Detection and sizing of extended partial blockages in pipelines by means of a stochastic successive linear estimator

Effective water system management depends upon knowledge of the current state of a water pipeline system network. For example, in many cases, partial blockages in a water pipeline system are a source of inefficiencies, and result in an increase of pumping costs. These anomalies must be detected and corrected as early as possible. In this study, an algorithm is developed for detecting blockages by means of pressure transient measurements and estimating the diameter distribution resulting from their formation. The algorithm is a stochastic successive linear estimator that provides statistically the best unbiased estimate of diameter distribution due to partial blockages and quantifies the uncertainty associated with these estimates. We first present the theoretical formulation of the algorithm and then test it with a numerical case study

Equivalence of Discrete Fracture Network and Porous Media Models by Hydraulic Tomography

Hydraulic tomography (HT) has emerged as a potentially viable method for mapping fractures in geologic media as demonstrated by recent studies. However, most of the studies adopted equivalent porous media (EPM) models to generate and invert hydraulic interference test data for HT. While these models assign significant different hydraulic properties to fractures and matrix, they may not fully capture the discrete nature of the fractures in the rocks. As a result, HT performance may have been overrated. To explore this issue, this study employed a discrete fracture network (DFN) model to simulate hydraulic interference tests. HT with the EPM model was then applied to estimate the distributions of hydraulic conductivity (K) and specific storage (S-s) of the DFN. Afterward, the estimated fields were used to predict the observed heads from DFN models, not used in the HT analysis (i.e., validation). Additionally, this study defined the spatial representative elementary volume (REV) of the fracture connectivity probability for the entire DFN dominant. The study showed that if this spatial REV exists, the DFN is deemed equivalent to EPM and vice versa. The hydraulic properties estimated by HT with an EPM model can then predict head fields satisfactorily over the entire DFN domain with limited monitoring wells. For a sparse DFN without this spatial REV, a dense observation network is needed. Nevertheless, HT is able to capture the dominant fractures.National Science and Technology Major Project of China [2017ZX05008-003-021]; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB10030601]; Youth Innovation Promotion Association of the Chinese Academy of Sciences [2016063]; US Civilain Research and Development Foundation (CRDF) under the award: Hydraulic tomography in shallow alluvial sediments: Nile River Valley, Egypt [DAA2-15-61224-1]; Global Expert award through Tianjin Normal University from the Thousand Talents Plan of Tianjin City6 month embargo; published online: 23 April 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The relative importance of head, flux, and prior information in hydraulic tomography analysis

Using cross-correlation analysis, we demonstrate that flux measurements at observation locations during hydraulic tomography (HT) surveys carry nonredundant information about heterogeneity that are complementary to head measurements at the same locations. We then hypothesize that a joint interpretation of head and flux data, even when the same observation network as head has been used, can enhance the resolution of HT estimates. Subsequently, we use numerical experiments to test this hypothesis and investigate the impact of flux conditioning and prior information (such as correlation lengths and initial mean models (i.e., uniform mean or distributed means)) on the HT estimates of a nonstationary, layered medium. We find that the addition of flux conditioning to HT analysis improves the estimates in all of the prior models tested. While prior information on geologic structures could be useful, its influence on the estimates reduces as more nonredundant data (i.e., flux) are used in the HT analysis. Lastly, recommendations for conducting HT surveys and analysis are presented

Author's personal copy Stochastic inversion of pneumatic cross-hole tests and barometric pressure fluctuations in heterogeneous unsaturated formations

a b s t r a c t The distributions of permeability and porosity are key factors that control airflow and gas phase transport in unsaturated formations. To understand the behavior of flow and transport in such formations, characterization procedure is a typical approach that has been widely applied to laboratories and fields. As is recognized by most investigations, this approach relies on accurate measurements, and more importantly, an adequate tool to interpret those measurements from experiments. This study presents a pneumatic inverse model that is capable to estimate the distributions of permeability (k) and porosity (/) with high resolution in heterogeneous unsaturated formations. Based on the concept of sequential successive linear estimator (SSLE), the developed model accounts for compressibility and density of air and estimates the geologic parameters using air pressure measurements from sequential cross-hole pneumatic pumping or injection tests. Four synthetic examples, including a one-dimensional well-posed, a horizontally two-dimensional, and two three-dimensional problems, are used to evaluate the developed model in estimating the distributions of permeability and porosity in unsaturated formations. Results of the numerical experiments are promising. The developed pneumatic inverse model can reconstruct the property (i.e., permeability and porosity) fields if the well-defined conditions are met. With a relatively small number of available measurements, the proposed model can accurately capture the patterns and the magnitudes of estimated properties for unsaturated formations. Results of two complex three-dimensional examples show that the proposed model can map the fracture connectivity using a small number of subsurface pressure measurements and estimate k and / in shallow soil layers using spatial variations of barometric pressure

Investigation of Karst Spring Flow Cessation Using Grey System Models

Karst aquifers are prominent sources of water worldwide; they store large amounts of water and are known for their beautiful springs. However, extensive groundwater development and climate variation has resulted in a decline in the flow of most karst springs; some have even dried up. In order to obtain a better understanding of the factors contributing to this development, this study introduced grey system models, which quantified spring flow, taking Jinci Springs (China), which dried up in May 1994, as an example. Based on the characteristics of Jinci Springs, spring flow was divided into two stages: first (1954–1960), when the spring flow was affected only by climate variation; and second (1961–1994), when the flow was impacted by both climate variation and anthropogenic activities. The results showed that Jinci Springs flow had a strong relationship with precipitation occurring one year and three years earlier in the first stage. Subsequently, a grey system GM (1,3) model with one-year and three-year lags was set up for the first stage. By using the GM (1,3) model, we simulated the spring flow in the second stage under effects of climate variation only. By subtracting the observed spring flow from the simulated flow, we obtained the contribution of anthropogenic activities to Jinci Springs’ cessation. The contribution of anthropogenic activities and climate variation to the decline was 1.46 m3/s and 0.62 m3/s, respectively. Finally, each human activity that caused the decline was estimated. The methods devised herein can be used to describe karst hydrological processes that are under the effects of anthropogenic activities and climate variation.Natural Science Foundation of Tianjin [18JCZDJC39500]; Program for Innovative Research Team in Universities of Tianjin, China [TD13-5078]; National Natural Science Foundation of China [41272245, 40972165, 40572150]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Two-Dimensional Probabilistic Infiltration Analysis in a Hillslope Using First-Order Moment Approach

A first-order moment analysis method is introduced to evaluate the pore-water pressure variability within a hillslope due to spatial variability in saturated hydraulic conductivity (K-s) during rainfall. The influences of the variance of the natural logarithm of K-s(ln K-s), spatial structure anisotropy of ln K-s, and normalized vertical infiltration flux (q) on the evaluations of the pore-water pressure uncertainty are investigated. Results indicate different responses of pressure head variability in the unsaturated region and the saturated region. In the unsaturated region, a larger variance of ln K-s, a higher spatial structure anisotropy, and a smaller q lead to a larger variability in pressure head, while in the saturated region, the variability in pressure head increases with the increase of variance of ln K-s, the decrease of spatial structure anisotropy, or the increase of q. These variables have great impacts on the range of fluctuation of the phreatic surface within the hillslope. The influences of these three variables on the variance of pressure head within the saturated region are greater than those within the unsaturated region, and the variance of ln K-s has the greatest impact. These results yield useful insight into the effects of heterogeneity on pressure head and uncertainty associated with predicted flow field.Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) [CUG170686]; China Scholarship Council [201406410032]; National Natural Science Foundation of China [41172282, 41672313]; Strategic Environmental Research and Development Program [ER-1365]; Environmental Security and Technology Certification Program [ER201212]; National Science Foundation-Division of Earth Sciences [1014594]; Outstanding Oversea Professorship award through Jilin University from Department of Education, China; Global Expert award through Tianjin Normal University from the Thousand Talents Plan of Tianjin City12 month embargo; published online: 25 April 2018This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Utilizing Precipitation and Spring Discharge Data to Identify Groundwater Quick Flow Belts in a Karst Spring Catchment

In karst terrains, fractures and conduits often occur in clusters, forming groundwater quick flow belts, which are the major passages of groundwater and solute transport. We propose a cost-effective method that utilizes precipitation and spring discharge data to identify groundwater quick flow belts by the multitaper method (MTM). In this paper, hydrological processes were regarded as the transformation of precipitation signals to spring discharge signals in a karst spring catchment. During the processes, karst aquifers played the role of signal filters. Only those signals with high energy could penetrate through aquifers and reflect in the spring discharge, while other weak signals were filtered out or altered by aquifers. Hence, MTM was applied to detect and reconstruct the signals that penetrate through aquifers. Subsequently, by analyzing the reconstructed signals of precipitation with those of spring discharge, we acquired the hydraulic response time and identified the quick flow belts. Finally, the methods were applied to the Niangziguan Spring (NS) catchment, China. Results showed that the hydraulic response time of the spring discharge to precipitation was 3 months at Pingding County; 4 months at Yuxian County, Yangquan City, Xiyang County, and Heshun County; and 27 months at Shouyang County and Zouquan County. These results suggested that Pingding County is located at a groundwater quick flow belt, which is a major passage of groundwater and contaminants, in the NS catchment. This is important since Pingding County is not only the key development area of karst groundwater but also the key conservation area for sustainable development of karst groundwater resources in NS catchment.Natural Science Foundation of Tianjin, China [18JCZDJC39500]; Program for Innovative Research Team in Universities of Tianjin [TD13-5078]; National Natural Science Foundation of China [41272245, 40972165, 40572150]6 month embargo; published online: 10 October 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Comparing control methods of water inrush disaster using mathematical programming: modelling, analysis and a case study

Water inrush from coal floor is one of the main disasters in underground coal mining operations. When establishing or selecting control methods, various factors, such as cost, risk and operability, should be taken into consideration. However, due to the lack of effective mathematical models, the selecting process in practice relies solely on engineering experiences, which may not lead to an optimal and effective decision. This paper proposes a method that considers the parameters, variables, and constraints in water inrush control and it adopts economic factors as the objective function to construct a multi-objective optimization model. Using this method, one can not only rank different control measures but also obtain a preferred control effect level, which is a trade-off between efficiency and economy. A case study is used to demonstrate the robustness of the proposed approach

Identification of groundwater basin shape and boundary using hydraulic tomography

Shapes and boundary types of a groundwater basin play essential roles in the analysis of groundwater management and contaminant migration. Hydraulic tomography (HT), a recently developed new approach for high-resolution characterization of aquifers, is not only an inverse method but a logical strategy for collecting non-redundant hydraulic information. In this study, HT was applied to synthetic 2-D aquifers to investigate its feasibility to map the irregular shapes and types of the aquifer boundaries. We first used the forward model of VSAFT2 to simulate hydraulic responses due to HT surveys in the aquifer with irregular geometry and predetermined constant head conditions at some boundaries, and no-flow conditions at others. The SimSLE (Simultaneous Successive Linear Estimator) inverse model in VSAFT2 was then used to interpret the simulated HT data to estimate the spatial distribution of hydraulic properties of the aquifer using a domain with a wrong geometry surrounded by boundaries of a constant head condition. The inverse modeling experiment used steady-state and transient-states data from the HT forward simulations, and it used the same monitoring network as in the aquifer with irregular geometry to assess the ability of HT for detecting types and shapes of the boundary as well as heterogeneity in the aquifer. Results of the experiment show that no-flow boundaries, which were incorrectly treated as constant head boundaries in inverse models, were portrayed as low permeable zones of the aquifer near the boundaries. Overall, the results show that HT could delineate not only the irregular shape of the aquifer in general but also heterogeneity in the aquifer. Improvements of the estimation with prior information of transmissivity and storage coefficient was also investigated. The study shows that using homogeneous initial guess parameters resulted in a slightly better estimate than others. Moreover, this study employs Monte Carlo simulations to ensure statistically meaningful conclusions.The Scholarship from the Royal Thai Government and the Department of Groundwater Resources, Thailand, and partially supported by U.S. NSF grant EAR193175624 month embargo; available online 21 May 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Effects of heterogeneity distribution on hillslope stability during rainfalls

The objective of this study was to investigate the spatial relationship between the most likely distribution of saturated hydraulic conductivity (Ks) and the observed pressure head (P) distribution within a hillslope. The cross-correlation analysis method was used to investigate the effects of the variance of lnKs, spatial structure anisotropy of lnKs, and vertical infiltration flux (q) on P at some selected locations within the hillslope. The cross-correlation analysis shows that, in the unsaturated region with a uniform flux boundary, the dominant correlation between P and Ks is negative and mainly occurs around the observation location of P. A relatively high P value is located in a relatively low Ks zone, while a relatively low P value is located in a relatively high Ks zone. Generally speaking, P is positively correlated with q/Ks at the same location in the unsaturated region. In the saturated region, the spatial distribution of Ks can significantly affect the position and shape of the phreatic surface. We therefore conclude that heterogeneity can cause some parts of the hillslope to be sensitive to external hydraulic stimuli (e.g., rainfall and reservoir level change), and other parts of the hillslope to be insensitive. This is crucial to explaining why slopes with similar geometries would show different responses to the same hydraulic stimuli, which is significant to hillslope stability analysis