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Reclamation of salt-affected soil has been identified by the FAO as being critical to meet the needs to increase agricultural productivity. This paper reviews commonly used reclamation methods for salt-affected soils, and provides critical identifiers for an effective reclamation practice of salt-affected soil. There are widely used methods to reduce salinity and sodicity of salt-affected soils, including salt leaching, addition of amendments, revegetation using halophytes and salt scrapping. Not all reclamation techniques are suitable for salt-affected land. The reclamation strategy must be tailored to the site, and based on understanding the soil, plant and climate interactions. On some occasions, a combination of techniques may be required for reclamation. This can include salt scrapping to remove salts from the surface soil, the addition of physical amendments to improve soil pore systems and enhance salt leaching, followed by amelioration of soil by chemical amendments to preserve soil physical conditions, and then halophyte establishment to expand the desalinization zone. This study reveals that soil hydro-geochemical models are effective predictive tools to ascertain the best reclamation practice tailored to salt-affected land. However, models need to be calibrated and validated to the conditions of the land before being applied as a tool to combat soil salinity.

Alum sludge is a byproduct of water treatment plants, and its use as a soil stabilizer has gained increasing attention due to its economic and environmental benefits. Its application has been shown to improve the strength and stability of soil, making it suitable for various engineering applications. However, to go beyond just measuring the effects of alum sludge as a soil stabilizer, this study investigates the potential of artificial intelligence (AI) methods for predicting the California bearing ratio (CBR) of soils stabilized with alum sludge. Three AI methods, including two black box methods (artificial neural network and support vector machines) and one grey box method (genetic programming), were used to predict CBR, based on a database with nine input parameters. The results demonstrate the effectiveness of AI methods in predicting CBR with good accuracy (R2 values ranging from 0.94 to 0.99 and MAE values ranging from 0.30 to 0.51). Moreover, a novel approach, using genetic programming, produced an equation that accurately estimated CBR, incorporating seven inputs. The analysis of parameter sensitivity and importance, revealed that the number of hammer blows for compaction was the most important parameter, while the parameters for maximum dry density of soil and mixture were the least important. This study highlights the potential of AI methods as a useful tool for predicting the performance of alum sludge as a soil stabilizer.

Ecosystem services mapping is becoming increasingly popular through the use of various readily available mapping tools, however, uncertainties in assessment outputs are commonly ignored. Uncertainties from different sources have the potential to lower the accuracy of mapping outputs and reduce their reliability for decision-making. Using a case study in an Australian mining region, this paper assessed the impact of uncertainties on the modelling of the hydrological ecosystem service, water provision. Three types of uncertainty were modelled using multiple uncertainty scenarios: (1) spatial data sources; (2) modelling scales (temporal and spatial) and (3) parameterization and model selection. We found that the mapping scales can induce significant changes to the spatial pattern of outputs and annual totals of water provision. In addition, differences in parameterization using differing sources from the literature also led to obvious differences in base flow. However, the impact of each uncertainty associated with differences in spatial data sources were not so great. The results of this study demonstrate the importance of uncertainty assessment and highlight that any conclusions drawn from ecosystem services mapping, such as the impacts of mining, are likely to also be a property of the uncertainty in ecosystem services mapping methods.

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.

Accurate scheduling of bauxite residue (red mud) deposition time is required in order to prevent the risk of storage facility failure. This study was conducted to precisely determine the hydraulic parameters of bauxite residue and investigate the capability of HYDRUS to accurately estimate the residue moisture profile and the timing for its deposition. The hydraulic properties of the bauxite residue profile were determined by solving an inverse problem. A one-dimensional hydrological model (HYDRUS-1D) was validated using a 300 mm long column filled with bauxite residue and exposed to a dynamic lower boundary condition. After numerical validation, the model was used to simulate the moisture profile of bauxite residue under the climatic conditions of an alumina refinery site in Queensland, Australia, as well as other scenarios (i.e., high (300 mm) and small (1.7 mm) rainfall events of the site). This study showed that the HYDRUS model can be used as a predictive tool to precisely estimate the moisture profile of the bauxite residue and that the timing for the re-deposition of the bauxite residue can be estimated by understanding the moisture profile and desired shear strength of the residue. This study revealed that the examined bauxite residue approaches field capacity (water potential −10 kPa) after three days from a low rainfall event (<1.7 mm) and after eight days from an intense rainfall event (300 mm) at the time of disposal. This suggests that the bauxite residue can be deposited every four days after low rainfall events (as low as 1.7 mm) and every nine days after high rainfall events (as high as 300 mm) at the time of deposition, if bauxite residue experiences an initial drying period following deposition.

The solubility and mobility of copper (Cu) in soil is strongly influenced by the presence of dissolved organic carbon (DOC); however, the interactions between Cu and DOC are complex and not yet fully understood. In this study, Cu and DOC concentrations were measured monthly for two years in leachates from self-constructed lysimeters installed at inter- and intra-row vineyard hilltop, backslope, and footslope areas at the SUPREHILL Critical Zone Observatory, Croatia. The aim was to quantify Cu and DOC leaching from the hilltop towards the backslope and the footslope. The assumed strong relationship between Cu and DOC in the leachates was statistically analyzed and explained using chemical equilibrium software. Leachates were analyzed for pH, EC, DOC, Cu, and major ion concentrations. The highest Cu concentrations found in leachates from the intra-row footslope suggested Cu downhill transport. Although not strong, a significant positive correlation between Cu and DOC in footslope leachates confirmed the relevance of Cu complexation by DOC. Speciation confirmed that more than 99.9% of total Cu in leachates was found as a Cu-DOC complex. Data implied the role of soil water flow pathways in explaining Cu downhill transport. Critical timing for applying Cu fungicides at sloped vineyards was highlighted.

Processes in hillslope soils present a particular challenge for agricultural production and soil management due to their hydropedological specifics and high soil erosion risk. Soil heterogeneities can cause preferential and/or lateral flow on the entire hillslope resulting in the off-site movement of water, fertilizers and chemicals used in crop production. A study was conducted under controlled conditions in a laboratory with undisturbed soil cores (250 cm3), which were used to estimate the soil hydraulic properties (SHP) using HYPROP and WP4C devices, while undisturbed soil columns (diameter = 16 cm, length = 25 cm) were used for the evaluation of preferential flow pathways using potassium bromide and Brilliant Blue. Samples were excavated in triplicate from the hilltop, backslope and footslope regions within the inter-rows of a vineyard from a critical zone observatory, SUPREHILL, in Croatia in Dystric Luvic Stagnosol. The aim of this study was to determine if the erosion-affected hillslope position affected the physical, chemical and hydraulic properties of soil and to identify water flow and possible preferential flow using dye and bromide tracers. The results of the sensor measurements and estimated SHPs were in agreement, showing a faster leaching of the irrigated rainwater in the footslope column. The tracer experiments showed variability even in the columns taken from the same position on the hillslope, which can be linked to plant roots and soil fauna activity. Altogether, the results showed a deeper loose layer at the footslope as a consequence of the soil erosion, which then resulted in higher hydraulic conductivity and the leached mass of the bromide due to better soil structure and pore connectivity. Thus, due to significant differences in the leached mass of bromide, this research should be later expanded in field experiments to reveal the impact of surface runoff, subsurface preferential and lateral flow on a larger scale.

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.

Soil heterogeneities can impact hillslope hydropedological processes (e.g., portioning between infiltration and runoff), creating a need for in-depth knowledge of processes governing water dynamics and redistribution. The presented study was conducted at the SUPREHILL Critical Zone Observatory (CZO) (hillslope vineyard) in 2021. A combination of field investigation (soil sampling and monitoring campaign) and numerical modeling with hydrological simulator HYDRUS-1D was used to explore the water dynamics in conjunction with data from a sensor network (soil water content (SWC) and soil-water potential (SWP) sensors), along the hillslope (hilltop, backslope, and footslope). Soil hydraulic properties (SHP) were estimated based on (i) pedotransfer functions (PTFs), (ii) undisturbed soil cores, and (iii) sensor network data, and tested in HYDRUS. Additionally, a model ensemble mean from HYDRUS simulations was calculated with PTFs. The highest agreement of simulated with observed SWC for 40 cm soil depth was found with the combination of laboratory and field data, with the lowest average MAE, RMSE and MAPE (0.02, 0.02, and 5.34%, respectively), and highest average R2 (0.93), while at 80 cm soil depth, PTF model ensemble performed better (MAE = 0.03, RMSE = 0.03, MAPE = 7.55%, R2 = 0.81) than other datasets. Field observations indicated that heterogeneity and spatial variability regarding soil parameters were present at the site. Over the hillslope, SWC acted in a heterogeneous manner, which was most pronounced during soil rewetting. Model results suggested that the incorporation of field data expands model performance and that the PTF model ensemble is a feasible option in the absence of laboratory data.

A quantitative understanding of actual evapotranspiration (ETa) and soil–water dynamics in a hillslope agroecosystem is vital for sustainable water resource management and soil conservation; however, the complexity of processes and conditions involving lateral subsurface flow (LSF) can be a limiting factor in the full comprehension of hillslope soil–water dynamics. The research was carried out at SUPREHILL CZO located on a hillslope agroecosystem (vineyard) over a period of two years (2021–2022) by combining soil characterization and field hydrological measurements, including weighing lysimeters, sensor measurements, and LSF collection system measurements. Lysimeters were placed on the hilltop and the footslope, both having a dynamic controlled bottom boundary, which corresponded to field pressure head measurements, to mimic field soil–water dynamics. Water balance components between the two positions on the slope were compared with the goal of identifying differences that might reveal hydrologically driven differences due to LSF paths across the hillslope. The usually considered limitations of these lysimeters, or the borders preventing LSF through the domain, acted as an aid within this installation setup, as the lack of LSF was compensated for through the pumping system at the footslope. The findings from lysimeters were compared with LSF collection system measurements. Weighing lysimeter data indicated that LSF controlled ETa rates. The results suggest that the onset of LSF contributes to the spatial crop productivity distribution in hillslopes. The present approach may be useful for investigating the impact of LSF on water balance components for similar hillslope sites and crops or other soil surface covers.