Seawater flooding of calcareous soils: Implications for trace and alkaline metals mobility

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. Freshwater flooding experiments were also conducted for comparison. After each flooding experiment, soil samples were collected at three depths (15, 30, and 45 cm), and analyzed for selected elements. Comparative analysis revealed significant releases of Mn, Fe, and Zn in both soils flooded by seawater compared to freshwater. In most cases, significant increments were evident as early as 1-day exposure to seawater flooding, which further increased with flooding duration. However, the impacts of seawater flooding had notable differences between the two soils. Seawater flooding in Krome soil for 28 days, resulted in higher Mn, Fe, and Zn contents by 58, 340, and 510% compared with freshwater flooding, while corresponding increases in Biscayne soil were 3.3, 130, and 180%, respectively. Comparable marginal increases in Cu content were observed for both soils. Similarly, seawater flooding increased K, Mg, and Na contents from single-day flooding. The interplay between soil type, column depth, flooding duration, and their interactions proved influential factors in determining Mn, Fe, Cu, and Zn releases, with peak levels typically observed on the 28th day of flooding and at bottom depths. Overall, these findings highlight the release of these elements, raising concerns about potential plant toxicity and groundwater or surface water contamination due to leaching and runoff.

Integrating machine learning and empirical evapotranspiration modeling with DSSAT: Implications for agricultural water management

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. Moreover, the effect of ETo model selection on sweet corn irrigation water use was investigated by integrating simulated ETo data from empirical and ML models using the Decision Support System for Agrotechnology Transfer (DSSAT) model at two locations (Citra and Homestead) in Florida. Furthermore, a linear bias correction calibration technique was employed to improve the performance of empirical models. Results were consistent in that the NN and RF models outperformed the empirical models. The empirical models tended to underestimate and overestimate small and high daily ETo values, respectively, with the HS model exhibiting the least accuracy. However, calibrated PT and TU models performed comparably to the ML models. Results also revealed that using an inappropriate ETo model could lead to over-irrigation by up to 54 mm during a single crop season. Overall, ML models have proven reliable alternatives to the PM model, especially in regions with access to long-term data due to their site-independent performance. In areas without long-term data for ML model training and testing, calibrating empirical models is viable, but site-specific calibration is needed. It is important to highlight that distinct plant species exhibit varying transpiration characteristics and, consequently, have different water requirements. These differences play a pivotal role in shaping the overall impact of ETo models on crop water use.

Evaluating the effects of DEM and soil data resolution on streamflow and sediment yield simulations in the Upper Blue Nile basin

While the availability of "big data" on biophysical parameters through citizen science and/or from public/private sources is expected to help in addressing data scarcity issues, there is little understanding of whether and/or how such data will improve watershed simulations. This research aimed to evaluate whether improvements in resolutions of Digital Elevation Model (DEM) and soil data will enhance streamflow and sediment yield simulations and thereby improve soil and water management decisions. The study was conducted in two different-sized watersheds (Anjeni and Gilgel Abay with ~ 1 km2 and ~ 1655 km2 area, respectively) in the Upper Blue Nile basin in Ethiopia. Effects of DEM and soil data resolutions on streamflow and sediment yield were evaluated using the Soil and Water Assessment Tool (SWAT). The results showed that the effect of DEM and soil data resolution on streamflow and sediment yield simulation was scale dependent finer resolution DEM and soil datasets improved streamflow and sediment yield simulations in the smaller Anjeni watershed, whereas DEM resolution had no effect in the bigger Gilgel Abay watershed. Small watersheds are often used to understand watershed processes, and thus the use of finer-resolution spatial data for watershed simulations could result in better results. Findings from the smaller Anjeni watershed suggested that the combined use of finer resolution DEM and soil data could potentially improve sediment yield simulations although the lack of observed sediment yield data did not allow verification of this at the larger Gilgel Abay watershed.

Impacts of soil and water conservation measures on soil physicochemical properties in the Jibgedel Watershed, Ethiopia

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. Therefore, this study was designed to evaluate the effects of SWC measures on selected soil physicochemical properties in the Jibgedel watershed, West Gojjam zone, Ethiopia. The study also assessed the farmers' perception of the benefits and impacts of SWC measures. Composite and core soil samples were taken at a depth of 0 to 20 cm from four farmlands with SWC measures (soil bund, stone bund, and soil bund with sesbania tree) and without SWC measures in three replications. Results have shown that employing SWC measures in the farmland significantly improved most of the physicochemical properties of the soil compared to farmland without SWC measures. Bulk density from soil bund with and without sesbania trees was significantly lower than stone bund and untreated farmland. Soil organic carbon, total nitrogen, electrical conductivity, and available phosphorus from soil bund with sesbania tree were significantly higher than other treatments. The result also revealed that most farmers perceived that the implemented SWC measures improved soil fertility and crop yield. SWC measures are easier to adopt for integrated watershed management when farmers are well-versed in them.

Using liquefied biomass hydrogel to mitigate salinity in salt-affected soils

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. The effectiveness of the produced hydrogel in mitigating soil salinity was evaluated based on an incubation experiment at two salinity levels (5 and 10 dS m^-1). The experiment was conducted by mixing liquefied hydrogel with soil at four application rates (0, 1, 2, and 3% w/w) with three replications. Porewater and soil samples were tested for pH and electrical conductivity (EC). Soil samples were also analyzed for selected cations and anions. The results demonstrated that hydrogel significantly reduced porewater EC at both 5 and 10 dS m^-1 salt solutions. In addition, hydrogel reduced Cl^-, P, Ca²⁺, and Al³⁺ concentrations in soil samples with maximum reductions observed from 3% hydrogel treatment. However, pH of porewater showed a consistent increase with hydrogel application. The application of hydrogel also increased NH₄-N at high salt level. Overall, hydrogel has shown promising results in reducing soil salinity and could potentially be used as a soil amendment for saline soils.

Characterization of residues from non-woody pulping process and its function as fertilizer

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. The high solubilities (>35 g/L) of both residues allow their use for fertigation or foliar applications. The salt index (30-50) is within the range of commercial chemical fertilizers such as potassium sulfate (42.6) and magnum sulfate (44). The E3/E5 ratios of residues suggest that the residues have small molecular sizes, which are similar to fulvic acids. Overall, wheat straw pulping residues demonstrate the potential as the sustainable organic fertilizers and the beneficial soil amendments. This work has the potential to resolve the severer effluent disposal problem faced by the non-woody pulping and papermaking industries, open a door to effectively utilize residues as value-added byproducts, and lead to both environmental sustainability and economic benefits.

Polyethyleneimine-modified biochar for enhanced phosphate adsorption

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. The effects of pH, coexisting anions, and ionic strength on P adsorption by PEI-modified biochar were also investigated. Results indicated that PEI was successfully grafted onto biochar which resulted an increase in surface amine group and in P adsorption. The peak of P adsorption occurred at pH of three and adsorption of P was decreased with increasing of ionic strength and when coexisting ions, such as HCO₃^-, SO₄^2-, NO₃^-, and Cl^-, were coexisted. The electrostatic interaction between P and surface functional groups of PEI-modified biochar served as the primary mechanism controlling the adsorption process. These results indicate that chemically functionalized biochar with amine groups can enhance P adsorption.

Impacts of land surface model and land use data on WRF model simulations of rainfall and temperature over Lake Tana Basin, Ethiopia

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). The performances of WRF configurations were assessed by comparing simulated and observed data from March to August 2015. The result showed that temperature and rainfall simulations were sensitive to LSM and land use data choice. The combination of NLU with RUC and TD produced very small cold bias (0.27 °C) and warm bias (0.20 °C) for 2m maximum temperature (Tmax) and 2m minimum temperature (Tmin), respectively. WRF model with RUC and NLU captured well the observed spatial and temporal variability of Tmax, while TD and NLU for Tmin. Moreover, rainfall simulation was better with NLU; especially NLU and Noah configuration produced the smallest mean bias (2.39 mm/day) and root mean square error (6.6 mm/day). All the WRF experiments overestimated light and heavy rainfall events. Overall, findings showed that the application of updated land use data substantially improved the WRF model performance in simulating temperature and rainfall. The study would provide valuable support for identifying suitable LSM and land use data that can accurately predict the climate variables in the Blue Nile basin.

Evaluation of phytotoxicity of three organic amendments to collard greens using the seed germination bioassay

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. Therefore, the objective of this study was to evaluate phytotoxicity of three commercial organic amendments, chicken manure, milorganite, and dairy manure, to collard greens using the seed germination bioassay and chemical analysis of the organic amendments. The seed germination bioassay was conducted by incubating collard greens seeds to germinate in 1:10 (w/v) organic amendment aqueous extracts. Results of this work identified phytotoxic effects of chicken manure and milorganite, but not dairy manure, to collard greens. Potentially phytotoxic chemicals such as copper, zinc, nickel, and salts were also higher in chicken manure and milorganite compared to dairy manure. In particular, nickel in chicken manure and milorganite aqueous extracts was 28-fold and 21-fold, respectively, higher than previously reported toxic levels to wheat seedlings. The results demonstrate the need for more research on phytotoxicity of commercial organic soil amendments to ensure their safe use in vegetable and fruit crop production systems.