This study was conducted in Melka Wakena catchment; south eastern Ethiopia to assess land use/cover change (LULCC) and topographic elevation effect on selected soil quality/fertility parameters. 144 soil samples collected from 0 - 30 cm depth under three land cover types across three elevation gradients were analysed for selected soil quality/fertility parameters. Data were statistically analyzed using analysis of variance (ANOVA) and mean comparisons were made using Least Significant Difference (LSD). The soil properties examined generally showed significant variations with respect to land-use/land cover changes and elevation. Soil particles, soil organic carbon, total N, pH, available phosphorus, potassium and calcium content significantly decreased as forestland is converted into cropland/grassland. Heaviest soil deterioration was recorded in soils under cropland and followed by grassland soils. The conversion of natural forest to different land uses without proper soil conservation and management practices resulted in the overall decline of soil fertility quality. Thus, integrated land resource management approach is indispensable for sustaining agricultural productivity and the environmental health of the Melka Waken a catchment.
Soil is a vital natural resource that has several functions in the biosphere and has several values to the society and environment. For instance, it regulates solute flow, filters, buffers, immobilizes, and detoxifies organic and inorganic materials, including industrial and municipal by-products and atmospheric deposition; stores and cycles nutrients and other elements within the earth’s biosphere; and provides support of socioeconomic structures and protection for archaeological treasures associated with human habitation [
Nevertheless, such proper function of soil and its fertility status bay large is adversely affected by human induced soil degradation resulted from land use changes, mainly conversion of natural forest to agricultural and grazing lands are known to result in changes in soil chemical, physical and biological properties [
Soil degradation is defined as a process that causes deterioration of soil productivity and low soil utility as a result of natural or anthropogenic factors [
Soil is subject to a series of human-induced degradation processes, which namely are displacement of soil material, and internal soil deterioration [
Biophysical factors, including geomorphologic features, rainfall variation and climate changes, and soil properties, also contribute significantly to land degradation [
Biophysical and human induced land degradation has become a serious environmental and socio-economic problem in this study catchment. This land degradation was reflected through observed soil erosion and soil nutrient loss, flooding, sedimentation of dams and river, and other associated issues such as water pollution and declining water storage capacity of the dam in the catchment of Melka-Wakena dam. Understanding the effects of land use/land cover change and topographic variation on soil quality/fertility helps to design sustainable land resource management practice in this study area. Therefore, the aim of this study was: 1) assess the effects of land use/land cover change and topography on soil fertility/quality; 2) assess local farmers’ perception on soil degradation.
The study catchment is located between 6˚40'00'' and 7˚25'00'' north latitude and 38˚38'00'' - 39˚45'00'' east longitudes, in West Arsi zone, Oromia regional state, Ethiopia (
The mean annual temperature of the study catchment is found between 2˚C - 15˚C in the higher altitude areas and 16˚C - 24˚C in the lower plateau areas. The study catchment is classified into two agro-climatic regions: The warm temperate/baddadaree/and cool temperate/badda/covering 24% and 76% of the total the area, respectively. The mean annual rainfall of the study area ranges from 1200 mm to 2940 mm. Geological survey shows that the relief of the study catchment is characterized by plain, hilly, valley and gorges, highest peaks and dissected plateaus. The mean elevation of the watershed is 2911 m with maximum of 4322 m (Kaka mountains peaks) and minimum elevation is 2143 m above sea level which is found near the Melka-Wakena dam sub-station. The catchment is naturally endowed with many rivers and streams as well as with one artificial lake.
The study area is characterized by a wide range of soil types. The dominant soils in the study catchment are Vertisols, Chernozems, Cambisols, Luvisols, Nitosols. The nature and distribution of the vegetation of these districts range from wooded grassland to Afro-Alpine. Alpine, Afro and sub Afro-Alpine vegetation are found in the area above 3100 m sea level of the area. Abundant low bush taught grasses and lichens are common species on the top of the mountain where temperature is very low. Below the Afro-Alpine and sub Afro-Alpine broad leafed forests which are dominated by Juniperus, Podocarpus, Hagena abyssinica tree species as well as shrub and bush which highly dominated by Asta/Erica species are found parts of Adaba and Dodola districts. The diverse climate and topographic phenomenon have provided a wide range of natural
environments, which form favorable habitat for a wide variety of fauna in study catchment. The local inhabitants rely on the forest to supply most of their needs, mainly fuel wood, pasture, timber, wild fruits and medicinal herbs [
Agriculture is the main livelihood base and economy of the study catchment. Like other parts of the Ethiopian highlands, the major farming system is mixed cereal-livestock. The cool and the sub-tropical climatic condition of the study catchment make the districts suitable for the production of major cereals crops such as Teff, Wheat, Barley and Maize. Rearing animals serve for a variety of purposes including food, draught power, transport, manure and skin. Modern livestock extension package of dairy and beef farms development was not well introduced and well adapted in the area, particularly in the rural areas. There is a gradual declining of pastureland and consequently declining the quantity and quality of livestock due to the expansion of farmland at the expense of grazing land.
The ever-increasing price of agricultural inputs (chemical fertilizer, improved seeds, insecticides and herbicides), expansion of weeds; soil erosion due to improper farming practices, and waterlogging were major agricultural problems that attributed to low agricultural production and productivity in study catchment. Besides, lack of long term credit, road inaccessibility to urban centers for selling their produces and scarcity of grazing land were other factors affecting agricultural development and the livelihoods of the local community in general [
The study was designed to evaluate soil fertility status under different land use cover types and soil variability across landscape in study catchment. Purposive stratified sampling was used to cluster sampling sites into strata of three elevation categories, three land use cover types and five transect walks to come up with random proportional sampling points.
For this effective, soil sampling sites were selected by stratifying the entire study catchment into three elevation categories based on dominant LULC types, dominant crops grown and differences in altitude and as well as using mosaic topographic map of the study catchment. With these considerations, the catchment was classified into three elevation categories from which three major land use/land cover types were identified. The elevation categories that were purposively identified include plain (2143 - 2462 masl), middle (2463 - 2948 masl) and upper (2949 - 4215 masl). Besides, the major land use/land cover types identified based on their area coverage and dominance were cropland (CL), grassland (GL) and forest land (FL). The study catchment covers about 4100 km2. Purposely, this large area of the catchment was further divided into five transects to make easy soil sample collection or reduce sampling errors.
Field soil samplings were undertaken from land use types and elevation categories along the identified transects in January to February 2016. To assess the effects of LULC change and topography on soil quality/fertility and to evaluate the overall soil fertility status of the study catchment a total of 144 disturbed soil samples were collected in the catchment, Accordingly, for each LC type and in each elevation range, 20 replications from CL and 14 replications each from WL and 3 GL (8 × 3 × 3 + 5 × 3 × 3 + 3 × 3 × 3 = 144) were taken randomly from the surface soil 0 - 30 cm depth, respectively. The sample was taken from 10 m × 10 m plot located within the same physiographic landforms. The samples at each elevation range and under different land use/land cover categories were then bulked/homogenized into a single composite sample representing the sample plot at each of the three elevation categories and land cover classes.
The soil was then air dried, grounded and passed through a 2 mm sieve for soil laboratory analysis. Soil samples were analyzed for their physical and biochemical properties. In this paper, average values of the replicates of analysis of soil parameters are reported. As conditions of native soil can serve as reference criteria for assessing soil quality/fertility changes [
Collected soil samples were analyzed for their physio-chemical properties at various soil analytical service laboratories (Sinana research center, Wondo Genet College of forestry and Ziway soil laboratory center).The composite soil samples were air-dried and ground to pass through a 2 mm sieve. Particle size distribution was determined by the Bouyoucous hydrometer method [
Soil degradation index (DI) was computed on assumptions that the status of soil properties under the CL, GL were once similar to less disturbed natural FL. Accordingly, differences between mean values of soil properties under CL, GL and FL were compared with mean values of soil properties under native WL and expressed as a percentage of the mean value of individual properties. In considering the values of important soil parameters for plant growth, SOC, N, P, K) were selected for soil degradation assessment. Laboratory results were subjected to descriptive statistics using deterioration index. The mean value of FL soil property minus the mean value of CL soil property was divided by the mean value of forest soil property, multiplied by 100. Deterioration index with negative (−) values indicates an appreciation in soil property while positive (+) value shows depreciation in soil property under CL.
Equation (1) computed percentage changes in the soil properties of cultivated land or grassland compared to forestland (ChCI,GI).
C h G l , G l = L u C l , o r G l − L u F l × 100
LuFl
where ChCI,GI is the percentage changes in soil property of cultivated or grasslands compared to forestland and LuCI, LuGI and LuFI are mean values of soil property under consideration of cultivated, grass and forestland respectively.
As environmental degradation impacts the daily life of farmers, an understanding of their perceptions on the matter is important for sustainable land management. Three hundred twenty-four (324) households selected using systematic sampling techniques were surveyed, and qualitative and quantitative data were collected from key informant interviews and structured and semi-structured questionnaires. The information collected was enriched by observations during field visits.
Statistical analysis Statistical analyses were performed to test the influence of land use and landscape position on soil nutrients using one-way ANOVA, and mean comparisons were made using the least significant difference (LSD) method with p < 0.05. The independent variables used in this study were land use types, landscape positions and slope aspects. A Pearson correlation coefficient matrix analysis was also employed to determine the nature of the relationship between the soil variables, LUC types and elevation. Multiple comparisons were also computed between groups and within the groups using Turkey’s HSD post hoc method. All data were analyzed using excel window and the Statistical Package for Social Science (SPSS—A statistical software program, version 20, 2017).
The soil in the catchment is characterized by a texture of clay ranging from 33% to 45% and silt varying from 28% to 36% (
On other hand, silt fraction increased with an increase in elevation, 27, 28 and 41 (lower, middle and upper) respectively. The reason probably that the surface downward elevation increment of clay size fraction is associated with selective
Soil parameters | Land use/cover change | Elevation categories | ||||
---|---|---|---|---|---|---|
crop | grass | forest | lower | middle | upper | |
Clay (%) | 44.75 (1.64)a | 41.85 (2.68)b | 33.46 (3.82)ab | 49.97 (0.62)a | 38.94 (1.97)b | 25.33 (2.20)c |
Silt (%) | 28.26 (1.56)b | 35.96 (0.71)a | 29.85 (1.61)a | 27.07 (0.79)b | 28.12 (0.84)b | 41.10 (1.03)a |
Sand (%) | 26.98 (1.82)bc | 30.56 (1.73)b | 28.26.14 (2.53)b | 24.82 (0.71)b | 30.25 (2.11)a | 32.00 (2.47)a |
OC (%) | 3.72 (0.04)b | 4.09 (0.06)bc | 7.82 (0.03)a | 3.38 (0.02)a | 4.72 (0.05)a | 7.25 (1.33)b |
TN (%) | 0.29 (1.09)b | 0.37 (1.18)a | 0.31 (2.24)a | 0.27 (1.20)a | 0.32 (0.74)a | 0.44 (2.16) a |
Av.P (%) | 8.58 (1.00)b | 5.56 (0.49)b | 7.08 (1.20)a | 11.94 (1.00)a | 6.59 (0.86)a | 8.49 (1.34)a |
*Mean values within rows of each soil property followed by the same letter(s) are not significantly different at p < 0.05 and values within brackets represent mean of standard error.
removal of the finer and lighter materials from the higher to lower elevation categories as the topography generally slopes/declines in that direction. This is because clay requires a relatively lower velocity in the water to be transported than the silt and sand particles [
On the other hand, the distribution of soil texture was not significantly affected by LULC types (
As indicated in
Generally, the increasing trends of sand and silt proportion towards the higher elevation may affect the amount of water and nutrient availability to plant growth, and at the same time water logging and aeration problem due to high clay fraction deposition at low-lying areas may reduce soil quality and subsequently affect soil productivity [
Organic matter in the soil exerts considerable influences on physical-chemical constituents and biological processes; and enhance on soil structure, water holding capacity, cation exchange capacity, and ability to form complexes with ions and as a nutrient source and store in soil pool [
Similarly, there was statistically significant difference (p < 0.01) in SOC content between different elevation ranges. In this regard, it was found that SOC showed an increasing trend with elevation in all identified land use/land cover type (
However, the interaction between land use types and elevation variation does not show any significant difference between them. This statistical insignificant variation of OC among them might be due to their interaction with multiple variables.
With reference to the forestland value of the SOC, cropland and grassland showed a degradation of 48% and 41% respectively. As SOC influences many of the soils physical and chemical properties, its decline by 48% after conversion of forestland to cropland can serve as a good indicator of soil quality/fertility degradation in the study catchment. Such a decline in SOC/SOM may result negative effects on crop productivity; emission of CO2 that may contribute to climate change. Therefore, improving its level is a prerequisite to ensuring soil quality; and future agricultural productivity and sustainability [
It is therefore essential to improve and sustain SOC content to ensure sustainable management of land and future agricultural productivity and sustainability.
Next to N, phosphorus is essential for plant growth and grain development. The mean differences between soil-available P of forestland and grazing lands, on the one hand, and cultivated and grazing lands, on the other hand, are statistically significant (p < 0.05) (
The finding of this study was in line with the observation made by [
Nitrogen is the most important nutrient element for crop growth, which normally produces the greatest yield response in crop plants [
Despite insignificant variation among land use types, there was the highest total N content in forestland. This was in line with other study reported the highest mean value of total N in soils of forestland and lowest in cultivated land in west-eastern [
Total nitrogen was significantly differed with elevation (p < 0.05) (
Regarding its relationship with other variables, soil total N had strong correlation with SOC (r = 0.391, p < 0.001); elevation (r = 0.391, p < 0.001); land use/land cover types (r = 0.287, p < 0.01) and Mg (r = 0.269, p < 0.001) (
All studied exchangeable bases/cations showed significant differences among LUC types and elevation gradients of the study catchment (
On the other hand, although there was no statistically significant mean difference between land use types, the highest mean value in forestland [
Soil parameters | Land use/cover change | Elevation categories | ||||
---|---|---|---|---|---|---|
crop | grass | forest | lower | middle | upper | |
pH (H2O) | 5.82 (0.13)b | 6.08 (0.09)b | 6.54 (0.31)a | 6.38 (0.09)a | 6.05 (0.12)a | 5.98 (0.29)a |
Ca (Cmol+/kg2 soil) | 16.98 (2.05)b | 16.41 (0.89)b | 28.71 (2.54)a | 16.22 (0.88)b | 19.68 (1.62)a | 22.77 (1.84)b |
Mg (Cmol+/kg2 soil) | 6.41 (0.72)a | 7.95 (0.57)a | 8.00 (0.32)a | 6.88 (0.49)a | 6.93 (0.17)a | 13.22 (0.35)b |
K (Cmol+/kg2 soil) | 0.15 (0.12)b | 0.15 (0.14)b | 0.19 (0.30)a | 0.17 (0.08)a | 0.16 (0.11)b | 0.16 (0.32)a |
*Mean values within rows of each soil property followed by the same letter(s) are not significantly different at p < 0.05 and values within brackets represent mean of standard error. *values in the brackets represent plus or minus (±).
pattern due to overgrazing has been reported in other parts of Ethiopia [
Exchangeable Mg mean values showed significant differences across elevations (p < 0.01) and LULC (p < 0.01) due to the interactive effect of LULC and elevation (p < 0.01) (
Compared to the soils of forestland, the overall pattern of exchangeable Ca, and Mg concentrations in cropland showed declining trends, but with varying rates (
Exchangeable K was highly influenced by the interaction effects of both LULC types and elevation (p < 001) (
Soil pH has been considered in soil health/quality tests to assess impacts of land use change and agricultural practices [
Parameters | Land use types | Elevation | Land use types X elevation | |||
---|---|---|---|---|---|---|
F | P | F | P | F | P | |
Clay (%) | 0.633 | 0.532 | 11.258 | 0*** | 0.380 | 0.768 |
Silt (%) | 0.910 | 0.405 | 7.686 | 0** | 0.265 | 0.851 |
Sand | 0.065 | 0.938 | 2.777 | 0* | 0.231 | 0.874 |
PH(H2O) | 1.928 | 0.149 | 6.444 | 0** | 0.418 | 0.740 |
Ca (Cmol+/kg2) | 2.486 | 0.087 | 4.172 | 0* | 1.056 | 0.370 |
Mg (Cmol+/kg2) | 5.566 | 0** | 4.890 | 0** | 4.691 | 0** |
K (Cmol+/kg2) | 1.096 | 0.337 | 0.062 | .940 | 4.260 | 0** |
P (mg/kg) | 0.201 | 0.818 | 2.928 | 0* | 0.558 | 0.643 |
OC (%) | 4.179 | 0* | 11.749 | 0*** | 0.233 | 0.874 |
TN (%) | 0.911 | 0.405 | 7.235 | 0.0** | 2.884 | 0.0* |
cropland and grassland and the highest value in the adjacent forestland. However, this does not show a significant variation of soil pH distribution understudied land use types. A similar result was reported in the Tsegede area in the northern highlands of Ethiopia [
Moreover, the acidifying effects of acid-forming nitrogen fertilizer, poor nutrient cycling, and the mining of basic cations through harvested crops, soil erosion, and acid rain may be attributed to lower pH values in cropland [
It is also suggested that the low soil pH values in higher altitudes (
With regard to relationship with other variables or parameters the values of soil pH were significantly and positively correlated with calcium(r = 599, p < 0.01) and potassium (r = 401, p < 0.01) (
Although lowest soil pH value is observed (5.1) in some area under cropland, in general the average soil pH status of the study catchment falls within the range of moderately acidic (5.82) to slightly acidic (6.54) [
Accordingly, differences between mean values of soil properties under CL, GL and FL were compared with mean values of soil properties under native WL and expressed as a percentage of the mean value of individual properties. For this purpose the most important soil parameters for plant growth (SOC, N, P, K) were selected for soil degradation assessment. Soil deterioration indices reflect differences in soil quality of different land use patterns, while changes in soil quality reflect management practices. The calculated deterioration indices of selected soil quality parameters at the surface layer (0 - 30 cm) showed a negative trend in all LC types from their values under WL cover. Soil parameters under CL showed the most negative cumulative effect (−389.87 percent) followed by GL (−387.29 percent) which indicate deterioration in soil quality from deforestation (
Sustainable land management practice depends on perceptions of land users such as farmers. Their perception and responses to environmental issues are reflected in their land use and management practices. In addition to the soil laboratory and soil data analysis of soil fertility, local community perception of their farm plot fertility was also evaluated. The majority of the respondents from lower, middle and upper streams perceived that the fertility of their farm plot was low (
LU | ELV | OC | OM | Av.P | pH | Sand | Clay | Silt | TN | Ca | Mg | K | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
LU | 1.0 | ||||||||||||
ELV | 0.1 | 1.0 | |||||||||||
OC | 0.1 | 0.4 | 1.0 | ||||||||||
OM | 0.1 | 0.4 | 1.0 | 1.0 | |||||||||
Av.P | −0.1 | 0.2* | 0.0 | 0.0 | 1.0 | ||||||||
pH | 0.2 | 0.2** | −0.1 | −0.1 | 0.1 | 1.0 | |||||||
Sand | 0.1 | 0.2** | 0.1 | 0.1 | −0.1 | 0.0 | 1.0 | ||||||
Clay | −0.1 | 0.4** | 0.3** | 0.3** | −0.2* | 0.1 | −0.8 | 1.0 | |||||
Silt | 0.1 | 0.3** | 0.3** | 0.3** | −0.2 | 0.0 | 0.1* | 0.5 | 1.0 | ||||
TN | −0.1 | 0.3** | 0.4 | 0.4 | 0.0 | 0.0 | 0.0 | −0.2 | 0.2 | 1.0 | |||
Ca | −0.1 | 0.1* | 0.3** | 0.3** | 0.3 | 0.6** | 0.2 | 0.3** | −0.1 | 0.1 | 1.0 | ||
Mg | 0.1 | 0.1 | 0.2** | 0.2** | −0.1 | 0.1 | −0.1 | 0.0 | 0.1 | 0.3 | 0.1 | 1.0 | |
K | −0.1 | −0.1 | 0.2 | 0.2 | 0.1 | .1** | 0.0 | 0.0 | 0.0 | 0.1 | 0.4** | 0.1 | 1.0 |
Soil Parameters | Land Use Types | |
---|---|---|
Significant Contrast of Value of Soil Property | P | |
Clay | Crop and Forest | 0.000** |
Forest and Grass | 0.007** | |
Silt | Crop and Forest | 0.004** |
Forest and Grass | 0,027* | |
Sand | Crop and Forest | 0.042* |
pH | Crop and Forest | 0.000*** |
Crop and Grass | 0.003** | |
Ca | Crop and Forest | 0.000*** |
Forest and GRASS | 0.000*** | |
Mg | ||
K | Crop and Wood | 0.002** |
Grass and Forest | 0.000*** | |
Av. P | ||
OC | Crop and Forest | 0.000*** |
TN | Crop and Forest | 0.017* |
Crop and Wood | 0.001** |
***Contrast is significant at the 0.001 level, **Contrast is significant at the 0.01 level and, *Contrast is significant at the 0.05.
Land use type | Selected Soil nutrients | Total | |||
---|---|---|---|---|---|
OC | TN | AV.P | K | ||
Wood land | 0 | 0 | 0 | 0 | |
Crop land | −96.28 | −99.71 | −91.42 | −99.88 | −389.87 |
Grass land | −95.91 | −99.63 | −94.40 | −99.88 | −387.29 |
Source: extracted from.
was the second most cited cause of poor soil fertility (70%), which was mainly attributed to fast growing human population in the area.
On the other hand, farmers in the mid-land identified that the inadequate application of fertilizer and waterlogging were the major causes of poor soil fertility problems in the area. In general speaking, according to the sample household heads, the major causes for this poor farm plot fertility were soil erosion, inadequate application of fertilizer, absence of fallowing system, and waterlogging (
The study reported that about 97%, 100% and 98% of sample household heads from lower, middle and upper streams perceived the prevailing of soil erosion in their locality (
Farmers associated the removal of upper layers of soil with soil erosion and declining soil fertility quality. Local perception of soil degradation concurred with the results of soil laboratory analysis. Respondents interviewed indicated that soil erosion and associated soil fertility decline resulted in lowered agricultural production, and thus more land was placed under cultivation to ensure agricultural viability, leading to more land degradation. The researchers’ observations of gullies in upper and middle elevation sections of the Melka Wakena confirmed the farmer responses. Efforts to combat soil erosion and improve soil fertility management practices to minimize effects of soil degradation need to be supported by adequate technical and material support to ensure sustainable land management practices that would improve local livelihoods and environmental health.
Perception of soil fertility | Respondents perception in percent at different sites | X2 | p | |||
---|---|---|---|---|---|---|
Lower altitude | Middle altitude | Upper altitude | ||||
Evaluation of farm plot fertility | Low | 77 | 64 | 73 | 5.281 | 0.260 |
Medium | 23 | 34 | 27 | |||
High | 0 | 0 | 0 | |||
Perceived causes of poor soil fertility | ||||||
Soil erosion | Yes | 58 | 66 | 71 | 23.999 | 0.000 |
No | 42 | 33 | 29 | |||
Inadequate application of fertilizer | Yes | 69 | 79 | 20 | 4.498 | 0.105 |
No | 31 | 21 | 80 | |||
Absence of fallowing | Yes | 61 | 54 | 70 | 4.888 | 0.087 |
No | 39 | 45 | 30 | |||
Water logging | Yes | 99 | 95 | 96 | 3.060 | 0.216 |
No | 1 | 5 | 4 |
Perception of soil erosion | Response | Percent of respondents | ||||
---|---|---|---|---|---|---|
Low land | Mid-altitude | High land | X2 | p | ||
Awareness of soil erosion as problem (N = 117) | Yes | 97 | 100 | 98 | 12.567 | 0.050 |
No | 3 | 0 | 2 | |||
If yes: how serious is the problem? (N = 114) | Low | 26 | 2 | 3 | 94.964 | 0.000 |
Medium | 6 | 23 | 6 | |||
High | 68 | 71 | 91 | |||
Observed change in the intensity of soil erosion over the last 20 years | Increase | 58 | 90 | 74 | 40.626 | 0.000 |
No change | 5 | 0 | 9 | |||
Decrease | 37 | 10 | 27 | |||
Do you believe erosion can be controlled? | Yes | 100 | 98 | 95 | 3.809 | 0.149 |
No | 0 | 2 | 5 | |||
Status of soil erosion protection structures | Totally removed | 29 | 12 | 3 | 29.908 | 0.000 |
Partially removed | 69 | 84 | 92 | |||
Well maintained | 2 | 4 | 5 |
Most studied soil quality/fertility parameters showed changes associated with LC type and across elevations within different circumstances of change. LC change from natural ecosystems (WL) to CL and GL influenced the distribution and content of soil particles, pH, calcium, potassium, total nitrogen and phosphorus across the catchment. Calculated deterioration indices of soil quality parameters (SOC, total N, P, K) at the surface layer (0 - 30 cm) showed negative in LC types from their values under WL cover. Soil parameter under CL showed the most negative cumulative effect (−388.82 percent) followed by GL (−387.29 percent), indicating deterioration in soil quality due to deforestation. The conversion of natural forest (native WL) to different land uses without proper soil conservation and management practices resulted in the overall decline of soil quality. Soil analysis confirmed declining trends of soil fertility quality, which farmers confirmed, was attributed to soil erosion, overcultivation, low fertilizer input and monoculture cropping system practiced by many farmers. Soil quality degradation is of concern for local communities, as it prevents food production increase and sustainable use of land resources. Therefore, practicing appropriate land resource management in order to promote sustainable agricultural development and environmental health in the study catchment is important. Further research on soil (quality) and integrated land resources in order to introduce land use planning for sustainable land resource management practices in the Melka Wakena catchment are required.
The authors acknowledge Madewalabu University ministry of water, irrigation and energy for funding this research and the farmers and local officials in the study catchment.
The authors declare no conflicts of interest regarding the publication of this paper.
Hayicho, H., Alemu, M. and Kedir, H. (2019) Assessing the Effects of Land-Use and Land Cover Change and Topography on Soil Fertility in Melka Wakena Catchment of Sub-Upper Wabe-Shebelle Watershed, South Eastern Ethiopia. Journal of Environmental Protection, 10, 672-693. https://doi.org/10.4236/jep.2019.105040