Nature-Based Water Harvesting Systems for Climate-Resilient Buildings: A Scoping Literature Review

Abstract

Water, a precious but limited resource since prehistoric times, has driven humans to develop systems for collecting and storing it. Evidence dating back to third millennium BC documents shows such systems among the Sumerians in the Fertile Crescent, as well as in Asia, Africa, China, and India. Aqueducts and cisterns, along with impluvium–compluvium systems, allowed the Romans to meet private and public needs; in Venice, wells provided filtered water until 1884. Today, climate change and increasing soil sealing urgently demand intelligent water collection and management, aligned with five of the 2030 Agenda Sustainable Development Goals (6, 11, 12, 13, 15). Buildings and construction account for about 35% of the global freshwater consumption. The construction sector, historically involved in the development of innovative rainwater harvesting and reuse systems, now faces a growing challenge in exploring innovative nature-based solutions for climate-resilient buildings (e.g., fog harvesting, green roofs for rainwater storage). Based on these considerations, we propose a scoping literature review of the last 15 years on innovative rainwater harvesting and storage systems. The analysis aims to provide a comparative mapping of the technological solutions that have emerged, to identify the geographical areas and climatic conditions favourable to each system, and to serve as a knowledge base for the development of integrated construction systems suitable for each specific context. A total of 136 peer-reviewed Open Access articles indexed in Scopus (2010–2024) were analysed following the PRISMA-ScR guidelines.

1. Introduction

Climate change and urbanisation have intensified the pressure on conventional water infrastructure, prompting the building sector to adopt adaptive strategies that enhance resilience while reducing dependence on centralised systems. Globally, water withdrawals are dominated by agriculture (~70%), followed by industry (~20%) and municipal uses (~10%). Within this framework, the building and construction sector represents a significant share of freshwater use [1]. Direct withdrawals associated with construction activities are estimated to be approximately 15% of global freshwater use, while lifecycle-based assessments—including material production, construction processes, and building operation—indicate that the sector’s total water footprint may approach 30%. This demand is driven by material production (e.g., concrete and steel), on-site processes, and operational consumption in buildings [2]. Moreover, demand is rising as temperatures increase and precipitation patterns become erratic [3]. Nature-based water-harvesting systems integrate ecological processes with built-environment infrastructure, leveraging vegetation, soil–water interactions, and biogeochemical cycles to capture, store, and treat precipitation at the building scale. Historical precedents demonstrate the viability of localised water harvesting [4,5,6].

Despite the growing adoption of individual technologies, such as fog collectors [7,8] and sponge concrete [9], their integration into unified building-scale systems remains limited. The existing literature addresses discrete components such as rainwater-harvesting efficiency [10], roof-geometry optimisation [11], or bioretention sizing. This review examines nature-based water-harvesting systems, evaluating peer-reviewed research, case studies, and technical reports over the last 15 years, focusing on temperate, subtropical, and Mediterranean climate zones where water stress and climate variability challenge efforts to build water security. This review contributes to expanding the existing body of knowledge by providing a structured mapping of nature-based water harvesting technologies, their application contexts, and emerging research trends, highlighting areas that remain largely unexplored and supporting future research and design strategies in the climate-resilient building systems domain.

2. Motivation

Three converging imperatives drive this review: climate adaptation requirements, water resource constraints aligned with the UN Sustainable Development Goals (SDGs 6, 11, 12, 13, 15) [12], and regenerative building design frameworks [13]. Building codes and rating systems [14,15] increasingly require climate-resilient features. Nature-based systems deliver multiple ecosystem services. In addition, RWHSs can contribute to flood mitigation by increasing the time required for rainwater to reach the drainage system, thereby reducing the peak runoff and improving the overall stormwater management. Municipal utilities in water-stressed regions implement demand management programs and tiered pricing that incentivise on-site capture and reuse, with buildings achieving significant potable water offsets depending on roof area, precipitation, and end-use applications [16,17]. Understanding system performance across contexts, economic viability, and implementation barriers will inform architects, engineers, and building scientists in climate-responsive design.

However, the recent literature has not comprehensively documented the scope, geographic distribution, climatic applicability, and performance characteristics of these technologies.

This paper details a Scoping Literature Review following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines, examining peer-reviewed publications from the last fifteen years. In line with typical scoping review methods, the goal is not to synthesise evidence for specific intervention recommendations or to evaluate individual studies through risk-of-bias assessments. Instead, this review aims to map the existing literature, to categorise the various types of nature-based water harvesting systems used in building and construction, to identify the geographic and climatic conditions linked to each system type, and to highlight gaps in the current knowledge. This knowledge base is designed to support future-focused research and to guide the development of context-specific, integrated construction systems.

3. Synthesis and Research Questions

Effective and climate-resilient water management requires integrating multiple aspects, such as traditional knowledge combined with innovative technologies, technical feasibility supported by economic sustainability, and appropriate regulatory and institutional frameworks. The literature shows that the effectiveness of such systems depends heavily on a tailored design for each specific context. Fog harvesting is suitable for specific coastal areas; sponge concrete requires space for large, pervious surfaces; first-flush systems are most effective where roof contamination is significant. Each technology occupies a niche rather than providing a universal solution. The challenge is to match technologies to contexts based on climate, hydrology, economics, social preferences, and policy implementation.

The papers reviewed highlight nature-based water harvesting systems as promising components of climate-resilient infrastructure. However, issues relating to long-term integration with conventional infrastructure, maintenance models, and economic viability are inconsistently addressed across the selected papers and fall outside the scope of this scoping review, which instead focuses on mapping technologies, contexts, and applications.

In light of these findings, this scoping review aims to answer the following three main questions (RQs):

• What is the geographical distribution and chronological trend of the studies on nature-based water harvesting systems in the building and construction sector, distinguishing between the country of scientific production and the country of documented implementation?
• Which of the nature-based water harvesting technologies and technological configurations are most frequently investigated in the literature, and which are documented in implemented case studies?
• At what scale of application (building, site, urban, regional) and on which building elements or physical locations are these technologies predominantly studied and implemented?
• What are the primary and secondary aims pursued in the literature on nature-based water harvesting systems, and how are these aims distributed across the study period?
• In which climatic contexts are nature-based water harvesting systems predominantly studied and implemented, and which climatic zones remain under-represented in the literature?

4. Framing Background

Ancient water harvesting systems—Greek cisterns, Roman aqueducts and impluvium–compluvium configurations, Venetian filtered wells, Chinese bell-shaped water cellars, and Nepalese Pokhari basins—established enduring design principles, such as underground storage to minimise evaporation, catchment optimisation using available surfaces, and construction adapted to local materials [18]. Their reliability over centuries has stemmed from passive operation, energy independence, and maintenance within household-level capabilities [6]. Climate change and accelerating urbanisation now urgently challenge these principles at scale: rising temperatures intensify evaporation, precipitation concentrates in intense events causing flooding rather than groundwater recharge, and impervious surfaces compound scarcity during dry periods [3,19,20]. Decentralised, nature-based systems—fog collectors, sponge concrete, first-flush diverters, green roofs, bioswales, and integrated wetlands—respond to these pressures by capturing, storing, and treating precipitation at the building scale, while delivering co-benefits, including urban heat island mitigation, stormwater management, evaporative cooling, and biodiversity support [7,9,16,21,22,23]. Economic evidence supports their adoption: harvested rainwater costs 0.16–0.28 USD/m³ against municipal supply costs of 0.37–1.4 USD/m³ [24], and payback periods are calculable from the catchment area, conventional water price, and initial investment [25]; however, viability depends more on context than technology, and policy instruments—from mandatory requirements (Belgium, Germany) to incentives covering 30–50% of installation costs—are frequently necessary for widespread uptake [10,19,26]. It is important to note that the comparison involves water sources with different quality characteristics. In addition, the cost of potable water is often influenced by socio-political factors and may be underestimated, which should be considered when interpreting the economic results.

Roof material and pitch, first-flush diversion, and cascade reuse strategies all influence water quality outcomes, though bacterial contamination in storage can exceed potable limits, and treatment intensity must be matched to end use [11,27,28]. Despite this body of knowledge, the following critical gaps persist: standardised design methodologies, performance benchmarks, and lifecycle assessment protocols suited to building-scale practice are absent [29]; climate downscaling from regional projections to building-scale design parameters remains underdeveloped [30]; integrated guidance for multi-component systems at neighbourhood and district scales is lacking; long-term maintenance frameworks for decentralised systems—without which field performance degrades rapidly—are unresolved; and co-benefit valuation methodologies acceptable to regulatory agencies and financial institutions do not yet exist. This review is framed by these antecedents and gaps.

5. Methodology

This scoping review examines the evolution of methods, strategies, and tools for rainwater and fog harvesting in the construction sector, with a particular focus, where possible, on their application to buildings, aiming to identify and highlight the unexplored potential.

No specific review protocol was documented for this scientific literature review, but it was conducted in accordance with the PRISMA-ScR guidelines, adopting a structured methodology to guide the selection and analysis of data in a progressive and targeted manner.

In line with the scoping review methodology, no formal critical appraisal of the studies examined was conducted. The aim of this scoping review is not to assess the methodological rigour of each selected article but to outline the scope and characteristics of the existing evidence for the exploitation of unexpressed or underutilised opportunities.

This approach aligns with the PRISMA-ScR guidelines, which consider critical appraisal optional for scoping reviews. The completed PRISMA-ScR checklist is available in Appendix A, Figure A1 [31].

5.1. Literature Selection Process

To provide an accurate and systematic analysis of the technologies and strategies used for rainwater and fog harvesting, a structured methodology was adopted to identify and analyse a large number of scientific publications, selecting the most relevant ones. The aim was to explore the evolution of the technologies and methods used in the AECO (Architecture, Engineering, Construction, and Operations) sector to collect and reuse rainwater and fog, thereby reducing drinking water consumption and managing the challenges posed by severe flooding.

5.2. Database Selection

To conduct this scoping review, we used Elsevier’s Scopus database, widely regarded as one of the most reliable sources of scientific literature for its broad disciplinary coverage and high-quality indexed content. Although this choice may result in a partial loss of contributions, it ensures an accurate and replicable dataset.

5.3. Preliminary Analysis and Selection of the Operative Keywords

The search keywords were defined through multiple analyses and stages to identify the most appropriate terms to describe and define the topic of rainwater harvesting and reuse. These stages, conducted directly in the Scopus databases, enabled us to test various keyword combinations, including synonyms and alternative terminology.

The preliminary analysis involved defining the main set for subsequent screening. In this case, wishing to address the above topic solely from the perspective of the AECO sector, without delving into the issue of water quality and, in general, without branching out into chemical–physical areas, the union of the keywords “Building*” and “Construction*” was set as the base set, for a total of 3,185,952 articles.

The next phase, using the Boolean operators “AND” and “OR”, further defined the database by isolating articles on topics represented by the following keywords: “Rainwater Harvesting”, “Rainwater Harvesting System*”, “Fog Collector*”, and “Fog Harvesting”. This allowed for the consolidation of a database of 1275 articles.

In addition to the application of the Boolean operators, the use of the special wildcard character asterisk (*) allowed for both the singular and plural forms of the keywords to be included without having to specify them manually in the search interface, significantly improving the effectiveness of the search. This approach produced a more representative and relevant set of papers, aligning with the objectives of this scoping review.

The search strategy set up in the database was based on three key elements of the articles—keywords, abstracts, and titles—to identify the highly relevant publications and to discard those that only deal with the topic marginally.

5.4. Inclusion and Exclusion Criteria

Starting with a dataset of 1275 papers selected by keyword, we further narrowed it for analysis by applying filters in the Elsevier Scopus database.

As a first filter, we limited the selection to scientific “Articles” and “Conference Papers” to refine the main sources of up-to-date academic contributions on the subject. Other types of contributions, such as reviews and editorials, were excluded to maintain the focus on studies based on validated analyses and methodologies. Filters for source type (“Journal” and “Conference Proceedings”) and language (“English” only) were also applied to further refine the results.

The research reference period, initially set at 25 years from 2000 to 2024, was reduced to 15 years (“2010–2024”) to ensure consistency in the density of the data sets after applying the Open Access filter. After applying the last two constraints in the Elsevier Scopus search interface, including the restriction to “All Open Access”, the number of papers was reduced from 887 to 343.

Table 1. Filters selected on Scopus.

Year Range	2010–2024
Document type	Article
	Conference Paper
Source type	Journal
	Conference Proceedings
Language	English
Open access	All Open Access

summarises all the filters applied.

5.5. Full Search Strategy

In order to identify the final dataset of papers useful for beginning the analysis, the following search string was entered into the Scopus database:

TITLE-ABS-KEY (“building*” OR “construction*”) AND TITLE-ABS-KEY (“rainwater harvesting system*” OR “rainwater harvesting” OR “fog collector*” OR “fog harvesting”) AND PUBYEAR > 2009 AND PUBYEAR < 2025 AND (LIMIT-TO (SRCTYPE, “j”) OR LIMIT-TO (SRCTYPE, “p”)) AND (LIMIT-TO (OA, “all”)) AND (LIMIT-TO (DOCTYPE, “ar”) OR LIMIT-TO (DOCTYPE, “cp”)) AND (LIMIT-TO (LANGUAGE, “English”))

This research was conducted on 23 October 2025, and its results reflect the database coverage and indexing status at that date.

5.6. Classification and Validation Criteria for the Analysed Literature

After applying the filters described in the previous paragraphs, which resulted in a database of 343 papers, a series of classifications were carried out to ensure a consistent structure for the analysis. A final manual check was also carried out, together with the identification of trends in innovative tools and methods for rainwater harvesting and fog collectors in the construction industry. The final classification of the articles was carried out according to the following three criteria:

• Progressive definition of an analytically consistent and fully verifiable subset through comprehensive manual checking, while ensuring the feasibility of in-depth analysis.
• The application of a quantitative support procedure through the use of artificial intelligence (AI) tools, in this case, in the ChatGPT Plus (version 5.2). Using the appropriate prompt, a preliminary pool of 136 papers was identified through a quantitative ranking procedure based on Cosine Similarity. The similarity threshold, ranging from 0 (no relevance) to 1 (maximum semantic relevance), was set to 0.35 to avoid making overly restrictive comparisons between our operative keywords and the titles, abstracts, and keywords of each of the 343 papers. The AI was instructed to provide, year by year, a list of the most relevant papers, assigning them a relevance value of low (≤0.25), medium (0.25 to 0.35), or high (>0.35), while also taking into account the number of citations. The use of a significant number of citations allows papers with greater scientific and academic impact to be considered [32].
• Qualitative validation through manual checking of the 343 papers. It emerged that the quantitative ranking procedure implemented using Cosine Similarity has variable accuracy from year to year, ranging from a minimum of 25% in 2016 (in red) to a maximum of 100% in 2012, 2018, and 2020 (in green), as shown in

  Table 2. Accuracy of Cosine Similarity check through AI. Year-by-year value and overall average.

  Year	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023	2024	AVG
  Accuracy	100%	67%	100%	50%	75%	50%	25%	50%	100%	75%	40%	50%	76%	59%	59%	65%

  . The overall average accuracy of the AI tool over the period considered was 65%.

Manual re-checking of all 343 papers ensured that the final selection was determined exclusively through independent manual assessment. This procedure verified the relevance of the 136 preliminarily identified papers, correcting AI misclassifications where necessary and replacing them with contributions deemed relevant to the scope of this scoping review.

The re-checking and manual selection process resulted in a final list of 136 papers (see the flowchart in Figure 1) closely related to the topics covered by our scoping review. In this case, since it is a single list that does not result from the union of sets derived from different constraints or keywords, it was not necessary to remove any duplicates.

6. Results and Discussion

After narrowing the selection to a final list of 136 papers, they were entered into a dedicated Excel file. This allowed the selected papers and their metadata, retrieved via Scopus, to be isolated. These data supported the further analyses described in this chapter.

6.1. Analysis of the Geographical Distribution of Papers and the Chronological Trend of Publications

This preliminary analysis provides insight into the origins of the researchers’ interest, both geographically and chronologically, and how it has developed over time.

As already mentioned in the previous chapter, the publications we are analysing cover the period 2010–2024 (15 years). Over these fifteen years, as shown in Figure 2, interest has grown in a predominantly linear trend, characterised by irregular peaks, with most occurring in the last five years, during which the researchers’ interest has doubled.

To understand the trend in academic interest over the 15 years under review, each researcher involved in the research projects reported in the analysed papers was evaluated. Each paper was then associated with the country of the academic institution to which the researcher belonged. At the country level (see Figure 3), however, researchers from the United States (28) addressed the topic most, followed by researchers from Indonesia (21) and Malaysia (21), both with over 20 researchers involved. Researchers from Spain (19) and China (18), together with those from the United Kingdom, Poland, Italy, Portugal, Turkey, and South Korea, followed with over 10 researchers involved, confirming the continental trend. The pie chart in Figure 4 shows the trend in interest over the period 2010–2024, split by continent. Over the period, on a continental basis, we can see strong interest mainly in Asia and Europe, followed by North America.

By dividing the analysis into five-year periods, we can see how academic interest has evolved. As shown in Figure 5, interest peaked in Europe (e.g., the United Kingdom, Portugal, Slovakia) and Asia (e.g., Malaysia and South Korea) during the period 2010–2014. In the following five-year period, 2014–2019, interest stabilised in Europe (e.g., Spain (10), United Kingdom (5)) and Asia (e.g., Indonesia (7), Malaysia (8)). During the same period, it also began to emerge in North America, where the United States (13) stands out (see Figure 6). In the next image (Figure 7), we can see the trend over the last five years, 2020–2024. Europe maintains its linear growth, with greater academic interest in Poland (11), Italy (8), and Spain (8). Asia, thanks to the strong interest shown by China (18) and India (11), as well as the stable presence of Indonesia (14) and Malaysia (8), is seeing an exponential growth in interest. In North America, on the other hand, the United States (14) maintains the same level of interest shown in the previous five years.

6.2. Analysis of Innovative Technologies

After analysing the geographical distribution of the papers and the trend in interest over the years, the next step is to assess which technologies have been most widely used in water harvesting. The identified technological solutions differ in their collection principles and areas of application. Rainwater harvesting systems (RWHSs) catch and store rainfall running off building surfaces. They typically use components such as gutters and storage tanks, and are widely used in urban environments due to their relatively high efficiency and their potential for architectural integration. On the other hand, fog harvesting systems rely on passive mesh collectors that capture humidity from the air. For this reason, they are particularly suitable for open regions characterised by frequent fog, such as arid and coastal areas. While RWHSs represent a mature and widely implemented solution, fog harvesting technologies offer complementary opportunities under specific climatic conditions, although their performance depends strongly on local environmental factors. Even without providing a quantitative comparison of the performance of the various systems examined, the mapping highlights how the effectiveness of different technologies is strongly context-dependent, especially in terms of climatic conditions, scale of application, and integration strategies.

In this case, the analysis was conducted in three steps.

In the first step, each abstract was analysed to identify sections of text characterised by the following three topics: Technology, Location, and Aim.

The second step involved an in-depth analysis of the findings for each of the three items, dividing them as follows:

• Technology, considered as follows:
  • Main Technology
  • Secondary Technology
  • Integrated Technology
  • Digital Tool
• Location where the technology is applied, as follows:
  • Level 1—Scale/Context
  • Level 2—Physical location/Building Element
• Aims for water harvesting, as follows:
  • Primary Aim
  • Secondary Aim

By carrying out this detailed study, the amount of data to be considered increases, allowing analyses that include more aspects of each item analysed; however, the data remains raw and unsuitable for comparison. For this reason, a third step was necessary, during which the extrapolated data were normalised and structured. This procedure collected, using a controlled vocabulary, all similar items that would otherwise be counted as unique data, making comparisons and classifications impossible.

The items in the various normalisation vocabularies were not considered mutually exclusive categories but rather multi-response variables.

Papers dealing with multiple entries were therefore counted for each relevant entry. As a result, the percentages refer to the proportion of studies that dealt with a given entry and do not add up to 100%. This approach was consistently applied across all subsequent analyses, including technologies, scales of application, physical locations, and research objectives.

6.2.1. Normalisation with Respect to the Technology’s Topic

The technologies identified in the literature operate at different scales and levels of integration, ranging from material-based solutions to system-level configurations. To clarify their respective roles and to relate the classification adopted in this study (MT, ST, IT, DT) to their functional contribution within building-scale water management, a synthetic mapping of the main terms and technologies is provided.

In analysing the Main Technologies (MT) used, normalisation enabled the classification of the various entries across the 136 articles into a controlled vocabulary of seven categories. The classification spans multiple levels of abstraction, from material-based solutions (MT3) to system-scale infrastructures (MT6–MT7), reflecting the heterogeneity of the approaches identified in the literature. To provide a clearer technical interpretation of the classification adopted in this study,

Table 3. Functional mapping of the Main Technologies (MT).

MT Code	Technology Category	System Scale	Hydrological Function	Operational Principle	Role Within Building Water System
MT1	Filtration System	Component/Building	Water quality control	Physical, biological, or chemical removal of contaminants (e.g., sedimentation, membrane filtration)	Enables safe reuse by conditioning harvested water for intended end-use (non-potable or potable)
MT2	Fog Harvesting System	Building/Façade/Site	Atmospheric water capture	Condensation of airborne moisture on mesh or surface collectors under specific climatic conditions	Provides supplementary water source in fog-prone regions, independent of rainfall
MT3	Rainwater Construction Material	Material/Element scale	Storage & infiltration	Use of permeable or porous materials (e.g., sponge concrete) to absorb and temporarily store water	Enhances decentralised retention and reduces runoff at surface level
MT4	Rainwater Harvesting System (RWHS)	Building	Collection & storage	Capture of roof runoff via drainage systems and storage in tanks or cisterns	Primary system for on-site water supply substitution (non-potable uses)
MT5	Stormwater Harvesting System	Site/Urban	Runoff control & storage	Collection and detention of surface runoff from impervious areas	Reduces peak discharge and enables reuse at larger spatial scales
MT6	Urban Water Management System	Urban/District	Integrated water cycle management	Combination of decentralised systems (green–blue infrastructure, storage, reuse networks)	Coordinates multiple flows (rainwater, greywater, stormwater) at urban scale
MT7	Wastewater Management System	Building/District	Treatment & reuse	Treatment of greywater/blackwater through mechanical, biological, or hybrid processes	Closes water loop by enabling internal reuse and reducing freshwater demand

summarises the Main Technologies (MT) identified in the literature, linking each category to its hydrological function, operational principle, and role within building-scale water management systems.

This step, as shown in Figure 8, enabled the identification of the most commonly used technologies in the examined articles. In cases where multiple technologies were found simultaneously, and it was not possible to identify the main one, it was decided to report the category as the sum of the identified technologies (e.g., MT4 + MT5 + MT7, MT4 + MT7).

In the same figure, it can be seen that the most widely used Main Technology is MT4, cited in 83% of the papers, rising to 88% when we also include the cases where it was not possible to define a single Main Technology. In second place, albeit with a clear gap, stands the MT2 category, which accounts for 6%. The remaining technologies, on the other hand, account for between 1% and 2%.

In addition, an analysis of the abstracts of the selected papers revealed that 61% of the papers are combined with a Secondary Technology (ST), while an Integrated Technology (IT) occurs in only 25% of cases. On the other hand, 18% of the papers analysed use a Digital Tool (DT).

It should be noted that, in the classification phase for ST, IT, and DT, all items were treated as technological solutions, even when expressed through building elements (e.g., roof, wall), since the distinction between technology and physical location had already been made in the initial extraction phase.

Given that, based on the MT analysis, MT4 was found to be predominant, representing over 80% of the corpus analysed, a further assessment of technological complexity was carried out exclusively within this main category (see Figure 9). The MT4 subset was then normalised and subsequently disaggregated by the presence and combination of STs, ITs, and DTs, allowing for the number and type of technological configurations associated with MT4 to be mapped without introducing over-representation or bias across the categories.

As shown in Figure 10, the set of papers characterised by MT4 can be broken down into STs (34%), ITs (10%), DTs (4%), and their combinations (27%).

Going into even greater detail and considering only the 113 papers characterised by the use of MT4—the light blue section of the primary pie chart in Figure 9—it was possible to analyse them and highlight the different relationships with other technologies.

Secondary Technologies (STs) are components or subsystems that support or enhance the performance of the main water-harvesting system. Unlike Main Technologies, Secondary Technologies are not standalone systems but functional components that contribute to specific phases of the water harvesting process (collection, storage, treatment, or control).

Specifically, the 68 papers in which the MT is accompanied by an ST were analysed by normalising the data using the following vocabulary.

Table 4. Functional mapping of Secondary Technologies (STs).

ST Code	Technology Category	System Scale	Hydrological Function	Operational Principle	Role Within Building Water System
ST1	Roof-based collection system	Building (roof)	Collection	Interception and conveyance of precipitation via roof geometry, slope, and drainage elements	Defines primary catchment efficiency and initial water quality
ST2	Wall-based collection system	Building envelope (façade/wall)	Collection	Vertical interception of rainwater or wind-driven precipitation, in some cases, fog condensation	Supplements horizontal catchment, particularly in dense or vertical urban morphologies
ST3	Storage system	Building/Site	Storage	Temporary accumulation of collected water in tanks, cisterns, or modular systems	Balances the temporal mismatch between supply and demand
ST4	Filtration/treatment component	Component/Building	Water quality control	Removal of suspended solids, organic matter, and contaminants through physical or biological processes	Enables safe reuse for specific end uses (e.g., irrigation, flushing)
ST5	Monitoring, sensing & control system	Building/System	Regulation & optimisation	Use of sensors, control logic, and automation to monitor flows, storage levels, and quality	Improves operational efficiency and system reliability
ST6	Green roof system	Building (roof)	Retention, delay, & evapotranspiration	Vegetated multilayer system that absorbs, stores, and gradually releases rainwater	Reduces runoff, enhances retention, and provides co-benefits (thermal, ecological)
ST7	Not specified	—	—	—	Category used when insufficient technical detail is provided in the source literature

provides a functional mapping of these elements, clarifying their role within the overall hydrological process and their contribution to building-scale water management.

This analysis revealed that ST1 (38) and ST3 (32) are the two most common Secondary Technologies (see Figure 11).

Integrated Technologies differ from Main and Secondary Technologies in that they do not represent discrete physical systems, but coordinated configurations that link multiple components across scales. For the 27 papers in which the Main Technology is combined with an Integrated Technology, the data were analysed using a specific normalised vocabulary.

Integrated Technologies (ITs) refer to system-level configurations that combine multiple components or processes to manage water flows across building and urban scales.

Table 5. Functional mapping of Integrated Technologies (ITs).

IT Code	Technology Category	System Scale	Hydrological Function	Operational Principle	Role Within Building Water System
IT1	Water Reuse & Recycling Systems	Building/District	Demand reduction & reuse	Collection, treatment, and redistribution of greywater or harvested water for non-potable uses	Reduces reliance on potable supply by closing internal water loops
IT2	Stormwater Management & Regulation Systems	Site/Urban	Runoff attenuation & flow regulation	Detention, retention, and controlled release of stormwater via basins, tanks, or distributed systems	Mitigates flooding risk and stabilises hydraulic loads on drainage infrastructure
IT3	Groundwater Interaction Systems	Site/Subsurface	Infiltration & aquifer recharge	Managed percolation of collected water into the ground through infiltration systems	Enhances groundwater recharge and reduces surface runoff volumes
IT4	Green–Blue Infrastructure Systems	Urban/District	Multifunctional retention, treatment & evapotranspiration	Integration of vegetated and water-based systems (e.g., wetlands, green corridors) to manage water flows	Provides ecosystem-based water management with co-benefits (cooling, biodiversity, water quality improvement)
IT5	Smart Control & System Coordination	Building/Network	System optimisation & dynamic control	Use of sensors, data acquisition, and control algorithms to coordinate multiple subsystems	Enables adaptive management and improves the efficiency of integrated water systems
IT6	Energy & Environmental Integrated Systems	Building/District	Resource coupling & efficiency	Integration of water systems with energy or environmental systems (e.g., heat recovery, cooling)	Enhances overall building performance through water–energy–environment synergies
IT7	Not specified	—	—	—	Category used when insufficient technical detail is provided in the source literature

summarises these technologies by linking each category to its hydrological function, operational principle, and role within integrated water management strategies.

This analysis revealed that IT1 (9) is the most widely used category of ITs, followed by IT2 (5), IT3 (4), and IT4 (4) (see Figure 12).

The final item analysed is the presence of Digital Tools. This category does not constitute physical water harvesting technologies but provides the computational and data-driven framework necessary for their design, evaluation, and operational control.

With regard to the 24 papers in which the MT is combined with a DT, the data were analysed using a specific normalised vocabulary: Digital Tools (DTs) represent analytical and computational instruments that support the design, simulation, optimisation, and operation of water-harvesting systems.

Table 6. Functional mapping of Digital Tools (DTs).

DT Code	Technology Category	System Scale	Hydrological Function	Operational Principle	Role Within Building Water System
DT1	GIS & Geospatial Analysis Tools	Site/Urban/Regional	Spatial assessment & resource mapping	Use of georeferenced datasets to analyse rainfall distribution, catchment characteristics, and site suitability	Supports site selection, scalability assessment, and spatial optimisation of water harvesting systems
DT2	Hydraulic & Hydrological Modelling Tools	Building/Site/Urban	Flow simulation & system sizing	Numerical modelling of rainfall–runoff processes, storage dynamics, and drainage behaviour	Enables dimensioning of tanks, pipes, and system components under varying conditions
DT3	Simulation & Computational Modelling	Building/System	Performance prediction	Computational simulations (e.g., parametric, stochastic) to evaluate system behaviour over time	Assesses efficiency, reliability, and sensitivity to climatic variability
DT4	BIM & Digital Building Modelling	Building	System integration & design coordination	Digital representation of building components and systems within an integrated modelling environment	Facilitates coordination between architectural, structural, and water systems during design
DT5	Monitoring, Sensors, & Smart Systems	Building/System	Real-time data acquisition & feedback control	Deployment of sensors to track flow rates, storage levels, and water quality parameters	Enables operational monitoring, fault detection, and adaptive management
DT6	Decision Support & Performance Evaluation Tools	Building/Urban	Optimisation & decision-making	Multi-criteria analysis, optimisation algorithms, and evaluation frameworks	Supports selection of optimal configurations based on technical, economic, and environmental criteria
DT7	Not specified	—	—	—	Category used when insufficient technical detail is provided in the source literature

summarises these tools by linking each category to its functional role within the modelling and management of building-scale water systems.

This analysis revealed that DT6 (7) and DT1 (6) are the most widely used DT categories (see Figure 13).

The figures indicate the percentage of articles in which each DT is present. The values do not add up to 100% because of the multi-response nature of the data.

6.2.2. Normalisation with Respect to the Location’s Topic

The term “Location” was used as a macro-category indicating the place where technologies are applied. Normalisation was split into the following two levels: the Scale/Context of application and the specific Building Element/Physical Location involved. Two distinct vocabularies were used to analyse the topic of Location.

The first, useful for outlining the Scale/Context of application (SC) of the technologies previously identified, consists of the following six items:

• Building-scale (SC1)
• Site-scale (SC2)
• Urban-scale (SC3)
• Regional-scale (SC4)
• Subsurface (SC5)
• Not specified (SC6)

As shown in Figure 14, 74% of the 136 selected papers focus on SC1. This percentage can reach 84% if we also include the papers that address multiple application scales simultaneously (e.g., SC1 + SC2, SC1 + SC3, SC1 + SC5). Continuing the analysis, we can see that the scale of application extends to SC3, ranking second with 7% of the papers examined. In this case, considering also papers that address SC3 alongside other scales of application (e.g., SC3 + SC5, SC1 + SC3, SC2 + SC3), the value reaches 14%. The other SCs, on the other hand, do not exceed 8% altogether.

The second vocabulary, on the other hand, was used to highlight the Building Element/Physical Location involved (BL) or the elements where water harvesting technologies are applied, as follows:

• Ground (BL1)
• Pipe (BL2)
• Internal hydraulic surface (BL3)
• Pavement (BL4)
• Green roof (BL5)
• Roof (BL6)
• Tank (BL7)
• Façade (BL8)
• Living façade (BL9)
• Wall (BL10)
• Urban green infrastructure (BL11)
• Not specified (BL12)

As shown in Figure 15, excluding the 35% of papers in which the Building Element/Physical Location of application is BL12 (Not Specified), 26% of the analysed papers report that the technologies are applied to the “Roof” (BL6). This category can reach 36% if we also consider the particular situations in which, in addition to BL6, multiple locations or elements of application were found in the paper (e.g., BL6 + BL1, BL6 + BL4, BL6 + BL2, BL6 + BL7). The BL5 category alone accounts for only 1% of papers, but can reach 5% if we also consider papers that use it alongside other applications (e.g., BL5 + BL7, BL5 + BL9, BL5 + BL4 + BL11).

The BL7 element ranks second in the graph, with 14% as a single category. For this category too, given the cases in which multiple application elements were found within the analysed papers, it is possible to increase this figure to 25% (e.g., BL7 + BL2, BL6 + BL7, BL10 + BL7, BL5 + BL7).

These initial data suggest the possibility of applying a further level of standardisation by grouping the categories previously identified in the chart into Building Areas (BA), as follows:

• Ground area (BA1)
• Wall area (BA2)
• Roof area (BA3)
• Internal hydraulic area (BA4)
• Element (BA5)
• Not specified (BA6)

In Figure 16, the percentages refer to the ratio of studies that addressed a specific category and do not add up to 100%. The category “Element” (BA5) refers to studies that specify a physical location but do not provide sufficient details for normalisation by area, while the category “Not specified” (BA6) includes papers in which the physical location of the application is not explicitly indicated.

6.2.3. Normalisation with Respect to the Aim’s Topic

A single vocabulary was used to analyse the primary and secondary aims described and pursued in the 136 papers, with the addition of the category “Not specified” to indicate the absence of secondary objectives.

The 10 + 1 categories used to standardise the analysis of the Aims (AM) are as follows:

• Alternative and Supplementary Water Supply (AM1)
• Climate Change Adaptation and Resilience (AM2)
• Decentralised, Urban and Social Water Systems (AM3)
• Energy and Economic Performance (AM4)
• Environmental and Resource Sustainability (AM5)
• Non-Potable Water Reuse (AM6)
• Potable Water Quality and Treatment (AM7)
• Stormwater and Flood Management (AM8)
• System Design, Integration, and Performance (AM9)
• Water Conservation and Efficiency (AM10)
• Not Specified (A11)

Figure 17 and Figure 18 show the percentages of AMs identified in the papers, normalised according to the defined vocabulary. The three categories that emerge as primary aims are AM9, AM6, and AM10, with values of 16%, 15%, and 14%, respectively, while the other categories remain below 10%.

A total of 53% of the papers analysed include a secondary aim. Among these, the normalised categories AM5 and AM1 are slightly more prevalent, at 8% and 7%, respectively. The other categories, on the other hand, range from 1% to 6%.

6.2.4. Focus on Case Studies Implementation and Distribution

After analysing all 136 selected papers, the next step is to examine in detail those that present projects supported by case studies.

As shown in Figure 19, 53 of the 136 selected papers (about 40%) feature a case study.

Once the number of papers characterised by case studies had been identified, an analysis was conducted to determine where these case studies on water harvesting technologies had been most widely applied.

At the continental level (see Figure 20), the analysis showed that most case studies were applied in Asia (51%) and Europe (26%). The other continents share the remaining papers (4–7%) almost equally.

Going into greater detail and continuing the analysis at the individual country level (see Figure 21), it emerged that, for the Asian continent, most case studies are concentrated in Indonesia (8), India (4), and Malaysia (4). In Europe, Portugal, with three case studies, is joined by Italy, the UK, Poland, and Cyprus, each with two case studies. The same is noted for countries on other continents, such as the USA, Iran, Ecuador, Ethiopia, and Türkiye.

Once the countries where case studies were implemented had been determined, the next step was to verify the Main Technology (MT) used in those areas.

In this analysis, too, as shown in Figure 22, “Rainwater Harvesting System” (MT4) is used in the majority of the papers (87%). Although in a 1:10 ratio with the main one, the second-most-representative technology is the “Fog Harvesting System” (MT2—8%), while the remaining percentage points are divided among combinations of MT4 and the other MTs.

To highlight any differences between the complete set of 136 papers and the 53 characterised by the use of a case study, a comparative analysis was conducted according to the following categories:

• Main Technology (MT)
• Secondary Technology (ST)
• Integrated Technology (IT)
• Digital Tool (DT)

Based on this comparison,

Table 7. Comparison between the complete set of 136 selected papers and the 53 characterised by Case Studies.

Cat.	136 Papers	Technology	53 Papers with Case Study
MT	113/136	Rainwater Harvesting System (MT4)	46/53
	9/136	Fog Harvesting System (MT2)	4/53
ST	38/68	Roof-based Collection System (ST1)	16/28
	32/68	Storage System (ST3)	14/28
IT	9/27	Water Reuse & Recycling System (IT1)	6/11
	5/27	Stormwater Management & Regulation System (IT2)	-
	4/27	Groundwater Interaction System (IT3)	3/11
	4/27	Green–Blue Infrastructure System (IT4)	-
DT	7/14	Decision Support & Performance Evaluation Tools (DT6)	2/7
	6/14	GIS & Geospatial Analysis Tools (DT1)	-
	-	BIM & Digital Building Modelling (DT2)	2/7

provides a summary of the most common technologies. As already mentioned in the respective sections of this paper, the values in the MT category refer to 100% of the papers concerned, whereas the other three categories—ST, IT, and DT—do not reach 100% due to the multi-response nature of the data.

By considering only the papers featuring case studies that used MT4 and applying the same normalisation dictionaries previously used for Secondary Technology (ST), Integrated Technology (IT), and Digital Tool (DT), it was possible to analyse the relationship between the case studies and these technologies in greater depth (see Figure 23). Thanks to this analysis, we determined that, among the papers using MT4, 45% also feature an ST. In second place is the combined category of ST with IT, accounting for 7% of the papers concerned (Figure 24).

Specifically, the 46 papers that focus on the use of MT4 as the primary technology are accompanied only by an ST (the blue section in the pie chart in Figure 22).

Furthermore, going into greater detail and considering only the 46 papers characterised by the use of MT4—the light blue section of the primary pie chart in Figure 23—it was possible to analyse and catalogue the different relationships with ST, IT, and DT.

Specifically, the 28 papers in which the MT is accompanied by an ST were analysed using the same vocabulary used for the more general analysis in Figure 11. In this case, the analysis revealed and confirmed that ST1 (16) and ST3 (14) are the two most common STs (see Figure 25).

On the other hand, the 11 papers in which the MT is accompanied by an IT were analysed using the same vocabulary used for the more general analysis in Figure 12. This analysis revealed that IT1 is the most widely used IT category (6), followed by IT3 (3) (see Figure 26).

The seven papers in which the MT is accompanied by a DT, as in the previous two analyses, were analysed using the same vocabulary used for the more general analyses in Figure 13. In this case, the analysis revealed that DT6 and DT4 (2) are the most widely used DT categories (see Figure 27).

Again, the percentages indicate the proportion of articles in which each ST is present. The values do not add up to 100% because the data are multi-response.

6.2.5. Climate Analysis per Case Study Distribution

As shown by the analyses presented at the beginning of the previous paragraph (Section 6.2.4), the 53 case studies are distributed across 29 countries on all continents, excluding the poles.

Each continent and each country has its own distinctive climate, and studying these helps us better understand why certain locations were chosen for the case studies (see Figure 20 and Figure 21).

The analysis is based on Köppen’s climate classification [166], which assigns three letters to each area (the first refers to the Main Climate, the second to Precipitation, and the third to Temperature, as shown in

Table 8. Climate classification following the Köppen–Geiger Climate Zones [167].

Main Climate		Precipitation		Temperature
A	Equatorial	W	Desert	h	Hot arid
B	Arid	S	Steppe	k	Cold Arid
C	Warm Temperate	f	Fully Humid	h	Hot Summer
D	Snow	s	Summer Dry	b	Warm Summer
E	Polar	w	Winter Dry	c	Cool Summer
		m	Monsoonal	d	Extremely Continental
				F	Polar Frost
				T	Polar Tundra

).

The first step was to apply the above classification to the countries in the case studies, assigning a maximum value of 1 when a country had a single predominant climate, 0.5 when it had two main climates, and 0.3 when it had three main climates. This procedure was applied to highlight, for each country, both the generic climate (single-letter classification; see the Main climate column in Table 7) and the specific climate (classification based on the combination of the three letters in all three columns of Table 7). For these calculations, each climate was counted as many times as the number of occurrences of the country associated with it, to give the distribution of case studies greater weight. Once this analysis was complete, the values were converted to percentages to facilitate a comparison with global climate percentages. Figure 28 shows the results of the climate distribution for the case studies, already expressed as percentages, for a comparison with the global distribution according to the Köppen–Geiger classification.

This comparative graph, which aggregates the climates emerging from the papers characterised by case studies at a global level and weights them by frequency, shows that tropical (A) and temperate (C) climates account for 37.8% and 37.4% of the analysed dataset, respectively. Compared to the global distribution of Köppen–Geiger [168], these classes are significantly over-represented, while arid (B) and cold (D) climates are relatively under-represented. Polar climates (E), on the other hand, are completely absent from the case studies analysed.

This imbalance highlights how research on RWHS tends to focus on climatic contexts characterised by significant rainfall regimes or marked seasonal precipitation, i.e., where the availability of rainwater makes such solutions technically and economically more feasible. On the other hand, it appears that arid and cold climates are less explored in the context of RWHS systems, even though they are characterised by specific water-related challenges.

7. Conclusions and Future Development

In conclusion, this scoping literature review shows that interest in research on RWHSs has increased since 2010, with a linear trend characterised by irregular peaks, mainly since 2020.

At a theoretical level, interest has grown steadily in Asia (41%) and Europe (37%), whereas in North America (11%), it began to emerge in 2015. At a practical level, however, case studies have been implemented mainly in Asia (51%) and Europe (26%). In fact, the clear prevalence of climate classes A and C, particularly those characterised by fully humid and monsoonal regimes, highlights that case studies of RWHS systems are mainly applied in contexts with high annual rainfall or marked seasonality, conditions that favour the effectiveness of collection and storage systems.

By referring to the Scale/Context of application (SC), these studies are generally conducted at the “Building Level” (SC1, 74%), with some interest also at the “Urban Level” (SA3, 7%). These data are also confirmed at the Building Element/Physical Location (BL), where “Roofs” (BL6, 26%) and “Tanks” (BL7, 14%) are the BLs most frequently mentioned.

When considering the Aim’s topic (AM), approximately 50% of the primary aims of the 136 selected papers are divided equally between “System Design, Integration, and Performance” (AM9), “Non-Potable Water Reuse” (AM6), and “Water Conservation and Efficiency” (AM10). Over 50% of the same set of papers have a secondary aim, of which 15% are equally represented by “Environmental and Resource Sustainability” (AM5) and “Alternative and Supplementary Water Supply” (AM1).

Even though the number of case studies on fog collection systems is significantly lower than that of rainwater harvesting systems (see Figure 22), the analysed papers report positive results for water collection in the specific climatic contexts considered. The results of this analysis contribute to advancing research in this field by providing not only a structured mapping of how different water harvesting technologies relate to specific climatic conditions and application contexts, but a functional interpretation of these technologies, clarifying their operational roles across building-scale water management systems, thereby supporting the development of more effective and context-adaptive design strategies for climate-resilient building systems.

Based on the results of this scoping review, the next step in future developments will be to focus on and investigate the integrated application of the two most representative technologies (see Figure 9 and Figure 23). This involves the use of Rainwater Harvesting Systems (RWHS) on roofs, combined with Fog Collectors on façades.

This technological integration aims to enhance overall water collection performance by combining mechanisms for collecting precipitation and atmospheric humidity. This strategy aims to increase the amount of water harvested, particularly in climates characterised by seasonal variability.

To continue this study, during the final drafting phase of this article, work began on defining a scalable prototype adaptable to different climatic and urban contexts.

In addition to further investigating rainwater and wastewater management systems, future research will focus on testing and validating this integrated configuration through selected case studies across different geographical and climatic areas.

8. Limitations

In this scoping review, to ensure the accessibility and transparency of the methodological approach, only articles indexed in the Scopus database and published in Open Access journals were considered. However, this decision imposes a limitation that may introduce selection bias, potentially excluding high-quality studies available in other bibliographic databases (e.g., Web of Science, ProQuest) or in non-Open Access journals.

The selected time period (2010–2024), chosen to capture technological developments and innovations in the field of RWH, may have overlooked relevant earlier contributions.

Furthermore, in line with the nature and objectives of scoping reviews, no formal critical appraisal of the included articles was conducted, as this is not mandatory in this type of review.

Although the decision to include only English-language publications may have excluded relevant studies published in other languages, it was adopted to ensure international comparability.

A preliminary quantitative support procedure based on cosine similarity was considered to facilitate the management of the dataset. However, the final selection of 136 articles was made through a comprehensive manual screening of all 343 records.

No review protocol was registered prior to conducting this study. However, the review process was conducted in accordance with the PRISMA-ScR guidelines to ensure methodological transparency and reproducibility.

Despite these limitations, the structured methodological approach adopted and the broad scope of the literature considered ensure that the review provides a comprehensive and representative overview of the technologies used in RWHSs.