Research Article Experimental Study of Site-Specific Soil Water Content and Rainfall Inducing Shallow Landslides: Case of Gakenke District, Rwanda Martin Kuradusenge , 1 Santhi Kumaran, 2 Marco Zennaro, 3 and Albert Niyonzima 4 1 African Centre of Excellence in Internet of Things, University of Rwanda, KN 67, Kigali 3900, Rwanda 2 School of ICT, The Copperbelt University, Kitwe 21692, Zambia 3 International Centre of Theoretical Physics, Strada Costiera, 11, I-34151 Trieste, Italy 4 School of Engineering, University of Rwanda, KN 67, Kigali 3900, Rwanda Correspondence should be addressed to Martin Kuradusenge; m.kuradusenge@ur.ac.rw Received 24 April 2021; Revised 3 August 2021; Accepted 14 August 2021; Published 9 September 2021 Academic Editor: Guanglei Zhang Copyright © 2021 Martin Kuradusenge et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Shallow landslides are among the natural threats causing death and damage. They are mostly triggered by rainfall in mountainous areas where precipitation used to be abundant. The amount of rainfall inducing this natural threat differs from one site to another based on the geographical characteristics of that area. In addition to the rainfall depth, the determination of soil water content in a specific zone has a major contribution to the landslide prediction and early warning systems. Rwanda being a country with hilly terrains, some areas are susceptible to both rainfall and soil water content inducing landslides. But an analytical study of the physical threshold determination of both rainfall and soil water content inducing landslides is lacking. Therefore, this experimental study is conducted to determine the rainfall and soil water content threshold that can be fed in to the landslide early warning system (LEWS) for alert messages using the Internet of Things (IoT) technology. Various experiments have been conducted for the real-time monitoring of slope failure using the toolset composed of a rain gauge, soil moisture sensors, and a rainfall simulating tool. The results obtained show that the threshold for landslide occurrence does not solely correlate with the total rainfall amount (or intensity) or soil moisture, but also influenced by internal (geological, morphological) and environmental factors. Among the sampled sites, the sites covered by forest indicated no sign of slope failure, whereas sites with crops could slip. The experiments revealed that for a specific site, the minimum duration to induce slope failure was 8 hours, 41 minutes with the rainfall intensity of 8 mm/hour, and the soil moisture was above 90% for deeper sensors. These values are used as thresholds for LEWS for that specific site to improve predictions. 1. Introduction Rainfall-induced shallow landslides are among the most nat- ural disasters that causes deaths and substantial economic losses damaging infrastructure or plants in different moun- tainous regions around the world [1–3]. In Rwanda, about 1,000 landslide cases have been identified during the past decade [4], affecting a significant number of citizens, agricul- ture land, livelihoods, and infrastructure that are valued in billions of dollars. For instance, almost 200 people died by landslide incidences during 2016-2018 [5, 6]. The most sus- ceptible areas in Rwanda are the northern and western prov- inces, which are characterized by mountains and steep slopes [7, 8]. Rainfall-induced landslides are mainly caused by intrin- sic factors like geological and geomorphological parameters and extrinsic factors such as hydrological conditions, cli- matic conditions, earthquakes, and volcanic eruptions [9– 11]. Hydrological factors such as rainfall and ground water table location influence the slope stability. The process of Hindawi Geofluids Volume 2021, Article ID 7194988, 18 pages https://doi.org/10.1155/2021/7194988