Targeted On-Demand Screening of Pesticide Panel in Soil Runoff

Using pesticides is a common agricultural and horticultural practice to serve as a control against weeds, fungi, and insects in plant systems. The application of these chemical agents is usually by spraying them on the crop or plant. However, this methodology is not highly directional, and so only a fraction of the pesticide actually adsorbs onto the plant, and the rest seeps through into the soil base contaminating its composition and eventually leaching into groundwater sources. Electrochemical sensors which are more practical for in situ analysis used for pesticide detection in soil runoff systems are still in dearth, while the ones published in the literature are attributed with complex sensor modification/functionalization and preprocessing of samples. Hence, in this work, we present a highly intuitive electroanalytical sensor approach toward rapid (10 min), on-demand screening of commonly used pesticides—glyphosate and atrazine—in soil runoff. The proposed sensor functions based on the affinity biosensing mechanism driven via thiol cross-linker and antibody receptors that holistically behaves as a recognition immunoassay stack that is specific and sensitive to track test pesticide analytes. Then, this developed sensor is integrated further to create a pesticide-sensing ecosystem using a front-end field-deployable smart device. The method put forward in this work is compared and validated against a standard laboratory potentiostat instrument to determine efficacy, feasibility, and robustness for a point-of-use (PoU) setting yielding LoD levels of 0.001 ng/ml for atrazine and 1 ng/ml for glyphosate. Also, the ML model integration resulted in an accurate prediction rate of ≈80% in real soil samples. Therefore, a universal pesticide screening analytical device is designed, fabricated, and tested for pesticide assessment in real soil runoff samples.

INTEGRATION OF DATA OF THE REMOTE SENSING, GIS, AND GAMMA-SPECTROMETRIC ANALYSIS TO STUDY SOIL MATERIAL REDISTRIBUTION

The paper discusses a problem of complex data application when accounting erosion network elements to study soil runoff and soil material redistribution on arable slopes. It is needed to estimate and account contribution of microrelief landforms to the sediment (washed out soil material) redistribution on arable areas to enhance accuracy of estimation of the soil runoff and accumulation. However, microrelief landforms are hardly detected on topographic maps and plans used traditionally in land management. For example, temporary streams formed in plowing furrows (in the case of along-slope plowing) can be detected only when survey and soil sampling data are attracted, or (partially) using remote sensing data.Due to such a context, we discover integrated analysis of map data (digital maps represented and processed in GIS environment), data of gamma-spectrometric analysis of the soil samples, and very high resolution satellite imagery, which is aimed onto detection of the role of stable and dynamically changing microrelief landforms in soil material redistribution.

GIS Based Assessment and Design for Areas Vulnerable to Soil Disasters: Case Study of Namhyeun-dong, South Korea

Due to climate change, heavy rainfall events that trigger landslips are becoming common. This study investigates patterns in the soil’s response to major rainfall events in mountainous areas and proposes a new approach for resilient disaster prevention technology and recovery based on the effect of soil runoff. Namhyeon-dong within Seoul was selected for the case study because of its vulnerable location between two mountains. A master plan was developed to cope with the predicted soil runoff based on the annual rainfall, local land use and a series of 10-year forecasts covering the period from 2021 to 2100. A total of 22 catchments in the study area were analyzed with Arc Hydro, an ArcGIS plug-in and appropriate technologies proposed to deal with the soil runoff likely to be experienced in each catchment in an extreme disaster. The resulting model was deemed adequate to deal with disasters during the period predicted to represent the highest risk, 2051–2060. The study’s findings will help to forecast disasters from flood that could impact residential areas in mountainous regions, to predict the magnitude of potential soil disasters in individual regions and develop design guidelines for disaster prevention technology based on the predicted amount of soil runoff.

The Effect of Different Tillage Methods on Erosion

During the years 2012‒2016 at the site threatened by erosion, the effect of different intensity and depth of soil tillage on the progression of erosion were evaluated on the plots with silage maize. Three different tillage methods were compared and evaluated - conventional tillage, including ploughing (CT), no-tillage using mulch and direct drilling (NT), and minimum tillage treatment with a lower depth of soil cultivation and organic matter incorporation (MT). Water and soil runoff on all of the experimental plots were measured during erosion events. Besides an analysis of naturally occurring rainfall causing erosions, we also conducted the test of soil infiltration abilities with a rain simulator after silage maize harvest. The effect of the tillage on aboveground biomass yield and the input costs was also analyzed. The results showed that NT and MT can significantly reduce water and soil runoff comparing CT. The highest yields were recorded in MT, while the lowest were in CT. Total input costs were higher in the case of NT and MT, but the share of mechanized work was lower for these technologies. Our results showed that NT and MT technologies, as a part of silage maize with a higher plant density stand establishment, should be a useable erosion control measure in areas vulnerable to erosion.

LARGE-SCALE INDICATIVE MAPPING OF SOIL RUNOFF

In our study we estimate relationships between quantitative parameters of relief, soil runoff regime, and spatial distribution of radioactive pollutants in the soil. The study is conducted on the test arable area located in basin of the upper Oka River (Orel region, Russia). Previously we collected rich amount of soil samples, which make it possible to investigate redistribution of the Chernobyl-origin cesium-137 in soil material and as a consequence the soil runoff magnitude at sampling points. <br><br> Currently we are describing and discussing the technique applied to large-scale mapping of the soil runoff. The technique is based upon the cesium-137 radioactivity measurement in the different relief structures. Key stages are the allocation of the places for soil sampling points (we used very high resolution space imagery as a supporting data); soil samples collection and analysis; calibration of the mathematical model (using the estimated background value of the cesium-137 radioactivity); and automated compilation of the map (predictive map) of the studied territory (digital elevation model is used for this purpose, and cesium-137 radioactivity can be predicted using quantitative parameters of the relief). The maps can be used as a support data for precision agriculture and for recultivation or melioration purposes.