*Using Rainfall Simulators to Design and Assess the Post-Mining Erosional Stability DOI: http://dx.doi.org/10.5772/intechopen.112240*

are vital for calibration and validation purposes of empirical, conceptual, or processbased rainfall-runoff-sediment transport mathematical models [24].

The credit for designing and building the first rainfall simulator goes to Nichols and Sexton [25] who used their first rainfall simulator (spray-bar rainfall simulator) to study soil erosion and measure the infiltration rate. By the mid-1950s of the last century, the use of rain simulators expanded steadily in experiments related to soil erosion, and the rapid technological development contributed to the introduction of many improvements to its first designs to avoid many issues that affect the performance, results, credibility, and the feasibility of these machines [26].

The main purpose of a rainfall simulator (RFS) is to generate and create an artificial rainstorm with precise specifications in terms of the duration and intensity of the rainfall, as well as in some way the size distribution of the droplets, and its kinetic energy. The ability to control the physical characteristics of the generated rainstorm makes it possible to keep the climatic factor (rain erosivity) constant while studying other factors that may affect the process of erosion such as soil erodibility, slope factor, or vegetation cover. It can be argued that any success of the RFS design depends entirely on how closely it is simulating natural precipitation conditions with respect to spatial uniformity, raindrop size, raindrop terminal velocity, and kinetic energy.

Although rainfall simulators are frequently utilized in soil erosion experiments, their ability to replicate natural rainfall conditions with precision has been a topic of concern. Many studies have been carried out to evaluate the reliability of results obtained from rainfall simulators and their usefulness in modeling soil erosion processes [27–31]. Among the important initiatives in this domain was the PLPEWC "Post-mining Landscape Parameters for Erosion and Water Quality Control" project, which was financially supported by ACARP (the Australian Coal Association Research Project) between 1992 and 1998.

The project performed a range of experiments, including laboratory rainfall simulation, field plots, and catchments (**Figure 1**).

The experimental approaches adopted were designed to measure the basic erosion parameters at the different scales. A large amount of data has been collected on 34 spoil and soil materials from 16 mines in Central Queensland, as well as 9 years of field plot and field catchment data [7, 32]. The data collected from those different experimental approaches/scales studies proved that although the need for field plots and catchment flumes studies still exists, the results obtained from laboratory rainfall simulators showed reliability so that their results can be used in modeling soil erosion

#### **Figure 1***.*

*Range of experimental approaches adopted to determine soil/spoil erodibility in a previous ACARP (the Australian coal association research project)*.

with a high degree of accuracy. Moreover, laboratory experiments using rainfall simulators are more manageable than field experiments, because the data on runoff and soil loss can be obtained without waiting for natural rain to happen.

Therefore, rill and interrill erodibilities and slope adjustment factors were measured for these 34 soil/overburden materials on a portable rainfall simulator tilting flume (3 m long 0.8 m wide, slope adjustable from 0 to 50%) at the University of Queensland Erosion Processes Laboratory. Each material was subjected to 100 mm. h<sup>1</sup> rainstorm for 30 min (equivalent to a 1-in-20-year event in Central Queensland) at 20% slope, followed by slopes of 5, 10, 15, and 30% for 15 min each. At these simulated rainfall intensities, a steady state was quickly formed. The data from these measurements and the derived parameters were used to develop the MINErosion V3.x model [33], which successfully estimates field scale erosion rates on simple linear hillslopes with various combinations of slope gradients and lengths. MINErosion 3 can also be used effectively to simulate multiple field plot experiments on a computer, based on a few measurements made on a tilting flume-rainfall simulator facility in the laboratory. MINErosion 3.4 cannot be used to predict sediment yield from a watershed with complex topography in terms of slope steepness and flow pathways. However, it is necessary and desirable to be able to estimate off-site sediment discharges from these rehabilitated post-mining landscapes. For this purpose, MINErosion 4 was developed, which combines the MINErosion 3.4 model and a geographic information system (GIS) package (ESRI ArcGIS 10.3 or the freeware QGIS 3.16), to estimate erosion rates and sediment movement and delivery from these constructed postmining landscapes. Both MINErosion 3 and 4 demonstrated the opportunities and the value of using the rainfall simulators at the mining sites to model and assess the erosional stability, which should be proven achievable under the given circumstances as it is one of the main considerations of the landform design report within the progressive rehabilitation and closure (PRC) Plan.

Subsequently, the effectiveness of using rainfall simulation as a method for obtaining erodibility information for other soil erosion models such as Areal Nonpoint Source Watershed Environmental Response Simulation (ANSWERS), Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS), and Water Erosion Prediction Project (WEPP) was recognized. Loch, Silburn [34], Silburn and Connolly [35], and Silburn and Loch [36] achieved accurate predictions of erosion under field conditions by utilizing parameters derived from rainfall simulation using these models. Nevertheless, Silburn and Loch [36] emphasized the significance of ensuring that the erosion processes happening on rainfall simulator plots were identical to those occurring in field areas in order to obtain reliable predictions.
