The study's aim was to assess the impact of using water from Lake Abaya for irrigation and its impact on soil quality at Mirab Abaya, Ethiopia. Six water samples from the edge of Lake Abaya and 30 (18 irrigated and 12 rain-fed) composite soil samples from farm lands in Wajifo, Fura and Algae were collected. Analyses showed that the use of water from Lake Abaya will bring a soil salinity hazard in future. The soil analyses showed variations in space and time in the physico-chemical components in the study area. The highest salinity was reported from Algae, the closest site to the Lake. The highest soil alkalinity was reported from Wajifo, which has a long irrigation history. The irrigated soils reported higher salinity than the rain-fed soils, indicating that water from Lake Abaya can affect irrigated soil quality. In general, Lake Abaya water is not suitable for salt-sensitive crops and caution is required in using it for irrigation.

  • Irrigation water quality is equally important as drinking water quality for sustainable and efficient irrigation project implementation.

  • If the irrigation water quality deteriorates it has its own impact on soil quality.

  • Due to that, irrigation water quality assessments will be mandatory for the implementation of efficient irrigation projects.

In Ethiopia, agriculture accounted for 42% of GDP in 2014 and about 85% of export earnings in 2010. It employs 83% of the active population (MoA 2011). Smallholders dominate the sector and the landholdings are increasingly fragmented. In 2015, there were 15.6 million agricultural households with an average farm size of 0.95 ha (CSA 2015). Ethiopian agriculture is primarily rain-fed and, as rainfall is highly erratic, there is a high risk of intra-seasonal dry spells and annual droughts. The government, therefore, promotes irrigation at the large, medium and small scale in its strategic plans.

The water management of small-scale irrigation schemes is the responsibility of the farmers themselves, mainly through informal/traditional community groups. Apart from the provision of extension and training services to the water user associations by the Ministry of Agriculture (MoA), no institution is directly involved in water management in small holder-irrigated agriculture. The absence of any appropriate local-level organs catering for small-scale irrigation has led to a lack of formal support to guide irrigation operation and maintenance at the community level. With irrigated areas and user numbers increasing, irrigation water management and water allocation rules are becoming more complex and problematic. The problems of smallholder irrigation farmers include loss of farmland, wastage of water and random water use without checking its suitability for irrigation. Good-quality crops can be produced by applying high-quality irrigation water if other inputs are optimal (Kitila et al. 2014). Likewise, irrigation with water of marginal quality could lead to the buildup of new soil characteristics that affect its fertility and lead to lower productivity (Belic et al. 2013). These impacts are commonly described in terms of salinity, sodicity, infiltration rate and toxicity (Ayers & Westcot 1985).

Salt accumulates in the soil when water evaporates from the soil surface, affecting crop growth adversely (Al-Rashdi & Sulaiman 2015). Salinity problems are found in and around irrigation projects. For example in the Awash Rift Valley, in central-eastern Ethiopia, some 4,114 ha (40%) of productive agricultural land was abandoned due to salinity between five and eight years after irrigation began (Taddese & Abegaz 2003).

The recent extensive use of Lake Abaya water for irrigation in the southern Rift Valley in Mirab Abaya district, Ethiopia, worries many stakeholders. Since about 2010, the western part of the Lake has been widely used for vegetable and fruit irrigation where the wetlands and bush have been cleared, using water pumped from Lake Abaya to supplement low rainfall (Abebe & Shewa 2017; Agidew & Amanuel 2018). Currently, farmers have no information about Lake Abaya water quality, and the local agricultural office only supplies pumps, not help with water quality analysis, irrigation operations or further soil impacts of the particular irrigation water. The short- and long-term effects of lake water use on soil quality are not good under such farming practices. Therefore, this study aimed to evaluate the impacts of using Lake Abaya water for irrigation on soil quality and sustainability. The specific goals were to (1) evaluate current soil salinity/sodicity and investigate changes after harvesting; (2) study lake water quality and soil water characteristics in the context of salt and nutrient loading to soils; (3) compare the soil quality changes in rain-fed and irrigated land; and (4) determine the suitability of Lake Abaya water for irrigation.

Locations and site description

The study was carried out in Mirab Abaya District, Southern Rift Valley, Southern Ethiopia, about 455 km from Addis Ababa. The district is bordered by Lake Abaya and has an elevation range between 1,170 and 2,700 m.a.s.l. The district covers about 1,405 km2, of which 17,437 ha are used for farming. Currently around 7,000 ha of the land are suitable for irrigation. Figure 1 shows the study area and sampling sites.

Figure 1

Study area and soil sampling sites.

Figure 1

Study area and soil sampling sites.

Close modal

Since about 2012, 10 of the 23 ‘Kebeles’ (smallest administrative structure) in the district have started using lake water for irrigation. The irrigated area has increased gradually by clearing the bushes around the lake buffer zone. It has been observed that some farmers have been forced, at the same time, to change crop type and abandon some of their land because of the soil quality deterioration.

Climate and agro-ecology

Mirab Abaya is characterized by moderately hot and dry climatic conditions with low and variable precipitation (Agidew & Amanuel 2018). The study area covers 62% of the district. Rainfall is bimodal, the highest occurring in April–May and September–October (rainy season). The rainy season is followed by the dry season from December to February, and it is sometimes dry in July and August (Abebe & Zeit 2015). The study area is characterized as arid and semi-arid, with mean annual rainfall of 863.7 mm. The minimum and maximum average air temperatures are 17.4 and 30.5 °C.

Farming

Both rain-fed and irrigation agriculture are practised. The irrigated crops include banana, pepper (capsicum), tomato, onion, potato and cabbage.

Sample collection

Water samples were collected at the point where irrigation water is withdrawn. Collection was done in 2 L plastic bottles from 20 cm below the water surface. The samples were stored in an icebox and transferred to Arba Minch University water quality laboratory for analysis. A total of six samples was collected from three sample stations during the study.

Soil samples were collected with an auger, pre- and post-harvest from Wajifo, Fura and Algae sites (all irrigated from Lake Abaya). Thirty composite soil samples were collected for analysis – see Table 1. At Wajifo and Fura both irrigated and rain-fed samples were taken, but only irrigated soil samples were collected at Algae. Each soil sample was collected from a depth of 0 to 20 cm. The sampling locations were determined using a Garmin GPS 60.

Table 1

Soil sample locations, etc

SiteLatitude, mLongitude, mAltitude, m.a.s.l.Number of samples
Irrigated
Rain-fed
Pre-harvestPost-harvestPre-harvestPost-harvest
Wajifo 716,634.4 364,144.2 1,181 
Fura 681,899.6 354,660.1 1,185 
Algae 695,067.6 367,526.9 1,183 
SiteLatitude, mLongitude, mAltitude, m.a.s.l.Number of samples
Irrigated
Rain-fed
Pre-harvestPost-harvestPre-harvestPost-harvest
Wajifo 716,634.4 364,144.2 1,181 
Fura 681,899.6 354,660.1 1,185 
Algae 695,067.6 367,526.9 1,183 

Water quality analysis

The water quality parameters were determined on the day of sampling. In case of delay, samples were stored at 4 °C. All analyses were conducted according to APHA (1999) unless otherwise stated.

Water temperature, electrical conductivity (EC), total dissolved solids (TDS) and pH were measured using a portable HQ40d meter (HACH) on-site and in the laboratory, consulting the manufacturer's manual. In the laboratory, the samples were filtered through 0.45 μm pore membranes to remove suspended solids before SO4−2, PO4−3, NO3, Na+ and K+ determination. Nitrate and phosphate were determined by UV-spectrophotometry at 420 and 690 nm respectively, and Na+ and K+ were determined by flame photometry (Olubanjo & Alade 2018). Total hardness, Ca2+ and Mg2+ were determined using standard ethylenediaminetetraacetic acid (EDTA) titration (Dinka 2016). Sample chloride content was determined by standard silver nitrate titration, while CO3−2 and HCO3 were determined by titration with 0.02 N H2SO4 and an appropriate indicator. Sulfate was determined by turbidity meter.

Soil quality analyses

Soil samples were air-dried, crushed and sieved (2 mm) for physico-chemical analyses. The soil quality parameters determined and methods employed are given in Table 2.

Table 2

Soil quality determinations

ParameterMethod(s)
pH Potentiometric (1:2.5 H2O, v/v) 
EC Conductometry (1:2.5 H2O, v/v) 
Soil texture Hydrometer 
Organic carbon (OC) Walkley Black 
Total nitrogen (TN) Kjeldahl 
Av. phosphorus (AvP) Olsen 
Cation exchange capacity (CEC) Ammonium acetate (1M NH4AC) 
Soluble sodium (Na+Flame photometry 
Soluble potassium (K+Volumetric and instrumental 
Soluble calcium (Ca2+EDTA (0.05 N) titrimetric 
Soluble magnesium (Mg2+
Carbonate (CO3−2Volumetric and instrumental 
Bicarbonate (HCO3Titration with 0.01 N H2SO4 
Chloride (ClTitration using 0.05 N AgNO3 
Sulfate (SO4−2Volumetric and instrumental 
ParameterMethod(s)
pH Potentiometric (1:2.5 H2O, v/v) 
EC Conductometry (1:2.5 H2O, v/v) 
Soil texture Hydrometer 
Organic carbon (OC) Walkley Black 
Total nitrogen (TN) Kjeldahl 
Av. phosphorus (AvP) Olsen 
Cation exchange capacity (CEC) Ammonium acetate (1M NH4AC) 
Soluble sodium (Na+Flame photometry 
Soluble potassium (K+Volumetric and instrumental 
Soluble calcium (Ca2+EDTA (0.05 N) titrimetric 
Soluble magnesium (Mg2+
Carbonate (CO3−2Volumetric and instrumental 
Bicarbonate (HCO3Titration with 0.01 N H2SO4 
Chloride (ClTitration using 0.05 N AgNO3 
Sulfate (SO4−2Volumetric and instrumental 

Irrigation water suitability evaluation

The suitability of Lake Abaya water for irrigation was evaluated on the basis of pH, EC, and major cation and anion concentrations, as well as salinity indices (RSC, SAR, SSP, KR, PI, PS, and MAR) – Table 3 shows the relevant equations used in this study. Piper and Wilcox diagrams were also used to evaluate the lake water.

Table 3

Salinity index equations

Index and EquationDefinitionReference
 Sodium adsorption ratio Ayers & Westcot (1985)  
 Exchangeable sodium percentage Shainberg & Letey (1984)  
 Soluble sodium percentage Hwang et al. (2017)  
 Magnesium adsorption ratio 
 Kelly ratio 
 Residual sodium carbonate 
 Residual sodium bicarbonate 
 Permeability index 
 Potential salinity 
Index and EquationDefinitionReference
 Sodium adsorption ratio Ayers & Westcot (1985)  
 Exchangeable sodium percentage Shainberg & Letey (1984)  
 Soluble sodium percentage Hwang et al. (2017)  
 Magnesium adsorption ratio 
 Kelly ratio 
 Residual sodium carbonate 
 Residual sodium bicarbonate 
 Permeability index 
 Potential salinity 

Key informant interviews

Key informant interviews about the irrigated farms and the advice offered to farmers were held at the local government agricultural offices when the study started. Interviews were also held with farm owners and workers during data collection. Field visits were conducted during the soil and water sampling to find out about salinity, type of crop, abandoned farms, etc.

Data analysis

The soil physico-chemical data obtained were analyzed statistically using SPSS version 21 (Getintopc 2013). Mean comparisons of soil properties were done before and after harvest using ANOVA at 95% confidence interval. The physico-chemical data for the water were subjected to descriptive statistics using MS Excel 2016, and the Piper and Wilcox diagrams using Aqua Chem 2014.2 (Getintopc 2013).

Lake Abaya water quality

The minima, maxima and means of the physico-chemical parameters of the Lake Abaya water and the recommended values of FAO for irrigation purpose are shown in Table 4.

Table 4

Lake Abaya water quality at Mirab Abaya

ParameterUnitsMinimumMaximumMean±SDFAO Value
EC dS/m 1.13 1.73 1.4±0.1 0–3 
TDS mg/L 578.00 911.00 703.8±57.8 0–2000 
pH  7.90 9.30 8.5±0.2 6–8.4 
Total hardness mg-CaCO3/L 66.00 180.00 126.0±18.1 – 
Calcium (Ca2+meq/L 1.56 2.20 1.8±0.1 0–20 
Magnesium (Mg2+meq/L 0.44 2.80 1.8±0.4 0–5 
Sodium (Na+meq/L 13.27 44.28 22.4±4.8 0–40 
Potassium (K+meq/L 0.48 0.89 0.6±0.1 0–0.1 
Sulfate (SO43−meq/L 0.81 5.16 2.4±0.7 0–20 
Carbonate (CO32−meq/L 0.33 1.67 1.2±0.2 0–1 
Bicarbonate (HCO3meq/L 6.36 10.50 7.9±0.6 0–10 
Chloride (Clmeq/L 3.16 7.19 5.2±0.7 0–30 
Phosphate (PO43−-P) meq/L <LoD <LoD <LoD 0–0.02 
Nitrate (NO3meq/L <LoD 0.01 <LoD 0–0.16 
Total alkalinity mg-CaCO3/L 474.00 716.00 551.3±34.5 – 
ParameterUnitsMinimumMaximumMean±SDFAO Value
EC dS/m 1.13 1.73 1.4±0.1 0–3 
TDS mg/L 578.00 911.00 703.8±57.8 0–2000 
pH  7.90 9.30 8.5±0.2 6–8.4 
Total hardness mg-CaCO3/L 66.00 180.00 126.0±18.1 – 
Calcium (Ca2+meq/L 1.56 2.20 1.8±0.1 0–20 
Magnesium (Mg2+meq/L 0.44 2.80 1.8±0.4 0–5 
Sodium (Na+meq/L 13.27 44.28 22.4±4.8 0–40 
Potassium (K+meq/L 0.48 0.89 0.6±0.1 0–0.1 
Sulfate (SO43−meq/L 0.81 5.16 2.4±0.7 0–20 
Carbonate (CO32−meq/L 0.33 1.67 1.2±0.2 0–1 
Bicarbonate (HCO3meq/L 6.36 10.50 7.9±0.6 0–10 
Chloride (Clmeq/L 3.16 7.19 5.2±0.7 0–30 
Phosphate (PO43−-P) meq/L <LoD <LoD <LoD 0–0.02 
Nitrate (NO3meq/L <LoD 0.01 <LoD 0–0.16 
Total alkalinity mg-CaCO3/L 474.00 716.00 551.3±34.5 – 

LoD=Limit of detection.

EC and TDS are important parameters in determining the salinity effects of irrigation water in agriculture (Laze et al. 2016). The minimum and maximum values of EC and TDS for Lake Abaya water were within the FAO's recommended range, showing that the water meets the minimum requirements for irrigation. It is classified as slightly to moderately saline water (0.7 to 3.0 dS/m), which can be used for salt-tolerant crops (Ayers & Westcot 1985).

Sodium is highly soluble and usually present in water. It is frequently associated with salinity problems when linked to chloride and sulfate ions (Ogunfowokan et al. 2013). The sodium concentration in Lake Abaya water was within the recommended limit. The vegetables grown in the study sites are classified as moderately sensitive and can tolerate 5 to 10 meq-Na/L (CCME 2008). However, the maximum concentration found exceeds the recommended limit, indicating that use of this water may pose a soil sodicity hazard at times. The water's potassium content exceeds the limits suggested by Ayers & Westcot (1985), perhaps due to the potassium-based fertilizer residues in the agricultural runoff. This may also have caused the rise in potassium content in the lake (Kitila et al. 2014).

Figure 2 is a Piper diagram of Lake Abaya water.

Figure 2

Piper diagram of Lake Abaya waters.

Figure 2

Piper diagram of Lake Abaya waters.

Close modal

Figure 2 shows that 5 of the 6 samples were dominated by bicarbonate, in terms of anions; with no dominant anionic type in the sixth. All samples were dominated by sodium and potassium in terms of cations. The upper part of the figure shows that all samples are of sodium bicarbonate type, i.e., the water is alkaline. Lake Abaya water is therefore slightly unsuitable for irrigation and long-term use of it may cause soil salinity.

Salinity indices of Lake Abaya water for irrigation

The suitability of Lake Abaya water for irrigation was determined using various indices – Table 5.

Table 5

Lake Abaya water salinity indices for irrigation

Irrigation WQIMean±StdAyers & Westcot (1985) Suitability for irrigation
SAR 16.8±3.3 0–26 Fair 
SSP (%) 85.0±2.1 0–60 Poor 
MAR (%) 47.6±7.0 0–50 Suitable 
KR 6.3±1.2 0–1 Unsuitable 
RSC (meq/L) 5.4±0.5 0–2.5 Unsuitable 
PI (%) 96.7±1.2 25–75 Class I (Good) 
PS 6.4±0.8 0–10 Good 
Irrigation WQIMean±StdAyers & Westcot (1985) Suitability for irrigation
SAR 16.8±3.3 0–26 Fair 
SSP (%) 85.0±2.1 0–60 Poor 
MAR (%) 47.6±7.0 0–50 Suitable 
KR 6.3±1.2 0–1 Unsuitable 
RSC (meq/L) 5.4±0.5 0–2.5 Unsuitable 
PI (%) 96.7±1.2 25–75 Class I (Good) 
PS 6.4±0.8 0–10 Good 

NOTE: SAR=sodium absorption ratio, SSP=soluble sodium percentage, KR=kelly ratio, RSC=residual sodium carbonate, PI=permeability index, PS=potential salinity.

SAR is an estimate of the degree to which sodium is absorbed by the soil concerned (Bauder et al. 2008). High SAR values suggest a sodium hazard, by the replacement of soil Ca and Mg with Na by cation exchange (Laze et al. 2016). This is undesirable because it can damage the soil structure, affect its fertility and lower crop yields (Marchuk 2013).

Lake Abaya water is classified with high salinity and sodium hazard (C3-S4) according to the Wilcox Diagram (Figure 3). The water is sodic-saline and may affect soil properties. Its SSP value also exceeds the FAO recommended level for irrigation. SSP exceeding 60% can cause sodium accumulation in soil (Kadyampakeni et al. 2018).

Figure 3

Wilcox diagram for Lake Abaya.

Figure 3

Wilcox diagram for Lake Abaya.

Close modal

Lake Abaya water's mean KR value was 6.3±1.2, implying that it is not suitable for irrigation because of excess sodium content. This is in line with an earlier study by Talabi et al. (2017). RSC is also used to estimate the carbonate content's potential hazardous effect in irrigation (Kadyampakeni et al. 2018), and Lake Abaya water is unsafe as its RSC exceeds 2.5 meq/L. The high concentration of bicarbonate indicates a tendency for Ca2+ and Mg2+ to precipitate in the soil (Laze et al. 2016; Husien et al. 2017).

In general, Lake Abaya water has moderate alkalinity and salinity hazards, so effective drainage is required to make its use sustainable in irrigation. The crops grown currently in the Mirab Abaya area are salt-sensitive. Therefore, consideration should be given to growing salt-tolerant crops, to use Lake Abaya water for irrigation.

Soil quality

Soil texture

The soil texture classes in the study area are shown in Figure 4.

Figure 4

Soil textures on the farm in the study.

Figure 4

Soil textures on the farm in the study.

Close modal

The soil textural classes pre- and post-harvest at Wajifo, Fura and Algae were silty clay, silty clay loam and clay loam, respectively. The soil at Fura has the highest silt content of the three. High silt content can increase the probability of major cation and anion accumulation in the soil from lake water.

Soil quality irrigated with Lake Abaya water

The soil quality at Wajifo, Fura and Algae is reported in Table 6.

Table 6

Soil quality at the farming areas studied

ParameterWajifo
Fura
Algae
Irrigated
Rain-fed
Irrigated
Rain-fed
Irrigated
Pre-harvestPost-harvestSig.Pre-harvestPost-HarvestSig.Pre-harvestPost-harvestSig.Pre-harvestPost-harvestSig.Pre-harvestPost-harvestSig.
pH.H2O (1:2.5) 8.04±0.10 8.46±0.12 0.06 8.02±0.03 8.03±0.06 0.96 7.973±0.03 7.97±0.22 0.98 8.24±0.15 8.25±0.09 0.96 8.22±0.24 8.26±0.14 0.88 
EC (dS/m) (1:2.5) 0.33±0.06 0.30±0.00 0.64 0.13±0.03 0.10±0.00 0.37 0.30±0.06 0.20±0.00 0.16 0.47±0.14 0.23±0.03 0.19 0.37±0.09 0.73±0.24 0.23 
OC (%) 1.50±0.09 0.96±0.14 0.03 1.13±0.10 1.19±0.03 0.59 0.75±0.08 0.55±0.09 0.18 0.98±0.25 0.54±0.01 0.15 1.55±0.34 1.72±0.04 0.64 
TN (%) 0.16±0.00 0.12±0.02 0.17 0.12±0.00 0.16±0.03 0.10±0.01 0.07±0.01 0.24 0.12±0.04 0.07±0.00 0.26 0.21±0.05 0.23±0.01 0.64 
AvP (mg-P2O5/kg) 68.17±2.94 55.92±4.73 0.09 49.77±3.35 51.92±4.56 0.72 53.77±7.84 64.87±10.8 0.45 47.82±4.76 54.91±11.89 0.61 59.25±7.27 78.07±8.68 0.17 
CEC (meq/100gm) 71.65±1.12 55.15±2.27 0.01 60.77±0.97 59.48±2.79 0.68 59.36±3.18 58.91±0.17 0.89 61.27±3.73 54.07±0.24 0.13 60.93±2.58 56.73±0.29 0.18 
ParameterWajifo
Fura
Algae
Irrigated
Rain-fed
Irrigated
Rain-fed
Irrigated
Pre-harvestPost-harvestSig.Pre-harvestPost-HarvestSig.Pre-harvestPost-harvestSig.Pre-harvestPost-harvestSig.Pre-harvestPost-harvestSig.
pH.H2O (1:2.5) 8.04±0.10 8.46±0.12 0.06 8.02±0.03 8.03±0.06 0.96 7.973±0.03 7.97±0.22 0.98 8.24±0.15 8.25±0.09 0.96 8.22±0.24 8.26±0.14 0.88 
EC (dS/m) (1:2.5) 0.33±0.06 0.30±0.00 0.64 0.13±0.03 0.10±0.00 0.37 0.30±0.06 0.20±0.00 0.16 0.47±0.14 0.23±0.03 0.19 0.37±0.09 0.73±0.24 0.23 
OC (%) 1.50±0.09 0.96±0.14 0.03 1.13±0.10 1.19±0.03 0.59 0.75±0.08 0.55±0.09 0.18 0.98±0.25 0.54±0.01 0.15 1.55±0.34 1.72±0.04 0.64 
TN (%) 0.16±0.00 0.12±0.02 0.17 0.12±0.00 0.16±0.03 0.10±0.01 0.07±0.01 0.24 0.12±0.04 0.07±0.00 0.26 0.21±0.05 0.23±0.01 0.64 
AvP (mg-P2O5/kg) 68.17±2.94 55.92±4.73 0.09 49.77±3.35 51.92±4.56 0.72 53.77±7.84 64.87±10.8 0.45 47.82±4.76 54.91±11.89 0.61 59.25±7.27 78.07±8.68 0.17 
CEC (meq/100gm) 71.65±1.12 55.15±2.27 0.01 60.77±0.97 59.48±2.79 0.68 59.36±3.18 58.91±0.17 0.89 61.27±3.73 54.07±0.24 0.13 60.93±2.58 56.73±0.29 0.18 

Sig.=significance difference at p=0.05.

As shown in Table 6, soil pH at Wajifo, Algae and Fura pre- and post-harvest was numerically different, but the differences were statistically insignificant at the 95% confidence interval (p=0.06, 0.88, 0.98, respectively). The soil pH was also similar for irrigated and rain-fed areas. The variation in pH of the irrigated soils is less than that of the rain-fed soils, and statistically insignificant at 95%, however, so Lake Abaya water did not affect soil pH. When the soil pH is below 8.2, the soil is saline; when it exceeds 8.2, it is alkaline (Ayers & Westcot 1985; Lord 2008), so the soil is slightly alkaline.

The soil EC at Wajifo and Fura fell between the pre- and post-harvest seasons, but the changes were insignificant at 95%. The fall in EC might be due to leaching in the rainy season during the observation period. However, the soil EC at Algae rose and the increase was statistically significant.

The changes in OC (p=0.031), ESP (p=0.047), CEC (p=0.003), and sulfate (p=0.031) were all statistically significant (at 95%) in the Wajifo irrigated soil, but were all insignificant in the rain-fed soil.

Soil – major cations and anions

The major soil cations and anions – in both irrigated and rain-fed soils – are shown in Figure 5. Na+ and Cl- report the highest cationic and anionic concentrations, respectively. The differences between them, however, are statistically insignificant, indicating that sodium chloride is the dominant soil salt type.

Figure 5

Major soil cation and anion concentrations. (a) Wajifo. (b) Fura. (c) Algae.

Figure 5

Major soil cation and anion concentrations. (a) Wajifo. (b) Fura. (c) Algae.

Close modal

As shown in Figure 5 there are statistically significant differences (95%) in the Na (p=0.00), Ca (p=0.03), Mg (p=0.00), Cl (p=0.01), and SO4 (p=0.03) in the irrigated Fura soil, but the differences were insignificant in rain-fed soil. The average soil SAR values at Algae, Wajifo, and Fura are within the FAO recommended range of 0 to 9 (Ayers & Westcot 1985). If a soil's KR is below 1.0, it can be irrigated (Hwang et al. 2017). The average KRs for the soils at Algae and Fura both exceeded 1.0, indicating soil sodium hazards. The average RSC values at all irrigation sites are below the 1.25 meq/L recommended maximum (Okubay 2019), indicating that calcium and magnesium are more abundant in the soil than carbonate and bicarbonate, and the soil bicarbonate concentrations are too low to impede crop growth (Okubay 2019).

The value differences of ESP, SSP, and MAR (Table 7) are not statistically significant between pre- and post-harvest. Soil PI and PS differences at Fura, on the other hand, were statistically significant (95%).

Table 7

Irrigated soil quality indices for Algae, Wajifo and Fura

IndicesAlgae
Wajifo
Fura
Pre-harvestPost-harvestPPre-harvestPost-harvestPPre-harvestPost-harvestP
SAR 2.0±0.5 3.4±1.2 0.34 1.9± 0.1 1.8± 0.4 0.86 2.2±0.3 2.2±0.1 0.92 
KR 1.0±0.2 1.7±0.7 0.39 1.0±0.1 0.8±0.2 0.40 1.0±0.1 1.2±0.1 0.13 
RSC (meq/L) −0.2±0.5 −0.2±0.5 0.98 −0.4±0.2 −0.4±0.2 0.98 −0.7±0.2 −0.3±0.2 0.28 
ESP (%) 1.7±0.7 3.5±1.6 0.34 1.5± 0.1 1.4± 0.5 0.85 1.9±0.5 2.0±0.2 0.91 
SSP (%) 49.6±6.7 59.7±8.3 0.39 51.8±2.0 47.1±4.6 0.40 50.6±3.2 56.7±0.6 0.13 
MAR (%) 31.7±1.1 30.7±1.3 0.57 31.8±1.6 32.3±1.1 0.80 32.4±0.5 30.2±1.7 0.29 
PI 32.9±1.3 26.5±2.3 0.07 84.0±3.7 78.4±3.6 0.34 77.0±2.6 87.5±2.6 0.05 
PS 2.0±0.2 3.0±0.4 0.10 1.8±0.2 2.1±0.4 0.50 2.7±0.3 1.7±0.2 0.05 
IndicesAlgae
Wajifo
Fura
Pre-harvestPost-harvestPPre-harvestPost-harvestPPre-harvestPost-harvestP
SAR 2.0±0.5 3.4±1.2 0.34 1.9± 0.1 1.8± 0.4 0.86 2.2±0.3 2.2±0.1 0.92 
KR 1.0±0.2 1.7±0.7 0.39 1.0±0.1 0.8±0.2 0.40 1.0±0.1 1.2±0.1 0.13 
RSC (meq/L) −0.2±0.5 −0.2±0.5 0.98 −0.4±0.2 −0.4±0.2 0.98 −0.7±0.2 −0.3±0.2 0.28 
ESP (%) 1.7±0.7 3.5±1.6 0.34 1.5± 0.1 1.4± 0.5 0.85 1.9±0.5 2.0±0.2 0.91 
SSP (%) 49.6±6.7 59.7±8.3 0.39 51.8±2.0 47.1±4.6 0.40 50.6±3.2 56.7±0.6 0.13 
MAR (%) 31.7±1.1 30.7±1.3 0.57 31.8±1.6 32.3±1.1 0.80 32.4±0.5 30.2±1.7 0.29 
PI 32.9±1.3 26.5±2.3 0.07 84.0±3.7 78.4±3.6 0.34 77.0±2.6 87.5±2.6 0.05 
PS 2.0±0.2 3.0±0.4 0.10 1.8±0.2 2.1±0.4 0.50 2.7±0.3 1.7±0.2 0.05 

The laboratory analyses of soil and irrigation water, on-site observation in April and December 2019, and key informant interviews of farm owners, all show that the major source of solutes in the farm land studied is Lake Abaya water. Although the soil type is important, soil salinization is a combination of solute transport towards the root zone to replenish evaporation and transpiration losses, and limited soil washing by rain or relatively low salt content irrigation water. Nachshon (2018) notes that key factors in soil salinization include climate, soil properties, groundwater level and irrigation water. Thus, more salinized soils are found closer to the lake (shallow groundwater) in the Mirab Abaya district, which is characteristically semi-arid and arid, where precipitation is less than evaporation – a characteristic of the Southern Great Rift Valley in eastern Africa.

A solution could be to irrigate sufficiently to leach the salts contributing to salinity, using the relationship in Equation (1). The excess water that removes salts from the root zone is the ‘leaching fraction’ (LF), defined as the fraction or proportion of the water penetrating below the root zone to lower the soil salinity below a specified level (Ayres & Westcot 1985; Nachshon 2018).
(1)
where,
  • LR (leaching requirement)=the extra water needed to leach solutes below the root zone:

  • ECI=the electrical conductivity of the irrigation water;

  • ECT=the electrical conductivity of the saturation extract of the irrigation water.

As a mechanism for reducing the salinization of smallholders' agricultural land, the relevant officers working in the sector must support farmers with proper information about leaching requirements, drainage techniques, cultivation practices, available biological solutions and water source blending to ensure sustainable irrigation and income.

The physico-chemical qualities of Lake Abaya water were shown, generally, to be moderately safe for irrigation use. The salinity indices, however, indicated that there might be salinity and alkalinity hazards. Lake Abaya water is, thus, unsuitable for salt-sensitive crops without remedial measures such as leaching and drainage facilities, for sustainable crop production.

Some statistically significant differences were observed between pre- and post-harvest season soil sample parameters. No such differences were found in the rain-fed soil parameters. This indicates that Lake Abaya water can cause secondary salinity and alkalinity in soil that is irrigated repeatedly for a long period, perhaps leading to non-productive land. Local professionals need, therefore, to support farmers in selecting water and farms for irrigation, and making such operations sustainable.

We would like to thank the Water Resources Research Center, Arba Minch University for the financial support of this project (project code GOV/AMU/Grand,2/AMIT/WRRC/06/2010). We also thank the Mirab Abaya agriculture office for their support during sample collection and in the provision of information.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

Abebe
A.
&
Shewa
A.
2017
Determinants of adoption of motorized water pump (Evidence from lake abaya and chamo basins of Gamo Gofa Zone, Southern Ethiopia)
.
MOJ Food Processing & Technology
5
,
343
347
.
Abebe
M.
&
Zeit
D.
2015
Irrigation for sustainable agricultural development in Ethiopia
.
Ethiopian Journal of Agricultural Sciences
25
(
1
),
31
44
.
Agidew
A.
&
Amanuel
S.
2018
Contribution of adoption of motorized water pump on the household farm income of smallholder farmers: evidence from Lake Abaya and Chamo basins of gamo gofa zone, southern Ethiopia
.
Journal of Development and Agricultural Economics
10(1), 22–27.
Al-Rashdi
T.
&
Sulaiman
H.
2015
Assessment of physiochemical properties of farm soils and irrigation water around a major industrial area in Oman
.
Procedia Environmental Sciences
28, 265–270.
APHA
1999
Standard Methods for the Examination of Water and Waste Water
.
American Journal of Public Health and the Nation's Health
,
Washington DC
.
Ayers
R. S.
&
Westcot
D. W.
1985
Water Quality for Agriculture
.
FAO Irrigation and Drainage Paper 29
,
Rome, Italy
.
Bauder
J.
,
Bauder
T.
,
Waskom
R.
&
Scherer
T.
2008
Assessing the Suitability of Water Quality for Irrigation – Salinity and Sodium
.
California Fertilizer Association
.
Belic
S.
,
Belic
A.
&
Vranesevic
M.
2013
Water Quality as A Limiting Factor for Irrigated Agriculture
.
IAHS-AISH Proceedings and Reports
.
CCME
2008
Canadian Water Quality Guidelines
.
Canadian Council of Ministers of the Environment
, Winnipeg, Canada.
CSA
2015
Key Findings of the 2014/2015 (2007 E.C.) Agricultural Sample Surveys
.
Central Statistical Agency
,
Addis Ababa, Ethiopia
.
Dinka
M.
2016
Quality composition and irrigation suitability of various surface water and groundwater sources at Matahara Plain
.
Water Resources
43, 677–689.
Husien
A.
,
Seboka
S.
&
Shifarra
W.
2017
Assessment of irrigation water quality of lowlands in the Bale Zone, South Eastern Oromia, Ethiopia
.
International Journal of Water Resources and Environmental Engineering
9(12), 264–269.
Hwang
J.
,
Park
S.
,
Kim
H.
,
Kim
M.
,
Jo
H.
,
Kim
J.
,
Lee
G.
,
Shin
I.
&
Kim
T.
2017
Hydrochemistry for the assessment of groundwater quality in Korea
.
Journal of Agricultural Chemistry and Environment
6
,
1
29
.
Kadyampakeni
D.
,
Appoh
R.
,
Barron
J.
&
Boakye-Acheampong
E.
2018
Analysis of water quality of selected irrigation water sources in Northern Ghana
.
Water Science and Technology
18(4), 1308–1317.
Kitila
G.
,
Gebrekidan
H.
&
Alamrew
T.
2014
Assessment of irrigation water quality and suitability for irrigation in the fincha'a valley sugar estate, Nile basin of western Ethiopia
.
Science, Technology & Arts Research Journal
3(1), 64–73.
Laze
P.
,
Rizani
S.
&
Ibraliu
A.
2016
Assessment of irrigation water quality of Dukangin basin in Kosovo
.
Journal of International Scientific Publications
4, 544–551.
Lord
K.
2008
Soil Sampling and Methods of Analysis
, Vol.
1
(
3
), 2nd edn.
Taylor & Francis Group
, Boca Raton, Florida.
Marchuk
A.
2013
Effect of Cations on Structural Stability of Salt-Affected Soils
.
University of Adelaide
, Adelaide, Australia.
MoA
2011
Small-scale Irrigation Situation Analysis and Capacity Needs Assessment
.
Ministry of Agriculture
,
Addis Ababa, Ethiopia
.
Nachshon
U.
2018
Review Cropland Soil Salinization and Associated Hydrology: Trends, Processes and Examples
.
Ogunfowokan
A.
,
Obisanya
J.
&
Ogunkoya
O.
2013
Salinity and sodium hazards of three streams of different agricultural land use systems in Ile-Ife, Nigeria
.
Applied Water Science
3, 19–28.
Okubay
G.
2019
Salinity and sodicity hazard characterization in major irrigated areas and irrigation water sources, northern Ethiopia
.
Cogent Food & Agriculture
5, 1–15.
Olubanjo
O.
&
Alade
A.
2018
Evaluation of irrigation water quality from major water sources in Ondo and Osun States, Nigeria
.
Journal of Experimental Agriculture International
24(2), 1–12.
Shainberg
I.
&
Letey
J.
1984
Response of soils to sodic and saline conditions
.
Journal of Agriculture Science
52(1), 1–57.
Taddese
G.
&
Abegaz
F.
2003
The Nature and Properties of Affected Soils in Middle Awash Valley of Ethiopia
.
International Livestock Research Institute
.
Talabi
A.
,
Afolagboye
L.
,
Aturamu
A.
&
Olofinlade
S.
2017
Suitability evaluation of river owan water for irrigation
.
IOSR Journal of Environmental Science
11(4), 74–88.
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