Mapping and Characterization of Planosols in the Omo-Gibe Basin, Southwestern Ethiopia

Abstract

Planosols are seasonally waterlogged soils characterized by an abrupt transition from coarse-textured surface horizons to dense, clay-enriched subsoils. Despite the increased agricultural expansion in the Planosol landscapes, these soils have been largely overlooked in Ethiopia. The FAO soil map of Ethiopia (1:200,000 scale) does not recognize the presence of Planosols. In contrast, the more recent digital soil map of Ethiopia, EthoSoilGrids v1.0, at a 250 spatial resolution, was not detailed enough to capture Planosol landscapes, reflecting their historical undersampling in the legacy data. To address this gap, we conducted a thorough mapping and characterization of Planosols in the Omo-Gibe basin, southwestern Ethiopian highlands. Using over 200 auger observations, 74 georeferenced soil profiles, 296 laboratory analyses, and Random Forest modeling, we produced a 30 m-resolution soil-landscape map. Our results show that Planosols cover about 18% of the basin, a substantial extent previously unrecognized in national exploratory maps. Morphologically, these soils exhibit abrupt textural change from the coarse-textured, light grey Ap/Eg horizon (about 30–40 cm thick) to a very clayey, grey–black Bssg/Bt horizon occurring below 40 cm depth. Analytical data on selected parameters show the following pattern: low clay contents (20–29%) and acidic pH (5.2–5.8) with relatively low CEC values (11–26 cmol/kg) in the surface horizons (Ap/Eg), but pronounced clay increase (37–74%), higher bulk density (1.3 g/cm³), higher pH (up to 6.5), and substantially higher CEC (37–47 cmol/kg) in the sub-surface horizons (Bss/Bt). In terms of soil fertility, Planosols are low in SOC, TN, and exchangeable K contents, but micronutrient levels are variable—high in Fe-Mn-Zn and low in B and Cu. The findings confirm the diagnostic features of WRB Planosols and align with regional East African averages, underscoring the reproducibility of our approach. By rectifying long-standing misclassifications and generating fine-scale, field-validated evidence on soil fertility constraints and management options, this study establishes a strong foundation for targeted soil management in Ethiopia. It offers transferable insights for Planosol-dominated agroecosystems across Eastern Africa. Globally, the dataset contributes to enriching the global scientific knowledge and evidence base on Planosols, thereby supporting their improved characterization and management.

1. Introduction

In the context of the environmental challenges of land degradation and food insecurity, the protection and sustainable management of soil resources in Africa are of paramount importance [1]. Comprehensive knowledge of soil resources in terms of spatial extent and properties is essential for sustainable management decisions based on the potentials and limitations of the soils [2,3].

The revised legend of the FAO-UNESCO soil map of the world recognizes Planosols as one of the major soil groups [4]. In the World Reference Base for Soil Resources (WRB), Planosols are accommodated under the set of soils with stagnic properties, and having an abrupt textural difference between a weathered volcanic ash surface layer and denser clayey sub-soil [5,6,7]. The soil atlas of Africa at 1:3 M scale depicts a large expanse of Planosols (276,762 km²) accounting for about 1% of the African landmass [1,8]. The eastern African region is one of the world’s major Planosol areas with clearly alternating wet and dry seasons [9]. In Ethiopia, Planosols are less common and restricted to pocket areas in the southwestern highland plateaus associated with the Main Rift valley [5,10]. The Planosol eco-region extends from the sub-humid southwestern Ethiopia to parts of northern Kenya, south Sudan, and northeast Uganda [8,9]. The soils are defined by a light-colored, eluvial (E) or ploughed (A) horizon with signs of periodic waterlogging, sharply overlying a dense, slowly-permeable clayey subsoil [9].

However, although the highlands of Ethiopia contain Planosol-bearing landscapes, explicit information on the extent and properties of Planosols is sparse and limited primarily to the pedogenetic development of Planosol profiles [5,7]. The soil resources of Ethiopia have been mapped at an exploratory scale (i.e., 1:2,000,000) based on aerial photos and satellite image interpretations that were not adequately validated with profile data inputs [10,11]. However, its coarse resolution and limited field validation have contributed to the widespread misclassification of Planosol landscapes. In several areas, Planosols were incorrectly identified as Vertisols or Andosols—likely because they share similar landscape positions (flat to gently undulating terrains) and physical characteristics, such as clay-rich subsoils and stagnic properties. More recently, a national-scale digital soil map of Ethiopia, EthioSoilGrids v1.0 [12], was produced at a 250 m resolution using ~14,700 legacy soil profile data points and Random Forest modeling to predict reference soil groups. Although this represents a significant improvement over the previous 1:2,000,000-scale national scale, the map still lacks sufficient topographic detail to capture the biophysical diversities in the Ethiopian highlands. Consequently, it cannot provide the functional information necessary for informed soil fertility management decisions at the local level. As a result, Planosols remain highly underrepresented in the predicted output (0.04% area coverage), reflecting both their historical undersampling in the legacy data used for this map and frequent misclassification with other vertic soils. To address this gap, the present study explicitly targets Planosol landscapes for higher-resolution mapping and field-based characterization to improve their recognition and management potential in Ethiopian highland agriculture.

The overall aim of the study is to test the hypothesis that higher-spatial-resolution mapping and the detailed characterization of Planosols will reveal the extent of the soils and their distinctive pedological properties, thereby avoiding their misclassification in soil surveys, and provide the essential information and baseline knowledge needed for their sustainable management in agricultural landscapes in the Ethiopian highlands. The specific objectives were to (a) map the spatial extent and distribution patterns of Planosols in the Omo-Gibe Basin at the reconnaissance scale (1:250,000), in order to improve the classification accuracy compared to previous exploratory-scale (1:2,000,000) maps that often misidentified Planosols as Vertisols and sometimes as Andosols; (b) characterize the morphological, physical, and chemical properties of representative Planosol profiles to generate scientifically robust baseline data for classification and pedological interpretation, addressing the current paucity of information on these soils in Ethiopia and Eastern Africa; and (c) assess the agronomic constraints and management implications of Planosol landscapes with a view to informing farmers, extension agents, and policymakers on sustainable agricultural utilization, particularly relevant for other Planosol-dominated regions in Eastern Africa and beyond, where similar soils remain under-researched and debated within the international soil science community. To this end, we quantitatively benchmarked key properties of Planosol profiles across Eastern Africa and identified actionable management guidance.

2. Materials and Methods

2.1. Study Area

The study covers the upper reaches of the Omo-Gibe basin, which extends to the western margin of the central Rift Valley of Ethiopia, feeding into the Turkana Lake (Figure 1). It covers about 2,967,237 ha, 99% of which falls in the Omo-Gibe River basin, and the remaining fraction drains into the Rift Valley basin. The major geomorphic features include moderate to high-relief hills (32%), dissected side slopes (26%) and undulating to rolling plateaus (15%), accompanied by driver gorges (6%), plains and pyroclastic plateaus (6%) [10]. The underlying geology is characterized by the trap series volcanics of the Tertiary period, which consist of massive lava flows consisting of nimbrite, trachyte, rhyolite, tuff, and volcanic ash flows [13].

The altitude ranges from as low as 648 m in the depressions to as high as 3393 m in the summits, particularly in the western part, but the most significant part of the study area lies within an altitude range of 1500–3000 m. The climate ranges from tepid to cool sub-moist highlands, reflecting the significant variations in altitude and topographic features. It is characterized by distinct alternating wet and dry seasons with bimodal patterns of rainfall. The short rainy season runs from February to April, while the primary growing season is from June to October, with peak rains in July and August. The long-term average rainfall ranges between 1200 and 1800 mm. The temperature is relatively constant, with a minimum of 0 °C and a mean of 25.3 °C to 27.5 °C. Figure 2 summarizes the long-term average rainfall and mean max and mean min temperature data for the study area.

2.2. Field Survey and Characterization

2.2.1. Auger Observation and Profile Pit Location

A field survey was conducted using a free survey method [11], utilizing the geomorphology and soil association map of Ethiopia at a scale of 1:2,000,000 as a base map. The base map depicts geomorphology (geology and landforms) with a legend describing the soil associations classified according to the FAO-UNESCO Soil Map of the World legend [14]. Over 200 systematic auger observations were examined along transects (summit, shoulder, backslope, foot slope) at a base spacing of 150–200 m in relatively uniform terrain. This captured shallow soil properties and helped identify boundaries between soil types identified based on breaks in slope, changes in surface soil color, stoniness, and land use patterns. For each mapping unit, a sample profile pit was located where auger observations indicated the most extensive soils based on examining 10–15 auger points in the immediate vicinity. This has led to the identification and description of 74 profile points that were georeferenced (Figure 1).

2.2.2. Profile Description and Sample Collection

Soil pits were opened to a depth of about 120 cm for profile description—genetic horizons were identified based on the recognized diagnostic surface and subsurface horizons. Soils were described in detail as per the FAO guideline for soil description [15]. Profile description focused on the characterization of the morphological features such as moist and dry Munsell color, texture by feel and coarse fragments, structure (grade–size–type), consistency (stickiness and plasticity); roots and pores (size–abundance); redoximorphic features (mottles, gleying, Fe–Mn nodules/concretions), among others. Master horizons (layers) were identified based on distinct changes in the morphological features and designated horizon symbols (A, E, Bs, Bt, etc.), and samples were collected from each horizon for laboratory analysis. All representative soil profiles were field-classified according to the WRB conventions, and subsequently validated and, where necessary, refined—using laboratory analytical data [6]. For Planosol profiles, soil samples were collected at fixed depth intervals (0–10, 10–40, 40–80, 80–120 cm) to align sampling with the distinct morphological characteristics in the observed pedogenic horizons, with particular attention paid to the abrupt textural change at a depth of about 40 cm separating bleached silty topsoil and clay-rich sub-soil layers in the profiles. A total of 296 samples were taken for the determination of selected physical and chemical properties at the soil fertility laboratory of the Water Works Design and Supervision Enterprise in Addis Ababa.

2.3. Laboratory Analysis

The samples were taken to the soil fertility laboratory of the Water Works Construction and Design Enterprise of the Ministry of Water in Addis Ababa, Ethiopia. The analytical methods followed the standard procedures, as outlined in [16]. The percentages of sand (0.05–2.0 mm), silt (0.002–0.05 mm), and clay (<0.002 mm) fractions of the fine earth (<2 mm) were determined using the modified sedimentation hydrometer procedure. Bulk density was determined by using the core-sampling method [17]. Soil pH was determined in water (pH-H₂O) using a 1:2.5 soil to water solution ratio with a pH meter as outlined in [16]. The organic carbon (OC) content was analyzed using the wet combustion method of Walkley and Black [18], and total nitrogen (TN) was determined by the Macro–Kjeldahl method [19]. In the determination of available phosphorus (AP), the Olsen sodium bicarbonate extraction solution was used at pH 8.5, and the amount of available phosphorus (Pav) was determined by spectrophotometer [16]. In the analysis of exchangeable bases and for cation exchange capacity (CEC), the ammonium acetate method at pH 7 was used. In the leachate, exchangeable Ca²⁺ and Mg²⁺ were determined using an Atomic Absorption Spectrophotometer (AAS), while Na⁺ and K⁺ were estimated using a flame photometer [16]. The contents of available micronutrients (Fe²⁺, Mn²⁺, Zn²⁺, Cu²⁺, and B²⁺) were extracted by using the di-ethylene tri-amine-penta-acetic acid (DTPA) extraction method [20].

2.4. Soil Mapping Procedures

The mapping combined field survey data (auger and profile observations) with spatial covariates using the Random Forest (RF) model. Digital soil mapping research suggests that RF has strong accuracy with messy geospatial predictors, especially when dealing with non-linear relationships, interactions, and correlated covariates, and it is a widely applied machine learning algorithm, particularly suited for handling complex, non-linear relationships and correlated predictors in digital soil mapping [12,21,22,23]. The theoretical and mathematical foundations of the RF model are well-documented [24,25,26,27]. The modeling process involved five steps: the selection of covariates, data preparation and integration, model training and tuning, model validation, and map production. Environmental covariates were selected as proxies for soil-forming factors, including geomorphology (geology, landform, relief), topography (DEM-derivatives such as slope, curvature, degree of dissection, etc.), spectral indices (e.g., NDVI and related indices), climate (precipitation, temperature, diurnal range) [21,25], and climate (precipitation, mean temperature, diurnal range). All raster layers were resampled to a uniform 30 m spatial resolution. Data preparation and integration included key soil property data such as depth to bedrock, texture, pH, CEC, exchangeable bases, organic carbon, and nutrients that were obtained from the analytical data of the profile samples. These were assigned to WRB soil reference groups following [28]. Model training and tuning were implemented in R v3.1.2 using the caret package [29]. Parameter tuning employed random search optimization with a random 3-fold cross-validation, repeated six times. The RF model was grown with 500 trees and a tuning length of 5 using statistical software v.3.1.2 [30]. Model validation involves comparing predicted soil classes against independent “hold-out” test data to evaluate performance, with model performance statistics generated using the caret R-package. Final maps were generated in ArcGIS v10.5 [31] using administrative boundaries from the GADM portal (https://gadm.org/ (accessed on 20 January 2024)). ‘Lattice’ was used in producing multi-panel (trellis) graphics and map visualization, displaying relationships between variables [32].

3. Results

3.1. Spatial Extent of Planosols Along Other Major Soil Types in the Basin

The digital soil map of the Omo-Gibe basin produced in this study identified a mosaic of soil types reflecting the basin’s environmental gradients. Eight Reference Soil Groups (RSGs) were mapped, and their spatial distribution aligns with expectations based on terrain, climate, and geology (Figure 3). The dominant soil types, in order of areal extent, are Nitisols (42%), Planosols (18%), Luvisols (16%), Leptosols (14%), Cambisols (5%), Andosols (2.5%), and Vertisols (1.5%). Nitisols are prevalent across the gently undulating to rolling landscapes and dissected plateaus, often intergrading with Luvisols. Less common soils include Alisols, found in isolated pockets on heavily leached, high-rainfall humid plateaus, and Regosols, which occur on eroded side slopes and mountainous escarpments.

Planosols, covering approximately 18% (545,531 ha) of the total study area, represent the second most dominant soil type in the Omo-Gibe basin, typically in the plains with seasonal water stagnation and gently sloping uplands with restricted drainage. Out of the 74 profiles studied, 6 were classified as Planosols, and these were considered for detailed sampling for physical and chemical characterization. The major qualifiers to classify mapping units as Planosol landscapes included (1) the presence of the light-colored Eg horizon; (2) the grey color and presence of mottles in this horizon; and (3) the abrupt textural change in the profile. These soils are primarily distributed across two distinct soil belts or eco-regions: (1) the Silte–Gurage–Wolaita belt, located along the eastern half of the basin near the margins of the Main Ethiopian Rift, and (2) the Omonada–Jimma soil belt, situated on the undulating plateaus and dissected side slopes of the western portion of the basin (Figure 4). In these landscapes, Planosols account for 80–90% of the agricultural landscapes (Figure 5).

3.2. Classification Error Matrix

Due to the integrating nature of the different soil types in the soil landscape, a prediction accuracy test of the Random Forest model was carried out using an error matrix and a kappa coefficient-dependent validation set of profile points, and classification accuracy metrics were developed (

Table 1. Error matrix showing prediction accuracy for each of the soil reference groups.

	AL	AN	CM	LP	LV	NT	PL	RG	VR	Total	ER
AL	11	0	0	0	1	2	0	0	0	14	0.21
AN	0	54	0	0	1	0	2	0	0	57	0.053
CM	0	0	22	0	5	1	3	0	0	31	0.290
LP	0	0	0	27	4	10	0	0	1	42	0.357
LV	0	2	0	0	76	22	7	2	2	111	0.315
NT	1	0	2	2	16	313	10	1	0	345	0.093
PL	0	2	1	0	3	2	160	1	19	188	0.149
RG	0	0	0	0	0	2	0	14	0	16	0.125

Abbreviations are set according to WRB 2014 [33]. AL, Alisols; AN, Andosols, CM, Cambisols; LP, Leptosols; LV, Luvisols; NT, Nitisols; PL, Planosols and RG, Regosols; ER, error.

). Class accuracy for Planosols classification was 89%, with a Kappa coefficient of 0.77, indicating substantial agreement between the predicted and observed Planosol occurrences and a reliable model performance in identifying this soil class. The largest misclassifications were between Planosols and Vertisols in the near-level depositional landscape positions, such as river terraces and valley bottoms. Other notable misclassifications occurred between Nitisols, Luvisols, and Cambisols, which frequently intergrade along the dissected side slopes and volcanic cone landscapes. These soils often share similar landscape positions, especially in transitional zones where soil boundaries are gradual rather than abrupt.

3.3. Typical Characteristics of Planosols

3.3.1. Morphological Properties

The morphological data on six Planosol profiles depict that the soils exhibit an Ap–Eg–Bssg–Bt horizon sequence. The Ap horizon was usually shallow (0–10 cm) while sub-soil Bssg/Bt horizons were very deep, mostly extending from 40 to 200 cm depth (

Table 2. Some morphological features of Planosol profiles.

Horizon/Depth (cm)	Profile Code	Color (Moist)	Structure Type/Size/Grade	Consistence Moist/Wet	Roots Abundance/Size
Ap (0–10)	1	10YR 4/2	CO, ME, WE	FR, NST, NPL	A, F
	2	7YR 4/1	GR, ME, WE	FR, NST, NPL	M, Me
	3	7YR 4/1	CO, ME, WE	FR, NST, NPL	C, F
	4	10YR 3/2	CO, ME, WE	FR, NST, NPL	M, Me
	5	10YR 4/2	CO, FM, WE	FR, NST, NPL	M, Me
	6	10YR 4/2	CO, ME, WE	FR, NST, NPL	C, F
Eg (10–40)	1	10YR 5/1	CO, ME, MO	FR, SST, SPL	A, F
	2	7.5YR 4/2	GR, ME, WE	FR, VST, VPL	F, F
	3	7.5YR 4/2	GR, ME, MO	SHA, NST, NPL	C, F
	4	10YR 6/1	GR, CO, WE	SHA, NST, NPL	C, VF
	5	10YR 5/2	CO, FM, WE	SHA, NST, NPL	F, F
	6	10YR 5/2	GR, ME, WE	SHA, VST, VPL	C, M
Bssg (40–80)	1	10YR 2/1	AB, ME, ST	SHA, VST, VPL	VF, F
	2	10YRY 3/1	SAB, ME, ST	FR, VST, VPL	VF, F
	3	10YR 2/1	AB, FI, ST	FI, SST, SPL	F, VF
	4	10YR 3/2	AB, FI, ST	SHA, ST, PL	F, VF
	5	10 YR 3/2	AB, ME, ST	HA, ST, PL	VF, F
	6	10YR 3/2	AB, FI, ST	SHA, VST, VPL	VF, F
Bt (80–120)	1	10 YR 2/1	AB, FI, ST	FI, ST, PL	None
	2	10YR 2/1	SAB, ME, ST	SHA, VST, VPL	None
	3	10YR 2/1	AB, ME, MO	FI, ST, PL	None
	4	10 YR 2/1	AB, FI, ST	VHA, VST, VPL	None
	5	10 YR 2/1	AB, FI, MO	SHA, VST, VPL	None
	6	10YR 2/1	AB, ME, ST	SHA, VST, VPL	None

). The most consistent morphological feature of the studied profiles is the clear textural differentiation with the light-colored and coarse-textured surface layer (Ap), and the clay-depleted Eg horizon that abruptly overlays the slowly permeable subsoil (Bssg/Bt). The “Eg and Bssg” horizons are indicative of stagnant conditions, and strong gleying (mottling) with abundance of the Fe and Mn concretions, while Bt indicates a clay-enriched illuvial horizon.

The color of the Ap horizon ranges from dark grey (7YR 4/1, moist) to dark greyish brown (10YR 4/1, moist), while the Eg horizon is grey (7YR6/1, moist) to greyish brown (10YR 5/2, moist). The Bt-horizon is mainly dark grey (10YR 3/2, most) to black (10 YR 2/1, moist), although very dark grey (10YR3/1) to very dark greyish brown (10YR3/2) colors were also observed in the Bssg horizons (Table 2). Typically, the soil profiles exhibited an abrupt textural change marked by a sharp transition from a coarser sandy loam to a finer, denser clay texture beginning at approximately 40 cm depth. Below this depth, clay content increased markedly in nearly all profiles, while sand and silt contents showed a corresponding decline (Figure 5).

Codes follow the soil description provided in FAO (2006) [15].

Structure: Gr, granular; ME, medium; WE, weak; PR, prismatic; ST, strong; BL, Blocky; AB, angular blocky; SAB, sub-angular blocky; CO, coarse; Mo, moderate; CR, Crumbly; FM, fine to medium;.

Consistency: FR, friable; NST, non-sticky; NPL, non-plastic; SST, slightly sticky; SPL, slightly plastic; HA, hard; SHA, slightly hard; VHA, very hard; VST, very sticky; VPL, very plastic; FI, fine.

Roots: A, abundant; C, common; VF, very fine; F, few; M, medium; MM, medium many.

3.3.2. Physical Properties

The surface horizons (Ap and Eg) are sandy loam to sandy clay loam in texture; coarse (very rarely granular) and weak to moderately developed in structure; friable, non-sticky, and non-plastic in consistency, with common to many fine to medium roots. The vertic sub-soil horizons (Bssg/Bt) have a moderate to strong angular blocky (AB) to sub-angular blocky (SAB) structure that is mostly fine to medium in size, having very fine to no roots. Its consistency ranges from slightly hard to tough when dry, slightly sticky and slightly plastic to very sticky and very plastic, which are characteristic vertic properties. In most cases, the Bt horizon was characterized by typical clear polygonal swelling–shrinkage patterns, cracks, and pressure face (i.e., slickenside), and mottling as in the case of Bssg horizons (Table 2).

The mean sand, silt, and clay contents ranged between 42%, 29% and 29% in the Ap and 36%, 36%, 28% in the Eg horizons, while the mean bulk density was 1.11 and 1.17 g/cm³, respectively. The silt/clay ratio values decreased from 1.0–1.29 in the Ap/Eg horizons to 0.22–0.26 in the Bssg/Bt horizons, suggesting that the sub-soil horizons were more weathered than surface horizons (

Table 3. Particle size distribution, silt/clay ratios, and bulk density in some Planosol profiles.

Horizon/Depth	Profile Code	Sand (%)	Silt (%)	Clay (%)	Silt/Clay	BD (g/cm3)	Texture Class
Ap (0–10 cm)	1	42	38	20	1.90	1.01	SL
	2	45	18	36	0.50	1.03	SCL
	3	46	30	24	1.25	1.05	SL
	4	38	32	30	1.07	1.19	SCL
	5	40	34	26	1.31	1.34	SL
	6	40	21	39	0.54	1.06	SCL
	Mean	42	29	29	1.00	1.11	SCL
Eg (10–40)	1	29	49	22	2.23	1.05	SL
	2	63	16	21	0.76	1.10	SL
	3	36	42	22	1.91	1.16	SL
	4	28	36	36	1.00	1.32	SCL
	5	30	34	36	0.94	1.24	SCL
	6	31	36	33	1.09	1.20	SCL
	Mean	36	36	28	1.29	1.17	SCL
Bssg (40–80)	1	25	23	52	0.44	1.16	C
	2	20	13	66	0.20	1.28	C
	3	16	18	66	0.27	1.29	C
	4	22	20	58	0.08	1.33	C
	5	26	20	54	0.14	1.28	C
	6	20	14	66	0.21	1.39	C
	Mean	21	14	60	0.22	1.29	C
	1	29	14	57	0.25	1.25	C
Bt (80–120)	2	31	10	59	0.17	1.32	C
	3	30	14	56	0.25	1.39	C
	4	18	10	72	0.34	1.33	C
	5	16	14	70	0.25	1.39	C
	6	21	14	64	0.22	1.35	C
	Mean	27	15	63	0.26	1.34	C

C, Clay; SL; sandy loam; SCL, sandy clay loam.

). As weathering advances, clay-sized secondary minerals increase with depth due to clay migration from the surface through eluviation and accumulation in the lower horizons [34].

The bulk density of the soils seems a mirror image of the morphological, structural, and textural differentiation that increased with depth. The coarse-textured surface horizons showed a lower bulk density, with mean values ranging from 1.11 to 1.17 g/cm³, while the dense-textured and vertic subsurface horizons showed higher bulk density with mean values in the range of 1.29 to 1.34 g/cm³ (Table 3). The high soil density in the Bt horizon (Table 2) is consistent with the morphological characteristics, such as medium to large angular or subangular blocky structures with strict consistency. This promotes an environment with deficient drainage, which makes it difficult for plant roots to aerate, and this, in turn, results in poor root development (Table 2). The higher bulk density in the deeper horizons is likely related to clay and mineral eluviation from the upper horizons, which is then deposited in the deeper horizons.

3.4. Selected Soil Chemical Characteristics

According to the ratings proposed by Landon [35], the soil pH (H₂O) ranges between strongly acid and slightly acid (5.0–6.3) in the Ap/Eg horizons with mean values of 5.64–5.86, which is moderately acid (

Table 4. Selected chemical properties of Planosol profiles.

Horizon/ Depth (cm)	Profile Code	pH (H2O)	OC (%)	TN (%)	AP (mg/kg)	CEC, Exchangeable Basis (Cmol(+)/kg)					BS (%)
						CEC	Ca	Mg	Na	K
Ap (0–10)	1	5.00	1.75	0.16	8	35	14	5	1.8	0.4	60
	2	5.40	1.53	0.03	8	25	9	3	2.4	0.5	60
	3	5.41	2.47	0.35	10	20	5	1	0.8	2.4	49
	4	5.99	3.36	0.28	5	22	10	3	0.2	0.6	63
	5	6.18	1.90	0.14	7	22	12	5	0.6	0.5	82
	6	5.88	3.33	0.26	6	30	13	2	0.7	0.1	52
	mean	5.64	2.39	0.20	7	26	11	3	1.08	0.75	61
Eg (10–40)	1	5.40	0.83	0.10	6	27	7	3	0.7	0.2	40
	2	5.20	1.07	0.02	4	22	6	2	1.1	0.5	44
	3	5.67	1.19	0.23	4	11	4	0	0.9	1.2	55
	4	6.35	1.88	0.16	3	18	7	2	0.3	0.4	54
	5	6.39	1.47	0.12	4	18	6	4	0.9	0.4	63
	6	6.16	2.16	0.17	4	22	7	2	0.7	0.1	45
	mean	5.86	1.43	0.13	4	20	6	2	0.77	0.47	50
Bssg (40–80)	1	5.40	0.67	0.08	4	49	26	9	2.7	1.2	80
	2	5.30	0.91	0.02	4	35	13	7	3.2	2.0	72
	3	6.85	0.68	0.05	6	60	43	12	1.8	2.4	98
	4	6.90	1.92	0.11	3	43	25	8	1.3	0.8	81
	5	6.63	1.09	0.11	4	36	25	6	1.9	0.9	92
	6	6.63	1.06	0.13	4	25	15	5	0.1	1.2	85
	mean	6.29	1.06	0.08	4	41	25	8	1.8	1.4	85
Bt (80–120)	1	7.30	0.32	0.03	2	64	43	5	2.3	1.4	81
	2	7.62	0.30	0.01	4	43	22	9	2.9	2.0	84
	3	7.60	0.75	0.03	3	58	45	8	1.5	2.3	98
	4	7.50	0.68	0.09	4	53	32	10	1.6	0.9	84
	5	7.22	1.03	0.11	4	43	30	9	2.3	1.2	99
	6	7.58	0.69	0.10	2	42	28	7	3.6	2.5	98
	mean	7.47	0.63	0.06	3	51	33	8	2.4	1.7	91

). The data show that Planosol surface layers are moderately acidic, while the Bssg/Bt horizons become neutral to slightly alkaline (Table 4). Pedons 1, 2, and 3 exhibit higher acidity (pH 5.64–5.86) than the others, likely reflecting the influence of higher rainfall and more intensive land use in those areas. The soils were depleted of organic carbon (OC), total nitrogen (TN) and exchangeable potassium, with mean values of 2.39%, 0.2% and 0.75 Cmol (+)/kg, respectively, while phosphate levels were in the medium range (7 mg/kg P-Olsson) in the plough layer. However, they sharply declined with depth (Table 4). The levels of exchangeable bases (Ca²⁺, Mg²⁺, Na⁺, K⁺) and CEC were in the medium range for the Ap horizon and low in the Eg horizons, but consistently high in the Bssg/Bt horizons across all profiles (Table 4).

According to the ratings suggested by Hazelton and Murphy [36], the levels of exchangeable K⁺ in Ap/Eg horizons were in the low to medium range (0.47–0.75 cmol(+)/kg), but high in the Bssg/Bt horizons with mean values of (1.4–1.7 cmol(+)/kg). Unlike most other Ethiopian highland soils in which Na⁺ appears only in trace amounts (Elias, 2016 [37]), the levels of exchangeable Na⁺ in the Planosols investigated are slightly sodic, showing an increasing trend with soil depth, suggesting the presence of salty groundwater. However, the exchangeable sodium percentage (ESP: exchangeable Na⁺/CEC multiplied by 100) was below 15%, suggesting that the soils were not yet saline/sodic. Considering the ratings for micronutrients proposed by Benton [38], the concentration of Fe²⁺, Mn²⁺, and Zn²⁺ is consistently high in all profiles, but Cu²⁺ and B²⁺ are in the low to very low range (

Table 5. Micro-nutrient content of the Planosol profiles.

Horizon/Depth (cm)	Profile Code		Available Micronutrients (mg/kg)
		Fe	Mn	Zn	Cu	B
Ap (0–10)	1	244	30	7.1	3.0	0.62
	2	164	85	4.1	3.0	0.61
	3	190	19	1.22	0.75	0.57
	4	277	163	4.04	2.36	0.57
	5	198	169	1.13	2.23	0.50
	6	208	67	2.25	1.63	0.38
	mean	214	89	3.00	2.16	0.54
Eg (10–40)	1	147	23	3.0	2.0	0.61
	2	160	80	2.0	3.0	0.57
	3	120	14	1.17	0.67	0.57
	4	170	13	1.02	2.10	0.47
	5	189	161	0.84	2.14	0.46
	6	169	42	1.96	1.97	0.16
	mean	159	56	1.67	1.98	0.47
Bssg (40–80)	1	138	14	2.0	2.0	0.59
	2	144	49	1.0	3.0	0.24
	3	140	30	0.29	0.47	0.45
	4	152	127	1.72	1.89	0.46
	5	184	146	1.07	1.85	0.38
	6	120	150	3.28	1.48	0.21
	mean	146	86	1.56	1.78	0.39
Bt (80–120)	1	133	10	1.0	1.0	0.46
	2	115	44	1.0	2.0	0.32
	3	130	20	0.24	0.27	0.42
	4	129	99	1.59	1.71	0.38
	5	149	78	0.95	1.59	0.30
	6	66	46	0.82	1.51	0.23
	mean	120	50	0.93	1.35	0.35

). There was a generally declining trend in the micronutrient contents with profile depth, which is inversely related to soil pH.

4. Discussion

4.1. Soil Distribution Across Landscapes

The Omo-Gibe Basin in southwestern Ethiopia hosts a diverse assemblage of soils shaped by the region’s complex interplay of topography, climate, and geology. The eight major soil types identified in this study exhibit a strong correlation with landscape position, reflecting pedogenic processes driven by elevation, parent material, drainage, and weathering intensity.

Nitisols emerged as the most extensive soil class, predominantly occupying upper landscape positions such as undulating plateaus, hilltops, and moderately steep slopes in the humid highlands. These soils integrate with Andosols on volcanic hilltops derived from pyroclastic parent materials. At the same time, transitions to Luvisols are commonly observed on gently to moderately sloping terrain under alternating wet and dry climatic regimes. The observed Nitisol–Luvisol landscape associations are consistent with previous studies in the Ethiopian highlands and with the global literature on primary soil resources [37,39].

Consistent with continental syntheses [1], Planosols are associated with gently undulating to flat foot slopes and seasonally wet valley fringes, where lateral and surface runoff tends to accumulate. In these slope positions, Vertic Planosols often mark transitional zones, exhibiting both abrupt textural discontinuities and slickensides indicative of shrinking-–swelling clays. In the volcanic plains or foot slope settings where volcanic ash overlies a dense clayey subsoil, Planosols were observed to integrate with Andosols. This pedogenic complexity may explain the frequent misclassification of Planosol-dominated landscapes as Vertisols—and occasionally as Andosols—on earlier coarse-scale maps [11,12]. In contrast, our 1:250,000 mapping separates stagnic Planosols from adjacent Vertic soils more reliably than national/global 250 m DSM products (EthioSoilGrids v1.0; SoilGrids 250 m) in dissected highland terrain, a known limitation of coarser grids trained on legacy profiles (Dewitte et al., 2013 [1]; Hengl et al., 2017 [40]).

The RF model has gained traction in digital soil mapping due to its robustness and superior predictive accuracy relative to other machine learning methods [24,25]. Our findings demonstrate that integrating geostatistical modeling with representative field observations enables the production of higher-resolution, cost-effective soil maps compared to conventional survey methods, which are often time-consuming and logistically demanding. Similar conclusions have been drawn by other studies in Ethiopia and beyond [2,3,21].

4.2. Relevance to the Sub-Humid Highlands

The new soil map of the Omo–Gibe Basin produced in this study makes a significant contribution to the sustainable management of the basin’s soil resources. Used alongside the Soil Atlas of Africa [1,8], it equips researchers, land managers, and policymakers with evidence to inform land-use planning and enhance agricultural productivity. Given that Ethiopia is one of the principal countries in the Eastern Africa region, our findings have relevance to the sub-humid highlands of Eastern Africa where Planosols are widespread [1]. Much of the physical and geological context associated with Ethiopian soils—particularly in the sub-humid southwestern highlands—is comparable to similar environments found throughout Eastern Africa [8]. Accordingly, the data and interpretations presented here provide valuable insights not only for national land management decisions, but also for regional soil classification and use, with specific implications for Planosols. More broadly, the dataset contributes to the global scientific knowledge and evidence base on Planosols, supporting improved characterization and management. To strengthen the global soil reference framework, there is a pressing need for more up-to-date, spatially explicit information on Planosols in the scientific literature. Developing such a reference database is essential for facilitating technology transfer, harmonizing classification systems, and enhancing communication and knowledge exchange among soil scientists at national, regional, and international levels [1,6,41].

4.3. Morphological Features and Textural Differentiation in Planosols

As shown in Figure 5, the pit wall reveals a light-colored, coarse-textured surface horizon sharply overlying a dark, clay-rich subsoil, with an abrupt textural change occurring at approximately 40 cm depth. This profile is consistent with the geogenic differentiation of clay. It aligns well with the WRB characterization of Planosols—namely, a bleached, loamy surface horizon abruptly transitioning to a denser, finer-textured B horizon [42]. The traditional practice is believed to contribute to the elevated silt content observed in the surface horizons, as reported in field studies from the area [43]. This may partly explain the notable variability in the silt/clay ratio across profiles. According to [44], silt/clay ratios below 0.15 generally indicate older parent materials, whereas ratios above 0.15 suggest relatively young parent materials.

The variation in color and thickness of the coarse-textured Ap/Eg horizon, compared to the very dark, heavy clay Bss/Bt horizon, may be attributed to hydromorphic conditions across the micro-relief, which influence soil water regimes. The development of the bleached Eg horizon is likely associated with pedimentation processes, such as erosion or denudation through scarp retreat. Periods of water-logging create reducing conditions that promote the accumulation of iron and manganese nodules within the Eg horizon [45]. These processes contribute to increased compaction, which may limit root penetration and reduce root abundance in the lower horizons.

It should be noted, however, that the geogenetic origin of the abrupt textural change remains a subject of debate in the literature. Ref. [7] outlines several possible explanations, broadly categorized into geogenetic and pedogenetic processes, as follows: (a) geogenetic processes involve differences in parent material, such as the sedimentation of sandy over clayey layers, the downslope movement (creep or sheet wash) of lighter-textured materials over finer substrates, the colluvial deposition of sandy materials atop clayey ones, or selective erosion where the fine fraction is removed from surface horizons; (b) physical pedogenetic processes include selective clay eluviation–illuviation in soils with low structural stability, which may contribute to the formation of a distinct Eg-Bss/Bt horizon boundary; (c) chemical pedogenetic processes, notably the mechanism known as ferrolysis [46], involve redox-driven transformations resulting from the microbial decomposition of organic matter. This process can lead to the destruction of 2:1 clay minerals and further accentuate clay translocation and horizon differentiation. These multiple pathways highlight the complex interplay of geological and pedological mechanisms contributing to the development of the characteristic horizonation in Planosols.

4.4. Quantitative Comparison of Planosol Profiles for Eastern Africa

By way of the cross-validation of the morphological characteristics observed in our study with the available data from previous works in the Ethiopian highlands and elsewhere in East Africa, we have made a quantitative assessment of selected properties—clay, bulk density, pH, and CEC horizon-wise (

Table 6. Quantitative comparison of mean values of selected properties of Planosol profiles for Ethiopia, Kenya, and the Eastern Africa region.

Property	Horizon	Ethiopia (Current Study)	Ethiopia (Previous)	Kenya (Mean)	East Africa (Mean)
Clay (%)	Ap	29	27	20	23
	Eg	28	23	28	27
	Bs/Bt	60	63	70	74
Bulk density (g/cm3)	Ap	1.10	NA	1.30	1.40
	Eg	1.20	NA	1.50	1.60
	Bs/Bt	1.29	NA	1.80	1.70
pH (H2O)	Ap	5.6	5.2	5.4	5.5
	Eg	5.8	5.3	5.8	5.7
	Bs/Bt	6.2	5.9	5.9	6.5
CEC (Cmol/kg)	Ap	26	21	21	18
	Eg	20	16	11	13
	Bs/Bt	41	46	47	37

NA—Not Applicable.

). Although there is limited published information and data on Planosols for quantitative comparison, we gathered available data on clay content, bulk density, pH, and CEC from various sources to compare our findings. Data on Planosols from previous work in the Ethiopian highlands were obtained from [7]. For Kenya, we extracted values from two profiles in the ISRIC Africa Soil Profile Database [47]. East Africa regional averages were approximated from the WRB lecture notes on the major soils of the world [9] and the ISRIC Africa Soil Profile Database. The quantitative means for Ethiopia, Kenya, and East Africa are summarized in Table 6. The data show that across the sub-region, surface (Ap/Eg) horizons of Ethiopian and Kenyan Planosols tend to have moderately low clay contents (20–29%) and acidic pH (5.2–5.8), with relatively low CEC values (11–26 cmol/kg) in the surface horizons (Ap/Eg). In contrast, subsurface (Bs/Bt) horizons exhibit a pronounced clay increase (37–74%), higher bulk density (1.7–1.8 g/cm³ in Kenya vs. ~1.3 g/cm³ in Ethiopia), higher pH (up to 6.5), and substantially higher CEC (37–47 cmol/kg). These values are entirely consistent with WRB reference ranges for Planosols and are closely aligned with East Africa regional averages —indicating no notable deviation of our data from regional precedents.

The close agreement between our Ethiopian dataset and the available East Africa averages reinforces the reliability and regional representativeness of our results, which not only validates our field and laboratory measurements, but also situates our findings within the broader pedological context of the region. By providing systematically collected and well-documented data on Planosoil morphological and chemical properties, our study fills an important knowledge gap in eastern Africa, where published quantitative information on this Reference Soil Group remains scarce. The addition of these new data points improves the existing regional soil information, enhancing future comparative studies, digital soil mapping efforts, and agroecological assessments. This strengthens the empirical foundation for both soil classification and targeted land management suggestions in regions where Planosols occur under similar agro-climatic and land-use conditions.

4.5. Fertility Limitations and Management Recommendations

4.5.1. Fertility Limitations of Planosols

The soils’ Ap horizons were generally depleted of OC and TN, which might be due to soil burning, overgrazing, and continuous cultivation that involves the complete removal of crop residues from fields [10]. The decline in phosphate levels with depth is reasonable because of the application of DAP (Di-ammonium phosphate: 18–46% N-P₂O₅) in the plough layer at the rate of 150 kg/ha in most of the cultivated fields. The levels of exchangeable bases and CEC consistently increase with profile depth, which can be explained by differences in the clay content and its mineral composition, and enrichment with clay with an abundance of high charge smectite clays [5,7]. As would be expected, the Eg horizon is base-depleted due to leaching and clay migration. Unlike most other Ethiopian highland soils, in which exchangeable sodium (Na⁺) typically occurs only in trace amounts [10], the Planosols examined here exhibited slightly elevated Na⁺ levels, indicating incipient sodicity. The general increase in the concentration of exchangeable Na⁺ with soil depth suggests the possible influence of saline or brackish groundwater [48]. Nevertheless, the exchangeable sodium percentage (ESP), calculated as (Exchangeable Na⁺/CEC) × 100, remained below the critical threshold of 15%, indicating that the soils are not yet classified as saline or sodic according to standard diagnostic criteria.

These results of chemical properties compare well with other studies elsewhere on Planosols, except for the relatively higher base status of the soil in much of the profile depth, which is in a way unique to the Ethiopian highland soils [5,34,49,50]. The generally high base saturation and CEC in these soils compared to Planosols elsewhere is explained by the fact that the soils in the Ethiopian highlands have developed on recent Quaternary lava flows that have high base status and CEC [10,13]. In addition, some volcanic parent materials such as rhyolites, granite, trachyte, and ignimbrites that are predominant in the southwestern Ethiopia plateau produce inherently acidic clays [51].

4.5.2. Management Recommendations

Planosols, which cover over half a million hectares in the Omo-Gibe basin, have the potential to significantly contribute to agricultural production and food security in this region, provided that appropriate soil management strategies are implemented to account for their inherent potential and limitations. The current EthioSIS recommendation of applying 100 kg NPS + B along with 100 kg urea per hectare [52] does not address potassium deficiency, and therefore warrants reconsideration. Given the observed severe deficiencies in nitrogen (N), phosphorus (P), and potassium (K) in these soils, the use of an NPKS + B blended fertilizer—comprising approximately 13.7% N, 27.4% P₂O₅, 14.4% K₂O, 5.1% S, and 0.54% B—is recommended as a more balanced nutrient input. Although the EthioSIS project, supported by the ATA and MoA, previously demonstrated the agronomic benefits of NPK-B blends [52], the observed copper deficiency in Planosols underscores the need for targeted crop response trials incorporating fertilizer blends with copper. Field verification trials are necessary to assess crop responses and determine site-specific optimal nutrient application rates for key crops grown on Planosols—such as teff, maize, and wheat—across diverse agroecological conditions. In addition, the application of agricultural lime is necessary to raise the low levels of soil pH and to improve nutrient availability, root growth, and overall crop productivity in these soils. Since the Ca:Mg ratios in these Planosols are relatively low, ranging from 3 to 4 across all profile horizons (Table 4), there is no concern of causing nutrient imbalance risks linked to lime application. Organic amendments such as compost/vermi-compost and residue incorporation can help build the surface structure, organic matter, and nutrient content of the soil.

Apart from nutrient-related issues, Planosols also present significant physical constraints for crop production. Water stagnation is a major problem, caused by inadequate surface drainage in the dense, nearly impermeable subsoil that severely restricts root development. This reflects the need for improved drainage management through the adoption of the Broad Bed and Furrow (BBF) system, which has been extensively tested across various agroecological zones of the Ethiopian highlands and found to be particularly suitable for vertic Planosols, where it enhances drainage and improves overall water management [53].

5. Conclusions

This study presents the first high-resolution (30 m) digital map of Planosol landscapes in Ethiopia’s Omo-Gibe basin that were previously misclassified as Vertisols and at times as Andosols in the national exploratory map at a 1:2,000,000 scale. By integrating over 200 auger observations, 74 georeferenced profiles, and 296 laboratory analyses with Random Forest modeling, we achieved 89% classification accuracy (κ = 0.77). We identified that Planosols occupy approximately 18% (545,531 ha) of the basin in two distinct eco-regional belts. The morphological and chemical characterization confirmed that these soils exhibit the key features of Planosols described in the WRB, and align closely with profiles reported elsewhere across eastern Africa.

Despite their inherent soil fertility limitations—nutrient deficiencies and acidity in the surface horizon, structural compaction and poor drainage—they are increasingly being brought under cultivation, particularly by landless youth expanding into communal grazing lands. This trend is driven by increasing population pressure and the resulting contraction and degradation of more agriculturally favorable soils, including Nitisols, Luvisols, Cambisols, and Andosols, which are increasingly affected by erosion, nutrient depletion, and unsustainable land use. Soil fertility and health management recommendations for sustainable agricultural production on these soils include applying NPK fertilizer blends supplemented with deficient micronutrients (particularly B & Cu), applying agricultural lime at appropriate rates to optimize pH, and using a broad-bed-maker to improve surface drainage.

The quantitative comparison of the morphological and chemical characteristics of the Planosol profiles in this study closely aligns with the criteria for Planosols outlined in the WRB and the information available for similar soils in eastern Africa, where Ethiopia is one of the key areas of Planosol occurrence. This reinforces our findings, demonstrating that the methods we applied and the management insights provided can be effectively transferred to similar agroecological settings in eastern Africa. Additionally, the results add to the current scientific debates about the classification and management of Planosols, a Reference Soil Group that is still under discussion and refinement within the World Reference Base system.