Sediment transport modeling at Stono Inlet and adjacent beaches, South Carolina

This report documents a numerical modeling investigation for dredged material from nearshore borrow areas and placed on Folly Beach adjacent to Stono Inlet, South Carolina. Historical and newly collected wave and hydrodynamic data around the inlet were assembled and analyzed. The datasets were used to calibrate and validate a coastal wave, hydrodynamic and sediment transport model, the Coastal Modeling System. Sediment transport and morphology changes within and around the immediate vicinity of the Stono Inlet estuarine system, including sand borrow areas and nearshore Folly Beach area, were evaluated. Results of model simulations show that sand removal in the borrow areas increases material backfilling, which is more significant in the nearshore than the offshore borrow areas. In the nearshore Folly Beach area, the dominant flow and sediment transport directions are from the northeast to the southwest. Net sediment gain occurs in the central and southwest sections while net sediment loss occurs in the northeast section of Folly Island. A storm and a 1-year simulation developed for the study produce a similar pattern of morphology changes, and erosion and deposition around the borrow areas and the nearshore Folly Beach area.

Responses of Runoff and Soil Loss on Slopes to Land Use Management and Rainfall Characteristics in Northern China

Soil conservation measures are widely used to control soil erosion and sediment loss; however, their proper usage relies on a deep understanding of the responses of runoff and sediment loss to land management and rainfall characteristics. In the present study, a long-term (2014–2020) monitored dataset derived from ten runoff plots in the upstream catchment of the Miyun Reservoir in Beijing, China, was used to study runoff and sediment loss responses to land use management and rainfall characteristics. The study results show that plots with no soil conservation measures had the highest runoff depth of 75 mm and suffered the highest sediment loss, at a rate of 3200 t km−2 yr−1. The terraced and vegetated plots generated lower runoff depths, with soil loss rates less than 213.0 t km−2 yr−1. With the exception of the contour tillage plots on steep slopes, the vegetation and engineering measures can efficiently reduce runoff and sediment loss, with both runoff and sediment reduction efficiencies higher than 76%. Statistical analyses indicate that, on the plots of bare soil and cultivation without soil conservation measures, runoff and sediment loss were mainly affected by the maximum 30 min rainfall intensity. However, on the plots with soil conservation measures, they were mainly determined by rainfall amount and duration. The sediment loss rate can be well fitted with the runoff depth using a power function. Based on the analyses, water-saving soil conservation measures are recommended for the study area. In addition, the size of terraces should be reconsidered on gentle slopes, and the coverage of forest, shrubs, and grass on slopes should be reduced, thus allowing for more surface runoff generation to ensure drinking water safety. In general, for the study area, soil conservation measures are required on the bare soil and cultivated slopes.

Effect of natural rainfall on the migration characteristics of runoff and sediment on purple soil sloping cropland during different planting stages

Due to the difficulty in monitoring subsurface runoff and sediment migration, their loss loads are still not clear and need further study. This study monitored water and soil loss occurring within experimental field plots for two calendar years under natural rainfall events. The sediment loss load was quantified by considering the corresponding water flow flux and its sediment concentration. The results showed that 60.04% of the runoff and 2.83% of the sediment were lost underground. The annual underground sediment loss reached up to 54.6 kg*ha−1*yr−1. A total of 69.68% of the runoff yield and 67.25% of the sediment yield were produced during the corn planting stage (CPS: March–July). Heavy rain and torrential rain events produced 94.45%, 65.46% of the annual runoff and 94.45%, 76.21% of the sediment yields during the corn-planting stage and summer fallow period (SFP: August–September). The rain frequency, rainfall, and rainfall duration of each planting stage significantly affected the resulting runoff and sediment yield. Measures aimed at the prevention and control of water-soil loss from purple soil sloping land should heavily focus on torrential rain and heavy rain events during the CPS and SFP. This paper aims to provide a practical reference for quantifying the water and soil loss from purple soil sloping cropland.

Mapping the Mangrove Vulnerability Index Using Geographical Information System

A mangrove vulnerability assessment's goal is to generate recommendations for reducing vulnerability. Mangrove forests, which grow in the intertidal zones and estuary mouths between land and sea, exist in two worlds at once. Mangroves provide crucial stability for preventing shoreline erosion. It helps to maintain land level by sediment accretion while balancing sediment loss by serving as buffers catching materials washed downstream. Climate change, especially the associated increase in sea level, poses a serious threat to mangrove coastal areas, and it is critical to devise strategies to mitigate vulnerability through strategic management planning. Experts are attempting to determine how mangroves have been affected by climate change and rising sea levels. How do we forecast the consequences and effect of rising sea levels on mangroves, and then adjust and mitigate them accordingly? Vulnerability implies the risk of being assaulted or hurt, whether physically or emotionally. Environmental vulnerability is a feature of impact exposure as well as ecological systems' susceptibility and adaptive potential to environmental tensors. Researchers in this study ranked mangrove vulnerability on a scale of 1 to 5, with 1 indicating very low vulnerability and 5 indicating very high vulnerability. The Physical Mangrove Index (PMI), Biological Mangrove Index (BMI), and Threat Mangrove Index (HMI) are the three major groups of the Mangrove Vulnerability Index (MVI)). The study's main objective is to develop an accurate and efficient GIS database system that has been formulated and tested or implemented in three (3) separate areas, namely, Kukup Island, Tanjung Piai, and Sungai Pulai. The study develops a GIS-based Mangrove Vulnerability Index (MVI) Model for a selected ecosystem, and highlights mangrove vulnerability by ranking them from least to most vulnerable using parameters. The study also provides a forecast for the mangrove loss in the next 50 and 100 years, as well as to classify areas where mangroves are most vulnerable.

Resilient pastures and sediment: a case study in Hawke's Bay

For many hill-country farms sediment will be a bigger regulatory issue than nitrates over the next decade. A dense, resilient pasture can reduce the risk of insidious sediment loss. Any ecosystem that relies on a few species is fragile. Sowing a single species leads to repeated re-sowing and increasing bare ground to remove competition, increasing the risk of sediment flows. An important issue during regulatory consultation will be establishing a natural, pre-human baseline for forest cover and documenting more recent changes in sediment flows. Hill country cropping and pasture renewal is incompatible with resilient pasture. This is a farmer’s perspective on a diverse and persisting hill country pasture-based system that can make a good return on capital without re-grassing or fodder cropping. Funding of independent research on pasture and fodder systems is essential if farmers are to make good decisions.

Straw mulch impact on soil properties and initial soil erosion processes in the maize field

<p><strong>Straw mulch impact on soil properties and initial soil erosion processes in the maize field</strong></p><p>Ivan Dugan*, Leon Josip Telak, Iva Hrelja, Ivica Kisic, Igor Bogunovic</p><p>University of Zagreb, Faculty of Agriculture, Department of General Agronomy, Zagreb, Croatia</p><p>(*correspondence to Ivan Dugan: [email protected])</p><p>Soil erosion by water is the most important cause of land degradation. Previous studies reveal high soil loss in conventionally managed croplands, with recorded soil losses high as 30 t ha<sup>-1</sup> under wide row cover crop like maize (Kisic et al., 2017; Bogunovic et al., 2018). Therefore, it is necessary to test environmentally-friendly soil conservation practices to mitigate soil erosion. This research aims to define the impacts of mulch and bare soil on soil water erosion in the maize (Zea mays L.) field in Blagorodovac, Croatia (45°33’N; 17°01’E; 132 m a.s.l.). For this research, two treatments on conventionally tilled silty clay loam Stagnosols were established, one was straw mulch (2 t ha<sup>-1</sup>), while other was bare soil. For purpose of research, ten rainfall simulations and ten sampling points were conducted per each treatment. Simulations were carried out with a rainfall simulator, simulating a rainfall at an intensity of 58 mm h<sup>-1</sup>, for 30 min, over 0.785 m<sup>2</sup> plots, to determine runoff and sediment loss. Soil core samples and undisturbed samples were taken in the close vicinity of each plot. The results showed that straw mulch mitigated water runoff (by 192%), sediment loss (by 288%), and sediment concentration (by 560%) in addition to bare treatment. The bare treatment showed a 55% lower infiltration rate. Ponding time was higher (p < 0.05) on mulched plots (102 sec), compared to bare (35 sec), despite the fact that bulk density, water-stable aggregates, water holding capacity, and mean weight diameter did not show any difference (p > 0.05) between treatments. The study results indicate that straw mulch mitigates soil water erosion, because it immediately reduces runoff, and enhances infiltration. On the other side, soil water erosion on bare soil under simulated rainstorms could be high as 5.07 t ha<sup>-1</sup>, when extrapolated, reached as high as 5.07 t ha<sup>-1 </sup>in this study. The conventional tillage, without residue cover, was proven as unsustainable agro-technical practice in the study area.</p><p><strong>Key words: straw mulch, </strong>rainfall simulation, soil water erosion</p><p><strong>Acknowledgment</strong></p><p>This work was supported by Croatian Science Foundation through the project "Soil erosion and degradation in Croatia" (UIP-2017-05-7834) (SEDCRO).</p><p><strong>Literature</strong></p><p>Bogunovic, I., Pereira, P., Kisic, I., Sajko, K., Sraka, M. (2018). Tillage management impacts on soil compaction, erosion and crop yield in Stagnosols (Croatia). Catena, 160, 376-384.</p><p>Kisic, I., Bogunovic, I., Birkás, M., Jurisic, A., Spalevic, V. (2017). The role of tillage and crops on a soil loss of an arable Stagnic Luvisol. Archives of Agronomy and Soil Science, 63(3), 403-413.</p>

Modelling Daily Surface Runoff, Sediment and Nutrient Loss at Watershed Scale Employing APEX Model Interfaced with GIS – A Case Study in Himalayan Landscape

Daily surface runoff, sediment and nutrient loss data collected from a watershed located in Uttarakhand state of Indian Himalayan region, in year 2010-2011 and of which half of the events data were used for calibration and remaining for validation. Model was calibrated for surface runoff, sediment loss and nutrient loss to optimize the input given to the model to predict the sediment loss, erosion and nutrient loss. The calibration was done by changing the sensitive parameters. Analysis showed that SCS CN number was found most sensitive to runoff, followed by saturated hydraulic conductivity, available water-holding capacity, CN retention parameter and C factor whereas erosion control practice (P) factor was found to be most sensitive, followed by C factor, sediment routing coefficient, average upland slope and soil erodibility (K) factor for the sediment and nutrient loss. APEX model calibrated for the watershed and it predicted quite well for the surface runoff (r=0.92, NSE=0.50), sediment loss (r=0.88, NSE=0.61 and nutrients of total carbon (r=0.78, NSE=0.59) and fairly for total nitrogen (r=0.77, NSE=0.19). Surface runoff was predicted well for low and medium rainfall; however, it was over predicted for high rainfall events. Over prediction may be attributed to the unaccountable conservation measures and practices which were not accounted by the model. Similarly, sediment loss was estimated on daily basis at the watershed scale and was well predicted for low and medium rainfalls but under-estimated for high rainfall events. The area is prone to landslips occurred at high rainfall events was not accounted by the model that may be a reason for under prediction of sediment loss by the model.