Engaruka has a large reticulated network of stone-lined farm fields (c. 2 Km²) and agricultural hillside stone terraces (c. 9 Km²) making it arguably the most prominent site among the Archaeological Islands of Intensive Agriculture in East Africa (AIIAEA) ([14]; [55]; [59]; [62]; [66]). These AIIAEA sites are regarded as islands due to their remoteness and the labor-intensive agricultural techniques employed by the original inhabitants ([66]). Several stratigraphic studies have demonstrated that the agricultural terraces on these sites are not terraces intrinsically but are instead sediment traps ([18]; [37]; [59]). For instance, in Konso Ethiopia, Ferro-Vázquez et al. ([18]) showed how the inhabitants would construct low-level dry-stone terraces in order to trap tillable top soil as well as mitigate soil erosion. They would then seasonally raise the walls of the terraces to improve efficiency. In Engaruka, after abandonment about 18th century CE followed by years of no or little maintenance efforts, most of these terraces have now been covered by soil (near-surface) due to denudation. This, combined with other factors like aridity, flash-floods, farmland encroachment and overgrazing has resulted to extensive gullying and severe land degradation (Figure 1 and Figure 2) particularly on the northern half of the site (Engaruka North). [65] demonstrated how a single high-magnitude process, the 1997-1998 El Niño denuded approximately 80 ha of the site (c. 6.6 mm denudation) and led to the rapid evolutions of gullies in Engaruka North (EN) ([65]), see Figure 2. [32] employed a medium resolution (30 m) global digital elevation model, DEM (ASTER DEM) in an agent-based model (Engaruka Sediment Transport and Trapping, ESTTraP) and estimated a denudation of approximately 3.5 mm for an area covering 3000 m² in Engaruka North, see Figure 2. These denudations translate to 108 & 42 Mg∙ha⁻¹∙yr¹ respectively assuming a 1.2 g/cm³ soil bulk density ([42]; [58]). Stump ([59]) stratigraphically estimated soil accumulation of over 2 m deep in the southern end of Engaruka over a period of 300 years. [31] further utilized a Structure for Motion (SfM) approach on archival photos and UAV images over the central section of the site (Engaruka Central) and detailed its usefulness cultural heritage management e.g. reconstruction of earlier landscapes especially in such a data poor region. They acknowledged the low accuracy of the 3D products from the archival data due to the lack of camera calibration metadata and scan errors. However, these studies neither quantified the spatial pattern of lateral movement of soil (amount and distribution of soil erosion/deposition) nor the eroded volumes within the gully channels and gorges in this archaeological area.

Figure 1.(a) A 1958 historical aerial image (British Institute in Eastern Africa (BIEA)) ([60]; [62]) showing the ancient stone-terraced landscape of Engaruka North Terraced Area (ENTA). The terraces and the farm plots appear as soil marks (light and dark linear variations); (b) A 2025 Google Earth image of the same extent as Figure 1(a) showing farmland encroachments onto the terraced site. Other visible landscape changes include settlement (the circular Maasai nomadic houses, Manyattas), gullies and transportation tracks and trails.

Figure 2.(a) A 1958 archive image (British Institute in Eastern Africa (BIEA)) ([60]; [62]) depicting minimal gullying. The red ellipse indicates the location Figure 2(b) was taken. The blue polygon gives the ESTTraP site location [32] (b) A 2023 on-field picture by the author showing how land degradation is affecting a stone-lined irrigation channels ([59]; [65]). Notice the savannah landscape and the towering rift escarpment in the background.

A recent review of soil erosion studies in cultural areas indicates that quantifying erosion in archaeological areas is a complex task due to the complexity of erosion processes hence the very low number of publications in the past three decades ([52]). In recognition of this critical need, international bodies like the United Nations have laid out goals (UNSDG 11.4.1) to promote conservation ([52]). Among the methods summarized in ([52]) is Mitasova et al.’s ([47]; [46]; [46]) Unit Stream Power-based Erosion Deposition (USPED) model which is a modification of the commonly used Revised Universal Soil Loss Equation (RUSLE). USPED parameterizes terrain curvature to map spatial pattern of erosion and deposition of a complex topography. It measures lateral movements of soil under sheet, rill and/or gully scenarios ([8]; [25]; [28]). Notable works of this model in natural & cultural heritage sites include ([9]; [21]; [43]; [44]; [51]). Some researchers e.g. ([23]) have further refined the outputs of this model by experimenting with VHR UAV-derived (DEMs). Similar to the RUSLE model, USPED is limited in that it doesn’t estimate gully sediment volumes. Geomorphological studies (non-archaeological) by Frankl et al. and Zhuang et al. ([19]; [20]; [73]) not only showed the value of 3D UAV data in modelling gullies within East Africa Rift System (EARS) but also demonstrated how aerial photographs from the colonial period can be of use in such a data-poor region. Jorayev et al. ([29]) computed Olduvai’s high erosion volume (585 million m³) in the adjoining Ngorongoro basin using UAV and highlighted the value of gorge morphometric data in heritage conservation. The aims of the study are: 1) to determine the soil erosion-deposition rates and sediment routing in Engaruka North Terraced Area (ENTA) based on the USPED empirical model and VHR UAV-DEM and 2) to complement the USPED results with 3D volumetric sediment analysis on an active section of the Intermediate North Gorge, (Gully site), ENTA.

We conducted ground visits as well as interpretation of the UAV very high-resolution images to check the validity the resultant USPED erosion-deposition (see Figure 22). Due to lack of reliable and valid field gauging stations, we compared our findings with other soil erosion studies in and around the Engaruka basin ([72]). The area’s erosion rate is slightly above the tolerable limits (25 t∙ha⁻¹∙yr⁻¹) for highland areas ([36]). Wynant et al. ([70]) utilized the RUSLE model in the neighboring Lake Manyara basin and mapped erosion hotspots dynamics without stating the erosion rates therein. Wynant et al. ([69]) also used geochemical fingerprinting/source-tracing technique in the Lake Manyara basin and found sedimentation rates to be between the range of 80 - 181 t∙ha⁻¹∙yr⁻¹.

Figure 22.(a), (b), (c) and (d) on-ground validation pictures for the ENTA USPED model focusing on intensive erosion and deposition areas ([51]).

Many other researchers have reported such erosion rates within the East Africa Rift Valley System ([1]; [17]; [33]; [64]; [68]). Subhatu et al. (Subhatu et al., 2017) applied the RUSLE model in the terraced croplands of Minchet catchment, Ethiopia and found an annual soil loss of 32 - 37 t∙ha⁻¹. In the neighboring Meatu Distirct, Simiyu region, Stocking ([58]) used low-level aerial photography and field survey with Universal Soil Loss Equation (USLE) and estimated erosion and deposition rates to 61.6 t∙ha⁻¹∙yr⁻¹ and 36.9 t∙ha⁻¹∙yr⁻¹ respectively. Defersha et al. (Defersha et al., 2012) reported erosion rates of 120 t∙ha⁻¹∙yr⁻¹ in the Mara River, Serengeti using Erosion-3D and Water Erosion Prediction Project (WEPP) models; [16] reported sediment rates of 15.7 t∙ha⁻¹∙yr⁻¹ in Lake Manyara basin using Soil and Water Assessment Tool (SWAT); [16] further used field erosion pins to study channel bed erosion in selected gullies within the Lake Manyarra national park and found maximum erosion pin measurements as 11.9 cm and 10.5 cm for erosion and deposition respectively. Frankl et al. ([19]) in Ethiopia and Zhuang et al. ([73]) also reported rapid evolution of gully systems within the Kenyan EARS based on historical images and UAV data. Other soil accumulation studies within the Engaruka Basin include Kabora et al. ([32]) (42 t∙ha⁻¹∙yr⁻¹) and Westerberg and Hagberg ([65]) (108 t∙ha⁻¹∙yr⁻¹). Our model results depicted high linear erosion pattern along linear features e.g. gullies, rills and road networks (see Figure 14 to Figure 19) as similar to other USPED studies ([23]; [44], [43]; [51]). Moreover, Figure 17 and Figure 18 show increased pattern of erosion and deposition due to land tilling which is in line with work of ([23]) that evaluated soil erosion and historical land use with USPED. In addition, Figure 14 indicates a more stable pattern in comparisons Figure 17 to Figure 18 due to the protective nature of vegetation i.e. trees. Gioia et al. ([23]) further suggested that linear physical features like roads and trails can reduce surface erosion by allowing water to flow in a channeled manner. While this is true, such channeled flow, especially on arid, hilly areas like Engaruka, can result to intensive gullying if there are control measures e.g. gabions and check dams. Some of the limitations of the USPED model is use include its inability to estimate short-term soil losses e.g. amounts for a single El-Nino event plus inability to model complex physical process of soil erosion ([2]). Therefore, there is need to plan for physical based models e.g. use or erosion pin measurements so as to improve such results and comprehensively understand erosion in the area. Use of equipment like terrestrial 3D laser scanners can further quantify detachment of stone features on the banks of gullies within the site ([3]) e.g. monitoring the exposed irrigation canal shown on Figure 2(b). Another recommendation is to incorporate field-scale techniques that can monitor the impact of trail erosion on the stone features in Engaruka ([30]).

Westerberg and Hagberg ([65]) demonstrated how both high and low magnitude geomorphic processes are main the drivers of soil erosion at Engaruka. Figure 23 shows some of the anthropogenic factors (overgrazing, farms & settlements) that further exacerbate this hazard. It’s worth mentioning that as depicted by the Google Earth images on Figure 23, the local inhabitants have encroached on the ancient terraced area in Engaruka North by approximately 300m between the years 2017 and 2025. Poor farming practice (little soil conservation measures e.g. no re-terracing) is evident on the Google Earth imagery. Studies like that of Wolka et al. ([68]) demonstrated how simple soil conservation measures e.g. terraces and bunds can reduce soil erosion rates by up 92%. Since gullying is now a severe problem that threatens to destroy the northern half of Engaruka site, it would be prudent for the concerned authorities (e.g. the Ngorongoro Conservation Authority), particularly in the interest of anticipated land use and climate change in the Serengeti region ([35]; [39]; [41]; [50]), to conduct thorough sensitization programs to educate the local community about heritage management.

Figure 23.Anthropogenic (socioeconominc) drivers of soil erosion in Engaruka archaeological site (a) overgrazing, Photo taken by Lars-Ove Westerberg (b) construction of Maasai settlements (Manyattas) resulting to structural damage of the stone bordered farm plots and terraces (c) 2017 Google Earth image showing farmland encroaching on to the terraced areas (notice the linear crop marks) (d) current (2025 Google Earth image) farmland boundary has shifted as indicated by the red arrows.

Soil erosion and deposition in Engaruka have led to some of the ancient remains being covered by topsoil and debris. Figure 24 shows more examples of some of surface and near-surface stone features on the site. Space radar has been shown to map subsurface archaeological features especially in homogeneous sand within desert areas ([10]; [12]; [24]). Although Engaruka doesn’t present such unique qualities favorable for radar penetration, for experimental purposes, we acquired two scenes of the second-generation, Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR-2) Spotlight (SL) mode data to test detectability of both surface and near-surface dry-stone features. The two PALSAR-2 SL datasets were acquired in the month of October which falls within the dry season for semi-arid Engaruka and in different specifications (incidence angle and direction). Similar to Balz et al. ([7]), Stewart et al. ([57]), and Cigna and Tapete et al. ([13]), we hypothesized that detectability of eroded dry-stone archaeological features (e.g. >2 m diameter, the linear stone terrace and reticulated stone-bordered patterns) in the VHR radar SL data will be high given the low biomass or vegetation during the dry conditions. We used SNAP software to process the Single Look Complex (SLC) data by radiometrically calibrating and geocoding each scene to map geometry. Backscatter images were interpreted alongside optical imagery, including archival photos, WorldView-2, UAV orthomosaics and Google Earth as well ground survey data. We avoided multi-looking and also experimented with unfiltered images in order to preserve the SAR spatial resolution ([7]). Due to high backscattering (speckling effect), none of these stone circles were visible or detectable on the processed radar images. However, a keen eye can pick out the faint linear pattern of stone terraces in Engaruka North (see Figure 25). Figure 26 gives an on-ground view of these stone terraces as well their appearance on optical imagery (linear pattern of soil and crop marks). Similar to ([7]), the linear stone terraces pattern was more detectable on the SL scene with lower incidence angle (34.2⁰). Nevertheless, more radar scenes with varying radar geometry would be needed for conclusive experimentation ([12]).

Figure 24.Example of dry-stone surface features we expected to be detected on the VHR PALSAR-2 SL images: (a) low-level stone circles; (b) mound-like stone collection (rock-piles); (c) high-wall stone circles. The scale bar visible on the pictures is 1m long. The human figure in the picture is 1.78 m tall. Example of dry-stone features near-surface features we expected to be detected on the VHR PALSR-2 SL images: (a) exposed irrigation channel walls ([65]) (party excavated), photo by Rob Marchant ([40]); Note the top left pedological profile inset from ([65]) indicting nature and stratigraphy of the Torripsamment soil type dominant in the area. In this inset, ‘A’ refers to Orchric epipedon layer, ‘C1’ for Sandy texture and ‘C?’ for Clayey or Silty texture (b) excavated irrigation walls from ([59]), the visible scales are 2 m by 1 m; (c) sediment traps and irrigation furrows from ([59]), scale is 1 m. These sediment traps cover an area of about 9 Km² in Engaruka North catchment ([32]).

Figure 25.The faint detection of the linear stone terrace pattern in ENTA by PALSAR-2 SL data: (a) the linear stone terrace pattern as picked by the 34.2⁰ incidence angle data. Non-archaeological features (Maasai nomadic house structures, Manyattas) are marked with a yellow box; (b) The linear stone terrace pattern as detected by the image with 51.4⁰ incidence angle data. The pattern is more visible on the 2016 image with a lower incidence angle.

Figure 26.(a) On-ground photo of the same area shown inFigure 25. Notice the linear stone terraces (yellow arrows) and soil deposition in between the terraces; (b) a Google Earth image for the same extent showing crop marks; (c) a false-color WorldView-2 image for the same extent; (d) a true color WorldView-2 image for the same extent. The visible circular, non-archaeological features are Maasai nomadic house structures, Manyattas.

Engaruka North faces a severe gully erosion problem and direly needs urgent soil conservation measures. The USPED model indicates elevated (pronounced) erosion-deposition patterns along the gully networks as well as in areas with land use changes e.g. current farmlands. Vegetated areas e.g. those with trees had more stable erosion-deposition levels as compared to barren or gullied areas. Is it possible for the Ngorongoro Conservation Authority to reestablish the stone-terraces and raise them as in ancient times ([18]) thereby regain control of surface runoff from the towering escarpment? Other possible measures may include erecting check dams, gabions as well as promoting tree planting in the lowland areas. This study highlights the importance of VHR DEM in understanding the distribution of sediment routing in an archaeological area. Our experimentation with radar data also forms a vital reference to other users intending to apply SAR data to study similar stone features in Sub Sahara region ([14]). The VHR datasets can also be incorporated in further studies in this data-poor area to monitor this crucial hydrogeological threat.

This study offers a valuable tool for the conservation and management of the da-ta-poor and semi-arid Engaruka archeological site. To the knowledge of the authors, this is the first attempt integrating different technologies (UAV, SAR and soil erosion/deposition models) in East African archaeological sites. However, it paramount to consider its limitations when applying the results for decision-making. It was difficult to quantitively validate the USPED empirical model results due to lack of measured/gauged stations. Future recommendation includes incorporation of complementary techniques such as physical erosion stakes, short-term sensors and more physical-based erosion models. The use of different datasets with different spatial resolutions can affect the results of empirical soil erosion models. Therefore, these results could be biased due to coarse spatial interpolation that compounds inherent limitations in the USPED model. USPED lacks a process-based structure thus fails to route sediment from its source to the sink ([25]). Moreover, the data used is not real time but from different acquisition dates affecting the absoluteness of the results. Lack of current and precise data for R, K, C factors and general assumption of a unit (“1”) P factor reduced the accuracy of USPED and restricted its ability to predict short-term losses. The C parameter fails to consider tillage methods that affects erosion redistribution patterns. These USPED parameters can also be modelled in a future sense to account for anticipated land-use and climate changes ([4]). Presence of sparse vegetation cover, soil types and the stone-strewn landscape limited the detection capability of the SAR data. However, the comprehensiveness of this analysis can be improved by incorporating multiple SAR data from different satellite missions and with different viewing radar specifications as recommended by ([7]; [11]). The study estimated E-D rates for the Engaruka North Terraced Area and not the entire archaeological site. In addition, only a small section of the Intermediate Gorge was imaged and also didn’t sample other active gorges e.g. north of Makayuni river. Errors in the 3D gully volume estimates included gully rim boundary line demarcation, light and wind speed conditions during data take, interpolation and surface processing errors e.g. shadows from vegetation canopy cover ([71]), see Figure 10 and Figure 11. Similar to ([19]; [38]) multitemporal UAV or close-range imaging can provide better E-D change rates within the active gullies especially at the temporal scale of singular rainfall events. The archived aerial image scans weren’t applied in a true two-date 3D change analysis due to lack of sufficient cam-era calibration metadata. Future research could consider high-resolution data, both spatial and temporal e.g. terrestrial laser scanners so as to monitor gully formations, reveal in-depth erosion processes and their governing factors. Such techniques can quantify low-magnitude processes (dry-bank and aeolian erosion, debris flow and archaeological feature disintegration due to gullying see Figure 27). Socioeconomic factors e.g. overgrazing, nomadic lifestyle and improper cultivation play an important role on land degradation and soil erosion in Engaruka. Further studies can access these socioeconomic factors via detailed questionnaires about small-holder land-use practices and pastoralism.

Figure 27.Examples of loactions within ENTA recommended for very-high resolution erosion monitoring. (a) erosion due to overgrazing, settelments and trails (b) dry and wet bank erosion (red arrows) and effect on archeaologcal channel artefacts (c) an on-site photo showing wind and dust storms (d) archaoeological rock slides and movement due to rills and gullies (a disintergating stone circle in close proximity to a gully (yellow arrow)).

Despite its limitations, this study represents a critical step in the analysis of cultural heritage in data-scarce regions and is useful for conservation and mitigation planning. The study highlights the need to devise anti-erosive management particularly oriented towards the foot slopes of the western EARS and the gully networks. ([22]) reported that smallholders in Konso, Ethiopia, a UNESCO AIIEA site responded to climate variability by adopting terracing, agroforestry, soil bunds, intercropping and reduced tillage. Other coping strategies they suggested include (1) reducing farm productivity and diversifying livelihoods into nonfarm/off-farm activities and (2) increasing community awareness on soil conservation so as to reduce encroaching onto the site ([4]). Similar measures can be adopted at Engaruka plus mechanical soil conservation measures for instance terrace reconstruction, check dams, gully plugs and minimizing the availability of rocks used to construct the Manyatta settlement wall fences contributing to the ruin of Engaruka’s dry-stone features.

The authors extend their gratitude to the University of Dar es Salaam and Department of Museums and Antiquities, Tanzania for their hospitality and assistance during field work. We also thank the Tanzania Commission for Science and Technology (COSTECH) for permitting us to obtain ground data within the Ngorongoro-Lengai UNESCO Global Geopark, Ngorongoro Conservation Area, COSTECH Permit No. 2019-682-NA-2019-386. Furthermore, the authors sincerely thank Professor Daryl Stump, his (Archaeology of Agricultural Resilience in Eastern Africa) AAREA team, Professor Amaury Frankl and Professor Lars-Ove Westerberg for their constructive insights. We appreciate the support we received from Mr. Christognas Ngivingivi, Ministry of Natural Re-sources and Tourism, Department of Antiquities, Tanzania. We finally would like to thank the reviewers who significantly enhanced this article.

George Watene, Yueping Nie, Lijun Yu were responsible for the conceptual and research method design. George Watene is the principal researcher and wrote the manuscript. Thomas Biginagwa, Christognas Ngivingivi and Leka Tingitana were responsible for UAV flight permits, data acquisition and data analyses. Felix Mutua, Thomas Ngigi, Xianhu Wei played the project supervision and administration roles. Yves Hategekimana and Thomas Ngigi were responsible for reviewing, statistical analysis and discussion. All authors have read and agreed to the published version of the manuscript.