Incorporating measured data into environmental simulation models through calibration helps to improve predictive performance and reduce uncertainty. Traditionally, this process involves transferring information from observations to parameters, requiring many model runs and parameter updates. The relationships between observations (simulated equivalents) and parameters are often non-linear, which can compromise predictions. Data space inversion (DSI) explores the posterior predictive distribution by building a surrogate model based on the covariance between model outputs that correspond to 1) field measurements, and 2) predictions of interest. DSI avoids updating physical model parameters by conditioning predictions on measurements of system behaviour. DSI is applied to the Soil and Water Assessment Tool (SWAT + ) coupled with a modified groundwater flow module (gwflow) for the Winnebago watershed (U.S.) to evaluate its robustness and efficiency in predicting streamflow and groundwater and to quantify associated uncertainty. The coupling with gwflow enables spatially distributed simulation of groundwater heads using cell-based aquifer properties, allowing increased parameterisation complexity compared to SWAT + alone and providing a rigorous test case for DSI. The DSI-based model predicted streamflow and groundwater head comparably to the physical model, based on acceptable model performance metrics. The DSI-based model enables computationally efficient analysis based on relationships between measurements and predictions, making it a practical tool for uncertainty assessment. Unlike the uncertainty bounds derived from the posterior ensemble of the physically-based model (quantified using iterative ensemble method), the DSI-based model's uncertainty bounds captured observed groundwater head values during both calibration and prediction periods, highlighting its potential for decision-support modelling.

Accurate land cover data and inflow estimates are important for hydrological modelling in lake catchments to enable efficient management. Flow model calibration is challenging in data-limited regions or where discharge measurements are difficult, such as braided river systems. This study applies the SWAT+ model to simulate daily flows in the Lake Opuha catchment, New Zealand, characterised by braided rivers flowing into a lake with a controlled outlet. The aim is to assess how flow simulations are influenced by improved land cover classification and calibration using different flow datasets. Objectives include updating bare land classes, developing a lake water balance model, and evaluating the effect of model parameters when using flow gauging station data and lake inflows for calibration. Results show that calibration with both flow gauge and lake water balance data provided reasonable streamflow simulations (calibration period: NSE = 0.63 and 0.58; validation period: NSE = 0.43 and 0.49). However, the model calibrated with lake water balance data achieved a greater reduction in flow prediction uncertainty. This study demonstrates that the lake water balance approach is a suitable method for model calibration in catchments with limited data.

Climate change threatens global agriculture, food security and nutrition. Understanding its regional impacts is necessary to help agricultural sectors adapt and increase their resilience in these changing climate conditions. In New Zealand (NZ), studies on the impacts of climate change on agriculture have been conducted on a limited number of crops, using different methods and without assessing uncertainties. This study aims to bridge these gaps by applying a consistent method of Land Suitability Analysis (LSA) to four key crops for NZ agriculture – apple, cherry, maize and wheat – and assessing suitability robustness. The results show that historical suitability patterns are consistent with current production areas. An increase in suitability is projected for all the crops in almost all of the South Island of NZ, whereas in the North Island, some of the crops are less suitable, highlighting both constraints and opportunities for future NZ agriculture. The robustness of results varies depending on the climate scenario and period considered. In addition, an increase in net irrigation requirements is also projected for the crops, requiring critical management of future water supplies. The limits of the study include the climate data resolution and the omission of the water availability seasonality and other biotic factors, such as diseases. The framework and methodology developed and applied in this study to New Zealand can readily be adapted for use in other regions.

Hydrologic models often exhibit inaccuracies in representing key hydrological fluxes due to uncertainties arising from the necessary simplification of complex processes and input data. Soil databases, commonly used in hydrological models, vary in format, resolution, and parameter range, leading to diverse approaches for generating soil inputs in process-based models. This study employs both linear (FOSM) and non-linear (iES) methods to quantify parameter and prediction uncertainty. A comparative perspective on how these approaches reflect uncertainty when using different soil databases is provided. The study area is the Mohaka catchment with an area of 2,428 km2, situated within the Hawke’s Bay Region of New Zealand. Four different soil databases were used in this study (FSL, S-map, HWSD, and ISRIC) with different spatial resolutions and the number of soil units covering the catchment. Although similar model evaluation metrics were obtained for streamflow simulation using the different soil databases, flow prediction uncertainty varied significantly for average, low, and high flows. For example, low and high flow predictions showed particularly high uncertainties for the global, low-resolution ISRIC database. Conversely, the local soil database S-map produced the lowest uncertainty range for low and high flow conditions. These findings highlight that while different soil databases may yield similar performance statistics during calibration, selecting those that minimise variance in key predictions can improve the reliability of model predictions. The findings emphasise the importance of selecting an appropriate soil database to enhance model reliability for the purpose under consideration.

IntroductionAgriculture in New Zealand (NZ) is facing major disruptions due to the impacts from change drivers, such as climate, environmental regulations, and emerging technologies. Strategies to respond to the risks and opportunities associated with these disruptors are needed to transform and strengthen agriculture to achieve economic and environmental objectives. Focusing on the arable sector is of particular importance as it plays a crucial role to ensure carbon neutrality, profitability, and food security. In this paper, we aim to explore potential pathways and interventions to achieve sustainable and resilient arable agriculture by 2050.MethodsWorking closely with stakeholders from the arable sector, critical scenarios related to food security, climate change mitigation and alternative protein production were co-designed. A decision support tool (DST) that integrates economic, environmental, and production data at the national scale was used to simulate the scenarios.ResultsResults suggest great opportunities for the sector to change and grow. Enhancing food security by producing 700 k tonnes of wheat (i.e., an extra 25 k hectares) and introducing this wheat in a Dairy livestock system could reduce carbon equivalent biogenic emissions by a factor of eight while using one-third less water for irrigation than is normally used for dairying. Complementing animal diets with 30% locally grown grains and reducing the herd by 10% achieves NZ emissions targets for 2050. Developing a pea and fava bean protein extraction market, with the implementation of a new extraction facility (processing 15 k tonne of peas/year), increase in productivity, area planted, and value (yields up from 3.5 to 5 t/ha; value rise from $960/t to $1,200/t; and land area increase to 25,000 ha) would result in a significant growth in arable agriculture profitability ($375 million) and emissions reductions.DiscussionBeyond these quantitative insights, the study demonstrates the value of participatory modelling as a policy-support mechanism: by aligning scientific outputs with stakeholder knowledge, the DST strengthens evidence-based dialogue on land-use planning, regional diversification, and the transition toward carbon-neutral agriculture.

The effective removal of excess heavy metals from surface stormwater is an important environmental goal due to their potential toxicity to aquatic organisms. In-channel stormwater treatment systems (ICSTS) are often used to remove pollutants from stormwater-impacted streams. However, the impact of hydraulic conditions on treatment performance is not well characterised. This research investigates the impact of varying groundwater conditions and bed media hydraulic conductivity on the dynamics of aluminium (Al), copper (Cu), and zinc (Zn) in ICSTS. Experiments conducted in a 19-m flume with gravel, bed media, and surface water under seepage, drainage, and neutral groundwater conditions revealed significant variations in heavy metal retention and release. Under groundwater seepage, there was an average decrease of dissolved Zn in the outlet and an increase in both total and dissolved Cu (5% for Zn; 16% for Cu) when using high hydraulic conductivity media (HH). Low hydraulic conductivity media (LH) under seepage led to a greater increase of dissolved and total Zn and Cu (7% for Zn; 44%–56% for Cu). Under drainage conditions, there was a decrease in dissolved Zn and Cu loads (14% for Zn; 15%–18% for Cu) with HH media and greater variation in pH and redox potential (Eh). Drainage with LH media resulted in lower Zn loads (8%) and an increase in total and dissolved Cu loads (34%–65%). Lower Zn concentrations were also observed in the groundwater (25%–46% decrease) after draining through the bed media, while Cu increased around 200% but only when using LH media. Total aluminium increased in concentration and loads while dissolved Al decreased in all scenarios. This research highlights the importance of designing ICSTS that promote drainage and high hydraulic conductivity bed sediment to enhance metal retention. It also emphasises the need for ongoing monitoring and maintenance to prevent clogging, contaminant release, and long-term performance decline.

The increasing frequency of urban flooding due to climate-induced extreme rainfall highlights the critical need for adaptive emergency preparedness. Maintaining public access to essential services during such events is critical, yet flood risks to the transport network can compromise public safety and mobility. This study employed a combined depth-velocity stability function to assess the risks posed to individuals navigating floodwaters and evaluates accessibility to key service points using basic risk-avoidance criterion. Transport network analysis compares the no-flood, depth-only and depth-velocity risk scenarios. Analysis indicates that risk assessments solely based on flood depth significantly underestimate localised risk in urban environments. At the flood peak, high-risk areas for vehicles and pedestrians are underestimated by 18.2% and 83.3%, respectively, while these increase to 36.4% and 240.0% for medium-risk areas. Applying depth-velocity thresholds determined the obstructed roads and inaccessible zones. Risk-adjusted alternative routes were generated considering the obstructions, providing viable paths for the public to use during the flood peak. The integrated approach, combining flood modelling, stability functions and network analysis offers a framework that can significantly contribute to the improvement of risk resilience and transport management for flood-prone cities.

In-channel water treatment systems remove excess nutrients through biological, chemical, and physical processes associated with the hyporheic zone. However, the impact of surface and groundwater interactions on these treatment processes is poorly understood. This research aims to assess the influence of varying groundwater conditions (neutral, drainage water, and groundwater seepage) and different bed sediment hydraulic conductivities on nitrogen and phosphorus dynamics in in-channel treatment systems. A flume containing bed sediment was used to study changes in surface water quality under different groundwater and bed sediment conditions. Compared to inlet and outlet concentrations, dissolved reactive phosphorus (DRP) and ammoniacal nitrogen (NH4-N) levels in the surface water increased by 11-65% and 10-51%, respectively, while nitrate (NO3-N) concentrations decreased by 11% under groundwater seepage conditions. The increase in NH4-N was due to ammonification, while the decrease in NO3-N was due to denitrification and mixing and dilution with the groundwater. The upward groundwater flux through the bed sediment transported both DRP and NH4-N into the surface water. Low hydraulic (LH) conductivity sediment led to greater changes in nutrient concentration than high hydraulic (HH) conductivity sediment (DRP increased by 65% and NH4-N by 51% for LH, compared to 11% and 10% for HH, respectively). However, HH conductivity sediment led to greater variations in pH and Eh values. The findings could assist the design and monitoring of in-channel treatment systems where groundwater and surface water interact.

The contribution of ecotoxic dissolved metals from metallic roofs into urban waterways is a global issue. Identifying the specific origin of dissolved metals is critical to enabling appropriate stormwater management approaches that can provide the intended outcome of cleaner urban waterways. An event load pollutant model, Modelled Estimates of Discharges for Urban Stormwater Assessments (MEDUSA2.0), was used to predict the zinc load contributed from individual roof surfaces, under a wide range of rainfall conditions. Zinc was chosen as the pollutant of most concern given the extensive area of zinc-based roof surfaces, and the prevalence and mobility of zinc within urban waterways. The model categorized each roof by surface material and condition, and was run for individual rain events across multiple years to illustrate the influences on zinc loads from both surface type and rainfall conditions. Scenarios of future management were also assessed through the model to compare their benefits in terms of load reductions against the current baseline loadings. To understand how the load prediction and scenario modelling can provide valuable guidance for stormwater management decision-makers, the model was applied to a large urban catchment in Christchurch, New Zealand. Seven representative subcatchments of the varying proportions of industrial, commercial and residential land use type were also modelled to compare zinc loads generated. Results showed that an individual catchment's composition of roof types was the main driver of zinc load generation rather than the catchment's land use type. The modelled management scenarios demonstrated that reductions of 30% zinc could be achieved by changing only 4-13% of a subcatchment's unpainted zinc-based roof surfaces.

Policy must address drivers, not just symptoms, of subsidence.

Future changes in land use, climate and downstream water demand can impact reservoir water supply performance. However, a comprehensive assessment that considers these factors poses challenges as it requires complex scenario simulations. To improve our understanding of potential combined effects and to facilitate analyses of reservoir performance, the Soil and Water Assessment Tool has been coupled with genetic optimization and applied to a case study, the Nuicoc multipurpose reservoir in Vietnam. Optimization analyses under a range of scenarios show that despite greater future rainfall, climate change combined with increases in urban area and agriculture resulted in 1-10% and 4-28% lower reliability and resilience, respectively, compared with the baseline. Reservoir sedimentation led to a vulnerability index increase of 0.1-10.5 and 150-400 Mm(3)/year greater water spillage. Reservoir performance can be improved by adjusting water allocation policies and best management practices in the watershed.

Agricultural systems have entered a period of significant disruption due to impacts from change drivers, increasingly stringent environmental regulations and the need to reduce unwanted discharges, and emerging technologies and biotechnologies. Governments and industries are developing strategies to respond to the risks and opportunities associated with these disruptors. Modelling is a useful tool for system conceptualisation, understanding, and scenario testing. Today, New Zealand and other nations need integrated modelling tools at the national scale to help industries and stakeholders plan for future disruptive changes. In this paper, following a scoping review process, we analyse modelling approaches and available agricultural systems' model examples per thematic applications at the regional to national scale to define the best options for the national policy development. Each modelling approach has specificities, such as stakeholder engagement capacity, complex systems reproduction, predictive or prospective scenario testing, and users should consider coupling approaches for greater added value. The efficiency of spatial decision support tools working with a system dynamics approach can help holistically in stakeholders' participation and understanding, and for improving land planning and policy. This model combination appears to be the most appropriate for the New Zealand national context.

Stormwater control measures (SCMs) are essential to manage runoff in urban areas. Mussel shell waste has been recently proposed as sustainable treatment media in SCM to remove metals from runoff. In this study, a group of laboratory-scale column experiments were conducted to investigate the use of crushed mussel shell waste to remove dissolved zinc from actual roof runoff during different filtration flow rates (1, 3, 5, 10 L/min). Heat-treated mussel shells (TMS) and untreated mussel shells (UTMS) were utilized as treatment media with two column depths (1.0 m and 0.8 m). The microstructures and chemical characteristics of TMS and UTMS were examined by using a group of Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) tests before and after the filtration process, and water samples were analyzed by using an Inductively Coupled Plasma Mass Spectrometry (ICP-MS) instrument. TMS and UTMS showed consistent high removal efficiency for dissolved zinc with (>98%) efficiency during 1 L/min filtration rate. The average removal performance was estimated at >94% and >82% for the 1.0 m and 0.8 m column depths of TMS media, and >92% and >72% for the 1.0 m and 0.8 m depths of UTMS media, respectively. The heat treatment improved the removal of zinc with significant statistical difference (i.e. p < 0.05) during short contact times (0.8 m depth, and high filtration rates). Mussel shell waste showed practical removal performance of zinc even during high filtration rates (>5 L/min). Mussel shell waste showed potential benefits as a sustainable and cost-effective filtration media for removal of dissolved zinc in future stormwater systems.

There is a clear research gap in understanding how future pathways and disruptions to the New Zealand (NZ) agricultural system will have an impact on the environment and productivity. Agriculture is in a period of significant change due to market disruptions, climate change, increasingly stringent environmental regulations, and emerging technologies. In NZ, agriculture is a key sector of the economy, therefore government and industry need to develop policies and strategies to respond to the risks and opportunities associated with these disruptors. To address this gap, there is a need to develop an assessment tool to explore pathways and interventions for increasing agricultural profitability, resilience, and sustainability over the next 5–30 years. A decision support tool was developed through Stella Architect, bringing together production, market values, land use, water use, energy, fertiliser consumption, and emissions from agricultural sectors (dairy, beef, sheep, cereals, horticulture, and forests). The parameters are customisable by the user for scenario building. Two future trend scenarios (Business as usual, Optimisation and technology) and two breakaway scenarios (Carbon farming, Reduction in dairy demand) were simulated and all met carbon emissions goals, but profitability differed. Future environmental regulations can be met by adjusting levers associated with technology, carbon offsets, and land use. The model supports the development and assessment of pathways to achieve NZ’s national agriculture goals and has the potential to be scaled globally.

Sedimentation is one of the major challenges for the long-term sustainable operation of a hydropower reservoir. Trapping of sediment reduces its storage capacity and consequently diminishes hydropower production. Here first the development of a REServoir Sediment MANagement routine (ResSMan) and its integration into a hy-drological model, the Soil and Water Assessment Tool (SWAT) is presented. ResSMan has functions to determine sediment accumulation in multiple reservoirs, and its impacts on the storage capacity and hydropower pro-duction under user-specified operation policies. It allows to compute the restoration of storage capacity due to the removal of sediment by flushing, i.e. the removal of sediment from a reservoir by passing water and sediment through the low-level outlets, and sluicing, i.e. passing sediment before suspended sediment solids have settled down in the reservoir. The capabilities (flushing and sluicing) of ResSMan were evaluated through a comparison with the Sediment Simulation Screening (SedSim) model, a well-tested sediment management simulation model and the resulting R2 values of 0.99 validated its capabilities. Subsequently, ResSMan was applied to assess and manage reservoir sedimentation using different management strategies in a complex system of 19 reservoirs (12 currently existing) in the Sesan and Srepok (2S) basin of the Mekong River for 2021-2120. The unregulated mean annual sediment yield at the outlet of the 2S basin was estimated as 7.24 million tonnes/year (Mt/y) and it will be reduced to 0.11 Mt/y due to the operation of the 19 reservoirs. In total 924 Mt of sediment will accumulate in these 19 reservoirs over 100 years, resulting in an average trapping efficiency of 74% (ranging from 11% to 97%). System-wide sediment management coordination simulations demonstrated that bi-annually and 5-yearly flushing of alternate reservoirs are effective options for efficiently releasing sediment in the 2S basin. However, the use of frequent flushing (annual or bi-annual) may be more favourable to minimize adverse impacts due to release of higher sediment loads on downstream ecosystems. The analysis is an initial step towards the coor-dination of sediment management plans and policies for the multi-reservoirs system in the Mekong basin.

INTRODUCTION Stormwater treatment systems (STSs) are being integrated across our urban landscapes in New Zealand and around the world with the intent of contaminant removal. Consistent downstream water quality and ecological health improvements are expected to follow STS installation; however, this is often not the case due to variability in treatment performance. A major source of variability in treatment performance comes from variation in contaminant load, which is a function of local climate and storm attributes as well as activities and changes in a catchment (Jefferson et al., 2017). Another source is variation in treatment systems themselves, which can be as wide ranging as the temporal differences in maintenance, age, and installation quality between units, and as detailed as the range of contaminants removed at a given location compared to another. Quantification of the variability witnessed in treatment performance and the determination of its sources can not only help designers to build and select more optimal treatment systems for a given location, but can also help planners set realistic expectations to improvements in water quality from investment. Zinc is a priority metal of concern in Christchurch’s urban waterways as identified by Christchurch City Council, and non-point source runoff from roofs contributes a substantial amount of the total load (Margetts and Marshall, 2018). While zinc occurs naturally in the aquatic environment, overexposure through bioaccumulation can lead to adverse health effects in humans and is toxic to aquatic organisms from microorganisms to vertebrates (Harding, 2005, Seto et al., 2013). Recent research suggests crushed mussel shells have a capability of removing dissolved zinc from stormwater runoff (Bremner et al., 2020). This ongoing study seeks to identify and quantify the impact of the most influential variables affecting the removal of dissolved zinc within two proprietary, at-source STSs: the Storminator™ developed at the University of Canterbury (UC), and the StormFilter™ sold by Stormwater 360.

•Urban carparks produce runoff with different pollutant characteristics.•Vehicle traffic influence contaminant concentrations in first-flush stormwater.•The highest pollutant yields originated from a high-traffic industrial carpark.•Traffic characteristics influence metal partitioning and metal species ratios.•Design of stormwater treatment systems should consider carpark traffic and characteristics.

Untreated metal roof runoff can contribute elevated zinc and copper to receiving waterways, with associated ecotoxic impacts on the aquatic ecosystem. The majority of the metals in roof runoff are in dissolved form, which can be difficult to remove with conventional stormwater treatment systems. Treatment materials such as limestone and zeolite are capable of removing dissolved metals, but most research to date has only assessed the performance of such materials using synthetic runoff and long contact times. This study assessed the performance of limestone, zeolite and waste mussel shells in a vertical downpipe configuration with short contact time using actual metal roof runoff. Metal removal was compared under flowrates of 1 L/min and 3 L/min, material compaction level (less/more), and material depth (1 m and 0.5 m). A 93%–99% reduction was achieved in dissolved zinc by all treatment materials for all flowrates, compaction levels and depths. Higher variance in dissolved Cu removal rates were observed, with material depth found to have the greatest influence on performance: 84%–99% removal rates were achieved by the three materials at 1 m depth, but for 0.5 m depths, 44%–99%, 34%–92%, and 47%–93% removal were achieved by zeolite, limestone, and waste mussel shells respectively. The mussel shell removal performance was comparable to zeolite and limestone, yet it provides the added benefit of using a waste resource that would otherwise be disposed of to landfill. While this study demonstrates the potential of waste mussel shells for dissolved metal treatment, long term field trials and experimental analysis of the removal mechanisms of waste mussel shells would enable optimization of this treatment technology.

Southeast Asia’s 3S river basin, which comprises the Sesan, Srepok and Sekong rivers, is an important tributary basin of the Mekong River. The 3S rivers rise in Lao PDR and Vietnam, and flow through Cambodia, where they join before discharging to the Mekong. Vietnam has the highest forest loss and the most (46) dams. Lao PDR retains much of its forest, however, 15 hydropower dams are either being built or licensed for construction in its portion of the Sekong river basin. Cambodia is planning multiple dams on each of the three rivers’ lower reaches. Cambodia’s dams will have the greatest impact on system connectivity and thus the 3S’s important migratory fishery. The flow regime of all three rivers has been altered as dam operations have increased dry season flow and reduced wet season flow. Increased Total Suspended Solids, Nitrate\Nitrite and Total Phosphorous have been observed in the Srepok River in Vietnam, whist there has been little change elsewhere. The three countries are at different stages of developing their national water governance frameworks, with Lao PDR the least developed. A range of climate and development scenarios have been generated for the 3S region. The 3S is highly vulnerable to climate change due to projected increases in temperature and the frequency of extreme floods and droughts. As the transboundary impacts of development in the 3S become clearer, so too does the need for cooperative management of the 3S basin and its water resources, to ensure a sustainable future as the climate changes.

Ovulation and fertility can be improved by weight loss in obese women with Polycystic Ovarian Syndrome (PCOS). The aim of this study was to investigate the effectiveness of a twelve-week supervised exercise program in combination with dietary restrictions for obese women with PCOS. The study is a quasi-experimental research and used an experimental pre- and post-test design. Fifteen women recruited from Fertility Clinic, Jessops Hospital for Women, Sheffield took part in this study. Respiratory exchange ratio (RER), heart rate, perceived exertion (RPE), and Houston non-exercise activity code were recorded. Height, weight, and body girth measurements were taken to calculate body mass index, fat percentage, and lean body weight. The intervention group lost an average of 3.1 kg and gained 3.45 kg of lean body weight. Loss of fat percentage was 12.1%. No significant difference was found in the control group. The RER and heart rate value decreased for the same workload in the intervention group, indicating higher tolerance towards exercise intensity. However, the changes for both groups were not significant. The average group compliance rate was 53% (at least two sessions per week). Bearing in mind the small sample size (n=4) for control, the improvement in fitness, significant weight loss, and body composition change (increase in fat-free mass) was achieved in this study. Twelve weeks of exercise, combined with dietary advice, were sufficient to benefit PCOS obese women. The research has achieved a commendable weight-loss objective and has demonstrated increases in standards of fitness among obese women.