Publications by authors named "Haimanote Bayabil"

Phosphorus (P) is an essential element for life on earth and a limiting nutrient for plant growth. However, its availability in saline-alkaline soils is significantly reduced, adversely affecting plant productivity. Saline-alkaline soil is a widespread problem that severely affects plant growth and productivity.

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While hydroponics is considered an efficient vegetable production system, there is a compelling need to investigate the efficiency of the current generic nutrient dosing recommendation primarily based on electrical conductivity (EC) measurements. Such information is critical to fine-tune and optimize the current hydroponic management practices for improved nutrient uptake efficiency. This study investigated the dynamics of some micro and macronutrients (N, P, Ca, Mg, K, Fe, and Mn) in a recirculating nutrient film technique (NFT) hydroponic system under lettuce cultivation.

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Developing management strategies to safeguard public health and environmental sustainability requires a comprehensive understanding of the solubility and mobility of trace and alkaline metals in the event of seawater flooding. This study investigated the effects of seawater flooding, along the duration of flooding, on the release of trace and alkaline metals (Mn, Fe, Cu, Zn, Ca, K, and Mg) in two calcareous soils (Krome and Biscayne) located in southern Florida. Seawater flooding experiments involved two soil types and four flooding durations (1, 7, 14, and 28 days) replicated three times.

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Article Synopsis
  • The research examines how big data from citizen science can address data scarcity for watershed simulations.
  • The study focuses on two watersheds in Ethiopia, using the SWAT model to evaluate how different resolutions of Digital Elevation Model (DEM) and soil data impact streamflow and sediment yield simulations.
  • Results indicate that finer resolutions improve simulations in smaller watersheds but show no significant effect in larger ones, suggesting that scale matters in the effectiveness of spatial data for watershed management.
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The availability of accurate reference evapotranspiration (ETo) data is crucial for developing decision support systems for optimal water resource management. This study aimed to evaluate the accuracy of three empirical models (Hargreaves-Samani (HS), Priestly-Taylor (PT), and Turc (TU)) and three machine learning models (Multiple linear regression (LR), Random Forest (RF), and Artificial Neural Network (NN)) in estimating daily ETo compared to the Penman-Monteith FAO-56 (PM) model. Long-term data from 42 weather stations in Florida were used.

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Erosion of soil refers to the process of detaching and transporting topsoil from the land surface by natural forces such as water, wind, and other factors. As a result of this process, soil fertility is lost, water bodies' depth is reduced, water turbidity rises, and flood hazard problems, etc. Using a numerical model of erosion rates and erosion risks in the Jejebe watershed of the Baro Akobo basin in western Ethiopia, this study mapped erosion risks to prioritize conservation measures.

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Soil erosion is the predominant agent affecting ecosystem services in the Ethiopian highlands. However, land management interventions aimed at controlling erosion in the region are hampered, mainly by a lack of watershed-based appropriate management practices and anticipated climate changes. This study examined the effectiveness of different land use changes and management scenarios in decreasing runoff and sediment loss under current and future climates in the drought-prone humid watershed of the Ethiopian highlands.

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In terms of land use and climate, the world is changing at an unprecedented rate and these changes have a significant influence on our water resources. This study was conducted to examine the individual and combined potential impacts of land use and climate change on the water balance of the Baro basin in Ethiopia for the baseline period (1985-2002) and near-future period (2023-2040) using the Soil and Water Assessment Tool (SWAT). The plausible land use scenarios considering current (CUR), business as usual (BAU), and further expansion of altitudinal forest and watershed management practices (CON), as well as climate change scenarios from regional climate model outputs (RCMs) under two representative concentration pathways (RCP4.

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Soil erosion significantly affects agricultural production. Soil and Water Conservation (SWC) measures have been constructed to reduce soil loss. However, the impact of SWC measures on physicochemical soil properties has rarely been investigated in most parts of Ethiopia.

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Salinity affects over 33% of irrigated farmland globally. Developing a low-cost, safe, and effective material as a soil salinity mitigation option would be of significant importance. This study proposed to synthesize a hydrogel using liquefied biomass from sugarcane bagasse, polyvinyl alcohol, and sodium tetraborate decahydrate.

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Pulping and paper industries using non-woody feedstocks face the challenge of its notorious waste disposal problem. To resolve this problem, in this study, we evaluated a variety of properties of solid residues reclaimed from the effluents of both wheat straw ammonium sulfate and Kraft pulping processes as organic fertilizers. The results show that both residues from the ammonium sulfate (RAS) and Kraft pulping (RKP) processes possess desirable C/N ratios, appropriate nutritional compositions, and low levels of harmful heavy metals.

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Biochar, a low-cost porous carbonaceous adsorbent, has low adsorption capacity for anion contaminants. The objective of this study was to improve biochar's ability to adsorb phosphorus (P) through polyethyleneimine (PEI) modification to form an amine-functionalized biochar. Biochars prepared by pyrolysis of bamboo biomass, before and after PEI modification, were characterized using the Fourier transformed infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM), elemental analysis, and batch sorption experiments.

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The Weather Research and Forecasting (WRF) model is one of the regional climate models for dynamically downscaling climate variables at finer spatial and temporal scales. The objective of this study was to evaluate the performance of WRF model for simulating temperature and rainfall over Lake Tana basin in Ethiopia. The WRF model was configured for six experimental setups using three land surface models (LSMs): Noah, RUC and TD; and two land use datasets: USGS and updated New Land Use (NLU).

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Small-scale vegetable and fruit crop producers in the USA use locally available commercial organic fertilizers and soil amendments recycled from municipal and agricultural wastes. Organic soil amendments provide crops with their nutrient needs and maintain soil health by modifying its physical, chemical, and biological properties. However, organic soil amendments might add unwanted elements such as toxic heavy metals or salts, which might inhibit crop growth and reduce yield.

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Soil moisture and organic matter level affects soil respiration and microbial activities, which in turn impact greenhouse gas (GHG) emissions. This study was conducted to evaluate the effect of irrigation levels (75% [deficit], 100% [full], and 125% [excess] of reference crop evapotranspiration requirements), and organic amendments (OA) type (chicken manure [CM] and bone meal [BM]) and OA application rates (0,168, 336 and 672 kg total N ha) on (i) soil physical properties (bulk density, organic matter content and soil moisture content) and (ii) soil carbon dioxide (CO) emissions from a highly weathered tropical Hawai'ian soil. Carbon dioxide readings were consistently taken once or twice a week for the duration of the cropping season.

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Studies show that the performance of soil water content monitoring (SWCM) sensors is affected by soil physical and chemical properties. However, the effect of organic matter on SWCM sensor responses remains less understood. Therefore, the objectives of this study are to (i) assess the effect of organic matter on the accuracy and precision of SWCM sensors using a commercially available soil water content monitoring sensor; and (ii) account for the organic matter effect on the sensor's accuracy.

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