07.03.2026

Rainwater Infiltration Calculation: Principles, Planning, and Examples

Building design

A drainage pipe in a trench—a common element of outdoor technical infrastructure. Photo: lazarusokuku

If you want to allow rainwater to infiltrate, you need more than just a depression in the yard or a hole in the ground. The rainwater infiltration calculation is the planning cornerstone of any decentralized rainwater management system: It determines how large an infiltration system must be so that it can reliably collect, temporarily store, and release the resulting stormwater into the ground—even during design rainfall events—without overflowing or causing damage. Anyone who understands this calculation process also understands why infiltration isn’t a sure thing, but rather an engineering task with clear rules, standards, and limits.

What rainwater infiltration means and what types of systems are available
The key hydraulic parameters that determine the calculation: rainfall intensity, runoff coefficient, design rainfall
How the key soil parameter, the kf value, is determined and why it is so crucial
Which standards and regulations govern the calculation, particularly DWA-A 138
How the calculation procedure according to DWA-A 138 works step by step
Which system types are suitable for which locations and land uses
What errors are typical in planning and construction, and how they can be avoided
How infiltration systems are integrated into the overall strategy of the “sponge city” and the urban water cycle

Basic Concepts and Types of Rainwater Infiltration Systems

Rainwater infiltration refers to the targeted diversion of stormwater from paved or built-up areas into the subsurface, where it passes through the soil and is fed into the groundwater. Unlike centralized sewer systems, which quickly divert rainwater out of the city, decentralized infiltration keeps the water cycle closed locally. This is not only ecologically sound but is also required by planning regulations in many federal states: Anyone creating new impervious surfaces must retain the resulting rainwater on the property or allow it to infiltrate, provided soil conditions permit.

The main types of systems can be distinguished by their geometric shape and mode of operation. Surface infiltration drains water over a wide area through active soil layers, typically via lawns, depressions, or depression-trench systems. Depression infiltration uses shallow, vegetated depressions in the ground that temporarily hold water and then allow it to slowly infiltrate. Trench infiltration relies on underground gravel or crushed stone beds that serve as temporary storage and release the water gradually into the subsoil. Well infiltration systems are vertical structures that direct water directly into deeper, permeable layers and are used where the upper soil is poorly permeable but a suitable layer lies beneath it. Combined trough-trench systems combine above-ground storage with underground infiltration and are particularly space-efficient.

Each of these types places different demands on the subsoil, the available space, and the inflow geometry. Choosing the right system type is therefore not a matter of personal preference, but rather the result of a systematic site analysis that is inextricably linked to the rainwater infiltration calculation.

Basic Hydraulic Parameters: What Goes Into the Calculation

Every rainwater infiltration calculation begins with determining the relevant input parameters. The most important of these is the rainfall intensity, which is used for the design calculation. It is expressed in liters per second per hectare (l/(s·ha)) and varies by location: Depending on the region of Germany, different amounts of rain fall during a rainfall event of the same frequency. The basis for this is provided by KOSTRA data (Coordinated Regionalization and Analysis of Heavy Precipitation by the German Weather Service), which provides rainfall intensities for various duration levels and return periods for each location.

The return period, also known as the annual frequency, describes how often a rainfall event of a certain intensity occurs statistically. For the design of infiltration systems, a return period of two years (n = 0.5 a⁻¹) to five years is generally used, depending on the vulnerability of the connected areas to damage. For systems located near buildings or with an increased risk of flooding, a less frequent—and thus larger—event is assumed. This decision is a planning-based risk assessment, not a purely mathematical one.

The connected impervious area, also referred to as the effective catchment area, is the second key input parameter. It is calculated as the actual paved or built-up area multiplied by the runoff coefficient. The runoff coefficient (Ψ, Psi) describes what proportion of precipitation actually occurs as surface runoff. For sloped roof surfaces, it is close to 1.0; for paved surfaces with joints, it ranges between 0.4 and 0.7; for lawns, between 0.1 and 0.3. The product of the area and the runoff coefficient yields the hydraulically effective area, which is included in the calculation.

The third basic parameter is the soil permeability coefficient, known as the kf value (hydraulic conductivity). It indicates how quickly water flows through the soil and is expressed in meters per second (m/s). The kf value is the key soil-mechanical parameter for any infiltration system: It determines how quickly the temporarily stored water can be discharged and thus significantly influences the required storage volume. Setting the kf value too high results in an undersized system that will overflow during heavy rainfall events.

The kf value: Determination, significance, and common errors

The kf value cannot be obtained from tables but must be determined for the specific site. DWA-A 138 (Design, Construction, and Operation of Systems for the Infiltration of Stormwater), the authoritative set of guidelines for infiltration planning in German-speaking countries, requires a site-specific determination. For smaller systems up to a certain catchment area, a simplified procedure may be used; for larger or more sensitive sites, a geotechnical report is required.

Common field methods for determining the kf value include the double-ring infiltrometer test and the Porchet test (borehole test). In the double-ring infiltrometer test, a metal ring is driven into the ground, filled with water, and the rate of infiltration is measured. The Porchet test is conducted in a borehole and measures the infiltration rate in the saturated zone. Both methods yield field values that, by their very nature, exhibit a certain degree of variation. DWA-A 138 recommends using the lower range of the measured values for design purposes to err on the side of caution.

Soils with kf values between 1 × 10⁻³ m/s and 1 × 10⁻⁶ m/s are suitable for an infiltration system. Although highly permeable soils (kf greater than 10⁻³ m/s) drain quickly, they offer little filtration, which can be problematic when discharging stormwater from roads. Soils with kf values below 10⁻⁶ m/s are considered too impermeable for a cost-effective infiltration system; in such cases, alternatives such as retention, drainage, or a combination with other measures must be considered. Loamy or clayey soils often fall into this range and preclude simple infiltration.

A common planning error is to derive the kf value from soil maps or literature values for the soil type without conducting a field measurement. Soil maps provide a rough guide, but local variability in the subsoil—due to stratification, compaction, backfilling, or previous land uses—can be significant. Anyone who plans based on tabulated values risks designing a system that will not function in practice.

The Calculation Method According to DWA-A 138: Step by Step

The calculation method specified in DWA-A 138 is the standard method recognized in Germany, Austria, and Switzerland for calculating rainwater infiltration. It is based on a storage approach: The system must be able to accommodate the volume of inflow during a design rainfall event, minus the volume that has already infiltrated during the same period. The required storage volume is determined by the difference between inflow and outflow over the design duration.

The calculation process can be broken down into the following steps:

Determination of the effective catchment area (Au) from paved area and runoff coefficient
Selection of the design rainfall: Rainfall intensity (r) for the selected return period and the relevant rainfall duration based on KOSTRA data
Determination of the kf value through field tests at the site
Calculation of the system’s infiltration rate: infiltration area (As) multiplied by kf and a safety factor (typically 0.5 according to DWA-A 138)
Calculation of the required storage volume (VS) for various rainfall durations and selection of the applicable maximum
Sizing the system so that the required storage volume is provided and the infiltration area is sufficient

The calculation is performed for several rainfall durations (typically 5, 10, 15, 30, 60 minutes, and longer) because it is not the most intense, but rather the most unfavorable combination of intensity and duration that results in the maximum storage volume. The result is a storage volume in cubic meters and a required infiltration area in square meters. Together, these two values determine the system’s geometry.

For trough infiltration systems, the infiltration area is the base area of the trough. For trench infiltration systems, the storage volume is derived from the pore volume of the gravel or crushed stone bed, which typically accounts for 30 to 35 percent of the total volume. For shaft infiltration systems, the infiltration area is the lateral surface area of the shaft within the permeable horizon. These geometric relationships make it clear why the selection of the system type and the calculation cannot be separated from one another.

Site Requirements, Safety Distances, and Planning Regulations

Infiltration systems may not be installed just anywhere. DWA-A 138 and the respective state water laws define minimum distances from buildings, property lines, drinking water wells, and bodies of water. Typical minimum distances from buildings range from 1.5 to 5 meters, depending on the system type and groundwater level. The distance to the groundwater table is particularly critical: A minimum distance of generally one meter must be maintained between the bottom of the system and the highest expected groundwater level to ensure sufficient soil passage and filtration.

Not all rainwater may be allowed to infiltrate without further consideration. The EU Water Framework Directive and the German Water Resources Act (WHG) require that infiltrated water have no adverse effects on groundwater. Special requirements apply to stormwater from roof surfaces made of uncoated metals (copper, zinc, lead), as these metals are leached out in significant quantities and can be detected in the infiltrated water. Street runoff from heavily trafficked areas contains heavy metals, hydrocarbons, and tire abrasion and, as a rule, may not be allowed to infiltrate directly but requires pretreatment, such as through sedimentation systems or filter layers.

Under planning law, the infiltration requirement is enshrined in many zoning plans and municipal drainage ordinances. Anyone submitting a building permit application must generally demonstrate that the rainwater generated on the property can be managed on-site. This proof is the rainwater infiltration calculation in its formal function: It is not only a technical tool but also a planning document that is submitted to authorities and permitting agencies.

Common Planning Mistakes and How to Avoid Them

One of the most common mistakes in practice is underestimating the catchment area. Anyone who only considers the roof area of a building but overlooks courtyards, driveways, or outbuildings will design a system that is too small. Particularly when property areas are subsequently sealed—for example, by carports, patios, or paving—the infiltration system is often not adjusted, even though the hydraulic load has increased.

A second common mistake is neglecting maintenance. Infiltration systems become silted up over time: fine material from the inflow clogs the infiltration surface and significantly reduces the effective kf value. Troughs lose their permeability due to vegetation growth and falling leaves, while swales can become blocked by root ingrowth or the accumulation of fine sediments. The DWA-A 138 standard therefore mandates regular inspection and maintenance. Systems without a maintenance plan are not reliable structures in the long term.

A third mistake concerns the design of the inflow. When water is discharged unfiltered and at high flow velocity into a trough or infiltration trench, it carries fine sediment that progressively clogs the infiltration surface. Upstream settling and filter chambers, inlet structures with sedimentation chambers, or vegetated inlet strips slow down the inflow and retain coarse material. These design details are not a luxury but a prerequisite for a system that functions reliably over the long term.

Finally, the topography of the site is often underestimated. An infiltration basin that is located on a slope or whose overflow is not secured can, when overloaded, divert water in undesirable directions—such as toward buildings or neighboring properties. Planning the overflow—that is, the controlled discharge of water that the system can no longer absorb when the design rainfall is exceeded—is an integral part of the rainwater infiltration calculation and must not be treated as an afterthought.

Infiltration in the Context of the Sponge City and Urban Rainwater Management

Decentralized rainwater infiltration is more than a single technical measure. It is a building block of the “sponge city” concept, which aims to make cities more resilient to heavy rain and heat by retaining, evaporating, and infiltrating rainwater where it falls. The concept draws on findings from urban hydrology: Highly impervious cities generate high peak runoff during rainfall, which overloads sewer systems and causes flooding. At the same time, there is a lack of water for evaporative cooling, which regulates the urban climate.

In this context, infiltration systems serve a dual purpose: they reduce runoff and replenish the groundwater, which in turn serves as a water reservoir for trees and vegetation. Infiltration basins along roads, green deep beds (bioretention cells), and permeable pavements are elements of an integrated stormwater management system that combines urban planning, open-space planning, and civil engineering. Rainwater infiltration calculations form the common technical foundation upon which all these measures are built.

For landscape architects and open-space planners, this means: Infiltration is not a downstream drainage problem that the engineer solves after the design is finalized. It is a design resource that influences terrain modeling, planting, path routing, and land allocation from the very beginning. Those who view infiltration basins as design elements, who design deep plant beds as urban furniture with a hydraulic function, and who interpret a site’s topography as a tool for water management are working in line with a contemporary understanding of planning.

In this sense, the rainwater infiltration calculation is not a bureaucratic formality but the backbone of planning that takes water seriously as a resource. It combines soil science, hydrology, building codes, and open-space design into a discipline that plays a growing role in urban climate adaptation. Those who master it plan not only in compliance with regulations but also with an eye toward the future.

26.12.2024

Portfolio

Design down to the smallest detail

Building design

Bathrooms become a harmonious work of art when even seemingly small elements fit into the design concept. This includes the taps as well as the toilet flush plate and the shower channel. Geberit therefore offers several products in new colors and materials that can be used to create a uniform and harmonious bathroom ambience. New additions to the range include the “Sigma21” and “Sigma50” toilet flush plates in concrete-look and walnut (wood) finishes. In an exciting contrast, the Sigma50 release buttons or the Sigma21 design rings can be selected not only in classic chrome, but also in the metal colors rose gold, brass or black chrome. The “Sigma20” and “Sigma30” toilet flush plates also offer more design freedom in new design variants – tone-on-tone with the respective surface. The design rings and strips are now also available completely in white or black as well as in white or black matt lacquered. Accents in the latest trend colors are also possible with the floor-level shower: the “CleanLine80” shower channel is characterized by a self-contained, solid channel profile. It is available in lengths of 90 and 130 cm, but can be shortened as required. There is a choice of three colors: black chrome, champagne and stainless steel. This means that the CleanLine80 can be used to match the look of the tiles as well as the material and color of the fittings. In addition, most of the products mentioned have an “easy-to-clean” coating that makes cleaning easier.

Geberit Vertriebs GmbH
Theuerbachstrasse 1
88630 Pfullendorf
www.geberit.de

30.01.2026

Digitization

Digital ethics in urban planning: how algorithms cement prejudices

Building design

aerial-view-of-city-buildings-at-night-6ITSrEbSujY — Night view of the city buildings from the air, photographed by Zongnan Bao

Digital ethics in urban planning: how algorithms cement prejudices? We are no longer just building with concrete, steel and glass – but with code. What sounds like digital progress, however, harbors explosive potential for urban development. Because as soon as algorithms take hold, not only the skyline but also the fairness of the city is at risk. Welcome to the urban laboratory, where bias is just as firmly embedded as parking garages.

The article sheds light on the role of algorithms in urban planning and how digital biases are created.
It explains why ethical standards are indispensable in digital urban planning.
It shows the state of digitalization in Germany, Austria and Switzerland – between pioneering spirit and regulatory paralysis.
Innovative examples and gloomy pitfalls are critically contrasted.
The influence of artificial intelligence on urban processes is analyzed from a technical and social perspective.
Sustainability issues and the risk of algorithmic discrimination are examined with technical depth.
Professional skills and necessary know-how for planners in the age of digital bias are discussed.
Current debates, international perspectives and visionary approaches round off the article.

Algorithm instead of master plan: When bias is in the source code

Urban planning was once considered a discipline of compromise, based on expert understanding, political wrangling and public participation. Today, however, digital urban planning is becoming the new gold standard – and algorithms are playing the secret leading role. Whether it’s traffic optimization, land development or social infrastructure, computational models are helping to identify patterns, calculate scenarios and justify decisions based on data. That sounds like transparency and progress. But the devil is in the detail – and above all in the data set. Because algorithms are anything but neutral. They are as prejudiced as the society from which they originate. Training data reflects social inequalities, historical settlement patterns and economic interests. It is precisely where the digital twin of the city flexes its muscles that the great danger looms: the uncritical adoption of existing distortions, precisely cemented in the source code.

Traffic planning is a prime example. Algorithms based on historical movement data recognize patterns – but only those of the past. If you primarily analyze commuter flows from the suburbs to the city centre, you get solutions for drivers, not for pedestrians or cyclists. In this way, algorithms reproduce what has always been true. Progress? More like perpetuation. It’s the same game in housing promotion: Those who plan with old social data miss out on new social realities. Migrant communities, creative milieus, young families – they often don’t even appear in the database because they were previously invisible.

The fear of “black box urbanism” is therefore justified. After all, the algorithm does not make decisions objectively, but according to the parameters that are fed into it. Whoever sets these parameters ultimately determines who benefits and who is left behind. But transparency is often lacking. Not even the planners themselves always know how their models arrive at the results presented. The result: decisions appear rational, but are highly ideologically charged – and without democratic control.

This trend has long since arrived in Germany, Austria and Switzerland. Urban data platforms, digital twins, AI-based forecasting systems – they are omnipresent in pilot projects. But where is the debate about their social consequences? Where are the control mechanisms? Cities such as Vienna and Zurich are experimenting with open data and algorithmic transparency. But in many places, the principle of hope still prevails: it will work out, the main thing is digital. Anyone who thinks this way is systematically building the prejudices of the past into the city of the future.

The international architecture and planning scene has therefore long been discussing digital ethics. In New York, London and Singapore, ethics committees are being set up, algorithms disclosed and bias checks implemented. And here in Germany? The big debate takes place in the back room of IT departments at best – certainly not in the boardroom of urban development. As a result, algorithmic bias remains invisible for the time being, but is more effective than ever.

Digitalization and AI in urban planning: progress or a bottomless pit?

Anyone who sees digitalization in urban planning as a purely technical evolution has already lost the game. Because with every additional sensor, every new algorithm, every AI-based simulation, the complexity increases – and with it the risk of blind spots not being recognized. Modern cities are increasingly relying on digital tools to speed up processes and save resources. But speed is no virtue if it becomes an end in itself. In Germany, Austria and Switzerland in particular, the picture is striking: pioneers such as Hamburg and Vienna are focusing on smart city strategies and digital twins, but the majority of municipalities are struggling with fragmented systems, poor interoperability and data protection pitfalls.

AI-based decision-making sounds rational. But how rational can a system based on non-transparent data be? In practice, new concentrations of power are emerging: Whoever programs, controls and operates the systems or feeds them with training data gains considerable influence over urban space. The hope of automated fairness is a fallacy. Instead, a new form of technocratic intransparency is looming. And all this under the guise of efficiency.

At the same time, the pressure on planners to deal with data science, machine learning and digital ethics is growing. It is no longer enough to draw the development plan – now the algorithm must also be checked. The technical know-how of the next generation of architects and urban planners must therefore go far beyond CAD and GIS. An understanding of data models, critical reflection skills and the ability to question algorithmic decisions are becoming mandatory. Those who ignore this are leaving the city to the programmers – and rarely to the benefit of users.

The international debate on “ethics by design” is much more advanced than German-speaking practice. In the USA and Scandinavia, ethical guidelines are already anchored in the software architecture. In Germany, there is still a debate as to whether smart city algorithms should be publicly accessible at all. This creates an innovation backlog that prevents not only technical but also democratic progress. As a result, anyone who wants to design digitally has to deal with resistance, fears and ambiguities – not only on a technical level, but above all on an ethical level.

The urban planning of the future will not fail because of the question of whether algorithms are used, but how. The real challenge is not the tools, but the principles according to which they are developed and used. Without ethics, digitalization will remain a bottomless pit – and the city a mirror of its algorithmic distortions.

Sustainability and algorithmic fairness: the invisible risks of digital bias

When people talk about sustainability in urban development, they usually think of energy efficiency, land consumption or CO2 balances. But the digital component is often left out of the equation. Yet it is precisely algorithms that promise sustainable solutions – and can create new injustices at the same time. An AI system that optimizes mobility flows may save emissions, but only if it takes the needs of all city dwellers into account. If certain neighborhoods are systematically less well connected because they are considered “unprofitable”, a new form of digital exclusion will emerge. Sustainability without fairness is pure window dressing.

The dark side of digital progress is also evident in the area of climate resilience. Algorithms that create flood or heat maps are based on historical data. But who decides which variables are weighted? Where are measurements taken? And whose reality of life is depicted? In the end, it is often privileged districts that benefit from digital early warning systems. Those who live in data gaps remain invisible – and therefore unprotected.

For planners, this means a double responsibility. They not only have to develop sustainable solutions, but also ensure the fairness of the underlying data and models. This requires not only technical expertise, but also a new form of interdisciplinary cooperation. Urban sociologists, ethicists, computer scientists and citizen representatives need to sit down at the table together – otherwise urban planning will degenerate into a technocratic ivory tower.

The sustainability debate in the digital context has so far remained toothless in Germany, Austria and Switzerland. Although sustainability goals are included in digitalization strategies, concrete implementation is lacking. There is a lack of tools that measure and guarantee fairness and sustainability in equal measure. Innovative approaches such as algorithmic impact assessments or fairness audits exist, but are rarely used. Yet this is exactly what is needed to make the city of the future not only efficient but also fair.

Globally, the trend is clear: cities such as Toronto and Barcelona are incorporating algorithmic fairness into their smart city charts. In Germany, people are still discussing data protection and subsidies. The road to genuine digital sustainability is therefore still a long one – but there is no alternative.

Skills, criticism and visions: What professionals in digital urban development really need to know

The list of new requirements for architects and urban planners reads like an excerpt from a computer science course. An understanding of data, basic algorithmic knowledge, ethical evaluation skills and the ability to communicate digital processes in an understandable way – all of this is now part of the compulsory program. Those who fail to prepare for this will be overwhelmed by reality. Because digital urban planning shows no mercy to the ignorant. The central challenge is not only to operate the new technologies, but also to critically question and shape them. The ability to recognize and address bias is becoming the central quality criterion for professional work.

But there are huge gaps in knowledge. Many planners blindly rely on the promises of software providers. “The tool is certified, it will work” – an attitude that is highly dangerous in the age of algorithmic urbanism. After all, certificates do not guarantee social fairness. Only the combination of technical understanding and ethical reflection opens up the opportunity to use digital tools responsibly. Training, exchange and discourse are needed – beyond marketing events and PowerPoint battles.

Criticism comes primarily from civil society and international professional associations. There are calls for more transparency, binding ethical standards and independent audits. The idea of an “urban algorithm MOT” is no longer utopian. In practice, however, there is a lack of legal framework conditions and political will. This means that the responsibility remains with the professionals – and they must finally learn to accept it.

There are plenty of visionary ideas. From participatory algorithm platforms to AI-supported citizen participation – the possibilities are endless. It is crucial that control over the city is not delegated to the source code. At the end of the day, it’s people who have to decide, not machines. This requires courage, a willingness to experiment and a readiness to keep learning. The future of urban planning belongs to those who not only think digitally, but also act ethically.

These questions have long been part of the global discourse. The German, Austrian and Swiss planning culture urgently needs to catch up. Digital urban planning is no longer an experiment, but a reality – and with it the responsibility for a fair, sustainable and inclusive city.

Conclusion: Those who sleep through digital ethics are building the prejudices of tomorrow

The digitalization push in urban planning is both a curse and a blessing. Algorithms offer unimagined opportunities, but also new risks. Anyone who believes that digital tools automatically bring fairness and transparency is very much mistaken. On the contrary: without clear ethical guidelines, progress can quickly turn into a digital dead end. It is up to planners, architects, developers and decision-makers not to delegate responsibility to the algorithm. Only those who take digital ethics seriously will truly build the city of the future for everyone – and not just for those who are already in the data set.