Modelling Hydrological Processes and Identifying Soil Erosion Sources in a Tropical Catchment of the Great Barrier Reef Using SWAT

Vascular plant communities and biocrusts act as controlling factors in mitigating soil erosion on the Great Wall in a semi-humid area of Northwestern China

The Great Wall, a World Heritage Site and a vertical wall habitat, is under threat of soil erosion. The role of vascular plants and biocrust in controlling soil erosion has attracted attention, yet our knowledge of the underlying mechanism is limited, and there is a lack of systematic strategies for erosion prevention and control. In this study, we quantified the vascular plant community functional composition (including species diversity, functional diversity, and community-weighted mean), biocrust coverage, and soil erosion levels associated with seven different zones (lower, middle, and upper zones on East and West faces, plus wall crest) of the Great Wall. We then employed a combination of linear regression analysis, random forest model, and structural equation model to evaluate the individual and combined effects, as well as the direction and relative importance of these factors in reducing soil erosion. The results indicated that the vascular plant species richness, species diversity, functional richness, community-weighted mean, and moss crust coverage decreased significantly from the crest to the lower zone of the Great Wall (P < 0.05), and were negatively correlated with the soil erosion area and depth on both sides of the Great Wall (P < 0.05). This suggests that higher zones on the wall favored the colonization and growth of biocrusts and vascular plants and that biocrusts and vascular plants reduced soil erosion on the wall. Based on these findings, we propose a "restoration framework" for managing soil erosion on walls, based on biocrust and vascular plant communities (namely target species selection, plant community construction, biocrust inoculation, and maintenance of community stability), which aims to address the urgent need for more effective soil erosion prevention and control strategies on the Great Wall and provide practical methods that practitioners can utilize.

Prediction of Sediment Yield in a Data-Scarce River Catchment at the Sub-Basin Scale Using Gridded Precipitation Datasets

Water-related soil erosion is a major environmental concern for catchments with barren topography in arid and semi-arid regions. With the growing interest in irrigation infrastructure development in arid regions, the current study investigates the runoff and sediment yield for the Gomal River catchment, Pakistan. Data from a precipitation gauge and gridded products (i.e., GPCC, CFSR, and TRMM) were used as input for the SWAT model to simulate runoff and sediment yield. TRMM shows a good agreement with the data of the precipitation gauge (≈1%) during the study period, i.e., 2004–2009. However, model simulations show that the GPCC data predicts runoff better than the other gridded precipitation datasets. Similarly, sediment yield predicted with the GPCC precipitation data was in good agreement with the computed one at the gauging site (only 3% overestimated) for the study period. Moreover, GPCC overestimated the sediment yield during some years despite the underestimation of flows from the catchment. The relationship of sediment yields predicted at the sub-basin level using the gauge and GPCC precipitation datasets revealed a good correlation (R2 = 0.65) and helped identify locations for precipitation gauging sites in the catchment area. The results at the sub-basin level showed that the sub-basin located downstream of the dam site contributes three (3) times more sediment yield (i.e., 4.1%) at the barrage than its corresponding area. The findings of the study show the potential usefulness of the GPCC precipitation data for the computation of sediment yield and its spatial distribution over data-scarce catchments. The computations of sediment yield at a spatial scale provide valuable information for deciding watershed management strategies at the sub-basin level.

On the Evaluation of Both Spatial and Temporal Performance of Distributed Hydrological Models Using Remote Sensing Products

Evaluating the spatial and temporal model performance of distributed hydrological models is necessary to ensure that the simulated spatial and temporal patterns are meaningful. In recent years, spatial and temporal remote sensing data have been increasingly used for model performance evaluation. Previous studies, however, have focused on either the temporal or spatial model performance evaluation. In addition, temporal (or spatial) model performance evaluation is often conducted in a spatially (or temporally) lumped approach. Here, we evaluated (1) the temporal model performance evaluation in a spatially distributed approach (spatiotemporal) and (2) the spatial model performance in a temporally distributed approach (temporospatial). We further demonstrated that both spatiotemporal and temporospatial model performance evaluations are necessary since they provide different aspects of the model performance. For this, a case study was developed using the Soil and Water Assessment Tool (SWAT) for the Upper Baitarani catchment in India, and the spatiotemporal and temporospatial model performance was evaluated against three different remotely based actual evapotranspiration (ETa) products (MOD16 A2, SSEBop, and TerraClimate). The results showed that an increase in the spatiotemporal model performance would not necessarily lead to an increase in the temporospatial model performance and vice versa, depending on the evaluation statistics. Overall, this study has highlighted the necessity of a joint spatiotemporal and temporospatial model performance evaluation to understand/improve spatial and temporal model behavior/performance.

Water Erosion Monitoring and Prediction in Response to the Effects of Climate Change Using RUSLE and SWAT Equations: Case of R’Dom Watershed in Morocco

Soil erosion is an increasingly issue worldwide, due to several factors including climate variations and humans’ activities, especially in Mediterranean ecosystems. Therefore, the aim of this paper is: (i) to quantify and to predict soil erosion rate for the baseline period (2000–2013) and a future period (2014–2027), using the Revised Universal Soil Loss Equation (RUSLE) and the Soil and Water Assessment Tool (SWAT) model in the R’Dom watershed in Morocco, based on the opportunities of Remote Sensing (RS) techniques and Geographical Information System (GIS) geospatial tools. (ii) we based on classical statistical downscaling model (SDSM) for rainfall prediction. Due to the lack of field data, the model results are validated by expert knowledge. As a result of this study, it is found that both agricultural lands and bare lands are most affected by soil erosion. Moreover, it is showed that soil erosion in the watershed was dominated by very low and low erosion. Although the area of very low erosion and low erosion continued to decrease. Hence, we hereby envisage that our contribution will provide a more complete understanding of the soil degradation in this study area and the results of this research could be a crucial reference in soil erosion studies and also may serve as a valuable guidance for watershed management strategies.

Pre-development denudation rates for the Great Barrier Reef catchments derived using 10Be

Understanding of the pre-development, baseline denudation rates that deliver sediment to the Great Barrier Reef (GBR) has been elusive. Cosmogenic ¹⁰Be in sediment is a useful integrator of denudation rates and sediment yields averaged over large spatial and temporal scales. This study presents ¹⁰Be data from 71 sites across 11 catchments draining to the GBR: representing 80% of the GBR catchment area and provide background sediment yields for the region. Modern, short-term, sediment yields derived from suspended load concentrations are compared to the ¹⁰Be data to calculate an Accelerated Erosion Factor (AEF) that highlights denudation "hot-spots" where sediment yields have increased over the long-term background values. The AEF results show that 58% basins have higher modern sediment yields than long-term yields. The AEF is considered a useful approach to help prioritise on-ground investments in remediation and the additional measured empirical data in this paper will help support future predictive models.

Hydrological Responses of Watershed to Historical and Future Land Use Land Cover Change Dynamics of Nashe Watershed, Ethiopia

Land use land cover (LULC) change is the crucial driving force that affects the hydrological processes of a watershed. The changes of LULC have an important influence and are the main factor for monitoring the water balances. The assessment of LULC change is indispensable for sustainable development of land and water resources. Understanding the watershed responses to environmental changes and impacts of LULC classes on hydrological components is vigorous for planning water resources, land resource utilization, and hydrological balance sustaining. In this study, LULC effects on hydrological parameters of the Nashe watershed, Blue Nile River Basin are investigated. For this, historical and future LULC change scenarios in the Nashe watershed are implemented into a calibrated Soil and Water Assessment Tool (SWAT) model. Five LULC scenarios have been developed that represent baseline, current, and future periods corresponding to the map of 1990, 2005, 2019, 2035, and 2050. The predicted increase of agricultural and urban land by decreasing mainly forest land will lead till 2035 to an increase of 2.33% in surface runoff and a decline in ground water flow, lateral flow, and evapotranspiration. Between 2035 and 2050, a gradual increase of grass land and range land could mitigate the undesired tendency. The applied combination of LULC prognosis with process-based hydrologic modeling provide valuable data about the current and future understanding of variation in hydrological parameters and assist concerned bodies to improve land and water management in formulating approaches to minimize the conceivable increment of surface runoff.