Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape to address the problem strategically. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviews the different sub-factors of USLE and RUSLE, and analyses how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with (R)USLE and related approaches. Within each sub-factor section, the strengths and limitations of the different equations are discussed, and guidance is given as to which equations may be most appropriate for particular climate types, spatial resolution, and temporal scale. We investigate some of the limitations of existing (R)USLE formulations, such as uncertainty issues given the simple empirical nature of the model and many of its sub-components; uncertainty issues around data availability; and its inability to account for soil loss from gully erosion, mass wasting events, or predicting potential sediment yields to streams. Recommendations on how to overcome some of the uncertainties associated with the model are given. Several key future directions to refine it are outlined: e.g. incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and compiling consistent units for the future literature to reduce confusion and errors caused by mismatching units. The potential of combining (R)USLE with the Compound Topographic Index (CTI) and sediment delivery ratio (SDR) to account for gully erosion and sediment yield to streams respectively is discussed. Overall, the aim of this paper is to review the (R)USLE and its sub-factors, and to elucidate the caveats, limitations, and recommendations for future applications of these soil erosion models. We hope these recommendations will help researchers more robustly apply (R)USLE in a range of geoclimatic regions with varying data availability, and modelling different land cover scenarios at finer spatial and temporal scales (e.g. at the field scale with different cropping options).

Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape and use land management and other strategies to effectively manage the problem. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is 10 the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviewed the different components of USLE and RUSLE etc., and analysed how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with R/USLE and related approaches. We investigate some of the limitations of R/USLE, such as issues 15 in data-sparse regions, its inability to account for soil loss from gully erosion or mass wasting events, and that it does not predict sediment pathways from hillslopes to water bodies. These limitations point to several future directions for R/USLE studies: incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and using consistent units for future literature. These recommendations help to improve the applicability of the R/USLE in a range of geoclimatic regions with varying data availability, and at finer spatial and temporal scales for scenario analysis. 20

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Tools that spatially model ecosystem services offer opportunities to integrate ecology into regenerative urban design. However, few of these tools are designed for assessing ecosystem services in cities, meaning their application by designers is potentially limited. This research reviews and compares a range of ecosystem services assessment tools to find those that are most suited for the urban context of Oceania. The tool classification includes considerations of type of input and output data, time commitment, and necessary skills required. The strengths and limitations of the most relevant tools are further discussed alongside illustrative case studies, some collected from literature and one conducted as part of this research in Wellington, Aotearoa using the Land Utilisation and Capability Indicator (LUCI) tool. A major finding of the research is that from the 95 tools reviewed, only four are judged to be potentially relevant for urban design projects. These are modelling tools that allow spatially explicit visualisation of biophysical quantification of ecosystem services. The ecosystem services assessed vary among tools and the outputs’ reliability is often highly influenced by the user’s technical expertise. The provided recommendations support urban designers and architects to choose the tool that best suits their regenerative design project requirements.

Abstract. Due to its location within the typhoon belt, the Philippines is vulnerable to tropical cyclones that can cause destructive floods. Climate change is likely to exacerbate these risks through increases in tropical cyclone frequency and intensity. To protect populations and infrastructure, disaster risk management in the Philippines focuses on real-time flood forecasting and structural measures such as dikes and retaining walls. Real-time flood forecasting in the Philippines mostly utilises two models from the Hydrologic Engineering Center (HEC): the Hydrologic Modeling System (HMS) for watershed modelling, and the River Analysis System (RAS) for inundation modelling. This research focuses on using non-structural measures for flood mitigation, such as changing land use management or watershed rehabilitation. This is being done by parameterising and applying the Land Utilisation and Capability Indicator (LUCI) model to the Cagayan de Oro watershed (1400 km2) in southern Philippines. The LUCI model is capable of identifying areas providing ecosystem services such as flood mitigation and agricultural productivity, and analysing trade-offs between services. It can also assess whether management interventions could enhance or degrade ecosystem services at fine spatial scales. The LUCI model was used to identify areas within the watershed that are providing flood mitigating services and areas that would benefit from management interventions. For the preliminary comparison, LUCI and HEC-HMS were run under the same scenario: baseline land use and the extreme rainfall event of Typhoon Bopha. The hydrographs from both models were then input to HEC-RAS to produce inundation maps. The novelty of this research is two-fold: (1) this type of ecosystem service modelling has not been carried out in the Cagayan de Oro watershed; and (2) this is the first application of the LUCI model in the Philippines. Since this research is still ongoing, the results presented in this paper are preliminary. As the land use and soil parameterisation for this watershed are refined and more scenarios are run through the model, more robust comparisons can be made between the hydrographs produced by LUCI and HEC-HMS and how those differences affect the inundation map produced by HEC-RAS.

Deltas are among the most productive and diverse global ecosystems. However, these regions are highly vulnerable to natural disasters and climate change. Nature-based solutions (Nbs) have been increasingly adopted in many deltas to improve their resilience. Among decision support tools, assessment of ecosystem services (ES) through spatially explicit modelling plays an important role in advocating for Nbs. This study explores the use of the Land Utilisation and Capability Indicator (LUCI) model, a high-resolution model originally developed in temperate hill country regions, to map changes in multiple ecosystem services (ES), along with their synergies and trade-offs, between 2010 and 2018 in the Vietnamese Mekong Delta (VMD). In so doing, this study contributes to the current knowledge in at least two aspects: high-resolution ES modelling in the VMD, and the combination of ES biophysical and economic values within the VMD to support Nbs implementation. To date, this is the highest resolution (5 by 5 m) ES modelling study ever conducted in the VMD, with ~1500 million elements generated per ES. In the process of trialling implementations of LUCI within the VMD’s unique environmental conditions and data contexts, we identify and suggest potential model enhancements to make the LUCI model more applicable to the VMD as well as other tropical deltaic regions. LUCI generated informative results in much of the VMD for the selected ES (flood mitigation, agriculture/aquaculture productivity, and climate regulation), but challenges arose around its application to a new agro-hydrological regime. To address these challenges, parameterising LUCI and reconceptualising some of the model’s mechanisms to specifically account for the productivity and flood mitigation capability of water-tolerant crops as well as flooding processes of deltaic regions will improve future ES modelling in tropical deltaic areas. The ES maps showed the spatial heterogeneity of ES across the VMD. Next, to at least somewhat account for the economic drivers which need to be considered alongside biophysical valuations for practical implementations of ES maps for nature-based solutions (Nbs) in the upstream VMD, economic values were assigned to different parcels using a benefit transfer approach. The spatially explicit ES economic value maps can inform the design of financing incentives for Nbs. The results and related work can be used to support the establishment of Nbs that ultimately contribute to the security of local farmers’ livelihoods and the sustainability of the VMD.

Information on soil hydraulic properties (e.g. soil moisture pressure relationships and hydraulic conductivity) is valuable for a wide range of disciplines including hydrology, ecology, environmental management and agriculture. However, this information is often not readily available as direct measurements are costly and time-consuming. Furthermore, as more complex representations of soils are being built into environmental models, users and developers often require sound hydraulic property information, while having limited access to specialist knowledge. Although indirect methods have been developed to obtain soil hydraulic properties from easily measurable or readily available soil properties via pedo-transfer functions (PTFs), few articles provide guidance for obtaining soil hydraulic properties over a wide range of geoclimatic and regional data availability contexts. The aim of this study is, therefore, to develop guidelines and an associated spatially referenced toolbox, NB_PTFs, to speed the process of acquiring sensible soil hydraulic properties for different geoclimatic and data-rich/sparse regions. The guide compiles available information about soil hydraulic properties, as well as a large number (151) of PTFs, not collated in any other guidance to date. NB_PTFs is an open-source ArcGIS toolbox which allows users to quickly get values, graphs and spatial distributions of soil hydraulic properties. The soil hydraulic properties, obtained using the guide and the toolbox, can be used as inputs for various models amongst other purposes. To demonstrate the use of the guidelines and the toolbox in different geoclimatic and data-availability contexts, the paper presents two case studies: the Vietnamese Mekong Delta and New Zealand Hurunui catchment. The Vietnamese Mekong Delta shows the use of these guidelines in a tropical, flat location with limited information on soil physical, chemical and hydraulic properties. The Hurunui catchment represents a case study for a semi-arid and hilly area in an area with detailed soil information.

The natural capital components in cities (“blue-green infrastructure” BGI) are designed to address long-term sustainability and create multi-benefits for society, culture, business, and ecology. We investigated the added value of BGI through the research question “Can the implementation of blue-green infrastructure lead to an improvement of habitat connectivity and biodiversity in urban environments?” To answer this, the Biological and Environmental Evaluation Tools for Landscape Ecology (BEETLE) within the Land Utilisation and Capability Indicator (LUCI) framework was adopted and applied in Christchurch, New Zealand, for the first time. Three ecologically representative species were selected. The parameterisation was based on ecological theory and expert judgment. By implementation of BGI, the percentages of habitats of interest for kereru and paradise shelduck increased by 3.3% and 2.5%, respectively. This leads to improved habitat connectivity. We suggest several opportunities for regenerating more native patches around the catchment to achieve the recommended minimum 10% target of indigenous cover. However, BGI alone cannot return a full suite of threatened wildlife to the city without predator-fenced breeding sanctuaries and wider pest control across the matrix. The socio-eco-spatial connectivity analysed in this study was formalised in terms of four interacting dimensions.