Yield, water productivity and nutrient balances under different water management technologies of irrigated wheat in Ethiopia

Development of irrigation technologies and agricultural water management systems holds significant potential to improve productivity and reduce vulnerability to climate change. Our study dealt with the behavior of irrigation water productivity, partial nutrient balance and grain yield of wheat under the application of different irrigation water management technologies in the Koga irrigation scheme in Ethiopia. For our analysis, we considered three nutrient fluxes entering and leaving farmers’ fields. Our experimental design had three irrigation blocks with three different irrigation water management practices (wetting front detector, Chameleon soil moisture sensor and farmers’ practice as control) on three farm plots replicated in each block. To calculate irrigation water productivity and grain yield of wheat, the amount of irrigation water applied and the agronomic attributes of wheat yield were recorded during the irrigation period. Further, three input and output variables were considered to determine the partial nutrient balances of nitrogen (N), phosphorus (P) and potassium (K). The results showed that the amount of irrigation water used was 33% and 22% less with a wetting front detector and Chameleon sensors, respectively, compared to the farmers’ practice. The wetting front detector (WFD) and Chameleon sensor (CHS) treatments gave a 20% and 15.8% grain yield increment, respectively, compared to the farmers’ practice plot. The partial nutrient balances of N and K were negative for the wetting front detector and chameleon sensor practices while it was positive for P in the control (farmers’ practice) treatment. We conclude that irrigation water management with appropriate technologies can improve yield, water productivity and the nutrient utilization. However, further research needs to be conducted on the suitability of irrigation management technologies to achieve full nutrient balance

Predicting optical water quality indicators from remote sensing using machine learning algorithms in tropical highlands of Ethiopia

Water quality degradation of freshwater bodies is a concern worldwide, particularly in Africa, where data are scarce and standard water quality monitoring is expensive. This study explored the use of remote sensing imagery and machine learning (ML) algorithms as an alternative to standard field measuring for monitoring water quality in large and remote areas constrained by logistics and finance. Six machine learning (ML) algorithms integrated with Landsat 8 imagery were evaluated for their accuracy in predicting three optically active water quality indicators observed monthly in the period from August 2016 to April 2022: turbidity (TUR), total dissolved solids (TDS) and Chlorophyll a (Chl-a). The six ML algorithms studied were the artificial neural network (ANN), support vector machine regression (SVM), random forest regression (RF), XGBoost regression (XGB), AdaBoost regression (AB), and gradient boosting regression (GB) algorithms. XGB performed best at predicting Chl-a, with an R2 of 0.78, Nash–Sutcliffe efficiency (NSE) of 0.78, mean absolute relative error (MARE) of 0.082 and root mean squared error (RMSE) of 9.79 µg/L. RF performed best at predicting TDS (with an R2 of 0.79, NSE of 0.80, MARE of 0.082, and RMSE of 12.30 mg/L) and TUR (with an R2 of 0.80, NSE of 0.81, and MARE of 0.072 and RMSE of 7.82 NTU). The main challenges were data size, sampling frequency, and sampling resolution. To overcome the data limitation, we used a K-fold cross validation technique that could obtain the most out of the limited data to build a robust model. Furthermore, we also employed stratified sampling techniques to improve the ML modeling for turbidity. Thus, this study shows the possibility of monitoring water quality in large freshwater bodies with limited observed data using remote sensing integrated with ML algorithms, potentially enhancing decision making

Application of advanced Wflow_sbm Model with the CMIP6 climate projection for flood prediction in the data-scarce: Lake-Tana Basin, Ethiopia [Abstract only]

Paper presented at the European Geosciences Union (EGU) General Assembly 2023, Vienna, Austria and Online, 24-28 April 2023

Dynamics of soil quality in a conserved landscape in the highland sub humid ecosystem, Northwestern Ethiopia

Several studies have assessed the dynamics of soil quality induced by soil and water conservation (SWC), but many showed disagreement over the efficacy of SWC interventions in the Ethiopian highlands. This study used a before and after soil and water conservation practices (SWCP) comparison approach to evaluate the effect of SWCP on soil quality dynamics. Fifty-four composite and 10 undisturbed soil samples were collected in 2012 (before SWCP) and 2022 (after SWCP). Statistical mean, analysis of variance, and principal component analysis were applied to test the significant differences among treatments. The findings demonstrated that SWCP has significantly improved most of the soil quality indicators such as soil organic matter, total nitrogen, available phosphorous, pH, total porosity, field capacity, and available water, and reduced the value of bulk density and coarse fragments. The interaction effect of landscape position and types of structures provided statistically significant results for soil organic matter, total nitrogen, magnesium, calcium, and base saturation. Soil and stone-faced soil bunds treated at lower landscapes were superior in improving soil quality attributes. The soil quality indexing showed, the overall soil quality improvement as a result of SWCP was about 32.15%. The level of improvement for different SWCPs was 32% for stone faced soil bunds and 33% for soil bunds. The findings revealed that SWCP implementation can improve soil quality. Soil organic matter is a key biological quality component that contributed 25% to the soil quality index and highly impacted soil physicochemical properties. We suggest additional assessment of best and integrated land management practices to ensure further improvement in soil quality, crop productivity, and ecosystem services in the subhumid ecosystems

A critical analysis of soil (and water) conservation practices in the Ethiopian Highlands: implications for future research and modeling

Soil and water conservation have been traditionally part of farming practices for thousands of years. Despite massive efforts to implement modern soil and water conservation practices (SWCPs) in the Ethiopian Highlands, soil erosion increased after the 1970s when social and political events led to a remarkable change in land use. This review aims to critically analyze the impact of conservation practices on soil loss and crop yield and highlight research and modeling gaps. In doing so, 120 published articles on experimental and simulated soil losses in the Ethiopian Highlands were retrieved from the refereed literature. We found that most published experimental studies evaluating SWCPs lasted less than five years in areas of less than 100 ha. Most modeling studies were over short periods, too; some models simulated soil loss over large areas. The literature analysis for these short-term experimental studies showed that SWCP decreased soil loss on individual sites and increased crop yield in semi-arid regions. Simulated sediment concentration increased as a function of watershed size, while observed soil losses did not follow this trend. Moreover, the decrease in soil loss due to the soil and water conservation practices on small plots was also greatly overestimated. Consequently, past research and current modeling techniques are inconclusive on the effectiveness of SWCPs in large catchments over periods exceeding five years and those with active gullies. Additional long-term experimental studies in catchments are required to evaluate whether SWCPs can decrease sediment loads

Estimation of Suspended Sediment Concentration from Remote Sensing and In Situ Measurement over Lake Tana, Ethiopia

Discharge from basins joining a lake is the main factor determining the lake volume and sediment inflow to the lake. Suspended sediment is an important parameter for describing the water quality of aquatic ecosystems. Lake Tana is an important and the largest lake in Ethiopia for the local ecological system. However, environmental change and anthropogenic activities in the area threaten its water quality. The conventional methods of suspended sediment concentration (SSC) observation are unable to determine and compare spatial and temporal SSC patterns for the lake over a period of years. Remote sensing methods have made it possible to map SSC. The objective of this study is to characterize the spatial and temporal distribution of suspended sediment of Lake Tana using in situ measurement and remote sensing applications and specifically to develop a relationship between in situ and remote sensing observation to retrieve suspended sediment concentration and map the spatal distribution of SSC. This study used MODIS-Terra and in situ data to characterize the spatial and temporal distribution of SSC in the rainy season. Four sampling campaigns (20 samples per campaign) were carried out on Lake Tana, and the first three sampled campaigns on May 11-13, 2018, June 08-10, 2018, and July 15-17, 2018, were used for calibration of regression models. MODIS-Terra reflectance in NIR was found best related to in situ water quality data and varies linearly with SSC (r(2) = 0.81) and turbidity (r(2) = 0.85). Secchi disc depth (SDD) found the best fit for a power relation with NIR band reflectance (r(2) = 0.74). The MODIS-Terra reflectance in red was found to be poorly related to in situ measurements. The relation in NIR reflectance was validated using the LOOCV (leave-one-out-cross-validation) technique and the fourth sampled data set collected on August 12-14, 2018. Developed models are validated with RMSE of 42.96 mg/l, 14.6 NTU, and 0.17 m, ARE of 23.3%, 27.6%, and 12.4%, and RRMSE of 25.1%, 44.5%, and 29.6% for SSC, turbidity, and SDD, respectively, using LOOCV. The equation was also validated using August 2018 collected data sets with RMSE of 87.6 mg/l, 11.7 NTU, 0.08 m, ARE of 20.8%, 25.9%, and 28.8%, and RRMSE of 17.8%, 20.5%, and 27.9% for SSC, turbidity, and SDD, respectively. Applying the developed regression model, a 10-year time series of SSC from 2008-2017 for May-August was estimated and the trend was tested using the Mann-Kendall trend test. It was found that an increasing trend was observed from the period 2008 to 2017. The result shows that satellite data like the MODIS-Terra imagery could be used to monitor and obtain past records of SSC with the developed equation. The increasing SSC can be reduced by implementing selected management practices in the surrounding watersheds of the lake to reduce nutrient and sediment inflow

Intricacies of an effective global "rooted" collaboration in soil and water research

Contains fulltext : 220249.pdf (publisher's version ) (Closed access)13 mei 202

Topography Impacts Hydrology in the Sub-Humid Ethiopian Highlands

Understanding the relationship between topography, hydrological processes, and runoff source areas is essential in engineering design, such as predicting floods and implementing effective watershed management practices. This relationship is not well defined in the highlands with a monsoon climate and needs further study. The objective of this study is to relate topographic position and hydrological response in tropical highlands. The research was conducted in the Debre Mawi watershed in the northwest sub-humid Ethiopian highlands. In the monsoon rain phase of 2017 and 2018, groundwater depth, infiltration rate, and surface runoff were monitored at the upslope, midslope, and downslope positions. Surface runoff rates were measured in farmer fields through distributed V-notch weirs as estimates of positional runoff. Average water table depths were 30 cm deep in the downslope regions and 95 cm in the upslope position. The water table depth affected the steady-state infiltration rate in the rain phase. It was high upslope (350 mm h−1), low midslope (49 mm h−1), and zero downslope. In 2017, the average runoff coefficients were 0.29 for the upslope and midslope and 0.73 downslope. Thus, topographic position affects all aspects of the watershed hydrology in the humid highlands and is critical in determining runoff response

Ecological status as the basis for the holistic environmental flow assessment of a tropical highland river in Ethiopia

There is an increasing need globally to establish relationships among flow, ecology, and livelihoods to make informed decisions about environmental flows. This paper aimed to establish the ecological foundation for a holistic environmental flow assessment method in the Gumara River that flows into Lake Tana in Ethiopia and the Blue Nile River. First, the ecological conditions (fish, macro-invertebrate, riparian vegetation, and physicochemical) of the river system were characterized, followed by determining the hydrological condition and finally linking the ecological and hydrological components. The ecological data were collected at 30 sites along the Gumara River on March 2016 and 2020. River hydrology was estimated using the SWAT model and showed that the low flow decreased over time. Both physico-chemical and macroinvertebrate scores showed that water quality was moderate in most locations. The highest fish diversity index was in the lower reach at Wanzaye. Macroinvertebrate diversity was observed to decrease downstream. Both the fish and macroinvertebrate diversity indices were less than the expected maximum, being 3.29 and 4.5, respectively. The normalized difference vegetation index (NDVI) for 30 m and 60 m buffer distances from the river decreased during the dry season (March–May). Hence, flow conditions, water quality, and land-use change substantially influenced the abundance and diversity of fish, vegetation, and macroinvertebrate species. The pressure on the ecology is expected to increase because the construction of the proposed dam is expected to alter the flow regime. Thus, as demand for human water consumption grows, measures are needed, including quantification of environmental flow requirements and regulating river water uses to conserve the ecological status of the Gumara River and Lake Tana sub-basin