western Dead Sea catchment, where runoff data and meteorological records are sparsely available. The challenge is to simulate the water budget, where the localized nature of extreme rainstorms together with sparse runoff data results in few observed runoff and recharge events. To overcome the scarcity of climate input data, we enhance the database with mean monthly rainfall data. The rainfall data of 2 satellites are shown to be unsuitable to fill the missing rainfall data due to underrepresentation of the steep hydrological gradient and temporal resolution. Hydrological models need to be calibrated against measured values; hence, the absence of adequate data can be problematic. Therefore, our calibration approach is based on a nested strategy of diverse observations. We calculate a direct surface runoff of the Western Dead Sea surface area (1,801 km²) of 3.4 mm/a and an average recharge (36.7 mm/a) for the 3,816 km² subsurface drainage basin of the Cretaceous aquifer system.     

A Bayesian trans-dimensional approach for the fusion of multiple geophysical datasets

We propose a Bayesian fusion approach to integrate multiple geophysical datasets with different coverage and sensitivity. The fusion strategy is based on the capability of various geophysical methods to provide enough resolution to identify either subsurface material parameters or subsurface structure, or both. We focus on electrical resistivity as the target material parameter and electrical resistivity tomography (ERT), electromagnetic induction (EMI), and ground penetrating radar (GPR) as the set of geophysical methods. However, extending the approach to different sets of geophysical parameters and methods is straightforward. Different geophysical datasets are entered into a trans-dimensional Markov chain Monte Carlo (McMC) search-based joint inversion algorithm. The trans-dimensional property of the McMC algorithm allows dynamic parameterisation of the model space, which in turn helps to avoid bias of the post-inversion results towards a particular model. Given that we are attempting to develop an approach that has practical potential, we discretize the subsurface into an array of one-dimensional earth-models. Accordingly, the ERT data that are collected by using two-dimensional acquisition geometry are re-casted to a set of equivalent vertical electric soundings. Different data are inverted either individually or jointly to estimate one-dimensional subsurface models at discrete locations. We use Shannon's information measure to quantify the information obtained from the inversion of different combinations of geophysical datasets. Information from multiple methods is brought together via introducing joint likelihood function and/or constraining the prior information. A Bayesian maximum entropy approach is used for spatial fusion of spatially dispersed estimated one-dimensional models and mapping of the target parameter. We illustrate the approach with a synthetic dataset and then apply it to a field dataset. We show that the proposed fusion strategy is successful not only in enhancing the subsurface information but also as a survey design tool to identify the appropriate combination of the geophysical tools and show whether application of an individual method for further investigation of a specific site is beneficial.     

A numerical model for estimating groundwater flux from subsurface temperature profiles

A simple numerical model is presented for estimating vertical groundwater flux from transient subsurface temperature profiles obtained from field measurements. The model developed utilizes the MacCormack scheme, which is based on the Finite Difference Method (FDM), for solving the governing partial differential equation of convection–diffusion heat transport with appropriate initial and boundary conditions within the subsurface. In order to validate the model, numerical solutions obtained for the study area located in the Nagoka plain, Japan are compared with the published measured data and results obtained by others. Results obtained show good agreement and fit the observed data with a correlation coefficient, R², of 0·88. The estimated groundwater flux is 1·85 × 10⁻⁷ m s⁻¹. Sensitivity analyses were also carried out to investigate the effect of variations in groundwater fluxes, thermal properties and the annual thermal variability due to climatic changes on the transient subsurface temperature profiles and to have a better understanding of the subsurface thermal dynamics. A substantial effect of annual climatic variability is observed on the temporal distributions of temperature depth profiles, and a better estimate of thermal parameters is required to estimate vertical groundwater flux. The largest change in subsurface temperature depth profiles due to groundwater flux over a year is within ± 4 °C. The influence of groundwater flux on subsurface temperature distributions in space and time may be more pronounced in areas where the top of the saturated layer fluctuates considerably. Variation in thermal diffusivity results in temperature change up to ± 1·5% and may cause change in groundwater flux estimate by ± 18%. The model presented has merits over analytical solutions (type curve matching techniques) in terms of suitability and applicability to real field problems, and can be a good asset to hydrological models as quantifying groundwater recharge or deducing it from other quantities, such as rainfall, evapotranspiration and runoff, is often complicated. Copyright © 2007 John Wiley & Sons, Ltd.     

Modelling of infiltration using artificial intelligence techniques in semi-arid Iran

ABSTRACT

Infiltration plays a fundamental role in streamflow, groundwater recharge, subsurface flow, and surface and subsurface water quality and quantity. In this study, adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM) and random forest (RF) models were used to determine cumulative infiltration and infiltration rate in arid areas in Iran. The input data were sand, clay, silt, density of soil and soil moisture, while the output data were cumulative infiltration and infiltration rate, the latter measured using a double-ring infiltrometer at 16 locations. The results show that SVM with radial basis kernel function better estimated cumulative infiltration (RMSE = 0.2791 cm) compared to the other models. Also, SVM with M4 radial basis kernel function better estimated the infiltration rate (RMSE = 0.0633 cm/h) than the ANFIS and RF models. Thus, SVM was found to be the most suitable model for modelling infiltration in the study area.     

Simultaneous Denoising and Interpolation of Seismic Data via the Deep Learning Method

Utilizing data from controlled seismic sources to image the subsurface structures and invert the physical properties of the subsurface media is a major effort in exploration geophysics. Dense seismic records with high signal-to-noise ratio (SNR) and high fidelity helps in producing high quality imaging results. Therefore, seismic data denoising and missing traces reconstruction are significant for seismic data processing. Traditional denoising and interpolation methods rarely occasioned rely on noise level estimations, thus requiring heavy manual work to deal with records and the selection of optimal parameters. We propose a simultaneous denoising and interpolation method based on deep learning. For noisy records with missing traces, we adopt an iterative alternating optimization strategy and separate the objective function of the data restoring problem into two sub-problems. The seismic records can be reconstructed by solving a least-square problem and applying a set of pre-trained denoising models alternatively and iteratively.We demonstrate this method with synthetic and field data.     

Homogenization of spatial patterns of hydrologic response in artificially drained agricultural catchments

Anthropogenic modifications to the landscape, with agricultural activities being a primary driver, have resulted in significant alterations to the hydrologic cycle. Artificial drainage, including surface and subsurface drainage (tile drains), is one of the most extensive manipulations in agricultural landscapes and thus is expected to provide a distinct signature of anthropogenic modification. This study adopts a data synthesis approach in an effort to characterize the signature of artificial subsurface drainage. Daily discharge data from 24 basins across the state of Iowa, which encapsulate a range of anthropogenic modifications, are assessed using a variety of flow metrics. Results indicate that the presence of artificial subsurface drainage leads to a homogenization of landscape hydrologic response. Non‐tiled watersheds exhibit a decrease in the area‐normalized peak discharge and an increase in the baseflow ratio (baseflow/streamflow) with increases in the spatial scale, while scale invariance is apparent in tiled basins. Within‐basin variability in hydrograph recession coefficients also appears to decrease with increases in the proportion of the catchment that is artificially drained. Finally, the differences between tiled and non‐tiled landscapes disappear at scales greater than approximately 2200 km², indicating that this may be a threshold scale for studying the effects of tile drainage. This decrease in within‐basin variability and the scale invariance of hydrologic metrics in artificially drained watersheds are attributed to the creation of a bypass flow hydrologic pathway that bypasses the complexity of the catchment travel paths. Spatial homogeneity in responses implies that it may be possible to develop more parsimonious hydrologic models for these regions. Copyright © 2013 John Wiley & Sons, Ltd.     

Target-oriented imaging using extended image volumes: a low-rank factorization approach

Imaging in geological challenging environments has led to new developments, including the idea of generating reflection responses by means of interferometric redatuming at a given target datum in the subsurface, when the target datum lies beneath a complex overburden. One way to perform this redatuming is via conventional model-based wave-equation techniques. But those techniques can be computationally expensive for large-scale seismic problems since the number of wave-equation solves is equal to two times the number of sources involved during seismic data acquisition. Also conventional shot-profile techniques require lots of memory to save full subsurface extended image volumes. Therefore, we can only form subsurface image volumes in either horizontal or vertical directions. To exploit the information hidden in full subsurface extended image volumes, we now present a randomized singular value decomposition-based approach built upon the matrix probing scheme, which takes advantage of the algebraic structure of the extended imaging system. This low-rank representation enables us to overcome both the computational cost associated with the number of wave-equation solutions and memory usage due to explicit storage of full subsurface extended image volumes employed by conventional migration methods. Experimental results on complex geological models demonstrate the efficacy of the proposed methodology and allow practical reflection-based extended imaging for large-scale five-dimensional seismic data.     

2D cooperative inversion of direct current resistivity and gravity data: A case study of uranium bearing target rock

Interpretation of a single geophysical data set is not sufficient to get complete subsurface information. Cooperative or joint inversion of geophysical data sets is the preferred method for most case studies. In the present study, we present the results of the cooperative inversion approach of direct current resistivity and gravity data. The algorithm uses fuzzy c-means clustering to determine the petrophysical relationship between density and resistivity to obtain the similarity. Synthetic data set has demonstrated that the cooperative inversion approach can produce more reliable and better resistivity and density models of the subsurface as compared to those obtained through individual inversions. To utilize the presented cooperative inversion algorithm, the number of geologic units (number of clusters) in the study region must be known a priori. As a field study, the cooperative inversion approach was used to identify the extension of uranium-bearing target rock around the Beldih open cast mine. We noted the inconsistencies in both resistivity and density models obtained from the individual inversions. However, the presented cooperative inversion approach was able to produce similar resistivity and density models while maintaining the same error level of the respective individual inversions. We have considered four geologic units in the presented cooperative inversion as a field case study. We have also compared our cooperative results with drilled borehole and found to be a reliable tool to differentiate between the target rocks (kaolinite and quartz–magnetite–apatite rocks) and the ultramafic rock (host rock quartzite/alkaline granite). However, this study is subject to certain limitations such as the inability to differentiate between closely spaced kaolinite and quartz–magnetite–apatite rocks.     

Application of a watershed runoff model to North-east Pond River,Newfoundland: to study water balance and hydrological characteristics owing to atmospheric change

The hydrological sensitivities to long-term climate change of a watershed in Eastern Canada were analysed using a deterministic watershed runoff model developed to simulate watershed acidification. This model was modified to study atmospheric change effects in the watershed. Water balance modelling techniques, modified for assessing climate effects, were developed and tested for a watershed using atmospheric change scenarios from both state of the art general circulation models and a series of hypothetical scenarios. The model computed daily surface, inter- and groundwater flows from the watershed. The moisture, infiltration and recharge rate are also computed in the soil reservoirs. The thirty years of simulated data can be used to evaluate the effects of climatic change on soil moisture, recharge rate and surface and subsurface flow systems. The interaction between surface and subsurface water is discussed in relation to climate change. These hydrological results raise the possibility of major environmental and socioeconomic difficulties and have significant implications for future water resource planning and management. © 1997 John Wiley & Sons, Ltd.     

我国地震地下流体学科的“八五”进展概述

本文根据１９９２－１９９４年间发表的１２５篇有关论文和“八五”短临预报攻关三级课题研究报告，简要地介绍了我国地震地下流体学科在观测技术、震例与预报方法、映震理论与数据处理、干扰因素与映震灵敏条件等方面取得的科学进展，为“九五”立项提供背景材料。