Search Results (9)

The Temperate Highland Peat Swamps on Sandstone (TPHSS) in the Sydney Basin of Australia provide critical ecological and hydrological services but are increasingly threatened by wildfires and human activities such as underground mining. The 2019–2020 wildfires severely impacted these swamps, raising concerns about their resilience and recovery. This study assessed the post-fire recovery of swamps and evaluated the ability of remote sensing techniques to determine recovery patterns. Specifically, it investigated differences in post-fire recovery patterns between swamps where groundwater levels and soil moisture contents were impacted by underground mining and those unimpacted by mining. Two mined and one non-mined swamp were studied. Soil moisture contents were monitored at five sites, and previously performed vegetation field surveys (2016–2022) were utilized. Remote sensing indices, including the Normalized Difference Vegetation Index (NDVI) and Soil Moisture Index (SMI), were calculated and compared with ground data to map post-fire responses. The results showed that hydrological conditions directly affect post-fire recovery, with slower recovery in mined swamps compared to non-mined ones. This study demonstrated that NDVI and SMI indices can effectively determine recovery patterns in terms of vegetation and hydrology. However, evaluating the recovery pattern of specific vegetation species requires more frequent field surveys. Full article

Java’s Brantas River Basin (BRB) is an increasingly urbanized tropical watershed with significant economic and ecological importance; yet knowledge of its land-use changes dynamics and drivers as well as their importance have barely been explored. This is the case for many other tropical watersheds in Java, Indonesia and beyond. This study of the BRB (1) quantifies the land-use changes in the period 1995–2015, (2) determines the patterns of land-use changes during 1995–2015, and (3) identifies the potential drivers of land-use changes during 1995–2015. Findings show that from 1995 to 2015, major transitions from forest to shrubs (218 km²), forest to dryland agriculture (512 km²), and from agriculture to urban areas (1484 km²) were observed in the BRB. Responses from land-user questionnaires suggest that drivers include a wide range of economic, social, technological, and biophysical attributes. An agreement matrix provided insight about consistency and inconsistency in the drivers inferred from the Land Change Modeler and those inferred from questionnaires. Factors that contributed to inconsistencies include the limited representation of local land-use features in the spatial data sets and comprehensiveness of land-user questionnaires. Together the two approaches signify the heterogeneity and scale-dependence of the land-use change process. Full article

Lakes commonly form in mine pits following the end of mining. A good understanding of the pit lake water balance over future decades to centuries is essential to understand and manage environmental risks from the lake. Evaporation is often the major or only outflow from the lake, thus being an important determinant of equilibrium lake level and environmental risks. A general lack of in situ measurements of pit lake evaporation has meant that estimates have usually been based on pan coefficients derived for other contexts or on alternative unvalidated evaporation models. Our research used data from an evaporation pan and weather station that were floated on a pit lake in semi-arid central Queensland, Australia. A deterministic aerodynamic evaporation model was developed from these data to infill missing values, and an adjusted aerodynamic model was used to reconstruct long-term historical daily evaporation data. With an average bias of 6.5% during the measurement period, this long-term model was found to be more accurate than alternative simple models (e.g., using the commonly used pan coefficient of 0.7 gave a bias of 45%). The reconstructed data were then used to fit and assess a stochastic model for the generation of future evaporation and rainfall realisations, assuming a stationary climate. Fitting stochastic models at a monthly time step was found to accurately represent the monthly evaporation statistics. For example, the cross-correlation between historical rainfall and evaporation was within the 25 and 75 percentiles of the modelled values in 11 of 12 months and always within the 2.5 and 97.5 percentiles. However, the stationary nature of the model presented limitations in capturing interannual anomalies, with continuous periods of up to 6 years, where the modelled annual rainfall was consistently lower and modelled annual evaporation consistently higher than the historical values. Fitting stochastic models at a daily time step had problems capturing a range of statistics of both rainfall and evaporation. For example, in 6 of the 12 months, the cross-correlation between historical rainfall and evaporation was outside the modelled 2.5 and 97.5 percentiles. This likely arises from the complex patterns in transitions from wet to dry days in the semi-arid climate of the case study. While the long-term model and monthly stochastic model are promising, further work is needed to understand the significance of the observed errors and refine the models. Full article

Although plot-scale erosion experiments are numerous, there are few studies on constructed landforms. This limits the understanding of their long-term stability, which is especially important for planning mined land rehabilitation. The objective of this study was to gain insight into the erosion processes in a 30 × 30 m trial plot on a mine waste rock dump in tropical northern Australia. The relationships between rainfall, runoff and suspended and bedload sediment export were assessed at annual, seasonal, inter-event and intra-event timescales. During a five-year study period, 231 rainfall–runoff–sediment export events were examined. The measured bedload and suspended sediments (mainly represented in nephelometric turbidity units (NTU)) showed the dominance of the wet season and heavy rainfall events. The bedload dominated the total mass, although the annual bedload diminished by approximately 75% over the five years, with greater flow energy required over time to mobilise the same bedload. The suspended load was more sustained, though it also exhibited an exhaustion process, with equal rainfall and runoff volumes and intensities, leading to lower NTU values over time. Intra-event NTU dynamics, including runoff-NTU time lags and hysteretic behaviours, were somewhat random from one event to the next, indicating the influence of the antecedent distribution of mobilisable sediments. The value of the results for supporting predictive modelling is discussed. Full article

Coal mine spoils have the potential to create environmental impacts, such as salt load to surrounding environments, particularly when exposed to weathering processes. This study was conducted to understand the effect of physical and chemical weathering on the magnitude, rate, and dynamics of salt release from different coal mine spoils. Five spoil samples from three mines in Queensland were sieved to three different particle size fractions (<2 mm, 2–6 mm, and >6 mm). Two samples were dispersive spoils, and three samples were nondispersive spoils. The spoils were subjected to seven wet–dry cycles, where the samples were periodically leached with deionised water. The rate, magnitude, and dynamics of solutes released from spoils were spoil specific. One set of spoils did not show any evidence of weathering, but initially had higher accumulation of salts. In contrast, broad oxidative weathering occurred in another set of spoils; this led to acid generation and resulted in physical weathering, promoting adsorption–desorption and dissolution and, thus, a greater release of salts. This study indicated that the rate and magnitude of salt release decreased with increasing particle size. Nevertheless, when the spoil is dispersive, the degree of weathering manages salt release irrespective of initial particle size. This study revealed that the long-term salt release from spoils is not only governed by geochemistry, weathering degree, and particle size but also controlled by the water/rock ratio and hydrological conditions of spoils. Full article

Typhoons are the main type of natural disaster in Korea, and accurately predicting typhoon-induced flood flows at gauged and ungauged locations remains an important challenge. Flood flows caused by six typhoons since 2002 (typhoons Rusa, Maemi, Nari, Dienmu, Kompasu and Bolaven) are modeled at the outlets of 24 Geum River catchments using the Probability Distributed Moisture model. The Monte Carlo Analysis Toolbox is applied with the Nash Sutcliffe Efficiency as the criterion for model parameter estimation. Linear regression relationships between the parameters of the Probability Distributed Moisture model and catchment characteristics are developed for the purpose of generalizing the parameter estimates to ungauged locations. These generalized parameter estimates are tested in terms of ability to predict the flood hydrographs over the 24 catchments using a leave-one-out validation approach. We then test the hypothesis that a more complex generalization approach, the Generalized Estimating Equation, which includes properties of the typhoons as well as catchment characteristics as predictors of PDM model parameters, will provide more accurate predictions. The results show that the predictions of Generalized Estimating Equation are comparable to those of the simpler, conventional regression. The simpler approach is therefore recommended for practical applications; however, further refinements of the Generalized Estimating Equation approach may be explored. Full article

Developing its large-scale mining industry is an economic priority for Colombia. However, national capacity to assess and manage the water resource impacts of mining is currently limited. This includes lack of baseline data, lack of suitable hydrological models and lack of frameworks for evaluating risks. Furthermore, public opposition to large scale mining is high and is a barrier to many proposed new mining projects mainly because of concerns about impacts on water resources. There are also concerns about impacts on the uplands that are important water sources, particularly the páramo ecosystem. This paper argues the case for a new framework for Strategic Assessment of Regional Water Impacts of Mining, aiming to support land use planning decisions by government for selected mining and prospective mining regions. The proposed framework is modelled on the Australian Government’s Bioregional Assessments program, converted into seven stages plus supporting activities that meet the Colombian development context. The seven stages are: (1) Contextual information; (2) Scenario definition; (3) Risk scoping; (4) Model development; (5) Risk analysis; (6) Database development; and (7) Dissemination by government to stakeholders including the general public. It is emphasised that the process and results should be transparent, the data and models publicly accessible, and dissemination aimed at all levels of expertise. Full article

The unpredictable climate in wet tropical regions along with the spatial resolution limitations of some satellite imageries make detecting and mapping artisanal and small-scale mining (ASM) challenging. The objective of this study was to test the utility of Pleiades and SPOT imagery with an object-based support vector machine (OB-SVM) classifier for the multi-temporal remote sensing of ASM and other land cover including a large-scale mine in the Didipio catchment in the Philippines. Historical spatial data on location and type of ASM mines were collected from the field and were utilized as training data for the OB-SVM classifier. The classification had an overall accuracy between 87% and 89% for the three different images—Pleiades-1A for the 2013 and 2014 images and SPOT-6 for the 2016 image. The main land use features, particularly the Didipio large-scale mine, were well identified by the OB-SVM classifier, however there were greater commission errors for the mapping of small-scale mines. The lack of consistency in their shape and their small area relative to pixel sizes meant they were often not distinguished from other land clearance types (i.e., open land). To accurately estimate the total area of each land cover class, we calculated bias-adjusted surface areas based on misclassification values. The analysis showed an increase in small-scale mining areas from 91,000 m²—or 0.2% of the total catchment area—in March 2013 to 121,000 m²—or 0.3%—in May 2014, and then a decrease to 39,000 m²—or 0.1%—in January 2016. Full article

The Multiplicative Discrete Random Cascade (MDRC) class of model is used to temporally disaggregate rainfall volumes through multiplying the volumes by random weights, which is repeated through multiple disaggregation levels. The model development involves the identification of probability density functions from which to sample the weights. The parameters of the probability density functions are known to be dependent on the rainfall volume. This paper characterises the volume dependency over the scarcely observed extreme ranges of rainfall, introducing the concept of volume-bounded MDRC models. Probable maximum precipitation (PMP) estimates are used to define theoretically-based points and asymptotes to which the observation-based estimates of the MDRC model parameters are extrapolated. Alternative models are tested using a case study of rainfall data from Brisbane, Australia covering the period 1908 to 2015. The results show that moving from a baseline model with constant parameters to incorporating the volume dependency of the parameters is essential for acceptable performance in terms of the frequency and magnitude of modelled extremes. As well as providing better estimates of parameters at each disaggregation level, the volume dependency provides an in-built bias correction when moving from one level to the next. A further, relatively small performance gain is obtained by extrapolating the observed dependency to the theoretically-based bounds. The volume dependency of the parameters is found to be reasonably time-scaleable, providing opportunity for advances in the generalisation of MDRC models. Sensitivity analysis shows that the subjectivities and uncertainties in the modelling procedure have mixed effects on the performance. A principal uncertainty, to which the results are sensitive, is the PMP estimate. Therefore, in applications of the bounded approach, the PMP should ideally be described by a probability distribution function. Full article