1 Objectives

The lack of specific data on implemented LID is widely recognized as big challenge since several organization on private and public areas are responsible for the mapping and maintenance of LID on their own ground. The purpose and objective of the construction of detailed LID-DNA of the cities is to evaluate the amount and types of LID in cities for international knowledge exchange and being able to compare best management practices. LID-DNA presents the ‘genetic information of the development and functioning of LID in a city’ and was first published in The Netherlands during ClimateCafés as evaluation for future design and maintenance of their stormwater management strategies in Rotterdam [1, 2]. The method for creating DNA-LID is ClimateScan that facilitates an open-source method for mapping and analysing the type and amount of LID in many cities of the world by every person and orgnanisation to stimulate international knowledge exchange [3]. The data can be freely used for LID-DNA analysing and is available for more complex follow-up calculations such as the climate adaptation speed in surface and storage to reach climate adaptation targets for challenges as flooding, drought and heatstress.

1.1 Origin of LID-DNA

The creation of LID-DNA is a fixed workshop in ClimateCafes in The Netherlands [2] and all around the world since 2015 [4]. ClimateCafé is a field education concept involving different fields of science and practice for capacity building in climate change adaptation with a focus on climate adaptation measures as LID. To collect, distribute, and share knowledge, the open access, web-based ClimateScan adaptation tool is used by policymakers and practitioners for mapping specific LID measures at specific locations with additional information. ClimateScan is also used as a citizen science tool giving the exact location of LID at private and public areas with website links, free photo, and film material on measures regarding climate mitigation and adaptation. Mapped LID in cities are related to stormwater infiltration, such as swales, rain gardens, water squares, green roofs, and permeable pavement.

1.2 Example LID-DNA Malmo

An example is ClimateCafe Malmo, Sweden where LID-DNA of the city was constructed during the evaluation of LID in the eco-city of Augustenborg in Malmö. Sine several LID or Nature-Based Solutions (NBS) were implemented in 1998 this is a very interesting case study for evaluation of the long-term efficiency of climate adaptation measures. ClimateCafé Malmö evaluated these LID with 20 young professionals from nine nationalities and seven disciplines with a variety of practical tools. 2 days, 175 NBS were mapped and categorised in Malmö using climatescan (Fig. 2). The representation of LID-DNA was presented to several stakeholders joining the international conference Cities, Rain and Risk 12–14 June 2019, Malmo Sweden [5].

1.3 Mapping LID with the climatescan tool

During the two days over 175 NBS were mapped on www.climatescan.org (Fig. 1) by the participants through uploading with the ClimateScan App in the field. The mapping included a short description, the location (GPS), category of NBS, and pictures. For some locations, additional information, documents, and websites for further information were added later using a desk computer with stakeholders from Malmo.

Fig. 1
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ClimateScan for Malmö city centre before ClimateCafé (left) and after (right): more than 175 NBS mapped on the open-source nature-based solution platform www.climatescan.org in the field during 2 days [6]

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Figure 2 shows the results of the LID mapping during the ClimateCafé in Malmö what is referred to as LID-DNA giving a quick overview of the amount and kind of LID constructed in the city. The 175 mapped climate adaptation solutions were distributed in 19 categories, with the majority within the green roofs and walls category (25.7%). The following categories were bio filters (13.7%), rain gardens (12%), and ponds (8.6%) [6].

Fig. 2
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LID-DNA of the city of Malmo, (based on 175 created during ClimateCafe Malmo in 2019) [6, 7]

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All LID-DNA can be constructed in the same way for several cities in the world with the help of ClimateScan. Before showing more LID-DNA’s of cities its important to have a basic background in formation in the potential but also the pitfalls in working with the open source citizen science database ClimateScan [3].

1.4 Data description climatescan

In 2024 over 14.000 Low Impact Development Devices (LID), sustainable urban drainage systems (SuDS) or nature-based solutions (NBS) projects where uploaded on the open-source database ClimateScan.org in the period of 2014–2024 [8, 9] by professional submissions and ‘citizen science’. This chapter describes potential calculations and visualisation of this database to get basic insights in (inter-)national climate adaptation. Municipalities and water authorities require basic insight in their assets regarding LID.

LID- DNA of cities: what is the distribution of LID measures in a certain region or city? Background: a total overview of LID, on private and public ground in a city or on national level is often not available. Often several types of LID are implemented and for maintaining the long-term efficiency of these LID several methods are required. Knowledge on the distribution of the specific LID with high scoring numbers of a certain type or ‘LID-DNA’ of (and their efficiency) can stimulate knowledge exchange between cities and will help urban planning and maintenance to plan their activities [10].

To answer the research question a large dataset is required of sustainable urban drainage systems (SuDS) or nature-based solutions (LID). The open-source citizen science platform ClimateScan mapped over 14.000 projects related to climate adaptation around the globe in 10 years with an average of more than 2000 registered users uploading projects thanks to the openness of the website and active online and offline promotion. The platform is the biggest inventory of nature-based solutions projects around the globe for international knowledge exchange [3].

Climatescan collects climate adaptation locations from all over the world (Fig. 3). The global platform can be used as a first step to collect data and share the knowledge on realized climate adaption measures of a certain city or region and compare this to other parts of the world. The tool ClimateScan focuses mainly on the topics surrounding the areas of urban resilience and climate proofing and climate adaptation. The main objective of this interactive international open access platform is knowledge exchange on climate adaptation projects through the platform itself and the connected social media channels as twitter, Instagram and Facebook. The Online citizen science knowledge-sharing platform ClimateScan.org contributes to an accelerated climate adaptation by promoting more green and blue spaces in urban areas. Basic insights can be made from the projects that contain information on the category and location and additional info (if available: photos, videos, research papers and data). Currently, all the data points are categorized into 7 sub-groups (Water, People, Nature, Heat, Energy, Urban Agriculture and Air quality) holding over 20 categories, which are each assigned a different colour as shown in the legend to the left of the webpage (Fig. 3).

Fig. 3
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Climatescan.org Platform with over 14.000 projects around the world

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Most of the uploaded projects belong to categories related to LID that are designed to reduce the rate [11] and quantity of surface water runoff from developed areas and to improve runoff water quality [12, 13]. Uploads on ClimateScan include constructed wetlands, bio swales, green roofs and walls, permeable pavements, rainwater gardens, and floating structures on public and private property (Table 1 and abbreviations). For this chapter the number of projects in categories are analysed, and the distribution of the projects by 2 cities: early adaptor municipality Amsterdam started implementing green infrastructure Amsterdam around 2000 [14] in contrast with Riga who started in 2020 with the green infrastructure transformation. Calculations are made with GIS of the majority of the measures implemented in the Netherlands for a first indication of the volumes of urban LID on national level.

Table 1 LID examples in Riga and Amsterdam
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2 Results and discussion

For this chapter the number of projects in categories with more than 100 implementations are analysed and visualised in Fig. 4.

Fig. 4
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Categories with highest project numbers in categories mostly referring to small scale urban nature-based solutions (status December 2023)

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Bio swales and raingardens (bio-filtration) and green roofs are dominant in de database with over 4000 international projects (Fig. 4). The quality control on this data is high since these categories are visual on the surface and are checked with arial photos. The first 3 categories (as number 6 and 7 on the top 20: constructed wetlands and grass filled grid pavers) have a higher accuracy than subsurface infiltration and permeable pavement (number 4 and 5) since from photos the dimensions of these measures are not always visual and easy estimated for accurate representation.

2.1 LID—DNA of cities

From cities where multiple uploads are available (Fig. 3) an overview can be created of what kind of categories are uploaded in numbers giving an indication what can be found in that city with proven implementation in practice (photos etc.) and location. 2 cities are chosen that have over 40 uploads from several users with different background given a multidisciplinary overview of solutions related to climate adaptation in that city in 2024. Figure 5 and 6 visualise the climate DNA of 2 cities in 2 different ways (percentages and total amount):

  1. 1.

    Riga city with low amount of green infrastructure where implementation of LID started around the year 2020 (Fig. 5)

  2. 2.

    Amsterdam city with high amount of green infrastructure where implementation of LID started around the year 2002 (Fig. 6)

Fig. 5
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LID-DNA of the city of Riga, Latvia (based on 40 projects implemented in the period of 2020–2024)

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Fig. 6
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LID-DNA of Amsterdam (based on 500 projects implemented in the period of 2000–2024)

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From Fig. 5 can be arrived that bio filtration such as swales and raingardens dominate the LID structure in Riga (based on 40 data points). Amsterdam with over 500 climate adaptation measures shows large quantities of green roofs (subsidised program), bio-swales and permeable pavement (Fig. 6). Next to a large quantity of green roofs bio filtration methods as bioswales and raingardens are upcoming in the capital city of The Netherlands (Fig. 7).

Fig. 7
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Bio-filtration locations in Amsterdam (source: climatescan.org)

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Comparing LID-DNA of other cities in the Netherlands such as Rotterdam (Fig. 8) we learn that for some LID such as ‘watersquare’ (see abbreviation in Table 1) that are common in that city have only 1 implementation that can be found in Amsterdam. Because of the challenges finding space for LID in urban dense areas national knowledge exchange is started to explore the possibilities of exchanging knowledge on certain LID’s as watersquares with lessons learned on the design, implementation but primarily focused on the maintenance of these systems.

Fig. 8
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LID-DNA of Rotterdam with relatively a large quantity of water squares compared to other cities (created in 2023)

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The LID-DNA of several other Dutch cities are constructed and compared (see Fig. 9). Also 3 international examples from Sweden (Malmo), Denmark (Copenhagen) and South Africa (Johannesburg) are added with their specific profile. Comparing LID-DNA from different continents in the world such as Johannesburg and Amsterdam might not seem relevant because of several different factors from geo-hydraulically to social factors point of view but was perceived with enthusiasm in some workshop. Climate change has given cities as Amsterdam new challenges as drought and therefor can learn from the multiple African LID that are implemented South Africa for that reason. The largest category “water demand management” related to drought is a major challenge in South Africa answered by many innovative LID that can also be used in cities as Amsterdam. Other projects uploaded using citizen science in South Africa show a large variety of climate adaptation projects such as Nature-based solutions: (bio) swales, green roofs and walls, constructed wetlands, retention ponds permeable pavement and rain gardens implemented to conserve water, cool down the city, and mitigate temperatures in the urban dense area (heat stress).

Fig. 9
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several other Dutch cities compared and 3 international examples from Sweden (Malmo), Denmark (Copenhagen) and South Africa (Johannesburg)

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Since many cities in Europe and Norh America are introduced to a new challenge of heatstress due to climate change, the approaches and projects in Johannesburg area can be an inspiration for all regions in the world facing drought problems. High density of mapped climate adaptation strategies in Europe allows more detailed categorization of specific measures as illustrated for bio swales in The Netherlands. Relating existing implementations to neighborhood typologies gave urban planners evidence-based proof that climate adaptation measures can be implemented in any type of city district. Furthermore, challenging examples of stormwater infiltration projects in “worse case” low-lying districts (under sea level) with high groundwater tables and low permeable soil have been an inspiration to stakeholders around the world. A good example is the international knowledge exchange between the Dutch cities Amsterdam and Rotterdam and the American city New Orleans that all have infrastructure under sea-level [15].General analysis of climate adaptation and specific examples enables stakeholders such as urban planners and stormwater managers with the design, plan, and implement climate resilient measures with more confidence.

3 Discussion

The results of this study are discussed with stakeholders from municipalities and their reactions on the LID-DNA can be grouped in policy makers, designers and departments that are responsible for the maintenance of LID:

  • Policy makers great overview of what the city has to offer and proof what LID we can use to combat heat, drought and floodings with improving biodiversity.

  • Maintenance less happy with the large variety of LID since the maintenance of such an arsenal of different LID across the city demands a high degree of equipment, capacity, and knowledge to ensure the long-term efficiency of all these individual LID across the city.

Several full scale testing have taken place on bio swales [16] and permeable pavement [17, 18] showing that maintenance is a challenge in municipality to keep the long term hydraulic performance meeting the national guidelines.

Both departments could benefit from evaluation of the efficiency of the LID measures in the city and have a more targeted strategy of some of the LID than having a wide range of different LID. All cities and departments agree on having these basic insights earlier in the process to make strategic decisions on the LID profile of their city to prevent mal-adaptation and disinvestments. They would like to see more detailed LID-DNA not only on the amount of LID but also on the dimensions such as water storage (m3) or surface (m2) and preferably the measured infiltration rates (m/d) in time which one of the most important criteria for possible floodings and maintenance (clogging).

Raising awareness and capacity building (Fig. 10) targeted on the high-ranking cost-efficient LID is advised in every city, preferably focused not only on the design but also the construction and maintenance of LID.

Fig. 10
figure 10

left: presenting and discussing the results of LID-DNA of Amsterdam and Riga (Riga, January 2024). Right: discussions during full scale testing bio swales in Riga on national television 2023 (https://replay.lsm.lv/lv/ieraksts/ltv/307804/lietus-udeni-novada-gravjos)

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4 Limitations

Despite the various uses ClimateScan can provide, there are limitations of the application and the dataset which were identified during mapping and workshops. Firstly, in order to accurately contribute to the LID-DNA of cities a level of knowledge of NBS is required on several categories. Climatescan is citizen science so a quality check on the data is advised during the analysing phase. Most citizens that contribute are not new to the climate adaptation category that they are uploading and frequent contributors often work in climate adaptation at a water authority, consultancy agencies or municipalities. Still, it is possible that examples mapped by some users may interpreted differently resulting in the profiles that are not representing the 100% true state of NBS implementation in a certain city. Without data check, which has been performed for this study, there can be uncertainty regarding the accuracy of the data reducing the confidence of decision-makers in the insights of LID-DNA. Since not all projects are mapped on climatescan in every city and some projects have multiple climate adaptation implementations there is always an underestimation of climate adaptation efforts in the city. For example, when a user initially uploads an example of a NBS, ClimateScan only allows one category to be selected from the issues that are available. Therefore, a user will often select the primary issue a NBS addresses but won’t log the other additional benefits which the example may provide. Consequently, the LID-DNA might not give a full reflection of the multiple benefits NBS can provide and so limits the knowledge that can be provided to decision-makers. Another observation with using ClimateScan is the limited number of NBS which have been mapped in most cities outside of the Netherlands. As a result, with few cities having enough LID mapped to produce a representative profile, the potential is limited for comparisons to be made and for lessons to be learnt on how to effectively implement LID. For this reason, uploads of projects around the globe are stimulated and will give a higher accuracy of the presence of LID as has been successfully done in Riga and Amsterdam and other places in the world with exceeding numbers of projects in the database every year (Fig. 11). Mapping will not only give the change of making LID DNA but also raise awareness and contribute to capacity building.

Fig. 11
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Increasing number of projects in the database climatescan.org

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5 Project quality

Last but not least is the point of the quality of data using citizen science which has been a discussing over the years resulting in a strategy. ClimateScan can hide lower quality projects from the map since new viewers can get overwhelmed with over 14,000 projects. The definition of lower quality projects are projects that only have a category and location, this is the minimum input for a project on climatescan which is sufficient for researchers and viewers to know where specific climate adaptation related projects are to visit or analyse. A projects is considered as ‘higher quality’ when a description and photos and videos are uploaded which proofs the existence of the project with additional information giving more opportunities to analyse the climate adaptation measure in more detail. Users of climatescan can choose to visualize on the map (Fig. 12):

  • Show all projects

  • Projects with description

  • Projects with photos & description

Fig. 12
figure 12

projects with a medial since research results of the LID is available in publications (added as info to climatescan)

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The highest quality of data are featured projects that display not only photos and description but also contain research data. These projects have a medal as indicated in Fig. 12.

From Fig. 11 can be derived that measurements have been taken in Vancouver, New Orleans and several points in The Netherlands and (as previously discussed) Riga. Publications can be found at every point with the detailed data.

6 Conclusions

This paper shows LID-DNA analysing and visualisations with ClimateScan platform data. Analysing the open-source Change Adaptation Platform ClimateScan shows that surface bio filtration as LID is the category with most uploads, with low amount of LID in the case of Riga (started green infrastructure around 2020, focus on bio-filtration with raingardens and swales based on 40 data points) in contrast to early adaptor (since around 2002) Amsterdam with over 500 LID implementations with relative a large quantity of green roofs (as result of a subsidy program). Semi structured interviews with stakeholders from different departments in 2024 formed the opinion that cities can benefit from the insights of their urban LID-DNA earlier in the process. This early insight will support a targeted LID strategy choosing a limited cost-efficient group of LID than having a wide range of different LID without evaluation of their efficiency. Different departments (policy to maintenance) in the city asked for more detailed insights to prevent mal-adaptation and disinvestments and be more efficient with their capacity. Because of the open-source character of the tool, every city can use ClimateScan to engage partners to upload climate adaptation measures and analyse and make their own ‘LID- DNA’. (inter)national knowledge exchange started on specific LID systems such as watersquares that are in the LID DNA of Rotterdam but not in similar urban dense areas as Amsterdam. Riga municipality has interested in the over 50 LID systems that are found in other cities and started to select the most efficient LID based on the lessons learnt from design, construction and maintenance of the long-term performance of LID around the globe.

In addition, the LID-DNA of 10 other cities is discussed including a non-European city Johannesburg with several LID implemented for the challenges drought and heatstress that many cities are facing due to climate change. The largest category “water demand management” in Johannesburg can be an inspiration for all regions in the world facing drought problems. General analysis of climate adaptation and specific examples enables stakeholders such as urban planners and stormwater managers with the design, plan, and implement climate resilient measures with more confidence.

In conclusion, the outcomes of the selected case studies with ClimateScan illustrate some of the possibilities of LID-DNA as a tool in workshops with stakeholders that have a clear demand for open-source collaborative knowledge sharing tools. In the near future, climatecafes and new international projects will proceed with mapping and analyzing climate adaptation measures with this method.

7 Recommendations

Future work will focus on more detailed LID-DNA visualisation not based on only the amount of LID but on the dimensions such as water storage (m3) and surface (m2) and stimulate monitoring of LID to make strategic decisions on measured infiltration rates (m/d) of LID as most important criteria for possible damage by floodings and maintenance (clogging). Raising awareness and capacity building targeted on the high-ranking cost-efficient LID is set up in both cities focused on the design, construction and maintenance of LID.

In the process of calculations and visualisations we came across some basic improvements to have more accurate outcomes which we will discuss with frequent users of ClimateScan:

  • Evaluating the platform with an increasing number of expert users since the platform is under constant change.

  • Detailed check on outcomes of the data with stakeholders from municipalities and water authorities

  • Follow up stakeholder meetings to verify the potential of further calculations and visualisations.