1. Introduction

Throughout the world, gravitational natural hazards pose risks to residential areas and infrastructures in mountainous, but also in other relief-rich areas. Such hazards include landslides, snow avalanches, but also channel processes including debris flows, bank erosion and flash floods. To protect against those hazards, nature-based solutions are increasingly used in addition to, or as replacement of, more classical engineered structures, often referred to as grey infrastructure (Getzner et al., 2017).

At present a vast amount of studies on nature-based solutions for mitigating natural hazards and the resulting risk reduction exists. These cover effects of protection forests, increasingly called protective forests (to avoid confusion with forest protection), green infrastructure (GI) and various types of ecological (eco-) or biological (bio-) engineering (Gray and Sotir, 1996, Bischetti et al., 2014, De Jesús Arce Mojica et al., 2019). In international policy jargon these nature-based solutions are often summarised under ecosystem-based disaster risk reduction (DRR), or in short: Eco-DRR (Onuma and Tsuge, 2018, McVittie et al., 2018, Estrella and Saalismaa, 2013). To demonstrate the efficacy and benefit of Eco-DRR measures, existing studies provide, in decreasing order (1) process evidence based on empirical data, experiments and modelling; (2) qualitative assessments and literature reviews; (3) economic evaluations including cost-benefit analysis; and (4) specific risk-based studies on avoided damage as as basis for calculating net-benefits.

Currently, standards for the implementation of Eco-DRR are generally lacking and, additionally, problems of land ownership and property rights arise in many cases (Klein et al., 2019). In addition to solving these mentioned problems, we believe that quantitative data on the effect as well as on the benefits or better the return of investment (ROI) of measures are prerequisite in order to ensure that Eco-DRR measures move from single case studies to an implementation at scale. Some studies (e.g., McVittie et al., 2018) mentioned that the co-benefits of Eco-DRR measures are the most convincing for their implementation. We underline and recognize that the co-benefits are a very important advantage of Eco-DRR measures in comparison to gray infrastructure. However, we argue that without sound quantified evidence of the net benefit of the specific protective function the measure fulfills, financial and organisational resources required for ensuring the durability and implementation at scale of Eco-DRR measures remain problematic.

In this review, we summarise existing studies that demonstrate the efficacy and benefit of Eco-DRR measures against gravitational natural hazards in mountains with the aim to propose a framework for providing quantitative evidence of natural hazard risk reduction provided by Eco-DRR in mountains.

2. Short overview of Eco-DRR solutions for different types of mountain hazards

Eco-DRR measures in mountains protect mainly from gravitational hazards, which refer to the downslope transport of surface material consisting of different mixtures of rock, soil and water under the force of gravity (McGillivray, 2011). In this paper, we also treat floods as a gravitional hazard, which are often classified as a climatic / meteorological hazard (UNDRR, 2016) since they result from extreme weather conditions. Often used Eco-DRR measures include different types of vegetation cover, ranging from forests to shrubs and grasses, river and channel widening for water and sediment retention and flood bypasses.

Forests covering steep slopes can directly protect against snow avalanche (Poratelli et al., 2020, Teich et al., 2012) and shallow landslide release (Goetz et al., 2015, Cohen and Schwarz, 2017), the impact of falling rocks (Dorren et al., 2005), bank and surface erosion (Porto et al., 2009, Borrelli et al., 2014, Gasser et al., 2019) and indirectly against debris flows (Brardinoni et al., 2003, De Graff et al., 2012, Sebald et al., 2019) and floods (Robinson et al., 2003, Sakals et al., 2006, Sebald et al., 2019). With regards to snow avalanches, forests reduce the probability of snow avalanche release significantly when compared to open land. The snow cover in forests is generally less thick, more variable in its structure and less influenced by wind compared to open land (Varhola et al., 2010). Also shallow landslide release is reduced by forests, mainly due to reinforcement effects of tree roots (Bischetti et al., 2009, Schwarz et al., 2015, Giadrossich et al., 2019, Ji et al., 2020), but also due to hydrological effects (Kim et al., 2017). The protective effect of forests against rockfall is linked to the barrier effect of individual trees and the reduction of the energy of falling blocks (Volkwein et al., 2011) and has been quantified in many scientific studies (e.g. Rammer et al., 2015, Moos et al., 2017, Farvacque et al., 2019). Depending on the spatial and temporal distribution of rainfall duration and intensity as well as the size of the watershed, forests can reduce the onset probability as well as the intensity of flood events (Kalantari et al., 2014). This is due to 1) an increased water infiltration into the soil (Neris et al., 2012, Sun et al., 2018), 2) increased water storage capacity in the soil (Liu et al., 2011, Ferreira et al., 2004) and 3) reduced concentration time of the catchment (Jost et al., 2012), because of increased evapotranspiration (Van der Velde et al., 2013), interception of precipitation by leaves (Wahren et al., 2012) and higher porosity of the soil (Beven and Germann, 2013). The key aspects of vegetation leading to a reduction of surface erosion are improved soil structure, improved aggregate stability and fixation of the soil by roots (Stokes et al., 2014). Herbaceous and shrub species contribute to erosion prevention and slope stability by protecting the surface directly from rain splash (Fernández-Raga et al., 2017). In addition, the surface membrane of densely interwoven fine roots and rhizomes help to bind and stiffen the upper soil mantle, which has a constraining influence on mobilisation of shallow landslides masses (Norris et al., 2008, Schwarz et al., 2010).

Other, completely different “nature-based” measures for flood prevention are channel widening (Stoffel et al., 2016) and flood corridors (Klauser et al., 2016). Channel widening refers to removing or relocating flood embankments further from the channel, thereby establishing a part of a valley floor where the river can develop its channel freely (Piégay et al., 2005). This is increasingly applied in mountain areas (Jäggi and Zarn, 1999, Habersack and Piégay, 2008) but because of limiting space, it is not a common as in lowlands. In addition, secondary channels are reconstructed along channelized rivers or reconnected with them (Hornich and Baumann, 2008), resulting in increased channel storage of floodwater and reduced bedshear stress of floodflows. Channel widening measures are often part of river restoration projects, which mainly focus on increasing the ecological integrity of a river (Stoffel et al., 2016). Flood corridors generally make use of lowering sections of flood dykes that are designed to be subject to overflow without breaching. They are built in locations where excess water may be diverted and discharged through corridors with minimal damage. The remaining flood water discharges without damage in the main river channel (Löschner and Nordbeck, 2019). Basically, this concept aims at giving more space for rivers (Zaugg, 2002), similar to the examples in the “Room for the river” project (2006 - 2015) in the Netherlands (Rijke et al., 2012). To implement flood corridors, it is key to adapt spatial planning and account for flood overload to prevent land development in the foreseen runoff corridors over time (Löschner and Nordbeck, 2019).

3. Methods for defining the benefits Eco-DRR

The protection from natural hazards is a so-called regulation function provided by ecosystems and is a “non-market good” as its benefit cannot directly be converted into monetary terms (Freeman et al., 2014). Just like other non-market ecosystem services (ES), such as recreational or cultural services, Eco-DRR contributes to human welfare, but its benefits are often underrated since its total economic value is rarely quantified (Ezebilo, 2016, Costanza et al., 2014). The valuation of the benefits of such ES has increasingly gained attention as it is regarded as prerequisite to avoid information asymmetries when it comes to trade-offs between different ES (Farber et al., 2002).

Several methods have been proposed to value the non-market benefits of ES and have also been applied to Eco-DRR in mountains (cf., e.g. Bianchi et al., 2018). These include:

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  replacement cost method (RCM)

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  hedonic pricing method (HPM)

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  contingent valuation method (CVM)

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  avoided cost method (ACM)

Despite the fact that the benefits of Eco-DRR in mountains are widely recognized, technical standards on the implementation and assessment are missing and studies providing a detailed estimation of the benefits using the above mentioned methods are still limited. In particular, the protective effects of nature-based measures against natural hazard processes are often barely quantified and based on rough estimates or general indicators (e.g. Häyhä et al., 2015, Blattert et al., 2017, Briner et al., 2013, Langner et al., 2017). Another common variant is that the benefit is simply equated to the costs of structural protection measures without quantifying the actual protective effect of the nature-based solution (e.g. Notaro and Paletto, 2012, Poratelli et al., 2020). This could be defined as a simple RCM.

Regarding gravitational hazards in mountains, there are nevertheless a few studies that provided an in-depth quantification of the physical effect of Eco-DRR measures and translated this into an economic value using a risk-based ACM (e.g. Teich and Bebi, 2009, Moos et al., 2018, Farvacque et al., 2019). However, in most cases, such studies quantified the Eco-DRR effect in a static system without taking potential dynamics and uncertainties in the protective effect over time into account (Moos et al., 2019).

4. Framework for providing quantitative evidence

A realistic valuation of the benefits of Eco-DRR measures in mountains is only possible if, firstly, their effects on the natural hazard processes are quantified with sufficient detail (which depends on the scope of the analysis) and finally expressed in monetary terms allowing for a cost-benefit analysis (CBA) and, secondly, possible temporal variations and uncertainties regarding the state and development of the Eco-DRR measure are taken into account. We propose a framework based on a risk-based approach allowing for the translation of the physical, protective effect of a nature-based solution on the natural hazard process into a reduction of the risk of fatalities as well as of property risks (in terms of the avoided costs - AC).

The risk can be interpreted as the expected damage resulting from a natural hazard event and is composed of three factors: the hazard, the exposure and the vulnerability (UNISDR, 2009). The hazard is the probability that a natural process causing damage does indeed occur at a given element at risk. This probability is obtained by multiplying the onset probability of the physical process with its probability of reaching an element at risk (propagation probability) (see Moos et al., 2018). The exposure is defined by the probability of presence of an element at risk (e.g., a car driving over a road) and its (monetary) value. To which degree an element at risk is finally damaged depends on its vulnerability, which is in turn a function of the intensity of the hazardous event (UNISDR, 2009) (See Fig. 1).

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Fig. 1. Illustration of the proposed framework.

As described in Section 2, Eco-DRR measures can influence natural hazard risks in various ways. In the case of shallow landslides or snow avalanches, vegetation is expected to reduce the onset probability and to a smaller extent the propagation probability and intensity of an event. For rockfall, on the other hand, trees hardly change the onset probability of rockfalls, but can decrease their propagation probability and intensity by stopping and decelerating falling blocks (Moos et al., 2017, Dupire et al., 2016). These effects have to be quantified for each of the relevant risk components and, thus, physically-based or empirical hazard models that sufficiently represent the forest effect are required (e.g. Stoffel et al., 2006, Cohen and Schwarz, 2017, Toe et al., 2018). Depending on the natural hazard process, existing models substantially vary regarding their accuracy of representing the effect of trees (e.g. homogeneous vegetation roughness vs. consideration of single trees).

In order to estimate the benefit of an Eco-DRR measure, risk has finally to be calculated for different scenarios with and without Eco-DRR and this for different return periods of the natural hazard to account both for small and frequent as well as big and rare events. In addition, the temporal development of Eco-DRR measures, incl. effects of disturbances and climate change, needs to be accounted for - as was done, for example, by Moos et al. (2021). The difference between the risk with and without Eco-DRR measure are the “average avoided costs” and can be regarded as its benefit. To do so, a basic understanding of the behaviour of the natural hazard process and the physical effect and temporal development of the Eco-DRR measure is prerequisite, as mentioned before.

It can then be compared to the costs potentially associated with the measure in a CBA (Schmidt et al., 2011, Kreibich et al., 2014, Kreibich et al., 2019). The CBA is a common method to evaluate protection measures and allows for the comparison of the economic efficiency of different protection measure scenarios, including “green” and “grey” protective measures and combinations thereof (Onuma and Tsuge, 2018). A protective measure is regarded as efficient if the ratio of benefits to costs is equal or larger than 1 (Gamper et al., 2006). Costs to be considered in CBA, both for Eco-DRR and technical protective measures, include installation and maintenance costs, which are usually less for Eco-DRR measures (cf. Ozment et al., 2019). In particular, technical protective measures might be associated with additional costs to the environment (e.g. landscape deterioration). On the other hand, Eco-DRR often have co-benefits for the society, such as perceived positive landscape effects (e.g., for tourism) or enhanced biodiversity (McVittie et al., 2018, Estrella and Saalismaa, 2013). Furthermore, green and grey protective measures can involve “economic ripple effects”, meaning that they can increase the local income thanks to public investments (Onuma and Tsuge, 2018).

Since the protective effect of an Eco-DRR measure is not constant over time due to natural dynamics (e.g., disturbances) or human interventions (e.g., cutting or planting of trees), benefits and costs of the measure have to be considered in the long-term integrating the associated uncertainties (Moos et al., 2018, Onuma and Tsuge, 2018). Farvacque et al. (2019), for example, demonstrated in a case study, how land-use and land-cover changes influence forest cover and, thus, protection from rockfall risk, using a scenario-based approach. Moos et al. (2019). propose a methodological framework to integrate uncertainties due to disturbances in the economic valuation of the protective effect of forests based on a probabilistic approach. They calculated the Net Present Value (NPV) of a rockfall protection forest considering variations in the protective effect and compare it to the NPV of rockfall nets.

Whether or not an Eco-DRR measure is more efficient compared to a technical protection measure depends mainly on its efficacy in mitigating the hazard, which is again depending on how constant the protective effect is over time, and its cost compared to the cost of the technical measure. Onuma and Tsuge (2018) presented a theoretical approach to evaluate under which condition a GIfor DRR is preferred to a grey infrastructure. They show that GI is particularly preferable when the size of the population exposed to a natural hazard is relatively low, due to the small damage potential. Logically, this however depends on the efficacy of the GI in protecting against the hazard as well as the vulnerability of the affected elements at risk.

5. Conclusions

Although the importance of Eco-DRR, also referred to as nature-based solutions, green infrastructure (GI), ecological (eco-) or biological (bio-) engineered measures, for reducing natural hazard risks in mountains is widely recognised, sound quantified evidence of the net benefit of such measures remain rare. Therefore, there is still a need for realistic valuation of the benefits of Eco-DRR measures in mountains, based on a quantification of the protective effects in detail and expressed in monetary terms which allows for a cost-benefit analysis. Moreover, possible temporal variations and uncertainties regarding the state and development of the nature-based solution need to be taken into account.

A framework based on a risk-based approach allowing for the translation of the physical effect of a nature-based solution on the natural hazard process into a reduction of the risk of human death as well as of property risks can provide the basis for the required quantitative evidence of Eco-DRR in mountains.