Balance of Catchment and Offshore Nutrient Loading and Biogeochemical Response in Four New Zealand Coastal Systems: Implications for Resource Management

Nutrient mass balance analyses are a way of obtaining ‘whole system’ viewpoints on coastal biogeochemical functions and their forcing. Seasonal mass balances are presented for four large bay systems in New Zealand (NZ), with the aim of showing how they can inform coastal management. Freshwater volumes, and surface and groundwater, wastewater and atmospheric inorganic and organic nitrogen (N) and phosphorus (P) were balanced with levels of salinity, N and P from ocean surveys, used to determine non-conservative N and P fluxes and, via stoichiometry, carbon (C) fluxes. For Golden and Tasman Bays and Hauraki Gulf, exchange with adjacent shelf waters usually dominated total N supply (80–85%). In contrast, for the Firth of Thames, 51% of total N and 85% of dissolved inorganic N supply originated from its agricultural catchment. Net ecosystem metabolism (NEM; balance of autotrophy and heterotrophy) of Golden and Tasman Bays and Hauraki Gulf was usually nearly balanced. In contrast, Firth NEM was highly seasonally variable, often exhibiting strong heterotrophy coincident with expression of respiration-related stressors (low O₂ and high DIC/low pH). Denitrification accounted for about 51% of total N export across the four systems, signifying its importance as a eutrophication-regulating ecosystem service. Budgets made 12 years apart in the Firth showed decreased denitrification efficiency, coincident with large increases in system N and phytoplankton. The findings for land-ocean nutrient balance, NEM and denitrification showed how mass balance budgeting can inform coastal management, including inventories of nutrient inputs, balances of oceanic and terrestrial nutrient loading, and potential for risk associated with biogeochemical responses.     

Using Simple Dilution Models to Predict New Zealand Estuarine Water Quality

A tool based on simple dilution models is developed to predict potential nutrient concentrations and flushing times for New Zealand estuaries. Potential nutrient concentrations are the concentrations that would occur in the absence of nutrient uptake or losses through biogeochemical processes, and so represent the pressure on a system due to nutrient loading. The dilution modelling approach gives a single time- and space-averaged concentration as a function of flow and nutrient input, with the capability to include seasonal nutrient and flow differences. This tool is intended to be used to identify estuaries likely to be highly sensitive to current nutrient loads based on their physical attributes, or to quickly compare the effects of different land-use scenarios on estuaries. The dilution modelling approach is applied both to a case study of a single New Zealand estuary, and used in a New Zealand-wide assessment of 415 estuaries. For the NZ-wide assessment, annual nutrient loads to each estuary were obtained from a GIS-based land-use model. Comparison with measured data shows that the predicted potential nitrate concentrations are significantly correlated with, but higher than, measured nitrate values from water quality sampling time series. This is consistent with expectations given that the measured concentrations include the effects of nitrogen uptake and loss. The estuary dilution modelling approach is currently incorporated into the GIS-land use model, and is also available as a web-app for assessing eutrophication susceptibility of New Zealand estuaries.     

Formation Mechanism of Mud Bank Along the Southwest Coast of India

Mud bank formation during the southwest monsoon along the southwest coast of India remains an enigma to the researchers and coastal community in spite of several earlier studies. The present study attempts to unravel the mystery through a high-frequency, season-long time-series observation at Alappuzha, located at the southern part of the west coast of India, a region of frequent occurrence of mud bank. Using 7-month-long weekly time-series observation, we identified strong winds and high waves associated with onset of the southwest monsoon and subsequent three episodic atmospheric low-pressure events (LPEs).With the help of in situ time-series data, we show that the strong winds and high waves associated with southwest monsoon pre-conditions the near shore bottom sediment to bring it into suspension. The high amplitude waves associated with the southwest monsoon, while propagating from the deep water to shallow water region, interact with the bottom initiating bottom-sediment movement and its suspension due to wave refraction and shoaling. The sporadic occurrence of the atmospheric LPEs enhances the process of suspension of bottom sediment in the near shore region leading to the formation of fluid mud. Simulations with a cohesive sediment transport model yielded realistic estimates of sediment transport, in the presence of an onshore current, a pre-requisite for transporting the fluid mud toward the coast. The prevailing onshore upwelling current during the southwest monsoon provides the favorable pre-requisite conditions for transporting the fluid mud through depression channel network towards the coast. Once sufficient quantity and thickness of fluid mud is accumulated in the near shore region, it acts as a wave damper for subsequent high monsoon waves, as indicated by the time-series wave data, leading to the formation of tranquil mud bank region. Depression channel networks extending from the shelf to the coast off Alappuzha, Kochi, Ponnani, Beypore, and Ullal were found in the bathymetric charts, thus explaining why mud banks occur only at few locations in spite of the prevalence of similar monsoon conditions.     

A non-hydrostatic model for the numerical study of landslide-generated waves

This paper proposes and demonstrates a two-layer depth-averaged model with non-hydrostatic pressure correction to simulate landslide-generated waves. Landslide (lower layer) and water (upper layer) motions are governed by the general shallow water equations derived from mass and momentum conservation laws. The landslide motion and wave generation/propagation are separately formulated, but they form a coupled system. Our model combines some features of the landslide analysis model DAN3D and the tsunami analysis model COMCOT and adds a non-hydrostatic pressure correction. We use the new model to simulate a 2007 rock avalanche-generated wave event at Chehalis Lake, British Columbia, Canada. The model results match both the observed distribution of the rock avalanche deposit in the lake and the wave run-up trimline along the shoreline. Sensitivity analyses demonstrate the importance of accounting for the non-hydrostatic dynamic pressure at the landslide-water interface, as well as the influence of the internal strength of the landslide on the size of the generated waves. Finally, we compare the numerical results of landslide-generated waves simulated with frictional and Voellmy rheologies. Similar maximum wave run-ups can be obtained using the two different rheologies, but the frictional model better reproduces the known limit of the rock avalanche deposit and is thus considered to yield the best overall results in this particular case.     

Precursory slope distress prior to the 2010 Mount Meager landslide,British Columbia

In 2010, the south flank of Mount Meager failed catastrophically, generating the largest (53 ± 3.8 × 10⁶ m³) landslide in Canadian history. We document the slow deformation of the edifice prior to failure using archival historic aerial photographs spanning the period 1948–2006. All photos were processed using Structure from Motion (SfM) photogrammetry. We used the SfM products to produce pre-and post-failure geomorphic maps that document changes in the volcanic edifice and Capricorn Glacier at its base. The photographic dataset shows that the Capricorn Glacier re-advanced from a retracted position in the 1980s then rapidly retreated in the lead-up to the 2010 failure. The dataset also documents 60 years of progressive development of faults, toe bulging, and precursory failures in 1998 and 2009. The 2010 collapse was conditioned by glacial retreat and triggered by hot summer weather that caused ice and snow to melt. Meltwater increased pore water pressures in colluvium and fractured rocks at the base of the slope, causing those materials to mobilize, which in turn triggered several secondary failures structurally controlled by lithology and faults. The landslide retrogressed from the base of the slope to near the peak of Mount Meager involving basement rock and the overlying volcanic sequence. Elsewhere on the flanks of Mount Meager, large fractures have developed in recently deglaciated areas, conditioning these slopes for future collapse. Potential failures in these areas have larger volumes than the 2010 landslide. Anticipated atmospheric warming over the next several decades will cause further loss of snow and glacier ice, likely producing additional slope instability. Satellite- and ground-based monitoring of these slopes can provide advanced warning of future landslides to help reduce risk in populated regions downstream.     

Implementing landslide path dependency in landslide susceptibility modelling

Landslide susceptibility modelling—a crucial step towards the assessment of landslide hazard and risk—has hitherto not included the local, transient effects of previous landslides on susceptibility. In this contribution, we implement such transient effects, which we term “landslide path dependency”, for the first time. Two landslide path dependency variables are used to characterise transient effects: a variable reflecting how likely it is that an earlier landslide will have a follow-up landslide and a variable reflecting the decay of transient effects over time. These two landslide path dependency variables are considered in addition to a large set of conditioning attributes conventionally used in landslide susceptibility. Three logistic regression models were trained and tested fitted to landslide occurrence data from a multi-temporal landslide inventory: (1) a model with only conventional variables, (2) a model with conventional plus landslide path dependency variables, and (3) a model with only landslide path dependency variables. We compare the model performances, differences in the number, coefficient and significance of the selected variables, and the differences in the resulting susceptibility maps. Although the landslide path dependency variables are highly significant and have impacts on the importance of other variables, the performance of the models and the susceptibility maps do not substantially differ between conventional and conventional plus path dependent models. The path dependent landslide susceptibility model, with only two explanatory variables, has lower model performance, and differently patterned susceptibility map than the two other models. A simple landslide susceptibility model using only DEM-derived variables and landslide path dependency variables performs better than the path dependent landslide susceptibility model, and almost as well as the model with conventional plus landslide path dependency variables—while avoiding the need for hard-to-measure variables such as land use or lithology. Although the predictive power of landslide path dependency variables is lower than those of the most important conventional variables, our findings provide a clear incentive to further explore landslide path dependency effects and their potential role in landslide susceptibility modelling.     

Influence of Geo-environmental and Chemical Factors on Thermotolerant Coliforms and <Emphasis Type="Italic">E.coli</Emphasis> in the Groundwater of Central Kerala

Geo-environmental studies in parts of Ernakulam district (Kerala, India) were carried out. The study area comprises of sedimentary (Limestone, sandstone, Clay and Lignite) and crystalline (Charnockite and gneisses) rocks. The sedimentary terrain is characterized by confined and unconfined aquifers. In hard crystalline formations groundwater occurs under phreatic conditions in the shallow weathered portions and under semi confined to confined conditions in the deep-seated fractures. The study area is demarcated into five areas based on soil types. Climate is hot humid to hot summer with heavily raining monsoon. Two major rivers Periyar and Muvattupuzha drain through the area. Agricultural and industrial activities are prevalent in Ernakulam district. The major cause of pollution in the study area is due to the presence of coliforms. Detailed investigations carried out to identify the coliforms indicated spatial and seasonal changes in the distribution pattern. Monsoon and post monsoon showed significantly high total coliforms compared to pre-monsoon. Thermo-tolerant coliforms is high during monsoon season. This seasonal change could be due to the effect of rainfall, overland flow, nutrient load and temperature change. Wide variations in the coliform counts are observed in wells situated near rivers, canals, paddy fields and in water bodies lying close to pilgrimage center, fertilizer industry, and public places. It is noticed that the chemical characteristics of the groundwater influence the coliform survival. pH, nitrite, bicarbonate, hardness, and alkalinity play a significant role in controlling coliform count. At the outset, the study highlighted the impact of anthropogenic activities on ground water in a coastal district of Kerala state.     

Prediction of fog/visibility over India using NWP Model

Frequent occurrence of fog in different parts of northern India is common during the winter months of December and January. Low visibility conditions due to fog disrupt normal public life. Visibility conditions heavily affect both surface and air transport. A number of flights are either diverted or cancelled every year during the winter season due to low visibility conditions, experienced at different airports of north India. Thus, fog and visibility forecasts over plains of north India become very important during winter months. This study aims to understand the ability of a NWP model (NCMRWF, Unified Model, NCUM) with a diagnostic visibility scheme to forecast visibility over plains of north India. The present study verifies visibility forecasts obtained from NCUM against the INSAT-3D fog images and visibility observations from the METAR reports of different stations in the plains of north India. The study shows that the visibility forecast obtained from NCUM can provide reasonably good indication of the spatial extent of fog in advance of one day. The fog intensity is also predicted fairly well. The study also verifies the simple diagnostic model for fog which is driven by NWP model forecast of surface relative humidity and wind speed. The performance of NWP model forecast of visibility is found comparable to that from simple fog model driven by NWP forecast of relative humidity and wind speed.     

Tellurium,selenium and cobalt enrichment in Neoproterozoic black shales,Gwna Group,UK: Deep marine trace element enrichment during the Second Great Oxygenation Event

Black shales of the late Neoproterozoic Gwna Group (570–580 Ma), UK, contain enrichments of tellurium (Te), selenium (Se) and cobalt (Co) relative to average shale compositions. The Te and Co enrichments bear comparison with those of ferromanganese crusts in the modern deep ocean. Gwna Group deposition coincides with the Second Great Oxidation Event, which had a significant effect on trace element fixation globally. Selenium and Te concentrations within these black shales indicate increased continental weathering rates, high biological productivity and corresponding increases in atmospheric O₂ concentrations. Cobalt, nickel (Ni) and arsenic (As) enrichments in this succession are secondary mineralisation phases. Demand for many of the trace elements found enriched in the Gwna Group black shales make their mechanisms of accumulation, and variations through the geological record, important to understand, and suggests that new resources may be sought based on black shale protoliths from this period.