Improving and parameterising nitrogen and phosphorus modelling for application of LUCI in New Zealand

<p>Over the last 50 years freshwater and marine environments have become severely impaired due to contamination from pathogens, heavy metals, sediment, industrial chemicals and nutrients (MEA 2005b). In many countries, including New Zealand, increased nitrogen (N) and phosphorus (P) loading to terrestrial and freshwater environments from diffuse nutrient sources are of particular concern (MEA 2005a; PCE 2015b; Steffen et al. 2015) and many governments now mandate control of diffuse nutrient loss to water. Water quality models are invaluable tools that can assist with decision making around this widespread issue through exploration of the current situation and future scenarios. Many water quality models exist, functioning at a variety of temporal and spatial scales and varying in detail and complexity. However, few, if any, simultaneously represent sub-field to catchment scale processes and outcomes, both of which are required to fully address water quality issues associated with diffuse nutrient sources. Those that do, likely require extensive time and expertise to operate. Water quality models embedded in the Land Utilisation and Capability Indicator (LUCI), an ecosystem service decision support framework, offer the opportunity to overcome these limitations. Being highly spatially explicit, yet straightforward to use, they can inform and assist individual land owners, catchment managers and other stakeholders with planning, decision making and management of water quality at sub-field to landscape scale. To model diffuse nutrient losses LUCI, like many catchment scale water quality models, requires some form of estimated nutrient loss, or export coefficient, from land units within the catchment of interest. To be representative export coefficients must consider climate, soil, topography, and land cover and management variables. A number of methods of export coefficient derivation exist, although generally they consider only very limited geo-climatic, land cover and land management variables. The principal aim of this study is development of algorithms capable of calculating New Zealand site specific N and P export coefficients from detailed geo-climatic, land cover and land management variables, for application in LUCI water quality models. Algorithms for pastoral land cover are developed from a large dataset comprising real pastoral farm input and output data from nutrient budgeting model OVERSEER. Algorithms are extended to land covers other than pasture, albeit in a limited manner. This is achieved through rescaling of the pastoral algorithms to account for relative differences in literature reported N and P losses from pasture and a variety of other New Zealand land covers. Application of the developed algorithms in LUCI water quality models results in positioning of export coefficients at the DEM grid square scale (≤ 15 m x 15 m for New Zealand). In addition, intra-basin configuration is considered in LUCI, at the same grid square scale, as water and nutrient flows are cascaded through the catchment. Application of the export coefficient calculating algorithms are applied to two contrasting New Zealand catchments. Tuapaka catchment, an 85ha agricultural foothill catchment in Manawatu, North Island, and Lake Rotorua catchment, a 502 km2 volcanic, mixed land cover catchment in Bay of Plenty, North Island. This research is supported by Ravensdown, a farmer owned co-operative, which plans to use LUCI extensively to advise and assist farmers with water quality issues. The ability to model mitigation strategies in LUCI is an important capability. Therefore, this research also includes a review of five particularly important on-farm mitigation strategies, which will later be used by the wider LUCI development team to assist with better parameterisation and improved performance of mitigation options in LUCI. Application of the developed algorithms at farm to catchment scale in LUCI results in considerably more nuanced, detailed maps and data showing N and P sources and pathways, compared to LUCI’s previously used ‘one export coefficient per land cover’ approach. Although results indicate absolute nutrient loss values are not always ‘correct’ compared to either OVERSEER predictions or in-stream water quality measurements, these differences appear comparable to those seen with similar water quality models. In addition, the issue of representativeness of OVERSEER predictions and in-stream water quality measurements exists. Nevertheless improvement to absolute predictions is always an aim. This research indicates further improvements to LUCI water quality predictions could result from refinement of both pastoral and other land cover algorithms, and from improved representation of attenuation processes in LUCI, including groundwater representation. However, lack of measured on-land and in-stream N and P loss data is a major challenge to both algorithm refinement and to evaluation of results. In addition, more detailed spatial data would provide more nuanced results from algorithm application. Although the algorithm application context in this research is LUCI water quality models applied in New Zealand, this does not preclude application of the developed algorithms in other export coefficient based, catchment scale water quality models. Using spatial data pertaining to climate, soil, topographic and land management variables, land units of combined variables can be identified and the algorithms applied, resulting in explicitly positioned export coefficients that can be fed into the catchment scale water quality model of interest. Therefore, developments made here potentially represent a wider contribution to catchment scale modelling using export coefficients.</p>

Improving and parameterising nitrogen and phosphorus modelling for application of LUCI in New Zealand

<p>Over the last 50 years freshwater and marine environments have become severely impaired due to contamination from pathogens, heavy metals, sediment, industrial chemicals and nutrients (MEA 2005b). In many countries, including New Zealand, increased nitrogen (N) and phosphorus (P) loading to terrestrial and freshwater environments from diffuse nutrient sources are of particular concern (MEA 2005a; PCE 2015b; Steffen et al. 2015) and many governments now mandate control of diffuse nutrient loss to water. Water quality models are invaluable tools that can assist with decision making around this widespread issue through exploration of the current situation and future scenarios. Many water quality models exist, functioning at a variety of temporal and spatial scales and varying in detail and complexity. However, few, if any, simultaneously represent sub-field to catchment scale processes and outcomes, both of which are required to fully address water quality issues associated with diffuse nutrient sources. Those that do, likely require extensive time and expertise to operate. Water quality models embedded in the Land Utilisation and Capability Indicator (LUCI), an ecosystem service decision support framework, offer the opportunity to overcome these limitations. Being highly spatially explicit, yet straightforward to use, they can inform and assist individual land owners, catchment managers and other stakeholders with planning, decision making and management of water quality at sub-field to landscape scale. To model diffuse nutrient losses LUCI, like many catchment scale water quality models, requires some form of estimated nutrient loss, or export coefficient, from land units within the catchment of interest. To be representative export coefficients must consider climate, soil, topography, and land cover and management variables. A number of methods of export coefficient derivation exist, although generally they consider only very limited geo-climatic, land cover and land management variables. The principal aim of this study is development of algorithms capable of calculating New Zealand site specific N and P export coefficients from detailed geo-climatic, land cover and land management variables, for application in LUCI water quality models. Algorithms for pastoral land cover are developed from a large dataset comprising real pastoral farm input and output data from nutrient budgeting model OVERSEER. Algorithms are extended to land covers other than pasture, albeit in a limited manner. This is achieved through rescaling of the pastoral algorithms to account for relative differences in literature reported N and P losses from pasture and a variety of other New Zealand land covers. Application of the developed algorithms in LUCI water quality models results in positioning of export coefficients at the DEM grid square scale (≤ 15 m x 15 m for New Zealand). In addition, intra-basin configuration is considered in LUCI, at the same grid square scale, as water and nutrient flows are cascaded through the catchment. Application of the export coefficient calculating algorithms are applied to two contrasting New Zealand catchments. Tuapaka catchment, an 85ha agricultural foothill catchment in Manawatu, North Island, and Lake Rotorua catchment, a 502 km2 volcanic, mixed land cover catchment in Bay of Plenty, North Island. This research is supported by Ravensdown, a farmer owned co-operative, which plans to use LUCI extensively to advise and assist farmers with water quality issues. The ability to model mitigation strategies in LUCI is an important capability. Therefore, this research also includes a review of five particularly important on-farm mitigation strategies, which will later be used by the wider LUCI development team to assist with better parameterisation and improved performance of mitigation options in LUCI. Application of the developed algorithms at farm to catchment scale in LUCI results in considerably more nuanced, detailed maps and data showing N and P sources and pathways, compared to LUCI’s previously used ‘one export coefficient per land cover’ approach. Although results indicate absolute nutrient loss values are not always ‘correct’ compared to either OVERSEER predictions or in-stream water quality measurements, these differences appear comparable to those seen with similar water quality models. In addition, the issue of representativeness of OVERSEER predictions and in-stream water quality measurements exists. Nevertheless improvement to absolute predictions is always an aim. This research indicates further improvements to LUCI water quality predictions could result from refinement of both pastoral and other land cover algorithms, and from improved representation of attenuation processes in LUCI, including groundwater representation. However, lack of measured on-land and in-stream N and P loss data is a major challenge to both algorithm refinement and to evaluation of results. In addition, more detailed spatial data would provide more nuanced results from algorithm application. Although the algorithm application context in this research is LUCI water quality models applied in New Zealand, this does not preclude application of the developed algorithms in other export coefficient based, catchment scale water quality models. Using spatial data pertaining to climate, soil, topographic and land management variables, land units of combined variables can be identified and the algorithms applied, resulting in explicitly positioned export coefficients that can be fed into the catchment scale water quality model of interest. Therefore, developments made here potentially represent a wider contribution to catchment scale modelling using export coefficients.</p>

Integrated Surface-Groundwater Modelling of Nitrate Concentration in Mediterranean Rivers, the Júcar River Basin District, Spain

High nutrient discharge from groundwater (GW) into surface water (SW) have multiple undesirable effects on river water quality. With the aim to estimate the impact of anthropic pressures and river–aquifer interactions on nitrate status in SW, this study integrates two hydrological simulation and water quality models. PATRICAL models SW–GW interactions and RREA models streamflow changes due to human activity. The models were applied to the Júcar River Basin District (RBD), where 33% of the aquifers have a concentration above 50 mg NO3−/L. As a result, there is a direct linear correlation between the nitrate concentration in rivers and aquifers (Júcar r2 = 0.9, and Turia r2 = 0.8), since in these Mediterranean basins, the main amount of river flows comes from groundwater discharge. The concentration of nitrates in rivers and GW tends to increase downstream of the district, where artificial surfaces and agriculture are concentrated. The total NO3− load to Júcar RBD rivers was estimated at 10,202 tN/year (239 kg/km2/year), from which 99% is generated by diffuse pollution, and 3378 tN/year (79 kg/km2/year) is discharged into the Mediterranean Sea. Changes in nitrate concentration in the RBD rivers are strongly related to the source of irrigation water, river–aquifer interactions, and flow regulation. The models used in this paper allow the identification of pollution sources, the forecasting of nitrate concentration in surface and groundwater, and the evaluation of the efficiency of measures to prevent water degradation, among other applications.

Numerical simulation of the impact of an integrated renovation project on the Maowei Sea hydrodynamic environment

Integrated renovation projects are important for marine ecological environment protection. Three-dimensional hydrodynamics and water quality models are developed for the Maowei Sea to assess the hydrodynamic environment base on the MIKE3 software with high resolution meshes. The results showed that the flow velocity changed minimally after the project, decreasing by approximately 0.12 m/s in the east of the Maowei Sea area and increasing by approximately 0.01 m/s in the northeast of the Shajing Port. The decrease in tidal prism (~ 2.66 × 106 m3) was attributed to land reclamation, and accounted for just 0.86% of the pre-project level. The water exchange half-life increased by approximately 1 day, implying a slightly reduced water exchange capacity. Siltation occurred mainly in the reclamation and dredging areas, amounting to back-silting of approximately 2 cm/year. Reclamation project is the main factor causing the decrease of tidal volume and weakening the hydrodynamics in Maowei Sea. Adaptive management is necessary for such a comprehensive regulation project. According to the result, we suggest that reclamation works should strictly prohibit and dredging schemes should optimize in the subsequent regulation works.

Water Quality Models and their Use in Monitoring the Quality of Surface Water Bodies

Water quality has been considered as one of the major challenges in water resource management. The main reason of degradation of water quality over the years is anthropogenic activities. Also, the monitoring of surface water bodies is a tedious as well as expensive process. For the depiction of water quality in simple and easy to understand terminology Water Quality Index (WQI) is found to be one of the widely used tool. It provides a transparent picture of the status of the pollution of a water body that is why it has been widely accepted by policy makers as well as other concerned authorities. Many WQI models have been developed throughout the world, using various water quality parameters, different techniques to generate subindices and also involving various mathematical techniques for aggregation of subindices. This paper deals with the comparison of various water quality models-based om number of parameters used, methods to generate subindices, aggregation techniques as well as their application and uses.

Release flux of heavy metals from river sediments at different flow rates

This paper simulates sediment motion under different hydrodynamic conditions, aiming to investigate the release flux of heavy metals in river sediments. During the lab experiments, carried out in a circular rectangular flume device, water velocity in the flume was altered by controlling the gate switch, and the flow rate was controlled from 0 to 1 m/s. Sediment from the Le'an River and chlorine-removed tap water were used as experimental sediment and water, respectively. Through analyses of Cu, Zn, Cd, and Pb concentration in water at different flow rates, the relationship between the release flux (y) of Cu, Zn, Cd, and Pb and the flow rate (x) was established with a fitting error of less than 15%. In order to judge the reliability of the conclusions, experimental results were verified outdoors. The results showed when the sediment particle size is between 0 and 250 μm, within 1 hour, a quadratic polynomial correlation between the release flux of Cu, Cd, and Pb from river sediments and water velocity when the water pH is 5–9 and the flow rate is 0–65 cm/s; when the water pH is 5–9, the flow rate is 0–35 cm/s, the release flux of Zn from river sediments was shown to have a quadratic polynomial relationship with water velocity. The error between the calculated and measured values of heavy metals released from sediment in the Le'an River were within 5–30%. Our results can provide a theoretical reference for the control and treatment of heavy metal pollution in rivers and further improve corresponding water quality models.

Comparing Log-Linear and Best-Fit Models to Evaluate the Long-Term Persistence of Enteric Markers in Sewage Spiked River Water

Water quality models use log-linear decay to estimate the inactivation of fecal indicator bacteria (FIB). The decay of molecular measurements of FIB does not follow a log-linear pattern. This study examined the factors associated with the persistence of Escherichia coli uidA, enterococci 23S rDNA, and Bacteroides thetataiotaomicron 1,6 alpha mannanase in microcosms containing 10% (vol/vol) sewage spiked river water stored at 4°C for up to 337 days. The study estimated the markers' persistence with log-linear models (LLMs) to the best-fit models, biphasic exponential decay (BI3) and log-logistic (JM2) and compared the estimates from the models. Concentrations of B. thetataiotaomicon decreased to levels below detection after 31 days in storage and were not fit to models. BI3 and JM2 were fit to E. coli and enterococci, respectively. LLMs had larger Bayesian information criterion values than best-fit models, indicating poor fit. LLMs over-estimated the time required for 90% reduction of the indicators (T90) and did not consider dynamic rates of decay. Time in storage and indicator species were associated with the persistence of the markers (p &lt; 0.001). Using the T90 values of the best-fit models, enterococci was the most persistent indicator. Our data supports the use of best fit models with dynamic decay rates in water quality models to evaluate the decay of enteric markers.