1. Please check and comment entries here.
Table of Contents

    Topic review

    Eco-safe Rural Roads assessment

    View times: 375
    Submitted by: Sanjaya Devkota

    Definition

    Rural roads are important for the communities in the hilly areas of Nepal as they introduce livelihood opportunities at the local level, provide better access to the health care, education and resources. Yet, most of the rural roads in Nepal are unplanned and non-engineered, and these roads are often closed for many months during and after the monsoon. Such roads require huge investments, especially post-monsoon, to clear debris and to keep them operational. In parallel, there is evidence that such roads lead to large number of slope failures and accelerated sedimentation, which degrade the environment and ecosystem services. To remedy such roadside slope failures, eco-engineering practices were tested and demonstrated in partnership with three communities in the Panchase Region of the Nepal’s Central-Western Middle Hills.  Eco-engineering is a hybrid approach, combining civil engineering works for drainage and slope stability, with the plantation of deep-rooted vegetation. It is one activity contributing to Nature based Solutions (NbS) for the sustainable and long-term operation of the rural roads in the Panchase geographic region.

    This paper describes the inter-disciplinary and community-based research, monitoring and evaluation methods applied, including, the establishment of onsite demonstration plots and Rhizotrons in which Key performance Indicators (KPI) analysis of plant species were performed. The results demonstrated the effectiveness of eco-engineering for reducing risk, while creating ecological co-benefits along rural roads (or eco-safe roads) in hilly areas.  Based on this research, an ‘Eco-safe Rural Road Assessment Framework’ was developed, outlining the systematic process to be followed for the design of eco-safe rural roads for more sustainable road construction and maintenance. The ecological engineering practices which are being promoted by this framework have been accepted by communities and could be further implemented by local government bodies and up-scaled in other similar hilly areas around the country. 

    [1] 1. Eco-safe Rural Roads - Concept and Definition

    Eco-engineering or soil bio-engineering measures encompass the use of vegetation, either alone or in combination with conventional civil engineering structures for control of soil erosion and shallow landslides [2]. In Eco-engineering systems, emphasis is given to the environment (e. g. soil, water, air, flora/fauna, society), inert and live construction materials [3] to stabilize soil slopes thereby avoiding disruptions. The plant species used in eco-engineering perform an engineering function proven to provide a combination of sustainability benefits such as protection against soil erosion in the short term and the long term stabilization due to the reinforcement effect of the roots on the soil [4][5]. There is now sufficient research to [3] demonstrate that eco-engineering measures are robust enough in many situations to constitute an alternative over civil engineering solutions. Often referred to as ‘hybrid’ ecological engineering, soil bio-engineering techniques can be combined with civil engineering measures for the most optimal protection, when they do not cause harm to natural system.

    The hypothesis of ‘Eco-safe Rural Road’ is that the roads should be operational year round to ensure economic activities at local level provide better access to the market, healthcare and education and increased the communities’ resilience. While the use of eco-engineering is for safer rural roads, as faulty roads are also dangerous roads and sustainable mitigation of road side slope failures [6]. The eco-engineering approach, using either vegetative or hybrid techniques is a type of NbS [7] [1], which is gaining attention among scientists, professionals and policy makers around the globe. NbS, which includes ‘Eco-safe road’ approaches, provides sustainable and cost-effective solutions with multiple purposes: reducing environmental degradation and improving livelihoods, thereby addressing climate change adaptation (CCA), integrated water resources management (IWRM) disaster risk reduction (DRR), bio-diversity conservation and public-health. [2][4][5][8][9]

    The European Union (EU) has endorsed NbS and is investing heavily in research on NbS through its Horizon 2020 [10] programme which focuses on various ecological engineering techniques, performance measures and policies for the sustainable development and DRR [11]. However, according to Nesshover et al. (2017) [12], there is still debate on how to define NbS with questions on the scope of interventions. A review of the literature reveals two definitions conceptualized and elaborated by IUCN and the European Commission (EC). IUCN defines NbS as “actions to protect, sustainably manage, and restore natural or modified ecosystems that address societal challenges effectively and adaptively, simultaneously providing human well-being and biodiversity benefits” [13]. The IUCN definition adopted eight foundational principles of endorsement of nature conservation norms, consideration of local natural and cultural contexts, fairness and equity in delivering societal benefits, application at the landscape scale, and a forward-looking attitude in considering the evolution of ecosystems and associated benefits, while EC's define NbS as the cost-effective, locally adapted and resource efficient solutions that are “inspired by, supported by or copied from nature” and “simultaneously provide environmental, social and economic benefits and help build resilience” by bringing “more, and more diverse, nature and natural features and processes into cities, landscapes and seascapes[14]. Both definitions of NbS recognize nature as a common denominator that can play major role in addressing the societal challenges, CCA and DRR, whereas the IUCN definition is stricter in its definition of what constitutes a natural ecosystem. Both definitions characterized NbS as ‘an umbrella’ concept of other established ecosystem based approaches [12] such as eco-engineering, Ecosystem-based DRR or Ecosystem-based Adaptation that encompass cost-effectiveness, adaptability, and application of participatory processes, multidisciplinary and evidence-based strategy. [4][8][15][16]

    2. Research Strategy

    In order to establish the assessment framework specific to the use of eco-engineering for safer rural roads, or ‘Eco-Safe Roads’ in the Panchase region of Nepal, the research followed a pragmatic approach combining published research and existing best practices. Review of published articles and consultation with the concerned stakeholders such as community people, professionals working in the rural road sector, policy makers and researchers was contextualized through workshops, scoping visits, focused group discussions (FGDs), key informants interviews (KII) and case studies. Nine semi-structured interviews with the range of stakeholders such as local authorities, engineers, conservation professionals, local non-governmental organizations (NGOs) and members of the community adjacent to the landslide susceptible road sides were conducted in 2013 and 2014 in the Panchase area of Central-Western Nepal. The FGDs and interviews were recorded and main themes and key words were analyzed in order to establish key principles for the development of an assessment framework for establishing ‘Eco-Safe Roads’.

    The scoping visits (November 15-17, 2013 and April 10-14, 2014) followed by the inception workshop provided useful information for identifying key issues related to landslides in the Panchase region. These included, that the region is highly susceptible to slope failure, not only due to the fragile landscape but also due to highly intense human activities, such as unplanned rural road construction. In conjunction to the scoping visits, the inception workshop identified three road side locations for establishing eco-engineering demonstration sites and locations for the Rhizotrons (Gharelu in Kaski, Bhatkhola in Syangja and Tilahar in Parbat Districts). Rhizotron is a root monitoring device [17] established near vertical (~850) excavated roadside slopes. The vertical part of the slope was fixed with transparent Plexi-glass and protected by three removable layers of insulating materials. On the upper slope of the Rhizotron, plant species were planted systematically dividing the Rhizotron length in equal divisions. The research was focused on perennial grass species as grasses can be established quickly, spread faster to give good ground cover and contain a high degree of tolerance [18]. The FGD identified seven local grass species: 1) Amriso (Thysanalana maxima), 2) Urlo-Khar (Cymbopogon microtheca), 3) Napier (Penniseluim purpurreum), 4) Salim-Khar (Chirysopogon gryllus), 5) Kans (Saccharum spontaneum), 6) Kush (Cannabis indica), and 7) Babiyo (Eulalioipsis binate). Although not being a local species Vetiver (Chrysopogon zizanioides) grass was also chosen as this species has well known strong and deep root systems [19]. Plantations took place during the early pre-monsoon (April, 2014) to allow the seedlings to develop roots and survive during the intense monsoon rainfall. Plantations before the monsoon requires careful action to maximize the plant survival [20].

    Various parameters such as species survivorship, canopy coverage, root-shoot (dry) biomass, root diameter and depth (shallow < 30 cm and deep ≥ 80 cm) followed by root contribution in soil cohesion were evaluated according to Wu et al. (1979) [21] while root mapping was performed as demonstrated by Bohm (1979) [22]. These parameters were considered to be the Key Performance Indicators (KPIs) of the plant species used. To quantify the KPIs of the species,  well-established principles and norms such as Bohm (1979) [23] and Pohl et al. (2011) [24] were adopted. The KPIs were fitted into a Principal Component Analysis (PCA) model to better understand the species quality for the eco-engineering measures. PCA is a statistical procedure that uses an orthogonal transformation  of a set of observations and explores the possible correlation among the linearly uncorrelated variables [25].

    The inventories of rural roads and landslides in the Phewa Lake watershed were prepared firstly from the Remote Sensing (RS) images and secondly verified through the field survey. To better understand the slope stability and underlying causes, the research was designed to implement physically based infinite slope stability model according to Chae et al. (2015) [26]. For this purpose, a sub-set of Panchase mountain region, the Phewa Lake watershed (~111.5km2) was modelled utilizing the soil properties, topographical variables derived from the 12.5 meter resolution Digital Elevation Model (DEM) and rainfall intensity, the Landslide Susceptibility Model (LSM) was established. The LSM was verified adopting Receiver Operating Characteristics (ROC) curve [27][28] utilizing the inventory maps. The research followed a pragmatic approach based on a regional rainfall Intensity-Duration-Frequency (IDF) model, published by Devkota et al. (2018)  [29] and the soil depth to bed rock (SDTB) [30] of the Phewa Lake watershed; saturation depth of the soil profile at watershed scale was estimated adopting Green-Ampt (GA) model according to Dingman (2002) [31] while soil physical and hydrological properties were derived either in the field or in the laboratory. The initial moisture content of the soil in the watershed was considered to be 80% due to the antecedent rain water.

    As part of the capacity development, a two-day long community-based soil bioengineering training was conducted for the road users adjacent to the demonstration sites. The community participation in the training was gender balanced with nearly equal participation of male and female members. During the training, a dialogue was established with community representatives to discuss the objectives of the demonstration sites and the research. A local road user’s group (RUG) was formed for each demonstration site while the RUG adjacent to the road were given to the role of determining which areas to rehabilitate, which area to select for the Rhizotron, which plant (grass) species to select and they were responsible for the seedling collection, plantation, and routine maintenance and weeding. In parallel, expert knowledge was used to design eco-engineering measures and quality control of the construction activities adopted from Devkota et al. (2014) [32]; Howell (1999a) [33]; Howell (1999b) [34] and Gray and Sotri (1996) [4] where applicable. Community people were also engaged and compensated for other construction activities such as roadside drainage, stone wall construction, and stone-rip-rap surface drainage, while local government officials and technical experts were assigned to design and co-monitor the work quality and progress with the community leaders.

    In order to address the sustainability of the eco-engineering measures implemented at the demonstration sites, this research attempted to establish knowledge transfer partnership (KTP) as suggested by Raymond et al. [35] among the key stakeholders such as researcher, academician, local government representative and local people. The integration of local knowledge and physical science adopted in the research established the foundation and the conceptualization for the proposed assessment framework. The case studies provided data and experiences for establishing and testing the eco-engineering concept, and its complexities and challenges.

    3. Rural Road and Landslides in Phewa Lake Watershed of Panchase Region

    Analysis of RS image and field mapping revealed the total length of the rural roads in the watershed was about 305 km through the end of August 2016, with a road density of about 2.74 km/km2. The unplanned and non-engineered construction of rural roads is one of the major causes of soil losses [36][37] in the region. There were 373 field validated slope failures events during the period of 2013 to 2016 out of which 199 events were caused by the roads, while the triggering factor was rain. The smallest and largest unit of mapped landslide was ~19 m2 and ~0.24 km2 respectively. Figure 1, presents the landslides (DMG 2002 and 2013-16) and the rural roads till the end of August 2016 in the Phewa Lake watershed. As of Vuillez et al. (2018) [38] the older landslides were observed mostly on natural slopes (e. g. forest and cultivated terraces) whereas most of the recent failures were along the roads.

      Inventory map (combined) rural roads, landslides (2013-16) and DMG 2002 [69], in the background false-color composite Rapid Eye image ( 5m x 5m) taken in 5 Oct 2015.

     Figure 1. Inventory map (combined) rural roads, landslides (2013-16) and DMG 2002 [39], in the background false-color composite Rapid Eye image ( 5m x 5m) taken in 5 Oct 2015.

    An infinite slope stability model was implemented under two different rainfall intensity scenarios (scenario 1:4.65 cm/hr, 100 year return period; scenario 2: 5.70 cm/hr, 500 year return period). The model results indicated that 4.84% and 7.26% of the watershed area was susceptible to failure (FS [1] <1) while 20.10% and 22.55% area was depicted to be critical (FS = 1-1.5) respectively for scenario 1 and 2. The ROC depicted that the scenario 1 (Figure 2) was better because of its higher AUC over the scenario 2 (scenario 1: AUC [14] = 76.4%, scenario 2: AUC= 71.5%). Despite the model result, the LSM also indicated that the majority of the rural roads in the watershed were either passing through the landslides or in landslide susceptible areas for which eco-engineering measures offer the most cost effective and sustainable solutions.     

      LSM of Phewa Lake watershed (scenario 1) indicting the rural roads, fault line and landslides inventory of 2013-2016.

     Figure 2. LSM of Phewa Lake watershed (scenario 1) indicting the rural roads, fault line and landslides inventory of 2013-2016.

    4. KPI of the Plant Species

    The perennial grass species that were recommended by the community, were also recommended by Devkota et al. (2006) [40] and Howell (1999a) [39], implying that the species selection through the local knowledge is useful. Altogether nine indicators were quantified to evaluate the performance of the eight model plant species (Table 3). Among the model species Babiyo (P. purpurreum) and Kans (D. bipinnata) respectively demonstrated highest and lowest survivorship of 81.33% and 65.33% and the same is valid for the canopy cover. Vetiver (C. zizanioides) followed by Babiyo (P. purpurreum) respectively demonstrated the highest shoot and root dry biomass among others. This research concluded that the model plant species can be divided into three classes as per the root depth: 1) deep, 2) moderately deep and 3) shallow according to which Vetiver (C. zizanioides) and Amriso (T. maxima) were the most deep rooted species followed by Urlo-Khar (C. microtheca) and Salim-Khar (E. binata) moderately deep rooted (≤ 50 cm) whilst Babiyo (P. purpurreum), Nepiyar (C. gryllus), Kans (D. bipinnata), and Kush (S. spontaneum) were the shallow (≤ 30 cm) rooted species. The measurement depicted that the root density is higher in the depth range of 0-10 cm followed by 10 cm – 30cm. As the rooting depth increases, the root density decreased. For entire mapping, the largest root (2.07 mm) measured in the Rhizotron profile was from Amriso (T. maxima) at the depth range of 0-10 cm. The root tensile strength is one of the important indicators that contribute to increasing the soil cohesion, known as root cohesion. Vetiver (C. zizanioides) demonstrated highest tensile strength (Tr) by the root cohesion (cr), which was followed by Amriso (T. maxima) among others. The Table presents the summary of all the nine KPIs of the model plant species.

    Species Local Name

    L-Name

    Survival (%)

    Canopy Cover (%)

    Biom-s-dry (kg)

    Biom-r-dry (kg)

    RAR-deep

    RAR-shallow

    Rooting Depth (cm)

    Tr (MPa)

    cr (kPa)

    Vetiver

    C. zizanioides

    80.00

    70.57

    0.83

    0.32

    0.0018

    0.0241

    0-100

    45.4

    14.08

    Urlo-Khar

    C. microtheca

    78.67

    48.33

    0.63

    0.33

    0.0018

    0.0092

    0-50

    24.11

    7.48

    Babiyo

    P. purpurreum

    81.33

    86.67

    0.78

    0.54

    0.0001

    0.0128

    0-30

    18.25

    5.66

    Nepiyar

    C. gryllus

    76.00

    60.27

    0.39

    0.28

    0.0004

    0.0082

    0-30

    25.28

    7.84

    Salim-Khar

    E. binata

    66.67

    51.43

    0.18

    0.19

    0.0003

    0.0104

    0-50

    23.1

    7.17

    Kans

    D. bipinnata

    65.33

    29.70

    0.26

    0.19

    0.0006

    0.0119

    0-30

    20.24

    6.28

    Kush

    S. spontaneum

    72.00

    41.10

    0.33

    0.15

    0.0010

    0.0084

    0-30

    21.53

    6.68

    Amriso

    T. maxima

    70.67

    78.63

    0.62

    0.30

    0.0099

    0.0657

    0-80

    26.65

    8.27

             

    L-name = Latin Name, Biom-s-dry= dry biomass of shoot, Biom-r-dry=dry biomass of root, RAR deep = Root area Ratio of deep roots, RAR shallow = Root area ratio of shallow roots, Tr = tensile strength, cr = root cohesion

    PCA model was developed utilizing the nine KPIs of the model species to test the quality of plant for eco-engineering measures. The model demonstrated the performance of Amriso (T. maxima) was better for soil depth of about 80 cm among the seven local species whilst Vetiver (C. zizanioides) was the best among all for the soil depth of 100 cm. Urlo-Khar (C. microtheca) and Salim-Khar (E. binata) are useful for the landscape where the soil depth is below 50 cm. Other species are useful where the landscape soil depth is lower than 30 cm.    

    5. Proposed Eco-safe Rural Road assessment Framework

    Based on the case study and review of the available research materials ‘Eco-safe Rural Road assessment Framework’ was contextualized. The framework that outlines the issues to be addressed through appropriate technique with the pre-defined objectives, and guides to understand, design, development, implementation and assessment of eco-engineering that deals with the NbS for the road side slope protection measures. The proposed framework consists of the following seven steps.  All the below steps need to be implemented together with the relevant stakeholders, ensuring full gender-balanced community participation from the very beginning through the final monitoring and evaluation 

    1. Define the problems to be addressed(baseline);
    2. Establish the NbS objectives;
    3. Identify NbS measures and alternatives for safe and sustainable rural roads;
    4. Implement the NbS plan for Eco-safe Rural Road;
    5. Establish an awareness and communication plan;
    6. Mobilize the community for implementation and Up-scaling;
    7. Establish monitoring and Evaluation Plan and follow-up.

    The framework also discussed the issues to be addressed at different stages of the eco-engineering implementation process in the Panchase region suitable for other similar geographical area of Nepal.

    6. Conclusions

    Roads are important infrastructures that bring livelihood opportunities and improve the quality of life. However unplanned and non-engineered rural roads are the cause of disasters such as landslides [41]. In Nepal, the problem of unplanned and non-engineered rural roads is pervasive as such roads are often nonoperational for 4-6 months during and after monsoon (June-Nov.) [42][43]. These roads are causal factors for landslide and soil erosion, while intense monsoonal rain is known to be the triggering factor damaging the lives and livelihoods, degrading the environment and ecosystem services [44].  In parallel, landslides cause human suffering and wastes economic resources by damaging and blocking roads, restricting rural communities in accessing health-care, education, and resources. At the present time, the government is not to adequately address this widespread problem due to limited resources and capacities.  It is now important to bring the Nature based Solutions (NbS) in the mainstream development activities for which eco-engineering approach can be a sustainable solution. Eco-engineering is a type of the NbS, used to mitigate a range of roadside slope failures, in which deep rooted plant species are used alone or in combination with civil engineering measures.

    Although soil bioengineering is popular in Nepal and many useful manuals and handbooks were developed in the past three decades, yet in practice soil bioengineering is not mainstreamed, especially for local community built roads.  Importantly, there is no comprehensive assessment framework for the sustainable rural road side slope protection. The proposed ‘Eco-safe road’ framework demonstrated the underlying causes of slope failure and outlined the process to be followed while undertaking eco-engineering measures for the safer and sustainable rural roads in the hills of Nepal. Data and information required for defining the underlying problems of rural road side slope failure were also discussed through the research and case study described in this article. The ‘Eco-safe Rural Road’ approach demonstrated in the three locations (Gharelu in Kaski, Tilahar in Parbat and Bhatkhola in Syangja Districts) has been accepted by the local communities, because of the depicted results and co-benefits.  Whereas, the local government representatives showed their interest as the techniques which were demonstrated are cost effective and sustainable. The eco-engineering approaches described through this research can be expanded to other similar geographic regions of the country for which this framework can be used as guideline for the successful implementation of eco-engineering measures.

    The upscaling of NbS for the ‘Eco-safe Rural Road’ can be possible during the demonstration stage as well as during the mainstreaming phase when teams learn from the project demonstrations [40]. During the demonstration phase, upscaling can contribute to strengthening government, stakeholders and investors’ confidence [45] and increase the number of NbS implementation projects and co-benefits. Upscaling of NbS requires multi-actor partnerships [46]. Scientists can provide the evidence base to predict the benefits of NbS while the societal stakeholders can be instrumental in informing key implementation issues; for example, finding suitable locations for NbS [47]. Planners can contribute to develop innovative ways to systematically incorporate NbS into governance instruments and regulations.

    References

    1. Santoro, S.; Pluchinotta, I.; Pagano, A.; Pengal, P.; Cokan, B.; Giordano, R. Assessing stakeholders’ risk perception to promote Nature Based Solutions as flood protection strategies: The case of the Glinščica river (Slovenia). Sci. Total Environ. 2019, 655, 188–201.
    2. Mickovski, S.B.; Why is the future ready for Environmental Geotechnics.. Environ. Geotech. 2016, 3, 63–64, https://doi.org/10.1680/envgeo.13.00107.
    3. Santoro, S.; Pluchinotta, I.; Pagano, A.; Pengal, P.; Cokan, B.; Giordano, R.; Assessing stakeholders’ risk perception to promote Nature Based Solutions as flood protection strategies: The case of the Glinščica river (Slovenia).. Sci. Total Environ. 2019, 655, 188–201, https://doi.org/10.1016/j.scitotenv.2018.11.116.
    4. UNDP. Proceedings of Nepal Country Workshop on Environments of the Poor in the Context of Climate Change and the Green Economy July 2011; Government of Nepal, National Planning Comission, UNDP and UNEP: Kathmandu, Nepal, 2011.
    5. van Wesenbeeck, B.; IJff, S.; Jongman, B.; Balog, S.; Kaupa, S.; Bosche, L.; Lange, G.M.; Holm-Nielsen, N.; Nieboer, H.; Taishi, Y.; et al. Implementing Nature Based Flood Protection: Principles and Implementation Guidance; World Bank Group: Washington, DC, USA, 2017.
    6. Gray, D.H.; Sotir, R.B. Biotechnical and Soil Bioengineering Slope Stabilization: A Practical Guide for Erosion Control; John Wiley & Sons: Hoboken, NJ, USA, 1996.
    7. Mickovski, S.; Thomson, C. Developing a framework for the sustainability assessment of eco-engineering measures. Ecol. Eng. 2017, 109, 145–160.
    8. Devkota, S.; Sudmeier-Rieux, K.; Adhikari, A.; Khanal, R.; Penna, I.; Jaboyedoff, M. Investing in Ecosystem Aproach for more resilient Disaster Risks Reduction: The case eco-safe roads in Nepal. In FIG-ISPRS Workshop 2015: International Workshop on Role of Land Professionals and SDI in Disaster Risk Reduction in the Context of Post 2015 Nepal Earthquake, Kathmandu, Nepal, 25–27 November 2015; Department of Survey: Kathmandu, Nepal, 2015; p. 13.
    9. Maes, J.; Jacobs, S. Nature-based solutions for Europe’s sustainable development. Conserv. Lett. 2017, 10, 121–124.
    10. European Commission. Nature-Based Solutions. Available online: https://ec.europa.eu/research/environment/index.cfm?pg=nbs (accessed on 10 May 2014).
    11. Bennett, E.M.; Cramer, W.; Begossi, A.; Cundill, G.; Díaz, S.; Egoh, B.N.; Geijzendorffer, I.R.; Krug, C.B.; Lavorel, S.; Lazos, E.; et al. Linking biodiversity, ecosystem services, and human well-being: Three challenges for designing research for sustainability. Curr. Opin. Environ. Sustain. 2015, 14, 76–85.
    12. Carsten Nesshöver; Timo Assmuth; Katherine Irvine; Graciela Rusch; Kerry Waylen; Ben Delbaere; Dagmar Haase; Lawrence Jones-Walters; Hans Keune; Eszter Kovács; et al. The science, policy and practice of nature-based solutions: An interdisciplinary perspective. Science of The Total Environment 2017, 579, 1215-1227, 10.1016/j.scitotenv.2016.11.106.
    13. Nesshöver, C.; Assmuth, T.; Irvine, K.N.; Rusch, G.M.; Waylen, K.A.; Delbaere, B.; Haase, D.; Jones-Walters, L.; Keune, H.; Kovacs, E.; et al. The science, policy and practice of nature-based solutions: An interdisciplinary perspective. Sci. Total Environ. 2017, 579, 1215–1227.
    14. Cariñanos, P.; Calaza-Martínez, P.; O’Brien, L.; Calfapietra, C. The cost of greening: Disservices of urban trees. In The Urban Forest-Cultivating Green Infrastructure for People and the Environment; David, P., Carlo, C., Roeland, S., Liz, O.B., Silvija, K.O., Giovanni, S., Rocío, A.d.A., Eds.; Springer International Publishing AG: Berlin/Heidelberg, Germany, 2017; Volume 7, p. 9.
    15. Bauduceau, N.; Berry, P.; Cecchi, C.; Elmqvist, T.; Fernandez, M.; Hartig, T.; Krull, W.; Mayerhofer, E.; Sandra, N.; Noring, L.; et al. Towards an EU Research and Innovation Policy Agenda for Nature-Based Solutions & Re-Naturing Cities: Final Report of the Horizon 2020 Expert Group on ‘Nature-Based Solutions and Re-naturing Cities’; Publications Office of the European Union: Brussels, Belgium, 2015.
    16. Raymond, C.M.; Frantzeskaki, N.; Kabisch, N.; Berry, P.; Breil, M.; Nita, M.R.; Geneletti, D.; Calfapietra, C.; et al. A framework for assessing and implementing the co-benefits of nature-based solutions in urban areas. Environ. Sci. Policy 2017, 77, 15–24.
    17. Mao, Z.; Bourrier, F.; Stokes, A.; Fourcaud, T. Three-dimensional modelling of slope stability in heterogeneous montane forest ecosystems. Ecol. Model. 2014, 273, 11–22.
    18. Mickovski, S.B. Why is the future ready for Environmental Geotechnics. Environ. Geotech. 2016, 3, 63–64.
    19. MacNeil, D.J.; Steele, D.P.; McMahon, W.; Carder, D.R. Vegetation for Slope Stability; Prepared for Quality Services, Civil Engineering, Highways Agency; TRL: Wokingham, UK, 2001.
    20. Truong, P. Vetiver System for Infrastructure Protection; Veticon Consulting: Brisbane, Australia, 2000; Volume 108, p. 11.
    21. Petrone, A.; Preti, F. Soil bioengineering for risk mitigation and environmental restoration in a humid tropical area. Hydrol. Earth Syst. Sci. 2010, 14, 239–250.
    22. Bohm, W. Methods of Studying Root Systems; Springer: Berlin/Heidelberg, Germany; New York, NY, USA, 1979.
    23. Wu, T.H.; McKinnell, W.P., III; Swanston, D.N. Strength of tree roots and landslides on Prince of Wales Island, Alaska. Can. Geotech. J. 1979, 16, 19–33.
    24. Bro, R.; Smilde, A.K. Principal component analysis. Anal. Methods 2014, 6, 2812–2831.
    25. Chae, B.-G.; Lee, J.-H.; Park, H.-J.; Choi, J. A method for predicting the factor of safety of an infinite slope based on the depth ratio of the wetting front induced by rainfall infiltration. Nat. Hazards Earth Syst. Sci. 2015, 15, 1835–1849.
    26. Remondo, J.; González, A.; De Terán, J.R.D.; Cendrero, A.; Fabbri, A.; Chung, C.-J.F. Validation of Landslide Susceptibility Maps; Examples and Applications from a Case Study in Northern Spain. Nat. Hazards 2003, 30, 437–449.
    27. Rizvi, A.R.; Baig, S.; Verdone, M. Ecosystems Based Adaptation: Knowledge Gaps in Making an Economic Case for Investing in Nature Based Solutions for Climate Change; IUCN: Gland, Switzerland, 2015; p. 48.
    28. Deng, X.; Li, L.; Tan, Y. Validation of Spatial Prediction Models for Landslide Susceptibility Mapping by Considering Structural Similarity. Int. J. Geo-Inf. 2017, 6, 10.
    29. Devkota, S.; Shakya, N.; Sudmeier-Rieux, K.; Jaboyedoff, M.; Van Westen, C.; Mcadoo, B.; Adhikari, A. Development of Monsoonal Rainfall Intensity-Duration-Frequency (IDF) Relationship and Empirical Model for Data-Scarce Situations: The Case of the Central-Western Hills (Panchase Region) of Nepal. Hydrology 2018, 5, 27.
    30. Devkota, S.; Shakya, N.M.; Sudmeier-Rieux, K.; McAdoo, B.G.; Jaboyedoff, M. (Eds.) Predicting soil depth to bedrock in an anthropogenic landscape: A case study of Phewa Watershed in Panchase region of Central-Western Hills, Nepal. In Proceedings of the 11th IAEG Asian Regional Conference (ARC-11)—Engineering geology for Geodisaster Management, Kathmandu, Nepal, 28–30 November 2017; Nepal geological Society: Kathmandu, Nepal, 2018.
    31. Dingman, S.L. Physical Hydrology; Prentice Hall: Upper Saddle River, NJ, USA, 2002; p. 646.
    32. Devkota, S.; Sudmeier-Rieux, K.; Penna, I.; Eberle, S.; Jaboyedoff, M.; Adhikari, A.; et al. Community-Based Bio-Engineering for Eco-Safe Roads in Nepal; University of Lausanne: Lausanne, Switzerland; International Union for Conservation of Nature: Gland, Switzerland; Nepal and Department of Soil Conservation and Watershed Management: Kathmandu, Nepal; Government of Nepal: Kathmandu, Nepal, 2014; p. 95.
    33. Devkota, B.; Paudel, P.; Omura, H.; Kubota, T.; Morita, K. Uses of vegetative measures for erosion mitigation in Mid Hill areas of Nepal. Kyushu J. For. Res. 2006, 59, 265–268.
    34. Karki, R.; Schickhoff, U.; Scholten, T.; Böhner, J. Rising precipitation extremes across Nepal. Climate 2017, 5, 4.
    35. ORCDC. Vetiver Grass Installation Guide: Pacific Islands Area; Oahu Resource Conservation and Development Council in cooperation with USDA Natural Resource Conservation Service (NRCS): Kunia Camp, HI, USA, 2012.
    36. Larsen, M.C. Rainfall-triggered landslides, anthropogenic hazards and mitigation strategies. Adv. Geosci. 2008, 14, 147–153.
    37. Vuillez, C.; Tonini, M.; Sudmeier-Rieux, K.; Devkota, S.; Derron, M.-H.; Jaboyedoff, M. Land use changes, landslides and roads in the Phewa Watershed, Western Nepal from 1979 to 2016. Appl. Geogr. 2018, 94, 30–40.
    38. DMG. Cartographer Engineering and Environmental Geologicla Map of Pôkhara Valley; Government of Nepal: Kathmandu, Nepal, 2002.
    39. Devkota, B.; Paudel, P.; Omura, H.; Kubota, T.; Morita, K. Uses of vegetative measures for erosion mitigation in Mid Hill areas of Nepal. Kyushu J. For. Res. 2006, 59, 265–268.
    40. Karki, R.; Schickhoff, U.; Scholten, T.; Böhner, J. Rising precipitation extremes across Nepal. Climate 2017, 5, 4.
    41. Pohl, M.; Stroude, R.; Buttler, A.; Rixen, C. Functional traits and root morphology of alpine plants. Ann. Bot. 2011, 108, 537–545.
    42. Petley, D.N.; Hearn, G.J.; Hart, A.; Rosser, N.; Dunning, S.; Oven, K.; Mitchell, W.A. Trends in Landslide occurrence in Nepal. Nat. Hazards 2007, 43, 23–44.
    43. Stokes, A.; Douglas, B.G.; ourcaud, F.T.; Giadrossich, F.; Gillies, C.; Hubble, T.; Kim, J.H.; Loades, K.W.; Mao, Z.; McIvor, I.R.; et al. Ecological mitigation of hillslope instability: Ten key issues facing researchers and practitioners. Plant Soil 2014, 377, 1–23.
    44. Kabisch, N.; Frantzeskaki, N.; Pauleit, S.; Naumann, S.; Davis, M.; Artmann, M.; Haase, D.; Knapp, S.; Korn, H.; Stadler, J.; et al. Nature-based solutions to climate change mitigation and adaptation in urban areas: Perspectives on indicators, knowledge gaps, barriers, and opportunities for action. Ecol. Soc. 2016, 21, 39.
    45. Connop, S.; Vandergert, P.; Eisenberg, B.; Collier, M.J.; Nash, C.; Clough, J.; Newport, D. Renaturing cities using a regionally-focused biodiversity-led multifunctional benefits approach to urban green infrastructure. Environ. Sci. Policy 2016, 62, 99–111.
    46. UNDP. Economic Analysis of Local Government Investment in Rural Roads in Nepal; LGCDP, UNDP, UNEP: Kathmandu, Nepal, 2011.
    47. Kathmandupost. Eco-Safe Roads. Available online: https://kathmandupost.ekantipur.com/news/2016-10-02/eco-safe-roads.html (accessed on 9 May 2019).
    48. Sudmeier-Rieux, K.; McAdoo, B.G.; Devkota, S.; Rajbhandari, P.C.L.; Howell, J.; Sharma, S. Invited perspectives: Mountain roads in Nepal at a new crossroads. Nat. Hazards Earth Syst. Sci. 2019, 19, 655–660.
    49. World Bank. Nepal Road Sector Assessment Study; Government of Nepal, World Bank, Asian Development Bank, DFID, SDC: Kathmandu, Nepal, 2012; p. 55.
    50. McAdoo, B.G.; Quak, M.; Gnyawali, K.R.; Adhikari, B.R.; Devkota, S.; Rajbhandari, P.L.; Sudmeier-Rieux, K. Roads and landslides in Nepal: How development affects environmental risk. Nat. Hazards Earth Syst. Sci. 2018, 18, 3203–3210.
    51. Cohen-Shacham, E.; Walters, G.; Janzen, C.; Maginnis, S. Nature-Based Solutions to Address Global Societal Challenges; IUCN: Gland, Switzerland, 2016; p. 97.
    52. Frantzeskaki, N.; Borgström, S.; Gorissen, L.; Egermann, M.; Ehnert, F. Nature-Based Solutions Accelerating Urban Sustainability Transitions in Cities: Lessons from Dresden, Genk and Stockholm Cities. In Nature-Based Solutions to Climate Change Adaptation in Urban Areas; Springer: Berlin/Heidelberg, Germany, 2017; pp. 65–88.
    53. need edit!
    More