Assessment of the intrinsic vulnerability of agricultural land to water and nitrogen losses: case studies in Italy and Greece

Abstract. LOS indices (abbr. of Losses) can be used for the assessment of the intrinsic vulnerability of agricultural land to water and nitrogen losses through percolation and runoff. The indices were applied on the lowland region of Ferrara Province (FP) in Italy and the upland region of Sarigkiol Basin (SB) in Greece. The most vulnerable zones in FP were the coastal areas consisting of high permeability sandy dunes and the areas close to riverbanks and palaeochannels, and in SB were the areas characterized by high slopes and high permeability soils at high altitude and areas belonging to the upper part of the alluvial plain close to the boundaries between agricultural land and mountainous regions. The application of LOS indices highlighted the specific features of both lowland and upland regions that contribute to water and nitrogen losses and showed their ability for use as tools in designing environmental management plans

High-resolution global grids of revised Priestley–Taylor and Hargreaves–Samani coefficients for assessing ASCE-standardized reference crop evapotranspiration and solar radiation

Abstract. The objective of the study is to provide global grids (0.5°) of revised annual coefficients for the Priestley–Taylor (P-T) and Hargreaves–Samani (H-S) evapotranspiration methods after calibration based on the ASCE (American Society of Civil Engineers)-standardized Penman–Monteith method (the ASCE method includes two reference crops: short-clipped grass and tall alfalfa). The analysis also includes the development of a global grid of revised annual coefficients for solar radiation (Rs) estimations using the respective Rs formula of H-S. The analysis was based on global gridded climatic data of the period 1950–2000. The method for deriving annual coefficients of the P-T and H-S methods was based on partial weighted averages (PWAs) of their mean monthly values. This method estimates the annual values considering the amplitude of the parameter under investigation (ETo and Rs) giving more weight to the monthly coefficients of the months with higher ETo values (or Rs values for the case of the H-S radiation formula). The method also eliminates the effect of unreasonably high or low monthly coefficients that may occur during periods where ETo and Rs fall below a specific threshold. The new coefficients were validated based on data from 140 stations located in various climatic zones of the USA and Australia with expanded observations up to 2016. The validation procedure for ETo estimations of the short reference crop showed that the P-T and H-S methods with the new revised coefficients outperformed the standard methods reducing the estimated root mean square error (RMSE) in ETo values by 40 and 25 %, respectively. The estimations of Rs using the H-S formula with revised coefficients reduced the RMSE by 28 % in comparison to the standard H-S formula. Finally, a raster database was built consisting of (a) global maps for the mean monthly ETo values estimated by ASCE-standardized method for both reference crops, (b) global maps for the revised annual coefficients of the P-T and H-S evapotranspiration methods for both reference crops and a global map for the revised annual coefficient of the H-S radiation formula and (c) global maps that indicate the optimum locations for using the standard P-T and H-S methods and their possible annual errors based on reference values. The database can support estimations of ETo and solar radiation for locations where climatic data are limited and it can support studies which require such estimations on larger scales (e.g. country, continent, world). The datasets produced in this study are archived in the PANGAEA database (https://doi.org/10.1594/PANGAEA.868808) and in the ESRN database (http://www.esrn-database.org or http://esrn-database.weebly.com)

NEW EQUATIONS FOR THE DETERMINATION OF SOIL SATURATED HYDRAULIC CONDUCTIVITY USING THE VAN GENUCHTEN MODEL PARAMETERS AND EFFECTIVE POROSITY

Modifications of the Kozeny-Carman approach (Ks=AΦB) for the determination of saturated hydraulic conductivity Ks using the van Genuchten model parameters and the effective porosity Φe are presented in this study. Two models {a two-parametric Ks(a, Φe) and a three-parametric Ks(a, Si, Φe)} were developed for Ks determination. In the two-parametric model the power constant was replaced by the f factor (f=aΦe). The factor f includes the parameter a of the van Genuchten model, in order to describe its effect on the part of the pore size distribution which participates in the effective porosity Φe. The three-parametric model was improved by inclusion of the water retention curve slope Si at the inflection point. The models were calibrated and validated using two published data sets which cover the 12 USDA soil texture classes. The proposed models were also compared with other published models of Ks, which are based on the van Genuchten parameters and the Kozeny-Carman approach. The results indicated an adequate predictive accuracy of the models through a calibration and validation procedure using data sets from different sources and better performance compared to other models, setting a new approach for the indirect determination of Ks using only data from the water retention curve

Water quality in irrigation and drainage networks of Thessaloniki plain in Greece related to land use, water management, and agroecosystem protection

A representative agricultural area of 150 ha located in a protected ecosystem (Axios River Delta, Thermaikos Gulf-N. Aegean, Greece) was selected in order to investigate water quality parameters [pH, electrical conductivity (ECw), NO3-N, NH4-N, total phosphorus (TP)] in irrigation and drainage water. In the study area, the cultivated crops are mainly rice, maize, cotton, and fodder. Surface irrigation methods are applied using open channels network, and irrigation water is supplied by Axios River, which is facing pollution problems. The return flow from surface runoff and the surplus of irrigation water are collected to drainage network and disposed to Thermaikos Gulf. A 2-year study (2006-2007) was conducted in order to evaluate the effects of land use and irrigation water management on the drainage water quality. The average pH and NO3-N concentration was higher in the irrigation water (8.0 and 1.3 mg/L, respectively) than that in the drainage water (7.6 and 1.0 mg/L, respectively). The average ECW, NH 4-N, and TP concentration was higher in the drainage water (1,754 μS/cm, 90.3 μg/L, and 0.2 mg/L, respectively) than that in the irrigation water (477.1 μS/cm, 46.7 μg/L, and 0.1 mg/L, respectively). Average irrigation efficiency was estimated at 47% and 51% in 2006 and 2007 growing seasons (April-October), respectively. The loads of NO3-N in both seasons were higher in the irrigation water (35.1 kg/ha in 2006 and 24.9 kg/ha in 2007) than those in the drainage water (8.1 kg/ha in 2006 and 7.6 kg/ha in 2007). The load of TP was higher in the irrigation water in season 2006 (2.8 kg/ha) than that in the drainage water (1.1 kg/ha). Total phosphorus load in 2007 was equal in irrigation and drainage water (1.2 kg/ha). Wetland conditions, due to rice irrigation regime, drainage network characteristics, and the crop distribution in the study area, affect the drainage water ending in the protected ecosystem of Thermaikos Gulf

Methodology to Assess the Effects of Rice Cultivation Under Flooded Conditions on van Genuchten’s Model Parameters and Pore Size Distribution

The effects of rice (Oryza sativa L.) cultivation under flooded conditions on soil's physical-hydraulic properties were studied in this article, using a new methodology based on a combined analysis on soil water retention curve (WRC) and pore size distribution (PSD). WRC analysis was carried out through the changes of van Genuchten's model parameters, the characteristics of WRC at the inflection point, and the specific water capacity curve. Analysis of PSD was performed on the volume changes of porosity fractions through a detailed pore size classification, while different pore size classifications based on their hydraulic and structural characteristics were also used. The methodology was applied using a small dataset obtained from fine-textured Entisol soils which were subjected to rice cultivation under flooded conditions in Axios River plain (Northern Greece). Measurements of WRC were obtained at four depths of the soil profile from two fields, before and after the growing season of rice. The analysis indicated that the van Genuchten's model parameters (θ s, a, and n) and the WRC characteristics at the inflection point (pressure head h i, pore equivalent diameter D i, and slope S i) significantly changed after the growing season following similar patterns, along the soil profile in both fields. The parameters θ s, a, D i, and S i were decreased, while n and h i were increased. The h i and a were the most sensitive parameters, while the values of (h i and 1/a) in each layer before and after the growing season for each field were linearly correlated and shifted to higher values because of compaction, indicating that it could be applied as a tool to evaluate the degree of soil compaction to similarly textured soils. The peaks of the specific water capacity curves were compressed (lower values of slope S i) and shifted to lower water potentials (h i) that corresponded to pores of equivalent diameter D i between 2 and 6 μm. The soils had few structural pores (>9 μm) and low air-filled porosity (>30 μm) before the growing season, which presented accessory reduction after the growing season in both fields. Total porosity was reduced at the expense of structural porosity along the soil profile, while the pore size class of 5-3 μm was identified as the threshold where the smaller pores' volume started to increase in all layers of both fields. The results indicated that the changes in the WRC and the PSD follow specific trends, which can be used in future studies to model temporal variability of soil's physical-hydraulic properties

A combined methodology to assess the intrinsic vulnerability of aquifers to pollution from agrochemicals

The groundwater vulnerability indices are valuable tools for the development of agrochemicals management strategies based on environmental/agricultural policies. The groundwater vulnerability methods of LOS, SINTACS, DRASTIC, Pesticide DRASTIC, GOD and AVI were applied for the agricultural fields of Sarigkiol basin (Northern Greece). The results of the aforementioned methods were examined and discussed in order to show how the dissimilarities in the vulnerability assessment approaches may become an advantage. The results of the methods were used to propose a combined conceptual approach which adds another two dimensions (depth and time) in the current two-dimensional vulnerability mapping (longitude, latitude) procedures. The LOS method provided information about the intrinsic vulnerability of the topsoil (30 cm) to water (+conservative pollutants) and nitrogen losses, and the AVI method described the vulnerability of the unsaturated zone to allow pollutants to reach the aquifer while the aquifer vulnerability was analysed using SINTACS, DRASTIC, Pesticide DRASTIC and GOD. In this study, the results of the SINTACS method were found more accurate to describe the local aquifer conditions. The final conceptual approach provided a stratified vulnerability (dimension of depth) of the overall hydrogeologic system using LOS for the topsoil, AVI for unsaturated zone and SINTACS for the aquifer. The dimension of time was introduced by the LOS and AVI methods, which provide quantitative results in time. The use of LOS method also highlighted the basic limitation of the other methods to describe the potential contribution to pollution of areas (especially upland areas) which are out of the aquifer boundaries

A Review and Synthesis of Bivariate Non-Linear Models to Describe the Relative Variation of Ecological, Biological and Environmental Parameters

There is a plethora of non-linear models to describe bivariate relationships related to ecological, biological and environmental problems, and this makes difficult to have a general aspect about the suitable models for a new-born dataset. Additionally, there is a special interest for bivariate non-linear models which can describe the relative variation of the dependent variable (NLR models) (i.e. these models provide a restricted range of values between 0 and 1) because they can easily be adjusted to fit different datasets which describe the same relationship. The aim of this study is to provide a review and synthesis of NLR models which can be used to describe bivariate relationships which follow bell-shaped, simple-double sigmoid, bilinear and periodical patterns. This attempt aims to save time and effort for the selection of a NLR model based on five steps (a) preparation of data, (b) visual identification of the suitable model based on pre-constructed graphs, (c) a starting point using the simpler form (base function) of the selected models which are given in complex general forms, (d) directions to increase the number of coefficients in order to improve fitting and (e) techniques to modify the given NLR models in order to derive new ones with inverted patterns

Correcting Thornthwaite evapotranspiration formula using a global grid of local coefficients to support temperature-based estimations of reference evapotranspiration and aridity indices

Thornthwaite's formula is globally an optimum candidate for large scale applications of potential evapotranspiration and aridity assessment at different climates and landscapes since it has the lower data requirements compared to other methods and especially from the ASCE-standardized reference evapotranspiration (former FAO-56), which is the most data demanding method and is commonly used as benchmark method. The aim of the study is to develop a global database of local coefficients for correcting the formula of monthly Thornthwaite potential evapotranspiration (Ep) using as benchmark the ASCE-standardized reference evapotranspiration method (Er). The validity of the database will be verified by testing the hypothesis that a local correction coefficient, which integrates the local mean effect of wind speed, humidity and solar radiation, can improve the performance of the original Thornthwaite formula. The database of local correction coefficients was developed using global gridded temperature and Er data of the period 1950-2000 at 30 arc-sec resolution (~1 km at equator) from freely available climate geodatabases. The correction coefficients were produced as partial weighted averages of monthly Er/Ep ratios by setting the ratios' weight according to the monthly Er magnitude and by excluding colder months with monthly values of Er or Ep <45 mm month-1 because their ratio becomes highly unstable for low temperatures. The validation of the correction coefficients was made using raw data from 525 stations of Europe, California-USA and Australia including data up to 2020. The validation procedure showed that the corrected Thornthwaite formula Eps using local coefficients led to a reduction of RMSE from 37.2 to 30.0 mm m-1 for monthly and from 388.8 to 174.8 mm y-1 for annual step estimations compared to Ep using as benchmark the values of Er method. The corrected Eps and the original Ep Thornthwaite formulas were also evaluated by their use in Thornthwaite and UNEP (United Nations Environment Program) aridity indices using as benchmark the respective indices estimated by Er. The analysis was made using the validation data of the stations and the results showed that the correction of Thornthwaite formula using local coefficients increased the accuracy of detecting identical aridity classes with Er from 63% to 76% for the case of Thornthwaite classification, and from 76% to 93% for the case of UNEP classification. The performance of both aridity indices using the corrected formula was extremely improved in the case of non-humid classes. The global database of local correction factors can support applications of reference evapotranspiration and aridity indices assessment with the minimum data requirements (i.e. temperature) for locations where climatic data are limited

The Role of Microbial Inoculants on Plant Protection, Growth Stimulation, and Crop Productivity of the Olive Tree (Olea europea L.)

The olive tree (Olea europaea L.) is an emblematic, long-living fruit tree species of profound economic and environmental importance. This study is a literature review of articles published during the last 10 years about the role of beneficial microbes [Arbuscular Mycorrhizal Fungi (AMF), Plant Growth Promoting Rhizobacteria (PGPR), Plant Growth Promoting Fungi (PGPF), and Endophytes] on olive tree plant growth and productivity, pathogen control, and alleviation from abiotic stress. The majority of the studies examined the AMF effect using mostly Rhizophagus irregularis and Glomus mosseae species. These AMF species stimulate the root growth improving the resistance of olive plants to environmental and transplantation stresses. Among the PGPR, the nitrogen-fixing bacteria Azospirillum sp. and potassium- and phosphorous-solubilizing Bacillus sp. species were studied extensively. These PGPR species were combined with proper cultural practices and improved considerably olive plant&rsquo;s growth. The endophytic bacterial species Pseudomonas fluorescens and Bacillus sp., as well as the fungal species Trichoderma sp. were identified as the most effective biocontrol agents against olive tree diseases (e.g., Verticillium wilt, root rot, and anthracnose)

An Integrated Approach to Assessing the Soil Quality and Nutritional Status of Large and Long-Term Cultivated Rice Agro-Ecosystems

The aim of this study is to develop an integrated approach to soil quality and fertility assessment in high-yielding rice agro-ecosystems threatened due to overexploitation of soil resources by intensive agriculture. The proposed approach is implemented considering representative pilot fields allocated throughout a study area based on the assumption that soils of similar general properties present a similar nutritional status due to common long-term management practices. The analysis includes (a) object-based image analysis for land zonation, (b) hot-spot analysis for sampling scheme evaluation, (c) setting of critical thresholds in soil parameters for detecting nutrient deficiencies and soil quality problems, and (d) Redundancy Analysis, TITAN analysis, and multiple regression for identifying individual or combined effects of general soil properties (e.g., organic matter, soil texture, pH, salinity) or non-soil parameters (e.g., topographic parameters) on soil nutrients. The approach was applied using as a case study the large rice agro-ecosystem of Thessaloniki plain in Greece considering some site specificities (e.g., high rice yields, calcareous soils) when setting the critical thresholds in soil parameters. The results showed that (a) 62.5% of the pilot fields&#8217; coverage has a simultaneous deficiency in Zn, Mn, and B, (b) organic matter (OM) was the most significant descriptor of nutrients&#8217; variance, and its cold spots (clustered regions of low OM values) showed important overlapping with the cold spots of K, Mg, Zn, Mn, Cu, and B, (c) a higher rate of availability increase in P, K, Mg, Mn, Zn, Fe, Cu, and B was observed when the OM ranged between 2 and 3%, and (d) the multiple regression models that assess K and P concentrations based on general soil properties showed an adequate performance, allowing their use for general assessment of their soil concentrations in the fields of the whole agro-ecosystem