How shifts in societal priorities link to reform in agricultural water management: Analytical framework and evidence from Germany, India and Tanzania

Climate change, environmental awareness, and food security are just some of the new priorities societies pursue. Due to the very large influence of agriculture on water quantity and quality, often a certain degree of reform in agricultural water management is required to accommodate such new priorities. To assess the degree of reform an analytical framework is introduced to account for social (e.g. contestation, path dependency) and biophysical limitations (water balance as a zero-sum game, limited gains in biomass productivity) to reform in agricultural water management. The hypothesis tested in this paper is whether the framework is capable to link shifts in societal priorities to actual reform in agricultural water management and if the framework can assess to what extent agricultural water management has changed to accommodate shifting societal priorities. The analytical framework and variables assess ex-post the degree of a reorientation, which is understood as the interplay between shifts in societal priorities and reform in agricultural water management to accommodate such shifts. The framework offers a causal chain of 6 variables to assess a reorientation. A test is performed by probing the framework in diverse contexts of Germany, India and Tanzania. Evidence from Germany, India and Tanzania confirm the validity of the social and biophysical limitations as they acted as real boundaries for the amount of reform achieved. In Tanzania much reform was achieved and agricultural water management accommodated the new priority of agricultural expansion, whereas in Germany and India few farm-level changes were achieved making new priorities of environmental conservation unattainable. Based on the test it can be concluded that the framework offers a realistic lense to study reorientations around the world. For further research, in-depth case studies are recommended to further develop the framework and advance insight in the complex biophysical and social interrelationships of reorientations.

Drought and water availability analysis for irrigation and household water needs in the Krueng Jrue sub-watershed

This study aimed to analyze drought conditions and evaluate irrigation water availability and household water needs in the Krueng Jrue sub-watershed, Aceh Province, Indonesia. The Z-score statistics method was developed to analyze the drought, and the Mock model was used to generate discharges. We performed model validation using linear regression, which produced a coefficient of determination (R ² = 0.90^**) and coefficient of regression (r = 0.95^**). In general, this area had a normal Z-score for precipitation (ZSP) class with 90 events (75%) and a normal Z-score for a discharge (ZSD) class with 89 events (74.2%). There were 0-11 (0-9.2%) moderate wet, very wet, extreme wet, moderate drought, and severe drought events. The consistency between the ZSP and ZSD indices reached 85.8%, indicating consensus between the meteorological droughts that were analyzed based on rainfall (ZSP) and hydrological droughts analyzed based on water discharge (ZSD). ZSP and ZSD indices showed negative values during the dry season (April to September) and positive values during the rainy season (October to March). There was a surplus of water availability for irrigation and household water needs during the rainy season and a deficit during the dry season. However, water deficits also occurred in certain months during the rainy rendeng planting season, for example, in October 2009, 2013, 2016, and 2017 as well as in February between 2008 to 2011 and from 2014 to 2017. This observation was probably due to the influence of global climate variables that need to be substantiated. This study offers necessary information for farmers, the community, and the local government when anticipating drought phenomenon, organizing the rice planting season, and evaluating water availability in other watersheds.

Spatiotemporal variation of irrigation water requirements for grain crops under climate change in Northwest China

Clarifying the spatiotemporal variation of crop irrigation water requirement (IWR) under the background of climate change is an essential basis for water resource management, determining the irrigation quota and adjusting the planting structure. Using 61 years of climate data from 205 stations in Northwest China, this study investigated the spatiotemporal variations of climatic factors and IWR during the growth period of five main grain crops (spring wheat, winter wheat, spring maize, summer maize, and rice) and explored the dominant climatic driving factors of IWR variation. Results showed that (1) the IWR of grain crops showed distinct differences. Rice was the highest water consumption crop (mean of 753.78 mm), and summer maize was the lowest (mean of 452.90 mm). (2) The variation trends and average values of IWR of different grain crops have spatial heterogeneity across Northwest China. For most crops, high values and increasing trends of IWR were mainly located in eastern Xinjiang, western Gansu, and western Inner Mongolia. (3) T_max (maximum temperature), T_min (minimum temperature), and P_eff (effective precipitation) showed an increasing trend during the growth period of each grain crop, while U₁₀ (wind speed at 10 m height), SD (solar radiation), and RH (relative humidity) presented decreasing trends. (4) SD, T_max, and U₁₀ promoted the increase of grain crops' IWR, while P_eff and RH inhibited it. The impacts of climatic factors on the grain crop IWR differed among different regions. P_eff was the most influential factor to the IWR of all grain crops in most areas. Therefore, under the premise of a significant increase in T and uncertain precipitation mode in the future, it is urgent to take effective water-saving measures according to the irrigation needs of the region. To cope with the adverse impact of climate change on the sustainable development of agriculture in the northwest dry area, to ensure regional and national food security.

A web-based GIS platform supporting innovative irrigation management techniques at farm-scale for the Mediterranean island of Crete

The aim of this paper is the creation of an integrated and free-access web platform for parcel irrigation water management on a large spatial scale (Water District of Crete, in Greece) in order to: a) accurately determine the irrigation needs of the main crops for Crete such as olives, citrus, avocados and vineyards, b) design strategies, for optimal adaptation of the agricultural sector in the context of climate change, and c) incorporate the dynamic integration of the above information through the creation of a digital platform. In the proposed decision-making system, essential factors are taken into account, such as real-time meteorological data, information about the type and spatial distribution of the agricultural parcels in Crete, algorithms for calculation crop evapotranspiration per development stage and age of the crops, satellite remote sensing techniques in combination with field surveys to depict accurate soil texture map for the whole island of Crete as well as sustainable cultivation practices for saving water per crop and parcel geomorphology. Based on the proposed decision-making system, users will have the opportunity in any specific location/farm in Crete to know the irrigation needs of the crops in real-time and obtain information about proper climate-water adaptation practices. The main novelty points of the proposed platform include the derivation of parcel-level soil texture data from Sentinel-2 satellite imagery and field samples, the comprehensiveness of the irrigation management information, the relatively low data requirements and the application interface simplicity provided to the end-user.

A data-driven approach using the remotely sensed soil moisture product to identify water-demand in agricultural regions

Effective agricultural water management requires accurate and timely identification of crop water stress at the farm-scale for irrigation advisories or to allocate the optimal amount of water for irrigation. Various drought indices are being utilized to map the water-stressed locations/farms in agricultural regions. Most of these existing drought indices provide some degree of characterization of water stress but do not adequately provide spatially resolved high-resolution (farm-scale) information for decision-making about irrigation advisories or water allocation. These existing drought indices need modeling and climatology information, hence making them data-intensive and complex to compute. Therefore, a reliable, simple, and computationally easy method without modeling to characterize the water stress at high-resolution is essential for the operational mapping of water-stressed farms in agricultural regions. The proposed new approach facilitates improved and quick decision-making without compromising much of the skills imparted by the established drought indices. This study aims to formulate a water-demand index (WDI) based on a parameter-independent data-driven approach using readily available remote sensing observations and weather data. We hypothesize that the WDI for an agricultural domain can be characterized by soil moisture, vegetative growth (NDVI), and heat unit (growing degree day, GDD). To this end, we used remote sensing-based soil moisture and NDVI and modeled ambient temperature datasets to generate weekly WDI maps at 1 km. The proposed methodology is verified over a few intensively irrigated agricultural-dominated areas with different climatic conditions. Our results suggest that the proposed approach characterizes water-stressed fields through WDI maps with good spatial representativeness. Overall, this study provides a framework to generate weekly WDI maps quickly with readily available measurements. These water-demand maps will help water resource managers to reduce dependence on established drought indices and prioritize the specific regions/fields with high water demand for optimum water allocations to improve crop health and ultimately maximize water-use efficiency.

Sustainable agricultural water management incorporating inexact programming and salinization-related grey water footprint

In arid and semi-arid regions, improper irrigation activities not only exacerbate water shortages, but also lead to environmental pollution such as soil salinization that hinders crop growth and agricultural sustainability. There has been a lack of agricultural water management tools that could support agricultural water management with salinization-related grey water footprints being considered and associated uncertainties being addressed. In this study, salinization-related grey water footprints were measured through accounting for relationships among irrigation, soil salinity, evapotranspiration and crop yield, and then incorporated into an agricultural water management model for supporting environmentally sound irrigation decisions. Such an agricultural water management model was also characterized by a newly proposed generalized fuzzy interval fractional programming (GFIFP) method that could address ratio problems of two objectives and dual uncertainties. The developed methodology coupling the GFIFP method and grey water footprints was applied to an irrigation region in northwestern China where water scarcity and soil salinization hindered local development. Five credibility levels corresponding to decision makers' varied satisfactory degrees over water availability, and nine weight coefficients of possibility and necessity measures were considered. Results showed that, in order to reduce negative environmental impacts while increasing economic benefits, more irrigation water should be allocated to wheat and sunflower rather than corn. When the credibility level is 0.5 and weight coefficient is 0.9, the system efficiency would be the highest. Compared to the benchmark year of 2018, this scenario would generate [0.330, 6.647] billion yuan more benefits and [16.0, 133.9] million m³ less grey water footprints. Compared to three conventional approaches, GFIFP could provide decisions with more flexibility and less environmental impacts. The developed approach could also be applied to agricultural water management problems in other areas aiming at reducing grey water footprints and enhancing environmental benefits under uncertainty.

Irrigation water intensity and climate variability: an agricultural crops analysis of Italian regions

This paper examines the relationship between the requirement of water resources for irrigation and climate variability and analyses the ranking of the best and worst performance of irrigation water intensity for each Italian region. To measure water resources demanded by agriculture, the irrigation water intensity (IWI) indicator has been computed as the ratio between volumes of irrigation water and total crop harvested. By applying panel data methodologies to a regional dataset spanning from 2000 to 2009, we may address heterogeneity and omitted variable issues. By merging meteo-climatic with agricultural variables, we may confirm that water precipitations, maximum temperature, irrigation propensity indicator, and yields are the main and relevant determinants of the IWI indicator. Moreover, results confirm our expectations that regions belonging to South and Islands macro-areas seem the best performers in terms of irrigation water intensity. Also, our analysis reveals limited availability of information on water resource data and suggests strengthening the need for regularly collecting data and producing statistics to support in designing adequate tools for optimal policies.

Evaluation of health and environmental risks for juvenile tilapia (Oreochromis niloticus) exposed to florfenicol

Intensive fish cultivation has a high incidence of infection, which is often controlled by administering antibiotics. Florfenicol (FF) is one of the two antimicrobial drugs permitted for aquaculture in Brazil. Due to their intensive use, potentially harmful effects on aquatic organisms are of great concern. In this sense, we investigated whether the presence of FF in cultivation water could change the health parameters of Nile tilapia. For this, we evaluated hemoglobin, hematocrit, mean corpuscular hemoglobin (MCHC) concentration, mean corpuscular volume (MCV), total plasma protein (TPP), number of circulating red blood cells and leukocytes, as lipid peroxidation levels, catalase activity and glutathione S-transferase activity of fish exposed to 11.72 mg L⁻¹ of FF in water for 48 h. The fish were divided into two groups: Nile tilapia in water with FF or without FF (control). Exposure to FF in cultivation water for a short period didn't change the hematological variables analyzed, but caused changes in liver ROS (Reactive oxygen species) markers of the Nile tilapia, which was revealed by lipid peroxidation levels, catalase activity, and glutathione S-transferase. The 48h exposure period was enough to induce oxidative stress in hepatocytes, causing cellular oxidative damage. Therefore, the antibiotic florfenicol may cause toxicity to organisms and aquatic ecosystems, even at a sublethal concentrations near 1/100 LC50-48h for fish species.

Partially treated domestic wastewater as a nutrient source for tomatoes (Lycopersicum solanum) grown in a hydroponic system: effect on nutrient absorption and yield

Using effluent from the anaerobic baffled reactor (ABR) of the decentralised wastewater treatment system (DEWATS) as a sole nutrient source is not sufficient for tomato plants grown in hydroponic system. The study investigated the effects of commercial hydroponic fertilizer mix (CHFM) combined with ABR effluent on tomato growth and yield. A media-based hydroponic technique consisting of three treatments, namely, ABR effluent, CHFM, and ABR effluent combined with CHFM (ABR + CHFM (50:50 v/v) was used. The results showed that plant growth parameters, biomass, fruit yield and shoot nutrient content were significantly higher in tomato plants fed with CHFM and ABR + CHFM than those grown in ABR effluent. Addition of 50 % dose of CHFM in ABR wastewater (ABR + CHFM) increased shoot N, K, Ca and Zn. These results indicated that adding 50% CHFM can alleviate nutrient deficiencies when partially treated wastewater from anaerobic digester is used as a nutrient source for hydroponic tomato cultivation.

Nationwide temporal variability of droughts in the Kingdom of Eswatini: 1981-2018

For adequate mitigation and adaptation measures, it is essential to have detailed analysis of droughts patterns. This study determined the i) occurrence and severity of droughts ii) drought recurrence frequencies and iii) drought trends across different agro-ecological zones in the Kingdom of Eswatini for the period 1981 to 2018. A Standardised Precipitation Index (SPI) computed from long-term precipitation data measured from six meteorological stations was used to determine drought occurrence and severity. Python software (Version 3.6) was applied on the SPI values to predict the recurrence of drought events over time in years. The SPI showed that in the Highveld, 42% of the droughts were moderate, 32% were severe and the remaining 26%, which all occurred post 1980 were extreme (SPI -2.34 to -2.82). The Middleveld had an even proportion of drought categories (29-35%). The Lowveld recorded 62% of moderate, 8% severe and 30% extreme droughts of which 70% occurred post 2000. Moderate droughts were found to recur every 4-5 years while extreme droughts are expected every 13-21 years. These findings are essential for mitigation and adaptation measures geared towards the adverse effects of droughts.

Non-destructive characterization of physical and chemical clogging in cylindrical drip emitters

Characteristics and deposition pattern of clogging material on cylindrical drip emitters was studied using non-destructive methods of evaluation. Two sets of four cylindrical emitter samples were collected from farm lands. One set of sample emitters was analyzed using Computed Tomography (CT). Other set was dissected and the clogging material extracted was analyzed using Energy Dispersive X-Ray Fluorescence (EDXRF) and X-Ray Diffraction (XRD). CT scans revealed the geometric properties of emitters and the spread of clogging material on the emitter surface. EDXRF analysis found statistically significant inverse relationship between the proportion of physical clogging and chemical clogging materials. XRD analysis indicated presence of physical and chemical clogging materials in their crystalline forms. Emitters having transverse flow path and the boundary optimized with curvature found with the least deposition of physical clogging materials. Corresponding proportion of chemical clogging (as Ca) was found to be much higher. All the samples were found with more clogging material closer to the outlets. Efforts to optimize emitter geometry shall also take into account the outlet area optimization and chemical clogging for obtaining best results.

Plant growth-promoting rhizobacteria (PGPR) improve the growth and nutrient use efficiency in maize (Zea mays L.) under water deficit conditions

Drought is one of the major abiotic stresses that affects crop yield worldwide. An eco-friendly tool that can broadly improve plants' tolerance to water stress is bioionocula comprising plant growth-promoting rhizobacteria (PGPR). In this study, the effect of two PGPR Cupriavidus necator 1C2 (B1) and Pseudomonas fluorescens S3X (B2), singly and/or co-inoculated at two inocula sizes (S1 - 3 × 10³ cells g^-1 dry weight (dw) soil and S2 - 3 × 10⁶ cells g^-1 dw soil), on growth, nutrient uptake, and use efficiency was assessed in maize (Zea mays L.) plants grown at three levels of irrigation (80% of water holding capacity (WHC) - well-watered, 60% of WHC - moderate water deficit stress, and 40% of WHC - severe water deficit stress) in a greenhouse experiment. The impact of water deficit and bioinoculants on soil microbial activity (fluorescein diacetate hydrolysis) was also evaluated. Moderate and severe water deficit negatively affected soil microbial activity, as well as, maize growth, by reducing plants' shoot biomass and increasing root/shoot ratio at 60 and 40% of WHC. Bioinoculants mitigated the negative effects on shoot biomass, especially when PGPR were co-inoculated, increasing up to 89% the aerial biomass of plants exposed to moderate water deficit. Bioinoculation also increased nitrogen (N) and phosphorous (P) use efficiency, which may have led to higher maize growth under water deficit conditions. The size of the inocula applied had marginal influence on biometric and nutrient parameters, although the higher concentration of the mixture of PGPR was the most effective in improving shoot biomass under moderate water deficit. This study shows that rhizobacterial strains are able to increase nutrient use efficiency and to alleviate water stress effects in crops with high water demands and have potential applications to keep up with productivity in water stress scenarios.

Salt-tolerance induced by leaf spraying with H2O2 in sunflower is related to the ion homeostasis balance and reduction of oxidative damage

Salinity is still one of the main factors that limit the growth and production of crops. However, currently, hydrogen peroxide (H₂O₂) priming has become a promising technique to alleviate the deleterious effects caused by salt. Therefore, this study aimed to test different leaf spraying strategies with H₂O₂ for acclimation of sunflower plants to salt stress, identifying the main physiological and biochemical changes involved in this process. The experiment was conducted in a completely randomized design, with four replications. Initially, four concentrations of H₂O₂ were tested (0.1; 1; 10 and 100 mM) associated with different applications: 1AP - one application (48 h before exposure to NaCl); 2AP - two applications (1AP + one application 7 days after exposure to NaCl) and 3AP - three applications (2AP + one application 14 days after exposure to NaCl), besides this two reference treatments were also added: control (absence of NaCl and absence of H₂O₂) and salt control (presence of 100 mM of NaCl and absence of H₂O₂). The experiment was conducted in hydroponic system containing Furlani's nutrient solution. Salt stress reduced the growth of sunflower plants, however, the H₂O₂ priming through leaf spraying was able to reduce the deleterious effects caused by salt, especially in the 1 mM H₂O₂ treatment with one application. H₂O₂ acts as a metabolic signal assisting in the maintenance of ionic and redox homeostasis, and consequently increasing the tolerance of plants to salt stress.

Spatio-temporal characteristics of adaptability between crop water requirements for summer maize and rainfall in Henan Province, China

It is very important to master the rainfall utilization efficiency and spatial-temporal distribution characteristics in order to improve the agricultural water resource utilization efficiency. In this study, an adaptability index (AI) was constructed to reflect the relationship between rainfall and crop water demand. Spatial analysis and clustering analysis were used to study the spatial distribution characteristics and evolution rules of the adaptability between water demand and rainfall in the growing period of summer maize in Henan Province of China. The results showed that there were significant spatial differences in the adaptability of different regions, and such differences change with time, indicating that AI has certain uncertainties in the region and growth season. In general, the AI of the whole growth period of summer maize is mainly determined by the AI of tasseling period-milky period, while the multi-year change rate of AI is mainly determined by the emergence period-jointing period, tasseling period-milky period, and milky period-maturity period The adaptability of summer maize to rainfall in the study area can be divided into three categories, among which the one with increased adaptability occupies the main part, and the one with sharply decreased adaptability were also distributed in the study area. The above studies indicate that it is important to pay attention to the adaptability of rainfall to agricultural water management. The complexity division of crop water demand by rainfall adaptability index can guide the establishment of reasonable and accurate irrigation system.

Co-addition of humic substances and humic acids with urea enhances foliar nitrogen use efficiency in sugarcane (Saccharum officinarum L.)

Humic substances (HS) and humic acids (HA) are proven to enhance nutrient uptake and growth in plants. Foliar application of urea combined with HS and HA offers an alternative strategy to increase nitrogen use efficiency (NUE). The objective of this study was to understand the effects of foliar application of HA and HS along with urea on NUE and response of different biometric, biochemical and physiological traits of sugarcane with respect to cultivar, mode of foliar application, geographic location and intervals of foliar application. To study this, two different independent Experiments were conducted in green house facilities at two different agro-climatic zones (USA and Brazil) using two different predominant varieties, modes and intervals of foliar applications. The three different foliar applications used in this study were (1) urea (U), (2) mixture of urea and HS (U+HS) and (3) HA (U+HA). In both Experiments, ¹⁵N (nitrogen isotope) recovery or NUE was higher in U+HS followed by U+HA. However, magnitude of NUE changed according to the differences in two Experiments. Results showed that foliar application of U+HS and U+HA was rapidly absorbed and stored in the form of protein and starch. Also induced changes in photosynthesis, intrinsic water use efficiency, protein, total soluble sugars and starch signifying a synergistic effect of U+HS and U+HA on carbon and nitrogen metabolism. These results showed promising use of HS and HA with urea to improve NUE in sugarcane compared to using the urea alone. Simultaneously, mode, quantity, and interval of foliar application should be standardized based on the geographic locations and varieties to optimize the NUE.

Effects of light intensities and varying watering intervals on growth, tissue nutrient content and antifungal activity of hydroponic cultivated Tulbaghia violacea L. under greenhouse conditions

Optimization of the quality and quantity of medicinal materials during cultivation could improve the value of medicinal plants. Light intensity and water availability affect physiological processes and growth of plants. Tulbaghia violacea L. (Alliaceae) bulbs and leaves are widely used traditionally in southern Africa for treatments of many ailments. The interactive effects of light intensity and watering regime on plant growth, nutrient uptake and antifungal activity of T. violacea were evaluated in the current study. Seedlings of T. violacea were grown hydroponically under two shading levels (0% and 40%) while being exposed simultaneously to one of three watering intervals: 5-day, 14-day and 21-day. Different growth parameters (plant height, plant fresh and dry weights) and tissue nutrient contents were evaluated at the end of the experiment. The antifungal activity of acetone extracts on Fusarium oxysporum were evaluated in a microdilution bioassay. Generally, significantly higher concentrations of macronutrients were recorded in the tissue of plants exposed to shorter watering interval. The results showed that different watering frequencies and light intensities significantly (p < 0.05) influenced plant growth parameters (height, and dry and fresh weights). Moreover, there were strong interactive effects of watering frequency and light intensity on most of the plant growth parameters. Remarkably, plants that were simultaneously exposed to the extended watering interval (21-day) and low light intensity showed the best anti-F. oxysporum activity. Key findings of this study revealed that shading alleviated the negative effects of water-deficit stress on plant growth and improved antifungal activity.

Aeromonas hydrophila, Bacillus thuringiensis, Escherichia coli and Pseudomonas aeruginosa utilization of Ammonium-N, Nitrate-N and Urea-N in culture

Agricultural drainage ditches represent a major source of nutrient pollution. Shifts in nitrogen source and use of animal manures have changed the bacterial composition both in species of bacteria and their abundance in agricultural ditches. This change affects how nitrogen is being cycled and potentially the final forms of available nutrients. In particular, animal manures often have bacteria such as Escherichia coli present, increasing the abundance of a bacterial species in ditches. Research has shown that the effect of different nitrogen sources is to change bacterial community composition (class, family). How this influences the role of an individual bacterial species is poorly understood. Thus, our question was how individual species would respond to different sources of nitrogen. We used Aeromonas hydrophila, Bacillus thuringiensis, Escherichia coli and Pseudomonas aeruginosa that are common in agricultural ditches and exposed them to different concentrations of nitrogen in cultures of 1 × 10⁰ and 1 × 10⁻¹ dilutions from a stock solution of bacteria. Nitrogen sources were ammonium chloride, sodium nitrate and urea. The results showed A. hydrophila and E. coli have strong similarities particularly with nitrate-N and urea-N utilization and the response was often correlated with the amount of nutrient added. P. aeruginosa while similar did not show any strong correlation with amount of nutrient added. B. thuringiensis was different from the other three bacteria in utilization or production. Research has provided insight into the role of some bacteria in nitrogen cycling and may be valuable in the future to developing management strategies to reduce nutrients.

Modelling adoption intensity of improved soybean production technologies in Ghana - a Generalized Poisson approach

Soybean is an important cash crop especially for farmers in the north of Ghana. However, cultivation of the commodity is dominated by smallholders equipped with traditional tools, coupled with low or no adoption of improved soybean production technologies. Using primary data collected from 300 soybean farmers across northern Ghana, the study employed count data modelling to estimate the determinants of adoption intensity of sustainable soybean production technologies. The study accounted for potential estimation errors due to under-dispersion and over-dispersion, by using a model based on the generalized Poisson distribution. On the average, a farmer adopted 50% of the identified sustainable soybean production technologies. Age, education, extension visits, mass media through radio, and the perception of adoption of soybean production technologies being risky are significant with positive influence on the adoption intensity of sustainable soybean production technologies. The study therefore recommends among others, that various extension programmes should intensify education on the benefits of adopting sustainable soybean production practices. There is the need to set up many technology demonstration farms to give farmers hands-on training during field days.

Geo-investigation on groundwater control in some parts of Ogun state using data from Shuttle Radar Topography Mission and vertical electrical soundings

Groundwater is a vital natural resource that plays a significant function in sustainability of living things on earth. Its exploration requires special skill for optimum exploitation. Shuttle Radar Topography Mission (SRTM)and Vertical Electrical Sounding (VES) were used to detectthe stratigraphy and subsurface structures controlling the groundwater system around Iju - Ota, Ogun State, Southwestern Nigeria. Nineteen (19) VES points were carried out where there were dense concentrations of lineaments and interconnected to establish the connection of the observed lineaments with groundwater occurrence in the study area using Schlumberger array, with electrode spacing of AB/2 varying from 180 to 320 m. The analysis of SRTM data revealedthe dominating structural NE-SW and NW-SE trends, which control aquifer structure. The geoelectrical parameters from the VES results were used to map the stratigraphic sequences in the study area. Six (6) units that comprisethe topsoil, lateritic clay, clayey sand, mudstone, sand (main aquifer), and shale or clay were identified in the study area. The aquiferous unit around Iju - Ota axis ranged from 30 to 80 m. Theextracted from the hill shaded SRTM data and the result of VES revealed that the thickness of the aquifer is as a result of interconnectivity of the lineaments observed in the SRTM data suggesting that the groundwater occurrence in the study area is chiefly controlled by these fractures.

Biological removal of iron and sulfate from synthetic wastewater of cotton delinting factory by using halophilic sulfate-reducing bacteria

Industrial and agricultural wastewater treatment, which has the potential to cause serious risks to human health and the environment, has special importance at the lowest cost and highest efficiency such as biological processes to treat wastewater. The purpose of the study was removing iron and sulfate from very saline synthetic wastewater by means of halophilic sulfate-reducing bacteria. This process was performed under anaerobic conditions to change wastewater to a chemical fertilizer to use in saline and alkaline soils. Three halophilic SRBs were isolated and purified from wastewater of the cotton delinting factory by Postage C medium which supplemented with sodium chloride and magnesium chloride hexahydrate. The highest NaCl tolerance strain (HSR973) was allocated to Desulfovibrio halophilus sp. This experimental study was conducted in a fluid bed reactor at anaerobic conditions. Diluted concentrations of cotton linters wastewater containing 50–400 ppm iron were added to the reactor. After the bacteria fixation to different iron concentrations, the maximum removal efficiency of iron and sulfate was achieved 85.3 % and 78.4 % at the optimum retention time of 24-hours respectively. Sulfate concentration in samples decreased to about 20 % of initial concentration after 24-h retention time. The highest production of H₂S at optimum operational conditions was about 228 ml l⁻¹. The reduction of sulfate and iron biological precipitation by anaerobic rector presented high performance. This removing accompanied with the alkalinity increase during the process which could be improved condition for acidic wastewater treatment. The produced iron sulfide sludge was not suitable for use as a chemical fertilizer due to its lack of complete separation. However, the total sludge produced was able to be consumed in saline and alkaline soils for various purposes after additional treatment.

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.

The effects of temperature and duration of thermal pretreatment on the solid-state anaerobic digestion of dairy cow manure

Cellulosic substrates such as dairy cow manure often yield low volumes of biogas and low concentrations of methane when digested anaerobically. Thermal pretreatment of dairy cow manure was investigated to determine if pretreatment temperature and duration can be optimized to maximize biogas yield and methane concentration. A central composite rotatable design was used to select combinations of temperature and duration. Based on measured data, statistical models were generated to estimate the biogas yield and methane concentration during digestion. The highest biogas yields were from the untreated samples and samples treated at the center temperature and duration of the statistical model (125 °C, 37.5 min). The model predicted the optimum pretreatment conditions of 140 °C for 30 minutes. Under the conditions of this experiment, temperature and duration had no significant effect on the biogas yield and methane concentration. This lack of significance may indicate that thermal pretreatment may be an unnecessary step in the anaerobic digestion of dairy cow manure, which could reduce capital and operating costs for the industry.

Optimal irrigation planning for addressing current or future water scarcity in Mediterranean tree crops

Water scarcity in the Mediterranean region is becoming a growing concern, threatening the viability of agriculture, which is one of the main economic sectors in many areas. The design of an optimal irrigation management plan, based on state-of-the-art measuring and modeling tools, can effectively contribute towards water saving efforts and potentially address the water scarcity issue in the region. This paper describes the development and application of an integrated decision-making system for the management of water resources of olive and citrus crops in the North of Chania, Crete, Greece. The system integrates different field measurements, for example 2088 soil moisture measurements taken within the study area, and modeling approaches to simulate flow in the unsaturated zone. After the successful calibration and validation of the model, the spatio-temporal representation of soil moisture and pore water pressure were used as guidance for developing optimal irrigation plans, taking into account the water needs of olive and citrus crops, aiming to maximize crop yield, agricultural income, and promote water saving efforts. According to the results, water use can be reduced by up to 36% during the dry season, compared to conventional irrigation practices for citrus trees. Similarly, for olive trees, the reduction in water use can reach up to 41%. The proposed methodology can also be cost-effective in terms of water value, saving about 40% from the typical water cost for irrigation in the study area. The impact of climate change on water resources availability in the area and water conservation efforts were also investigated for the period of (2019-2030). Results show that, comparing the Baseline, RCP 8.5 and RCP 4.5 climatic scenarios, the highest savings on average are observed for emission scenario RCP 4.5 with 53.3% water savings for olive trees and 46.7% for citrus trees.