SEEP/W地下水渗流分析软件详解与应用

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"GeoStudio SEEP/W 是一个专业的地下水渗流分析工具，它涵盖了从简单的饱和到复杂的非饱和渗流问题，以及稳态和瞬态渗流情况的分析。这款软件能够处理渗透异质性，并通过瞬态分析揭示不同时段不同位置的孔隙水压力变化，这些数据对SLOPE/W进行边坡和路堤稳定性的动态评估至关重要。此外，SEEP/W计算的地下水渗流速度在CTRAN/W中应用，用于模拟污染物的扩散和迁移，服务于岩土工程、水利水电、市政、土木、环境和采矿等多个领域的渗流问题分析与设计。" SEEP/W软件的核心功能包括： 1. **渗流模型建立**：用户可以构建多层地质结构模型，考虑不同土层的渗透系数和边界条件，模拟实际工程中的复杂渗流场景。 2. **渗透异性处理**：SEEP/W允许用户定义材料的渗透异性，这意味着它可以处理不同方向渗透率不同的情况，更准确地反映地层的特性。 3. **稳态与瞬态分析**：对于静止或随时间变化的地下水流动，软件提供两种分析模式，以满足不同工程需求。瞬态分析尤其重要，因为它可以揭示地下水动态变化对工程稳定性的影响。 4. **孔隙水压力分布**：SEEP/W能计算出孔隙水压力分布图，这对于理解地下水动力学及预测可能的渗漏或浮力问题至关重要。 5. **与其它模块的集成**：SEEP/W与其他GeoStudio产品（如SLOPE/W和CTRAN/W）紧密集成，共同解决边坡稳定性、污染物运输等综合问题。例如，SEEP/W的结果可以输入到SLOPE/W中，以评估地下水变化如何影响边坡的长期稳定性；而地下水流动速度则可以传递给CTRAN/W，以分析污染物的扩散路径和速度。 6. **广泛应用领域**：SEEP/W被广泛应用于多种工程项目，包括但不限于岩土工程中的防渗设计、水利水电项目中的库区渗流分析、市政工程中的地下水管理、土木工程的地基处理、环境工程的污染控制，以及采矿工程中的地下水资源评估。 7. **专业支持和资源**：Geo-SLOPE International Ltd. 提供了详细的用户手册和技术支持，帮助用户理解和掌握软件的使用方法，确保用户能够充分利用SEEP/W的强大功能。 SEEP/W是一款强大的渗流分析工具，其精确性和灵活性使其成为全球工程师解决地下水问题的首选软件。通过对地下水流动的深入理解，工程师们能够制定更科学、更安全的工程设计方案。

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Chapter 2: Numerical Modeling SEEP/W

Page 8

Quantitative predictions

Most engineers, when asked why they want to do some modeling, will say that they want to make a

prediction. They want to predict the seepage quantity, for example, or the time for a contaminant to travel

from the source to a seepage discharge point, or the time required from first filling a reservoir until

steady-state seepage conditions have been established in the embankment dam. The desire is to say

something about future behavior or performance.

Making quantitative predictions is a legitimate reason for doing modeling. Unfortunately, it is also the

most difficult part of modeling, since quantitative values are often directly related to the material

properties. The quantity of seepage, for example, is in large part controlled by the hydraulic conductivity

and, as a result, changing the hydraulic conductivity by an order of magnitude will usually change the

computed seepage quantity by an order of magnitude. The accuracy of quantitative prediction is directly

related to the accuracy of the hydraulic conductivity specified. Unfortunately, for a heterogeneous profile,

there is not a large amount of confidence about how precisely the hydraulic conductivity can be specified.

Sometimes defining the hydraulic conductivity within an order of magnitude is considered reasonable.

The confidence you have defining the hydraulic conductivity depends on many factors, but the general

difficulty of defining this soil parameter highlights the difficulty of undertaking modeling to make

quantitative predictions.

Carter et al. (2000) presented the results of a competition conducted by the German Society for

Geotechnics. Packages of information were distributed to consulting engineers and university research

groups. The participants were asked to predict the lateral deflection of a tie-back shoring wall for a deep

excavation in Berlin. During construction, the actual deflection was measured with inclinometers. Later

the predictions were compared with the actual measurements. Figure 2-5 shows the best eleven submitted

predictions. Other predictions were submitted, but were considered unreasonable and consequently not

included in the summary.

There are two heavy dark lines superimposed on Figure 2-5. The dashed line on the right represents the

inclinometer measurements uncorrected for any possible base movement. It is likely the base of the

inclinometer moved together with the base of the wall. Assuming the inclinometer base moved about

10 mm, the solid heavy line in Figure 2-5 has been shifted to reflect the inclinometer base movement.

At first glance one might quickly conclude that the agreement between prediction and actual lateral

movement is very poor, especially since there appears to be a wide scatter in the predictions. This

exercise might be considered as an example of our inability to make accurate quantitative predictions.

However, a closer look at the results reveals a picture that is not so bleak. The depth of the excavation is

32 m. The maximum predicted lateral movement is just over 50 mm or 5 cm. This is an extremely small

amount of movement over the length of the wall – certainly not big enough to be visually noticeable.

Furthermore, the actual measurements, when corrected for base movement fall more or less in the middle

of the predictions. Most important to consider are the trends presented by many of the predicted results.

Many of them predict a deflected shape similar to the actual measurements. In other words, the

predictions simulated the correct relative response of the wall.

Consequently, we can argue that our ability to make accurate predictions is poor, but we can also argue

that the predictions are amazingly good. The predictions fall on either side of the measurements and the

deflected shapes are correct. In the end, the modeling provided a correct understanding of the wall

behavior, which is more than enough justification for doing the modeling, and may be the greatest benefit

of numerical modeling, as we will see in more detail later.

SEEP/W Chapter 2: Numerical Modeling

Page 9

Figure 2-5 Comparison of predicted and measured lateral movements of a shoring wall

(after Carter et al, 2000)

Numerical modeling is sometimes dismissed as being useless due to the difficulty with defining material

properties. There are, however, other reasons for doing numerical modeling. If some of the other

objectives of numerical modeling are completed first, then quantitative predictions often have more value

and meaning. Once the physics and mechanisms are completely understood, quantitative predictions can

be made with a great deal more confidence and are not nearly as useless as first thought, regardless of our

inability to accurately define material properties.

Compare alternatives

Numerical modeling is useful for comparing alternatives. Keeping everything else the same and changing

a single parameter makes it a powerful tool to evaluate the significance of individual parameters. For

modeling alternatives and conducting sensitivity studies it is not all that important to accurately define

some material properties. All that is of interest is the change between simulations.

Consider the example of a cut-off wall beneath a structure. With SEEP/W it is easy to examine the

benefits obtained by changing the length of the cut-off. Consider two cases with different cut-off depths

to assess the difference in uplift pressures underneath the structure. Figure 2-6 shows the analysis when

the cutoff is 10 feet deep. The pressure drop and uplift pressure along the base are shown in the left graph

in Figure 2-7. The drop across the cutoff is from 24 to 18 feet of pressure head. The results for a 20-foot

cutoff are shown in Figure 2-7 on the right side. Now the drop across the cutoff is from 24 to about 15

feet of pressure head. The uplift pressures at the downstream toe are about the same.

The actual computed values are not of significance in the context of this discussion. It is an example of

how a model such as SEEP/W can be used to quickly compare alternatives. Secondly, this type of

-60 -50 -40 -30 -20 -10 0 1

Depth below surface (m)

Deflection (mm)

-60 -50 -40 -30 -20 -10 0

measured

computed

SEEP/W Chapter 2: Numerical Modeling

Page 11

Figure 2-8 Example of a tornado plot (O’Kane, 2004)

Discover & understand physical process - train our thinking

One of the most powerful aspects of numerical modeling is that it can help us to understand physical

processes in that it helps to train our thinking. A numerical model can either confirm our thinking or help

us to adjust our thinking if necessary.

To illustrate this aspect of numerical modeling, consider the case of a multilayered earth cover system

such as the two possible cases shown in Figure 2-9. The purpose of the cover is to reduce the infiltration

into the underlying waste material. The intention is to use the earth cover layers to channel any infiltration

downslope into a collection system. It is known that both a fine and a coarse soil are required to achieve

this. The question is, should the coarse soil lie on top of the fine soil or should the fine soil overlay the

coarse soil? Intuitively it would seem that the coarse material should be on top; after all, it has the higher

conductivity. Modeling this situation with SEEP/W, which handles unsaturated flow, can answer this

question and verify if our thinking is correct.

For unsaturated flow, it is necessary to define a hydraulic conductivity function: a function that describes

how the hydraulic conductivity varies with changes in suction (negative pore-water pressure = suction).

Chapter 4, Material Properties, describes in detail the nature of the hydraulic conductivity (or

permeability) functions. For this example, relative conductivity functions such as those presented in

Figure 2-10 are sufficient. At low suctions (i.e., near saturation), the coarse material has a higher

hydraulic conductivity than the fine material, which is intuitive. At high suctions, the coarse material has

the lower conductivity, which often appears counterintuitive. For a full explanation of this relationship,

refer to Chapter 4, Materials Properties. For this example, accept that at high suctions the coarse material

is less conductive than the fine material.

thinner

deep shallow

low high

high bare surfacelow

low high

Thickness

of Growth Medium

Transpiration

Hydraulic Conductivit

of Compacted Layer

Root Depth

Hydraulic Conductivity

of Growth Medium

Base Case

Decreasing

Net Percolation

Increasing

Net Percolation

Chapter 2: Numerical Modeling SEEP/W

Page 12

Figure 2-9 Two possible earth cover configurations

Figure 2-10 Hydraulic conductivity functions

After conducting various analyses and trial runs with varying rates of surface infiltration, it becomes

evident that the behavior of the cover system is dependent on the infiltration rate. At low infiltration rates,

the effect of placing the fine material over the coarse material results in infiltration being drained laterally

through the fine layer, as shown in Figure 2-11. This accomplishes the design objective of the cover. If

the precipitation rate becomes fairly intensive, then the infiltration drops through the fine material and

drains laterally within the lower coarse material as shown in Figure 2-12. The design of fine soil over

coarse soil may work, but only in arid environments. The occasional cloud burst may result in significant

water infiltrating into the underlying coarse material, which may result in increased seepage into the

waste. This may be a tolerable situation for short periods of time. If most of the time precipitation is

modest, the infiltration will be drained laterally through the upper fine layer into a collection system.

So, for an arid site the best solution is to place the fine soil on top of the coarse soil. This is contrary to

what one might expect at first. The first reaction may be that something is wrong with the software, but it

may be that our understanding of the process and our general thinking is flawed.

A closer examination of the conductivity functions provides a logical explanation. The software is correct

and provides the correct response given the input parameters. Consider the functions in Figure 2-13.

When the infiltration rate is large, the negative water pressures or suctions will be small. As a result, the

Material to be

protected

Fine

Coarse

Fine

Material to be

protected

Material to be

protected

Fine

Coarse

Fine

Material to be

protected

1.00E-10

1.00E-09

1.00E-08

1.00E-07

1.00E-06

1.00E-05

1.00E-04

1 10 100 1000

Suction

Conductivity

Coarse

Fine

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