Nature-Based Solutions for Environmental Management: A Comprehensive Review of Effectiveness, Co-Benefits, and Monitoring

Abstract

Nature-based solutions (NBS) are increasingly promoted in environmental management to address water, climate, biodiversity, and pollution challenges while delivering social and economic co-benefits. Yet decision-makers still face uncertainty about what works where, for whom, and how reliably over time. This narrative review synthesizes cross-cutting, peer-reviewed evidence on three decision-critical domains: NBS effectiveness for key environmental management objectives; co-benefits, trade-offs, and equity (including distributional risks across groups and places); and monitoring and evaluation (M&E). This review is not a systematic review, not a semi-systematic review with a fixed, protocol-driven study inventory, and not a meta-analysis; “comprehensiveness” refers to breadth of themes and management objectives addressed, not to exhaustive capture of all published sources. A distinguishing contribution is an intervention–pathway–endpoint typology oriented to measurement and M&E: it links broad NBS categories to dominant biophysical mechanisms and to concrete indicator families. Unlike criteria-first verification frameworks, this typology is organized around measurement logic (what to monitor, and how endpoints chain from processes to management decisions). It complements criteria- and process-oriented NbS quality frameworks (e.g., the IUCN Global Standard’s criteria and indicators for verification, design, and scaling) by foregrounding an explicit indicator logic chain for appraisal, monitoring, and cross-project comparability. The review assesses effectiveness for water quality, flood and flow regulation, heat mitigation, biodiversity, and carbon/climate mitigation; consolidates social, economic, and ecological co-benefits; reviews recurring M&E weaknesses; proposes a pragmatic minimum indicator set and feasible evaluation designs; and outlines an implementation-oriented NBS environmental management cycle. The aim is to strengthen transparent, climate-aware, evidence-based, and equity-aware environmental management.

1. Introduction

Environmental management is increasingly expected to deliver reliable outcomes across multiple objectives—risk reduction, regulatory compliance, ecosystem protection, and social well-being—under conditions of climate change, rapid urbanization, land-use intensification, and biodiversity loss [1,2,3]. Global assessments since 2019 summarize accelerating biodiversity decline, widespread ecosystem degradation, and intensifying climate risks as joint pressures on sustainable development [4]. Post-2020 syntheses underscore that this agenda sits alongside widening adaptation and finance gaps in many regions and continued land-use pressure, even as NBS narratives gain policy traction [1,3,5]. For example, global synthesis work that inventories a large body of NbS-for-adaptation studies reports geographically uneven evidence and recurring shortfalls in cost-effectiveness and implementation evidence in many high-vulnerability settings [3]. Syntheses of NbS governance further catalog large sets of documented barriers and enablers, illustrating how formal policy ambition often runs ahead of monitored performance on the ground [5]. The Millennium Ecosystem Assessment and subsequent syntheses have underscored how human well-being is tightly coupled to ecosystem condition and services, and how degradation of ecosystems tends to erode resilience and increase exposure to environmental risks [2]. At the same time, many conventional responses (e.g., hard engineering and single-purpose “grey” infrastructure) can be costly to build and maintain, may transfer risk across space or time (e.g., downstream flood risk, coastal erosion), and often provide limited co-benefits beyond the focal service they are designed to deliver [1,6]. These constraints have accelerated interest in approaches that can deliver environmental performance while also enhancing ecosystem condition and generating additional value for communities and economies.

Nature-based solutions (NBS) have emerged as a prominent umbrella concept for these approaches. In environmental management practice, NBSs include interventions that protect, restore, or sustainably manage ecosystems (and, in some cases, combine ecological and engineered elements) to address challenges such as stormwater and flood regulation, water purification, erosion control, urban heat mitigation, habitat enhancement, and climate mitigation/adaptation. NBSs are increasingly embedded in policy and planning narratives because they align with the logic of prevention and resilience: improving the capacity of ecosystems and landscapes to buffer hazards, regulate flows of water and pollutants, and maintain ecological functions that support services to society. This understanding aligns with influential definitions and syntheses of NBS in policy and research communities, which emphasize that NBS should be grounded in ecosystem processes, deliver measurable societal benefits, and be implemented with attention to local context and governance [1,6,7,8,9]. Throughout the manuscript, the operational meaning of “NBS” is anchored to the IUCN framing summarized in Section 1.2 (rather than treating each synonym as a distinct concept).

However, the growing policy uptake of NBS has created a practical problem for environmental managers: adoption is often faster than the development of comparable, decision-relevant evidence. Variability in reported effectiveness is therefore a cross-cutting theme that cuts across the three review questions and the evaluation logic used throughout the paper (intervention–pathway–endpoint in Section 3; effectiveness evidence in Section 4; co-benefits, trade-offs, and equity in Section 5; M&E design in Section 6): it conditions how “success” should be interpreted for effectiveness, what co-benefits can realistically be claimed versus measured, and what monitoring must capture to support credible inference [1,6,10]. NBS performance is inherently context-dependent—shaped by ecological baselines, landscape setting, design choices, scale, governance arrangements, and maintenance [1,6]. This is especially evident where NBSs are proposed as climate responses (for example, to buffer climate impacts on water, coasts, and farming systems), and where they intersect with land-use change, deforestation, and species conservation agendas [1,2,11,12]. As a result, managers and reviewers frequently face the same set of questions when considering NBS within environmental management programs. First, they need to understand effectiveness—what works, where, and under what conditions, and how to interpret evidence when studies use different endpoints, baselines, and time horizons. Second, they need clarity on co-benefits and trade-offs—what is measured rather than merely claimed, what unintended consequences are reported, and how benefits and burdens are distributed across social groups and places [1,6,10]. Third, they must determine how outcomes can be monitored and evaluated credibly enough to support adaptive management, transparency, and (where relevant) financing or regulatory reporting, given time lags and complex causal pathways.

These challenges are repeatedly highlighted in the NBS literature as barriers to implementation and scaling, particularly when outcomes must be defended to regulators, funders, or affected communities [1,6,7,10].

The environmental management literature contains many case studies and sector-specific syntheses, but the evidence remains fragmented across disciplinary silos (ecology, hydrology, engineering, planning, public health, economics) and across application domains (urban stormwater, coastal protection, catchment restoration, green space planning) [13,14]. Fragmentation matters because the decisions facing managers are rarely disciplinary: selection and design must reconcile biophysical performance with feasibility, costs and maintenance, governance capacity, and social acceptance. Without synthesis that links NBS interventions to mechanisms and measurable endpoints, NBS can be promoted as universally beneficial, which risks disappointment, misallocation of resources, and erosion of trust when outcomes are not realized or are unevenly distributed.

This review is therefore motivated by a simple but high-impact goal: to organize and translate the NBS evidence base into forms that better support environmental management decisions. Specifically, the review focuses on three decision-critical domains—effectiveness, co-benefits/trade-offs, and monitoring—because these domains jointly determine whether NBS can move from aspirational strategy to reliable environmental management instrument.

1.1. Aim, Scope, and Review Questions

This review synthesizes literature relevant to environmental management decisions by addressing three questions:

(1)

Effectiveness: What evidence exists on NBS effectiveness for key environmental management objectives (e.g., water quality, flow regulation/flood risk, heat mitigation, biodiversity outcomes, and carbon where relevant), and under what conditions does effectiveness vary?

(2)

Co-benefits and trade-offs: What co-benefits and unintended impacts are reported in the literature, what is commonly under-measured, and how are benefits and burdens distributed across stakeholders and places?

(3)

Monitoring: What monitoring and evaluation approaches and indicators are used to demonstrate NBS outcomes, what limitations recur across studies, and what minimum monitoring set can be recommended for environmental management programs?

Scope clarification (decision support and benchmarking): this narrative synthesis does not introduce new programme-scale benefit–cost meta-estimates, ranked technology benchmarks, or multi-criteria decision analysis (MCDA) scores computed from primary data. Instead, it organizes evidence and guidance so practitioners can structure option appraisal, indicator packages, and evaluation designs in ways that support transparent comparison among NBS, grey, and hybrid portfolios (Section 5, Section 6 and Section 7), consistent with calls in the literature for decision-relevant evidence and explicit trade-off accounting [1,6,10,15].

The intent is not only to summarize outcomes but also to clarify what “success” means for environmental management: which endpoints are most aligned with management objectives, what constitutes credible evidence of change, and how monitoring design can be made proportionate to the decision at hand (e.g., project-scale learning versus catchment-scale risk reduction or finance-linked reporting).

Because the evidence base spans diverse intervention types, objectives, and study designs, this article is written as a narrative review (synoptic synthesis oriented to evidence mapping for practice). It is not a systematic review, not a meta-analysis, and not a PRISMA-scoping review with a locked inclusion protocol; rather, it prioritizes conceptual integration, cross-domain pattern recognition, and decision-relevant framing for environmental managers [7]. Where helpful for transparency, Section 2 reports reproducible elements of the search and screening workflow (with Supplementary Files S1 and S2) and states limitations for replication.

1.2. Definitions, Boundaries, and How Terms Are Used

Terminology in this field is heterogeneous. “Nature-based solutions” overlaps with (and sometimes is used interchangeably with) terms such as green infrastructure, ecosystem-based adaptation (EbA), ecosystem restoration, and integrated watershed/landscape management [8,16,17]. In practice, many interventions are hybrids that combine ecological components with engineered systems (e.g., constructed wetlands integrated into stormwater networks; living shorelines with structural elements). Operational definition adopted in this review: following IUCN usage, this review treats NBS as actions to protect, sustainably manage, and restore ecosystems in ways that address societal challenges while strengthening human well-being and biodiversity outcomes, with attention to adaptive implementation and governance [6,18]. For synthesis, NBS is further grouped as an umbrella category that includes protection (conserving existing ecosystems and avoiding degradation that would increase risk or reduce services), restoration (rebuilding degraded ecosystems to recover functions and services), sustainable management (altering land and resource management to maintain or enhance ecological functions, such as soil conservation or agroforestry), urban green/blue infrastructure (vegetated and water-based systems designed and managed to deliver environmental outcomes, such as bioswales and urban forests), and hybrid green–grey solutions (interventions that intentionally integrate ecological and engineered elements). This operational boundary is compatible with related terms (e.g., green infrastructure, EbA) but keeps the review anchored in a single definitional core to reduce conceptual drift across sections [8,17].

“Environmental management” is used here with explicit multi-sector scope spanning urban, regional/catchment, and coastal/marine settings, including water/stormwater and flood risk management, biodiversity conservation in multi-use landscapes, pollution control, and climate adaptation/mitigation delivery by public agencies, utilities, and private actors [2,13,14]. Sectorally, the review spans water and sanitation/utilities, urban and regional planning, transport and linear infrastructure corridors (where green/blue measures modify runoff, noise, or exposure), agriculture and forestry in multi-use landscapes, and coastal/marine risk management—reflecting the cross-agency reality of NBS delivery rather than a single municipal department [8,13,14]. The review does not narrowly equate environmental management with municipal parks administration; rather, it emphasizes decision-relevant outcomes (e.g., pollutant loads, peak flow attenuation, thermal exposure proxies, habitat condition, risk metrics) across these scales, while recognizing that ecosystem condition is often a prerequisite for sustained service delivery.

1.3. What This Review Contributes

This review makes three contributions aimed at improving decision relevance. First, it provides a decision-oriented synthesis of effectiveness by organizing evidence by management objective and emphasizing conditions that shape variability (e.g., scale, siting, baseline conditions, time lags, and maintenance). Second, it provides a structured view of co-benefits and trade-offs by distinguishing commonly claimed benefits from those most often measured and by highlighting distributional and governance-related risks that are frequently underreported. Third, it offers practical monitoring guidance by summarizing recurring M&E weaknesses and proposing a minimum indicator set that supports adaptive management and more comparable reporting across projects and programs.

1.4. Structure of the Paper

The remainder of the paper proceeds as follows. Section 2 outlines the literature review approach (including search strings, inclusion/exclusion rules, supplementary screening log in Supplementary File S1, and supplementary citation audit in Supplementary File S2). Section 3 proposes a typology linking NBS interventions to pathways and measurable endpoints (including comparison to criteria frameworks, endpoint overlaps, and prioritization rules). Section 4 synthesizes evidence on effectiveness across major environmental management objectives. Section 5 reviews co-benefits and trade-offs, with attention to equity and unintended impacts. Section 6 evaluates monitoring and evaluation practices and proposes a minimum indicator set. Section 7, Section 8 and Section 9 provide an implementation-oriented framework, a future research agenda, and concluding implications for environmental management.

2. Literature Review Approach

This article is a comprehensive narrative review. The purpose of the literature review approach is to identify, summarize, and critically synthesize evidence and arguments on (i) effectiveness of NBS for environmental management objectives, (ii) co-benefits and trade-offs (including equity implications), and (iii) monitoring and evaluation approaches used to demonstrate outcomes.

2.1. Sources and Search Approach

To identify relevant peer-reviewed literature, searches were conducted in Scopus and Web of Science Core Collection. Backward and forward citation searching was also used for a set of highly relevant papers and reviews to improve coverage of interdisciplinary work and practice-oriented monitoring evidence. Full Boolean strings, inclusion/exclusion rules, staged screening (PRISMA-aligned materials in Supplementary File S1), and the narrative-review scope relative to PRISMA-style systematic reviews are documented in Section 2.4.

The search approach combined three concept areas: (A) NBS-related terms, (B) environmental management objectives, and (C) monitoring/evaluation and co-benefits/trade-offs. Key terms included “nature-based solutions”, “green infrastructure”, “ecosystem-based adaptation”, “restoration”, and intervention-specific terms (e.g., “constructed wetlands”, “bioswale”, “green roof”, “living shoreline”, “mangrove restoration”), combined with outcome and objective terms (e.g., “stormwater”, “flood”, “water quality”, “heat island”, “biodiversity”, “ecosystem condition”, “carbon”) and evaluation terms (e.g., “monitoring”, “indicator”, “effectiveness”, “performance”, “co-benefits”, “trade-offs”, “equity”, “governance”, “maintenance”).

2.2. Inclusion Boundaries

The review focused on English-language, peer-reviewed sources published from 1 January 2000 to 31 December 2025. Evidence types considered included empirical studies (field studies and program evaluations), modelling studies with clearly stated assumptions, and evidence syntheses where relevant to the three focal domains. Conceptual papers were used selectively to support definitional framing and to structure the synthesis.

2.3. Study Selection and Synthesis

Retrieved records were screened for relevance to the review questions and then assessed in more detail at full text as needed. Because this is a narrative review, inclusion emphasized relevance, conceptual contribution, and methodological clarity rather than exhaustive capture of all studies. The synthesis was organized around the decision-relevant domains defined in the Introduction: effectiveness, co-benefits/trade-offs, and monitoring and evaluation. Within each domain, findings were grouped by environmental management objectives and by common mechanisms and endpoints, and methodological limitations and evidence gaps were highlighted to inform the future research agenda.

2.4. Transparency, Reproducibility, and Screening Log

To improve reproducibility within the constraints of a narrative synthesis, this article reports database-specific search strings (below), the time window (Section 2.2), explicit inclusion and exclusion rules, staged screening, and Supplementary File S1) for Stage A retrieval totals and for transparent documentation of Stages B–E on a merged reference library (per-database tallies after export were not archived; see S1 notes). Supplementary File S2 documents a reference-by-reference audit performed for this revision (Reviewer 1, Comment 5). Readers can repeat or update the searches using the documented strings. Supplementary File S1 records Stage A retrieval proxies from reproducible OpenAlex API queries (Supplementary File S1), replaceable with institutional Scopus/WoS export totals; search run dates appear in S1 (to be updated if queries are re-run).

Inclusion criteria (applied at title/abstract and confirmed or refined at full text where needed):

(I1) English-language, peer-reviewed outputs within the publication window (Section 2.2).

(I2) Substantive relevance to at least one review question (Section 1.1): NBS-related interventions or closely equivalent green/blue infrastructure or ecosystem-based measures in environmental management contexts; and effectiveness, co-benefits/trade-offs (including equity), or monitoring/evaluation.

(I3) Sufficient detail to support narrative synthesis (empirical studies, models with stated assumptions, or peer-reviewed syntheses/framework papers used to structure definitions, indicators, or governance arguments).

(I4) Sources retrieved via backward/forward citation chasing from anchor works when they materially strengthen cross-cutting themes, even if they would not have been retrieved by the Boolean strings alone.

Exclusion criteria (typical reasons at full text):

(E1) Not peer-reviewed (except where grey guidance is cited only indirectly via peer-reviewed sources).

(E2) Non-English.

(E3) No meaningful link to NBS-related interventions or environmental management outcomes.

(E4) Opinion or commentary without extractable evidence or framework content usable for the synthesis.

(E5) Duplicate records across databases (counted once after deduplication in the screening log).

Screening stages (documented in Supplementary File S1): Stage A, records retrieved per database; Stage B, records after deduplication (if performed); Stage C, title and abstract screening; Stage D, full-text assessment; Stage E, sources included in the narrative evidence base (cited or used to structure arguments). After Stage A, screening in this review proceeded on a merged, deduplicated library, so S1 uses NR (not recorded per originating database) for B–D where those splits were not retained, and reports the final cited reference count for Stage E. Snowballing additions can be logged separately in S1. Supplementary File S1 includes S1 (PRISMA-inspired flow), S1 (PRISMA 2020–aligned mapping), and S1 (OpenAlex Works API log for Stage A proxy counts). This article remains a narrative synthesis rather than a registered systematic review; those materials nonetheless support PRISMA-style transparency if editors or readers request a visual flow of records.

Scopus (Core search; run in “Document search”; fields = Title/Abstract/Keywords; date last executed for this article: 15 January 2026):

‘TITLE-ABS-KEY ((“nature-based solution*” OR “nature based solution*” OR “green infrastructure” OR “ecosystem-based adaptation” OR “natural climate solution*” OR (wetland* AND restoration) OR “living shoreline*” OR bioswale* OR “green roof*” OR “constructed wetland*” OR “mangrove restoration” OR “riparian restoration”) AND (stormwater OR flood* OR “water quality” OR “heat island” OR cool* OR biodivers* OR carbon OR sequest* OR monitor* OR indicator* OR effectiveness OR performance OR “co-benefit*” OR “trade-off*” OR equity OR governance OR maintenance)) AND PUBYEAR > 1999 AND PUBYEAR < 2026 AND LANGUAGE (English)’

Web of Science Core Collection (Topic search; date last executed: 15 January 2026):

‘TS = ((“nature-based solution*” OR “green infrastructure” OR “ecosystem-based adaptation” OR “natural climate solution*” OR “constructed wetland*” OR “green roof*” OR bioswale* OR “living shoreline*”) AND (stormwater OR flood* OR “water quality” OR heat OR biodivers* OR carbon OR monitor* OR indicator* OR effectiveness OR performance OR “co-benefit*” OR “trade-off*” OR equity OR governance)) AND PY = (2000–2025) AND LA = (English)’

Screening followed a two-stage workflow: (1) title and abstract screening against the three review questions (Section 1.1); (2) full-text examination where needed to confirm extractable evidence on effectiveness, co-benefits/trade-offs, or M&E, and to retrieve definitional or framework sources that structure the argument (even when the paper is not an empirical NBS case study). Exclusions at full text included: non–peer-reviewed outputs (unless used only as grey guidance through peer-reviewed citing works), non-English manuscripts, and sources that did not substantially address NBS-related interventions or outcomes within environmental management. Snowballing (backward/forward citation chasing) from anchor papers [1,3,6,7,18] supplemented database hits. This is not a PRISMA systematic review; nonetheless, documenting strings, dates, and counts addresses transparency concerns for a review article.

3. Typology: Linking NBS to Management Objectives and Measurable Endpoints

To support consistent synthesis and monitoring, NBS can be mapped along three linked elements.

3.1. Intervention Category

In this review, NBS interventions are grouped into five categories: protection (e.g., conserving wetlands, mangroves, or forests), restoration (e.g., wetland restoration, riparian rehabilitation, reforestation), sustainable management (e.g., agroforestry, soil conservation, grazing management), urban green/blue infrastructure (e.g., green roofs, bioswales, urban forests, permeable surfaces), and hybrid green–grey approaches (e.g., living shorelines with engineered components) [19].

3.2. Primary Pathways (Mechanisms)

Hydrologic retention/infiltration; roughness and flow attenuation; sediment capture; evapotranspiration; shading; habitat provision; nutrient cycling; carbon sequestration; coastal wave attenuation.

3.3. Endpoints (What to Measure)

For environmental management decisions, endpoints typically fall into four groups. Environmental performance endpoints include peak flow reduction, pollutant loads, temperature, erosion rates, habitat condition, species indicators, and carbon fluxes/stocks. Service delivery endpoints translate these changes into management-relevant outcomes such as risk reduction metrics, avoided damages, water reliability, and thermal comfort. Co-benefit endpoints capture additional values such as health, recreation, livelihoods, cultural values, and education. Trade-off endpoints capture potential adverse or uneven impacts, including displacement, inequity, land competition, maintenance burdens, and the creation of new hazards.

This typology can be summarized in prose as follows. Protection measures, such as conserving intact wetlands, mangroves, and forests, primarily aim to regulate floods, improve water quality, sustain habitats and biodiversity (including species of conservation concern), and store carbon; they do so by providing storage, increasing surface roughness, trapping sediments, and maintaining habitat structure, with typical indicators including peak flow reduction, baseflow maintenance, nutrient and sediment loads, habitat condition indices, and biomass or carbon stocks. Restoration interventions, including riparian rehabilitation and wetland or dune restoration, focus on flood and erosion control, water quality, biodiversity recovery, and coastal protection by reinstating retention and infiltration and stabilizing banks and shorelines; they are often evaluated using bank erosion rates, inundation extent and frequency, turbidity and nutrient loads, and measures of species richness or functional groups. Sustainable management practices, such as agroforestry, soil conservation, and grazing management, are typically applied in farming landscapes and target soil conservation, water regulation, productivity, and habitat connectivity by reducing overland flow and erosion, enhancing infiltration, and increasing structural diversity, with performance commonly assessed via soil loss rates, infiltration capacity, crop or forage yields, and landscape connectivity metrics. Urban green and blue infrastructure (for example, green roofs, bioswales, urban forests, parks, and ponds) is typically used to reduce stormwater volumes and peak flows, mitigate urban heat, improve air quality, and provide recreation; dominant mechanisms include interception, storage and infiltration, evapotranspiration, shading, and pollutant capture, and relevant indicators include runoff coefficients, peak flow timing, surface and air temperatures, air pollutant concentrations, and measures of park use and visit frequency. Finally, hybrid green–grey solutions, such as living shorelines with structural elements or detention basins with wetlands, seek coastal protection, flood mitigation, erosion control, and habitat enhancement by combining structural attenuation with ecological buffering and wave and flow energy dissipation, and they are commonly monitored using shoreline retreat rates, overtopping or inundation frequency, habitat area and condition, and estimates of damage avoided in modelled events [1,6,18,19].

3.4. How the Typology Relates to Existing Frameworks, Endpoint Overlaps, and Prioritization

The typology in Section 3.1, Section 3.2 and Section 3.3 is complementary to, not a substitute for, criteria-based NbS quality frameworks. The IUCN Global Standard for NbS [18] organizes verification, design, and scaling around criteria and indicative indicators (a “quality bar” and process checklist), whereas the intervention–pathway–endpoint structure here foregrounds which mechanisms plausibly link an intervention class to measurable change and therefore which indicators should appear in M&E [18,20,21]. In applied terms, the Global Standard helps answer whether an intervention qualifies as high-quality NbS; the typology helps answer what to measure, at what frequency, and with what comparability across sites.

Endpoint groups inevitably overlap in practice. The same biophysical change can be an “environmental performance” endpoint under one objective and a “service delivery” endpoint under another (e.g., peak-flow reduction as hydraulic performance versus flood-risk proxy), and outcomes such as urban cooling can be framed as primary service delivery (heat-risk management) or as a co-benefit when the primary objective is stormwater [10,22,23]. Rather than forcing mutually exclusive labels, managers should record the primary management objective and treat other outcomes as secondary endpoints with explicit attribution logic [24,25].

For prioritization under constraints, a practical rule consistent with structured indicator guidance [18,20,25] is: (P1) align indicators to the primary objective and statutory/regulatory endpoints first; (P2) add the minimum set of co-benefit/trade-off indicators needed to address foreseeable distributional or ecological risks (Section 5); (P3) reserve exploratory indicators for learning where budget allows, rather than collapsing monitoring into convenient proxies (e.g., canopy cover alone) when the decision hinges on exposure or risk [10,25].

4. Effectiveness: What the Evidence Generally Supports (and Where It Is Weak)

The NBS evidence base is broad but uneven. Across studies, effectiveness tends to be context-dependent and strongly influenced by design, scale, and maintenance.

4.1. Water Quality and Pollution Control

Across the literature, riparian buffers, wetlands, and green stormwater infrastructure are frequently associated with reductions in nutrient and sediment loads through filtration, settling, and biogeochemical processing [26,27]. Reported performance varies substantially with hydraulic loading, soil saturation, antecedent conditions, and pollutant type; importantly, some systems can export nutrients under certain conditions [26]. Interpretation of effectiveness is constrained by inconsistent pollutant metrics (particularly concentration-based reporting rather than loads), limited long-term datasets, and weak attribution when multiple interventions co-occur within the same catchment or urban drainage system [1,6,26].

4.2. Flood Risk, Stormwater, and Flow Regulation

Urban green infrastructure is commonly reported to reduce runoff volumes and delay peak flows for frequent events, although extreme events may overwhelm capacity depending on design and antecedent conditions. At the site scale, interventions such as bioretention systems, swales, permeable pavements, and detention basins can substantially reduce effective imperviousness and attenuate flows, particularly when soils are permeable, maintenance is adequate, and designs account for local rainfall intensity–duration–frequency relationships [10,26,28,29,30,31]. However, performance tends to be event- and context-specific: storage elements can saturate during prolonged storms, pollutant build-up and clogging can reduce infiltration over time, and retrofitting constraints in dense urban fabrics can limit feasible scale of deployment.

At larger scales, catchment-level flood outcomes typically require sufficient areal extent, appropriate siting, and coordination across sub-catchments; localized interventions do not necessarily translate to downstream flood reduction without integrated planning. Portfolio-based analyses of NBS and green infrastructure therefore emphasize strategic placement (e.g., focusing on headwaters, key flow paths, or high-contributing sub-catchments) and the need to integrate NBS with grey infrastructure capacity upgrades, rather than assuming that dispersed small-scale measures will automatically deliver system-wide risk reduction [1,6,7]. For fluvial and coastal flooding, protection and restoration of wetlands, floodplains, dunes, and mangroves can reduce peak flows and wave heights, but effects depend on geomorphic setting, sediment supply, and the degree of disconnection created by historical engineering [2,6,11,12,32].

A persistent limitation is the scale mismatch between plot- or site-level measurements and catchment- or shoreline-scale risk objectives, compounded by limited use of counterfactual designs that would support stronger causal inference. Many evaluations report hydrologic metrics (e.g., runoff coefficients, peak discharge at a single outfall) without linking them to risk-relevant indicators such as inundation extent, depth–duration–frequency, or damages avoided. There is also limited comparative work that quantitatively assesses how NBS-based strategies perform against purely grey or hybrid options under a range of scenarios, including compound events (e.g., pluvial–fluvial or fluvial–coastal interactions) [1,6]. Strengthening this evidence base requires longer-term monitoring, explicit articulation of design return periods, and integration of NBS performance into flood risk models used for planning and investment decisions.

4.3. Heat Reduction and Microclimate Regulation

Urban tree canopy and green spaces are widely associated with reductions in surface and near-surface air temperatures through shading and evapotranspiration, although effect sizes vary by intervention type and context [28]. Empirical syntheses report wide ranges across studies and metrics (for example, air-temperature differences of roughly a few degrees Celsius between vegetated and built settings are commonly reported under favorable summer daytime conditions, alongside smaller or inconsistent effects at night or at regional scales), but headline numbers are sensitive to season, weather, canopy maturity, and sensor placement [28,33]. The magnitude and persistence of benefits vary with canopy structure, irrigation and soil moisture, background climate, surrounding urban form, and nighttime conditions [28,33,34,35]. Evidence comparability is limited by short study durations, inconsistent measurement protocols (including differences in sensor placement and timing), and limited integration with human exposure and health-relevant metrics [28,34,35].

4.4. Biodiversity and Ecosystem Condition

Habitat restoration and connectivity interventions are generally reported to support biodiversity outcomes, although responses depend on baseline degradation, landscape context (including surrounding land uses and deforestation pressures), invasive species pressures, and ecological time lags. Restoration of riparian zones, wetlands, dunes, and forests can increase habitat area and structural complexity, support recolonization, and improve connectivity between remnant patches, with benefits for a range of taxa from plants and invertebrates to birds and mammals [2,6,18,36,37,38,39]. In agricultural landscapes, measures such as woodland islets, hedgerows, riparian buffers, and agroforestry can also reconnect habitats and support species conservation while maintaining farming functions [37,38,39]. However, the magnitude and trajectory of responses differ strongly among ecosystems and species groups, and many studies show that biodiversity outcomes lag behind hydrologic or microclimate responses by years to decades.

Time lags and historical legacies have important implications for monitoring and expectations. In highly degraded landscapes, restored habitats may initially be dominated by generalist or pioneer species, with more sensitive or specialist taxa responding only once key structural attributes and landscape context improve (e.g., larger patch size, corridor development, or reduced edge contrast) [1,2,36]. Conversely, some interventions can inadvertently simplify habitat structure (e.g., using a narrow palette of fast-growing species) or facilitate invasive species if disturbance regimes and propagule pressure are not accounted for, resulting in biodiversity outcomes that are weaker or even negative relative to expectations. Invasion risk is not merely a “side issue” for NBS: disturbed soils, planting stock, and novel corridors can increase propagule pressure; climate-driven range shifts can increase exposure; and poorly specified maintenance (or absent biosecurity protocols) can allow invasive dominants to outcompete planted natives, undermining both biodiversity and service objectives [1,6,38]. Managing these risks requires explicit monitoring of non-native cover, early detection/rapid response where feasible, and design choices that reduce reliance on a narrow genotype or species palette without matching site context [2,6,38]. These dynamics reinforce the need to treat biodiversity responses as part of a long-term trajectory rather than a short-term output.

Integrating ecological time lags into evaluation design. Because biodiversity responses can lag hydrologic or microclimate responses by years to decades, M&E plans should specify minimum monitoring horizons by objective (e.g., establishment versus functional maturity), pre-specify how null/negative trajectories will be interpreted, and pair short-term process indicators with longer-term outcome indicators where policy cycles otherwise truncate learning [37,38,40]. This is the operational bridge between Section 4.4 and the evaluation-design guidance in Section 6.

The evidence base for biodiversity and ecosystem condition in NBS is constrained by overreliance on a limited set of taxa (often birds or charismatic groups), insufficient baseline ecological surveys, and underreporting of negative or null outcomes. There is also limited uptake of standardized biodiversity indicators that could support cross-site comparison and integration with broader monitoring frameworks such as essential biodiversity variables [36,41]. Emerging opportunities include the use of remote sensing to track habitat extent, fragmentation, and some functional attributes at scale [41], coupled with targeted field surveys and community-based monitoring to capture taxon-specific and culturally important biodiversity values. Together, these approaches can make biodiversity outcomes more visible in environmental management decisions and improve understanding of the conditions under which NBS deliver durable ecological gains.

Effectiveness findings in Section 4 are intentionally paired with Section 5 because distributional and equity-related trade-offs (who gains cooling, flood safety, or amenity; who bears costs of land conversion, restrictions, or maintenance) often determine whether biophysically plausible benefits translate into fair and durable outcomes [10,42,43].

4.5. Carbon and Climate Mitigation (When Relevant)

Forests, wetlands, and coastal “blue carbon” ecosystems can store substantial carbon, although permanence and additionality depend on protection status, disturbance regimes, and leakage [11]. Avoided deforestation and degradation are therefore central to many nature-based climate strategies, alongside restoration and sustainable management. Broader syntheses of land-based mitigation also emphasize that “natural climate solutions” can contribute materially to near-term mitigation portfolios, while varying widely by action type, feasibility constraints, and assumptions [12]. Global-scale portfolio exercises illustrate large theoretical mitigation potential from conservation, restoration, and improved management pathways, coupled with wide uncertainty once economic feasibility, permanence, leakage, and competing land uses are applied [12]. Carbon-focused outcomes can also conflict with other objectives—for example, water availability impacts in some afforestation contexts or biodiversity losses where single-species plantations replace diverse ecosystems—underscoring the need to evaluate multi-objective trade-offs explicitly [1,11,12]. A simple cross-objective trade-off matrix is useful in appraisal: (i) carbon versus water quantity/quality; (ii) carbon versus biodiversity and structural complexity; (iii) fast establishment versus long-term resilience to pests, fire, and climate extremes; (iv) localized sequestration gains versus off-site leakage driven by market responses [1,10,11,12]. Across the carbon-focused literature, mitigation and stock estimates are highly sensitive to methods, baselines, permanence, leakage, feasibility filters, and scenario assumptions; transparent, comparable reporting of uncertainty therefore remains uneven [1,11,12]. Related indicator-framing work underscores why management claims require explicit causal logic from interventions to metrics [24,25].

5. Co-Benefits and Trade-Offs: What Is Reported and What Is Missed

5.1. Co-Benefits Commonly Claimed

Co-benefits are often described across social/health, economic, and ecological domains, but the depth and consistency of measurement vary widely across studies [1,2,6,7,10]. A useful organizing frame for co-benefits in environmental management is the ecosystem services lens, which clarifies how changes in ecosystem structure and function translate into outcomes valued by people [2,22,23]. For measurement design, the ecosystem-service “cascade” (biophysical structure/function → service potential → realized use/benefits → value) and related indicator grammars help separate measurable ecological change from claimed welfare outcomes, and they align naturally with the intervention–pathway–endpoint typology in Section 3 [22,23,25]. In practice, NBS co-benefits frequently span multiple services simultaneously, which is a core part of their appeal but also a driver of evaluation complexity and attribution challenges [1,6,10].

Social and health co-benefits are among the most frequently cited, especially in urban settings. They commonly include improved thermal comfort, reduced stress, enhanced mental well-being, increased opportunities for physical activity, recreation, and social interaction, and improved neighborhood aesthetics. These pathways and outcomes are supported by substantial, though heterogeneous, evidence on “nature contact” and greenspace exposure and health outcomes, including synthesis work that highlights plausible mechanisms (e.g., stress reduction, physical activity, social cohesion, heat and air quality pathways) and mixed strength of evidence across endpoints [34,35,44,45,46]. Yet many NBS evaluations refer to these co-benefits qualitatively or infer them from proxy indicators (e.g., increased tree cover) rather than measuring changes in exposure, behavior, or health outcomes directly. Because access to greenspace and exposure opportunities are often unequally distributed, co-benefits are frequently discussed alongside questions of environmental justice, planning priorities, and the risk that greening can unintentionally reinforce inequities if distributional outcomes are not explicitly managed [10,42,43,47].

Economic co-benefits are often framed as avoided damages, avoided treatment costs, or avoided expenditures on conventional infrastructure, alongside potential employment in restoration, maintenance, and stewardship. However, economic claims are frequently asserted without transparent accounting assumptions or without long-term cost and performance data. This is one reason the literature increasingly calls for consistent approaches to valuing co-benefits and costs that are tied to specific outcomes and decision contexts, rather than generic claims that NBS are “cost-effective” [1,6,10]. Ecological co-benefits include habitat provision, improved connectivity, water quality improvements, and enhanced soil condition; these benefits may be central to management objectives (e.g., biodiversity) or may be necessary enabling conditions for service delivery over time [2,6,18,36]. Across domains, what is most often “missed” are co-benefits that accrue to marginalized groups, to future time periods, or to non-market values, which are rarely captured in routine project appraisal.

5.2. Trade-Offs and Unintended Impacts

Environmental management decisions require explicit consideration of trade-offs, because NBS can redistribute risks and benefits across space, time, and social groups. A recurring concern is distributional inequity, where benefits are captured by some groups while costs (e.g., land set-asides, use restrictions, maintenance burdens) fall on others. In cities, the “greening paradox” is well documented: new or improved green amenities may improve health and environmental conditions while simultaneously increasing neighborhood desirability, contributing to rent increases and displacement pressures unless housing and land policies are addressed in parallel [10,42,43]. Beyond displacement, inequities can also appear through uneven access (who can safely use a park, who benefits from cooling), uneven participation in planning, and uneven exposure to short-term construction impacts or maintenance burdens [6,10].

Trade-offs also arise across objectives. Some interventions prioritize one outcome at the expense of others (e.g., maximizing carbon sequestration without attention to biodiversity or water impacts), and outcomes can differ across time horizons (e.g., short-term disturbance during restoration followed by longer-term gains) [1,11,12]. Opportunity costs can be substantial where land competition with agriculture, housing, or industry is strong, and may be borne by groups with limited decision power. In addition, governance and financing limitations can create “performance trade-offs,” where designs optimized on paper degrade in practice due to underfunded maintenance, unclear responsibility allocation, or institutional fragmentation [1,6,10]. Ecological risks include invasive species, altered disturbance regimes (including fire), unintended hydrologic changes, and water consumption impacts in some revegetation strategies [1,2]. Many of these risks are underreported, in part because monitoring focuses on intended outcomes and in part because negative results can be difficult to publish, which skews the visible evidence base toward success stories.

5.3. Measuring Co-Benefits Credibly

Co-benefits are often discussed qualitatively rather than measured with consistent indicators, and studies frequently emphasize outputs (e.g., area planted, number of trees) rather than outcomes (e.g., temperature exposure reductions or health endpoints). Stronger practice begins with explicit causal pathways (a theory of change) that connect the intervention to expected intermediate changes and final outcomes, including the plausible time lags. This supports indicator selection that is decision-relevant and reduces post hoc “cherry-picking” of favorable outcomes [6,10,20,48]. Mixed-methods evaluation is often required because many co-benefits are partly biophysical and partly social (e.g., perceived safety influences park use; governance influences maintenance and thus performance). Equity-sensitive measurement requires disaggregated reporting that clarifies who benefits, who bears costs, and who participates in decisions, and it should include indicators that are meaningful for vulnerable groups rather than relying only on average effects [10,42,43].

Critical evaluation of proxies. Proxies are defensible when they are tied to a clear mechanism and validated against outcome metrics, but risky when treated as outcomes by default. Common pitfalls include: (i) equating vegetation area or NDVI with human heat exposure without time-of-day, accessibility, and vulnerability context [10,28]; (ii) equating habitat extent with biodiversity outcomes without taxon-appropriate sampling and lag-aware horizons [36,37,41]; (iii) equating carbon stocks with climate benefits without permanence, leakage, and additionality logic [1,11,12]; and (iv) reporting economic “savings” without transparent counterfactual infrastructure performance and maintenance cost boundaries [1,6,10]. Where proxies are used for tractability, studies should report the assumed causal chain and the expected sign/magnitude relationship and should plan spot-checks against more direct measurements when stakes are high [24,25].

Where economic co-benefits are claimed, credible reporting requires transparent assumptions and consistent cost boundaries, including long-term maintenance and replacement. More broadly, the conservation and environmental policy literature has repeatedly emphasized that investments should be evaluated empirically rather than assumed effective, particularly when resources are scarce and opportunity costs are high [49]. This implies a need for longitudinal data that links NBS to changes in avoided damages, service reliability, and co-benefits, rather than one-off cost comparisons. Finally, co-benefit measurement and synthesis depend on transparent data practices. Where ethical and feasible, sharing metadata and indicator definitions in reusable formats improves comparability and cumulative learning; aligning with FAIR principles can support data reuse across sites and programs and facilitate future meta-analyses and evidence maps [50]. Emerging digital and AI-enabled tools for data integration and visualization can help, but their value ultimately depends on whether the underlying indicators are robust, relevant, and collected with sufficient attention to context and equity.

6. Monitoring and Evaluation (M&E): From Project Reporting to Credible Evidence

6.1. Common Weaknesses in Current Monitoring

Common weaknesses include missing or inadequate baseline data, absence of counterfactuals (or inappropriate comparators), and monitoring periods that are too short relative to ecological response times. Baseline limitations are particularly damaging for NBS because many expected benefits are incremental and context-dependent; without an adequate “before” picture and a defensible comparison, attribution becomes speculative [1,49]. Across projects, indicator inconsistency limits synthesis and comparative learning, and outputs (e.g., “trees planted” or hectares restored) are sometimes reported as if they were outcomes, without corresponding evidence on risk reduction, ecosystem condition, or social benefits. Transparency issues also recur, including limited uncertainty reporting, incomplete documentation of missing data practices, and limited reporting of maintenance actions even though maintenance is often a primary determinant of long-term performance [6,18,50]. Where indicators are bundled into dashboards or scorecards, explicit causal framing reduces the risk that correlated metrics are misread as outcomes [24,25].

Another recurring weakness is the mismatch between what is easy to measure and what decision-makers need to know. For example, canopy cover is easy to measure, but the decision question may be heat exposure reduction for vulnerable populations, which requires different metrics and contextual information (e.g., timing, accessibility, social vulnerability). Similarly, simple flow or water quality metrics may not align with regulatory endpoints or damage functions that matter for investment decisions. Recent NbS monitoring discussions therefore emphasize structured indicator selection processes that start with the management objective, define assessment targets, and then select feasible indicators that preserve interpretability and comparability across projects [6,10,18,25]. In practice, this often requires co-design with end users (e.g., regulators, utilities, communities) to ensure that monitoring focuses on questions they actually need answered, rather than on what is most convenient to measure.

Resourcing and institutional capacity are cross-cutting constraints. Many NBS projects have limited budgets and short funding cycles, leading to minimal baseline data collection and early termination of monitoring just as slower variables (e.g., vegetation establishment, soil development, biodiversity) begin to change. Responsibilities for monitoring can also be fragmented across agencies or contractors, with no single actor accountable for integrating data or reporting outcomes consistently. These institutional factors help explain why even high-profile NBS programs may have impressive portfolios of projects but relatively weak evidence on long-term performance.

6.2. Recommended Evaluation Designs (Choose Based on Feasibility)

Evaluation design should be matched to feasibility and decision stakes. Before–After designs can be practical when only one site is feasible to monitor, but they are weak for attribution when background trends are strong or when other interventions occur concurrently. Before–After–Control–Impact (BACI) designs strengthen causal inference when comparable controls exist; the broader “beyond BACI” literature also emphasizes the importance of sampling design (e.g., multiple control and impact sites, sufficient temporal replication) for distinguishing impact signals from natural temporal variability [40]. Even approximate controls can substantially improve interpretability relative to simple before–after comparisons.

In multi-site urban programs, matched comparisons or synthetic controls can improve attribution when randomization is infeasible; synthetic control methods are one well-established approach for comparative case studies when only a small number of treated units exist [51]. Matching approaches can also be used to compare NBS and non-NBS sites or catchments with similar baseline characteristics, providing more credible estimates of added value. Time-series and interrupted time-series approaches are valuable where long historical monitoring exists, enabling detection of changes in level or trend after NBS implementation relative to expected patterns. For some endpoints (e.g., flood peaks, extreme temperatures), long records and attention to climate variability and change are essential for robust inference.

For complex governance settings and multi-intervention programs, mixed-methods contribution analysis can complement quantitative endpoints by clarifying plausible causal pathways and assessing the relative contribution of NBS compared with other factors [1,6]. In such contexts, combining quantitative monitoring with qualitative evidence (e.g., stakeholder interviews, process tracing, document analysis) can provide a more realistic picture of how NBS contribute to observed outcomes and why some interventions succeed or fail. Importantly, evaluation designs should be planned alongside project design rather than retrofitted after implementation, so that baselines, controls, and sampling strategies are in place from the outset.

6.3. Minimum Monitoring Indicator Set (Proposed)

A practical minimum indicator set for environmental management reporting should span intervention condition, environmental performance, service/risk outcomes, co-benefits and equity, and transparency. This approach is consistent with the growing push for standardized criteria and indicators for designing and verifying NbS, including those articulated in the IUCN Global Standard for Nature-based Solutions [18]. Intervention condition indicators establish whether the NBS remains functional over time (e.g., area/extent, vegetation cover, survival/health metrics, maintenance actions, and connectivity/fragmentation measures). Environmental performance indicators should be tailored to objectives and include hydrology (runoff volume, peak flow timing, infiltration or water table indicators as relevant), water quality (preferably nutrient and sediment loads rather than concentrations alone, plus turbidity and relevant contaminants), temperature (surface temperature and near-surface air temperature measured at standardized times), and biodiversity/ecosystem condition (a habitat quality index and selected indicator taxa).

Service and risk outcomes should translate endpoints into management-relevant metrics, such as flood/erosion risk proxies or modeled risk (with transparent assumptions), thermal exposure metrics for people where urban heat is a goal, and avoided damages or cost estimates reported with uncertainty ranges. For many decision contexts (e.g., regulatory compliance, infrastructure planning, climate adaptation finance), such “translation” is essential for NBS to be considered alongside conventional investments. Co-benefits and equity indicators should capture access and use (counts and surveys), perceived benefits, participation quality, distributional indicators (disaggregated where possible by income, gender, age, or other relevant axes), and screening for displacement or livelihood risk in relevant urban and rural contexts [10,42,43]. Finally, transparency indicators should include a clear data availability statement, metadata, QA/QC protocols, and uncertainty reporting to support credibility and reuse, aligned with FAIR data principles where feasible [50].

In practice, a minimum indicator set should be seen as a floor, not a ceiling: it defines what is needed for basic accountability and comparability, but additional indicators may be warranted for specific projects or research questions. It is also important to keep indicator sets realistic relative to capacity; overly ambitious designs that cannot be maintained may be less useful than a smaller number of well-chosen indicators measured consistently over time.

Illustrative Monitoring Horizons and “Threshold Thinking” (Context-Dependent, Not Universal Standards)

NBS monitoring rarely supports one-size-fits-all numeric thresholds across climates, institutions, and objectives; thresholds in practice are typically standards set by regulation, design criteria (e.g., return-period performance targets), or locally negotiated performance bands. Still, environmental management benefits from making expectations explicit. Illustratively: (i) for urban heat, programs often pair standardized summertime temperature measurement campaigns with exposure-relevant timing (afternoon peaks) and stratification by vulnerable geographies [28,33]; (ii) for stormwater, site-scale practices are commonly evaluated across multiple events and seasons because performance is strongly antecedent-dependent [26,29]; (iii) for biodiversity, multi-year trajectories are typically needed before interpreting species composition outcomes [37,38]. These are not universal pass/fail limits; they are reminders that monitoring duration and event sampling should match the temporal dynamics of the endpoint [37,40].

Worked example (illustrative minimum package). For a city-wide green stormwater retrofit portfolio, a proportionate minimum might include: maintenance logs and visual clogging/infiltration checks (intervention condition); event-scale runoff/peak timing at representative outfalls (performance); one social-access indicator for co-benefit/equity (e.g., disaggregated survey or use counts in high-vulnerability neighborhoods); and a documented QA/QC and data-management plan (transparency) [10,18,20]. Packages should be scaled up when regulatory compliance, insurance, or finance requires stronger causal evidence [18,49].

6.4. Remote Sensing and Digital Monitoring

Remote sensing supports scalable monitoring (canopy cover, land surface temperature, habitat fragmentation, shoreline change), but should be paired with ground truthing where feasible. Remote sensing is also increasingly discussed as a practical pathway to improve biodiversity monitoring and indicator coverage at policy-relevant scales [41]. For decision relevance, monitoring systems should be designed around the intervention’s theory of change and prioritized endpoints, not only what is easiest to measure. Coupling Earth observation data with in situ sensors (e.g., water level and quality loggers, microclimate sensors, camera traps) can provide multi-scale perspectives on NBS performance and enable detection of trends that would be missed by occasional manual sampling.

Digital data platforms and AI-enabled analytics can further enhance M&E if deployed thoughtfully. Centralized or federated databases that store NBS monitoring data with standardized metadata can reduce duplication of effort and support cross-project learning, while dashboards and visualization tools can make results more accessible to practitioners and communities. Machine learning methods can assist with pattern detection and anomaly identification in large monitoring datasets [52], but they should be used to complement—not replace—clear hypotheses, transparent indicator definitions, and sound sampling designs. Ultimately, digital tools and remote sensing will only improve M&E if they are integrated into coherent evaluation frameworks that prioritize decision-relevant questions and maintain strong links between data, analysis, and management action.

7. Implementation-Oriented Framework for Environmental Managers

Translating NBS from policy ambition into reliable environmental management outcomes requires a structured process that connects problem definition, option selection, design, delivery, and learning. Documented implementation shortfalls are not only “technical”: recent governance-oriented syntheses catalog extensive empirical evidence on barriers and enablers (e.g., fragmented mandates, financing gaps, procurement rules favouring grey assets, contested evidence, and weak long-term maintenance accountability), showing that institutional conditions frequently determine whether biophysically plausible designs perform in practice [5]. Many on-the-ground failures therefore stem from unclear objectives, under-specified maintenance and governance, or monitoring that is disconnected from decision points—consistent with broader patterns reported across NbS governance case literature [1,5,6,10]. Implementation frameworks and standards—such as the IUCN Global Standard for NbS and EU-oriented practitioner guidance on NbS design and scaling—stress the need for clear criteria, stakeholder engagement, and explicit consideration of trade-offs at each stage [14,18,19]. Recent reviews of NbS governance further highlight that enablers (e.g., co-design, evidence on performance and co-benefits, dedicated funding) and barriers (e.g., path dependency favouring grey infrastructure, fragmented responsibility, lack of long-term commitment) must be addressed within the management process itself rather than treated as external constraints [5]. This section therefore outlines a concise “NBS environmental management cycle” that managers can use to align planning, delivery, and evaluation.

An “NBS environmental management cycle” is proposed to link decision-making, delivery, and learning. The cycle begins with problem definition, specifying the stressor, risk, and target endpoints, and making explicit what success looks like in measurable terms. In this first step, managers should articulate the baseline (including existing infrastructure and ecosystem condition), relevant scales (site, catchment, neighborhood, coastline), and constraints (regulatory requirements, social acceptability, finance) [1,2,6]. Clear problem framing also requires early attention to equity: who is currently exposed to risk, who stands to benefit, and whose priorities are shaping the definition of “success” [10,42,43]. These choices anchor subsequent design and evaluation decisions.

The second step is options appraisal, comparing NBS, grey, and hybrid options using consistent criteria (effectiveness, cost, feasibility, equity, and co-benefits). Appraisal should explicitly define the counterfactual (what would happen without the intervention or under alternative investments) and the time horizon (short-term performance versus long-term resilience), because these choices strongly shape what “cost-effective” or “effective” means for NBS [1,6,10]. Rather than framing NBS as a separate track, decision processes should consider portfolios that combine ecological and engineered measures, and they should make trade-offs transparent—for example, between up-front capital costs, maintenance burdens, risk reduction, co-benefits, and distributional outcomes. Formal decision-support methods—multi-criteria decision analysis (MCDA), scenario analysis, monetary valuation, and benefit–cost or cost-effectiveness framing—are standard ways to make trade-offs explicit when no single alternative dominates across objectives [15,53]. These tools do not remove uncertainty, but they clarify criteria weights, performance scoring logic, and sensitivity to assumptions; for NbS portfolios they should be anchored in the indicator and uncertainty issues summarized in Section 3 and Section 6 rather than treating proxies as outcomes [10,20,25]. Tools such as multi-criteria analysis and scenario modelling can help structure these comparisons when evidence is incomplete or heterogeneous. Urban climate adaptation and green-infrastructure planning studies similarly emphasize integrating biophysical performance, feasibility, and spatial planning criteria when comparing portfolios of measures [54].

The third step is design for outcomes. Here, siting and scale are matched to pathways and endpoints, maintenance is planned and costed, governance roles are assigned, and monitoring is designed before implementation begins. This is closely aligned with guidance that frames NbS design and scaling around clear criteria and indicators and requires explicit consideration of trade-offs and stakeholder needs [1,6,14,18,20]. Practically, this means: (i) using the typology in Section 3 to identify mechanisms and endpoints; (ii) co-designing interventions with affected communities and operational staff to ensure feasibility and acceptance; (iii) embedding minimum indicator sets and evaluation designs from Section 6 into project plans and contracts; and (iv) building in triggers for adaptive management if performance falls below agreed thresholds. Experience from NbS implementation frameworks emphasizes that co-benefits and costs are produced throughout the project life cycle (problem definition, selection, design, implementation, monitoring) and therefore require ongoing engagement and communication rather than a one-time consultation [10].

The fourth step is delivery and maintenance, treating maintenance as part of the intervention rather than an afterthought. In environmental management terms, this implies specifying responsibility (who maintains), resourcing (how maintenance is financed), and performance thresholds (what triggers adaptive action), and it may require new institutional arrangements when NBS cross traditional sectoral boundaries (e.g., water utilities, parks departments, housing authorities) [6,10]. The final step is monitoring, evaluation, and adaptation, using results for adaptive management and publishing learnings to reduce future uncertainty. Feedback loops should connect monitoring data back to operations (e.g., adjusting maintenance regimes), planning (e.g., revising design standards), and finance (e.g., demonstrating performance to funders or regulators). A key implication is that NBS programs should not only “build projects” but also build evaluation and learning capacity. Across conservation and environmental policy, the need for empirical evaluation of investments is repeatedly emphasized, and the same logic applies to NBS: without credible evaluation, scaling risks repeating ineffective designs and misallocating scarce resources [1,49]. Where data sharing is possible, making monitoring outputs and metadata reusable supports cross-site synthesis and reduces duplication, consistent with FAIR principles [50].

8. Discussion and Future Research Agenda

Taken together, the evidence reviewed in this article suggests that NBS can make meaningful contributions to multiple environmental management objectives, but that performance is highly contingent on context, design, and governance. Effectiveness is clearest and most consistent where mechanisms are well understood and relatively proximal to the intervention (e.g., local runoff reduction, shading and evapotranspiration, habitat provision), and weakest where outcomes depend on large-scale coordination, long time horizons, or complex socio-political dynamics (e.g., catchment-scale flood risk, long-term biodiversity and species conservation outcomes under land-use change, or distributional equity in climate adaptation) [1,2,6,7,10,11,12]. Across domains, weak counterfactuals, short monitoring periods, and inconsistent indicators limit the strength of inference and complicate comparative assessment. In addition, the geographic distribution of evidence is uneven: many studies and syntheses are biased toward Europe and North America, whereas climate vulnerability, deforestation pressures, and implementation needs are often highest in the Global South, where fewer peer-reviewed evaluations are available [3,11,12]. Cost-effectiveness and benefit–cost comparisons of NBS versus grey or hybrid options remain scarce, and few studies report long-term maintenance costs or life-cycle performance, which are critical for investment decisions [1,5,49].

The review also underscores that NBSs are not a panacea. Trade-offs and unintended impacts occur when interventions are poorly sited, under-maintained, or implemented without attention to distributional outcomes and local governance capacity. In some cases, NBS may underperform relative to expectations or shift risks spatially or socially (e.g., flood risk shifting downstream, green gentrification pressures, or ecological simplification) [1,6,10,42,43]. For environmental managers, this implies that NBS should be framed as one set of options within a broader portfolio that includes grey and hybrid solutions, and that rigorous evaluation and adaptive management are essential to avoid over-claiming benefits.

Future work should prioritize standardization through shared indicator definitions and reporting templates for NBS outcomes and co-benefits. The rapid growth of NBS in policy and practice has outpaced comparable evidence, and the absence of harmonized endpoints makes it difficult to generalize “what works” across settings or to build cumulative learning across projects [1,7]. A practical starting point is to align monitoring and reporting with established criteria and indicators for NBS quality and effectiveness (e.g., the IUCN Global Standard) and to make indicator selection explicit to the management objective being targeted [10,21]. For biodiversity-related outcomes, further alignment with widely discussed biodiversity monitoring frameworks (e.g., essential biodiversity variables) can improve comparability between project-scale monitoring and national or global reporting needs [36].

Stronger causal evidence is needed via broader use of BACI, time-series, and quasi-experimental designs, alongside publication of null and negative findings. In particular, the “beyond BACI” literature emphasizes that designs must anticipate temporal variability and select sampling structures that can reliably detect changes attributable to interventions rather than background variation [40]. Where NBS are deployed as portfolios (e.g., multi-site green infrastructure programs), evaluation approaches that combine site-level monitoring with program-level counterfactuals (including matched comparisons and synthetic controls) deserve further development and testing, especially for outcomes expected to emerge only at larger scales or over longer time horizons [51].

Monitoring time horizons should be extended to capture ecological lags, maturation effects, and the consequences of maintenance decisions. Many NBS benefits are front-loaded in communication but time-delayed in reality (e.g., vegetation establishment, soil development, habitat recovery), and the durability of outcomes often depends on routine maintenance and governance capacity [1]. Research that explicitly compares short-term versus long-term performance, including failure modes and degradation pathways, would improve risk management and life-cycle planning.

Equity, justice, and governance require deeper empirical attention. Research should move beyond the general claim that co-benefits exist to explicitly evaluate who benefits, who bears costs, and how distributional outcomes evolve through time and across neighborhoods, land tenures, and institutional arrangements [42,43]. In urban settings, a key priority is integrating displacement-risk analysis and housing/land policy considerations into NBS planning and evaluation, rather than treating “green gentrification” as an externality that sits outside environmental management [42,43]. In rural and coastal settings, priorities include the politics of land access, benefit-sharing, and the legitimacy of decision-making processes when interventions affect livelihoods or customary uses.

Comparative effectiveness should move from “NBS versus grey” narratives to transparent, decision-grade comparisons among NBS, grey, and hybrid systems using consistent risk, performance, and life-cycle metrics. This includes clearer articulation of the counterfactual (what would happen without the intervention), explicit treatment of uncertainty, and attention to compound objectives and trade-offs (e.g., flood mitigation, water quality, biodiversity, and social benefits) [6]. Comparative studies should also test transferability: which design features and governance conditions are portable across contexts, and which are not.

Remote sensing and digital monitoring offer opportunities to address scaling constraints, but research should focus on validated indicator pipelines rather than technology adoption alone. Priorities include linking remotely sensed variables to management-relevant endpoints, improving ground-truth strategies, and designing monitoring systems that can support both adaptive management and policy reporting [41]. Where biodiversity is a stated goal, integrating remote sensing with biodiversity monitoring frameworks can support multi-scale inference and reduce duplication of effort [36,41].

New analytical approaches, including advances in machine learning and artificial intelligence, could substantially strengthen NBS evidence and design when coupled with robust data and clear questions. For example, AI methods are increasingly used to process high-volume remote sensing and sensor data, detect spatial and temporal patterns in ecosystem condition, and identify candidate relationships between interventions and outcomes that can then be tested with more targeted field studies and causal designs [52]. Similarly, optimization and decision-support algorithms can help explore large design spaces for NBS portfolios (e.g., siting, configuration, and combinations with grey infrastructure) under multiple objectives and constraints, supporting more transparent trade-off analysis for planners and engineers.

AI and related digital tools may also accelerate evidence synthesis and learning if used carefully. Natural language processing and related text-mining approaches have been widely discussed as aids to literature identification and screening in systematic-style evidence syntheses [55]. Machine-learning methods can help process large Earth-observation and sensor archives and surface patterns for follow-up testing [52]. Interactive dashboards and knowledge platforms can make monitoring data and evaluation results more accessible to practitioners; integrated modelling environments (sometimes described as “digital twins” in urban and infrastructure planning) are increasingly used to explore scenario futures under climate, land-use, or demographic change [56]. These opportunities reinforce the need for high-quality, interoperable data and transparent documentation of methods, because AI models will only be as reliable and equitable as the data and assumptions on which they are trained.

As an example of emerging, practice-oriented tools, UNEP has released Environment-GPT (public beta) to support access to a curated library of UNEP and selected partner publications with cited responses, which may help improve the accessibility and transparency of environmental evidence used in planning and evaluation [57].

This review itself has limitations. It is narrative rather than systematic, focuses on English-language, peer-reviewed sources, and emphasizes cross-cutting themes rather than exhaustive coverage of every intervention type or region. As a result, some sector- or context-specific evidence, gray literature, and local knowledge are under-represented. The agenda outlined above should therefore be read as a set of priorities emerging from the published research base, to be complemented by place-based consultation and ongoing learning as NBSs are implemented in diverse environmental management settings.

Finally, transparency and reproducibility should be strengthened through open science practices. For evidence syntheses, search strategies should be reported clearly enough to enable updating and verification by other researchers. For primary NBS evaluations, data and metadata should be shared where ethical and feasible, aligned with FAIR principles, enabling cross-site synthesis and the development of future meta-analyses and evidence maps [50]. At minimum, studies should report the indicators used, sampling designs, baselines, monitoring duration, and uncertainty in a consistent and machine-readable manner to support cumulative learning.

9. Conclusions

NBSs offer substantial promise for environmental management, but this review shows that their effectiveness is highly context-dependent and still difficult to compare across settings due to inconsistent endpoints, heterogeneous designs, and weak evaluation practices. Evidence is strongest for relatively proximal mechanisms such as local runoff reduction, microclimate regulation, and habitat provision, and more fragile where outcomes depend on large-scale coordination, long time horizons, or complex socio-political dynamics, such as catchment-scale flood risk reduction, long-term biodiversity recovery, or distributional equity [1,2,6,7,10]. Co-benefits are central to NBS value propositions yet are frequently undermeasured or inferred indirectly, while trade-offs and unintended impacts, especially those related to equity, governance, and ecological risks remain underreported relative to their importance for real-world decisions.

Taken as a structured synthesis, the argument of this review proceeds along the three review questions in Section 1.1: effectiveness patterns (Section 4), co-benefits/trade-offs/equity (Section 5), and M&E and evaluation design (Section 6), held together by the intervention–pathway–endpoint typology and prioritization rules (Section 3.4) and translated into an implementation cycle (Section 7).

To address these gaps, the review has proposed an implementation-oriented typology that links NBS categories to pathways and decision-relevant endpoints; highlighted common strengths and weaknesses in the evidence base for effectiveness across key objectives; synthesized what is known and often missed about co-benefits, trade-offs, and equity; and outlined a pragmatic approach to monitoring and evaluation, including a minimum indicator set and feasible evaluation designs. Together with the NBS environmental management cycle in Section 7, these elements are intended to help managers and policy-makers move from aspirational narratives about NBS to more transparent, comparable, and accountable environmental management practices. In practical terms, this means integrating NBS into option appraisal on equal footing with grey and hybrid alternatives, designing interventions around clearly articulated mechanisms and endpoints, and resourcing long-term monitoring and maintenance as core components of NBS programs rather than optional extras.

Looking ahead, the most urgent priorities are to strengthen causal evidence through better-designed evaluations, extend monitoring horizons to capture slow ecological and social dynamics, and embed equity and governance considerations at the heart of NBS planning and assessment. Advances in Earth observation, interoperable environmental data, and machine-learning-supported analytics can scale up monitoring and synthesis, provided analyses remain anchored in clear indicators, uncertainty reporting, and open science practices [41,50,52]. Broader planning syntheses continue to highlight the role of NBS in climate adaptation portfolios [58], links among biodiversity, ecosystem services, and human well-being for setting objectives [59], ecosystem-service valuation logics in urban contexts [15], mapped evidence patterns for adaptation effectiveness [3], and governance constraints on implementation [5]. By combining careful design, credible evidence, and sustained attention to who benefits and who bears costs, NBS can evolve from a broadly appealing concept into a reliable, adaptable component of environmental management portfolios under accelerating global change.