Globally, flooding is one of the most damaging abiotic stresses, besides drought, that affects 17 million km² of land surface annually. Recent research indicates that climate change is resulting in more extreme weather events, such as flooding or soil waterlogging, that negatively affect crop production. Therefore, it is imperative to understand how flooding stress affects crops and to develop improved production practices that make cropping systems more resilient and able to cope with extreme weather events. This review paper summarizes the current state of knowledge on the impacts of flooding or soil waterlogging on crop production losses, nitrogen (N) losses, and provides potential management strategies to reduce these losses. The factors affecting the extent of flooding injury in plants as well as plant adaptations under waterlogging stress are also discussed briefly. For the purpose of this review, “flooding” refers to the situation when all or part of the plant is submerged under water, whereas “soil waterlogging” refers to the situation where soil pores are saturated with water. Soil waterlogging also promotes soil N losses through runoff, leaching, and denitrification. Potential management practices that can be used to mitigate soil waterlogging stress include the use of flood‐tolerant varieties, adjusting management practices, improving drainage, and practicing adaptive nutrient management strategies. However, these might be site‐ or crop‐specific management practices and they should be validated for their economic viability before developing future management plans that promote sustainable crop yields from waterlogged soils.

Balanced and integrated use of organic and inorganic fertilizers may enhance the accumulation of soil organic matter and improves soil physical properties. A field experiment having randomized complete block design with four replications was conducted for 36 years at Punjab Agricultural University (PAU), Ludhiana, India to assess the effects of inorganic fertilizers and farmyard manure (FYM) on soil organic carbon (SOC), soil physical properties and crop yields in a maize (Zea mays)–wheat (Triticum aestivum) rotation. Soil fertility management treatments included were non-treated control, 100% N, 50% NPK, 100% NP, 100% NPK, 150% NPK, 100% NPK + Zn, 100% NPK + W, 100% NPK (-S) and 100% NPK + FYM. Soil pH, bulk density (BD), electrical conductivity (EC), cation exchange capacity, aggregate mean weight diameter (MWD) and infiltration were measured 36 years after the initiation of experiment. Cumulative infiltration, infiltration rate and aggregate MWD were greater with integrated use of FYM along with 100% NPK compared to non-treated control. No significant differences were obtained among fertilizer treatments for BD and EC. The SOC pool was the lowest in control at 7.3 Mg ha⁻¹ and increased to 11.6 Mg ha⁻¹ with 100%NPK+FYM. Improved soil physical conditions and increase in SOC resulted in higher maize and wheat yields. Infiltration rate, aggregate MWD and crop yields were positively correlated with SOC. Continuous cropping and integrated use of organic and inorganic fertilizers increased soil C sequestration and crop yields. Balanced application of NPK fertilizers with FYM was best option for higher crop yields in maize–wheat rotation.

Core Ideas: Soil solution sampling is essential to better understand water and solute movement in soils. A review of different types of soil solution samplers is provided in this paper, including: drainage lysimeter or soil column, pan lysimeter, resin bags or membranes, wick lysimeters, suction cup, and suction plate. Recent developments, modifications, and recommendation criteria are provided for selecting appropriate soil solution extraction samplers. A number of contaminants including agrochemicals (fertilizers, pesticides), heavy metals, trace elements, and pathogenic microbes along with pharmaceuticals and hormones used in animal production move through the soil and are responsible for degradation of groundwater quality. Therefore, it is essential to sample soil solution for better understanding of movement and environmental fate of various contaminants in soils. We review different soil solution extraction samplers. The soil solution samplers discussed here are: drainage lysimeter or soil column, pan lysimeter, resin bags or membranes, wick lysimeters, suction cup, and suction plate. We have reviewed 304 journal articles representing a wide array of scientific disciplines. A brief history of soil solution monitoring and terminology used for describing various soil solution samplers is also provided. This review classifies literature on the basis of type of soil solution extraction samplers, soil type, land use–land cover (LULC), and analytes measured. Recommendation criteria are provided for selecting appropriate soil solution extraction samplers based on spatial and temporal variation, cost, soil type, amount of disturbance caused during installation of soil solution samplers, and monitoring of leachates involving different cations, anions, carbon, pH, EC, colloids, pesticides, and microbes. Use of advanced techniques with lysimeters for monitoring soil moisture content, soil water potential and flux is also discussed in this review.

Use of electromagnetic induction (EMI) sensors along with geospatial modeling provide a better opportunity for understanding spatial distribution of soil properties and crop yields on a landscape level and to map site-specific management zones. The first objective of this research was to evaluate the relationship of crop yields, soil properties and apparent electrical conductivity (ECa) at different topographic positions (shoulder, backslope, and deposition slope). The second objective was to examine whether the correlation of ECa with soil properties and crop yields on a watershed scale can be improved by considering topography in modeling ECa and soil properties compared to a whole field scale with no topographic separation. This study was conducted in two headwater agricultural watersheds in southern Illinois, USA. The experimental design consisted of three basins per watershed and each basin was divided into three topographic positions (shoulder, backslope and deposition) using the Slope Position Classification model in ESRI ArcMap. A combine harvester equipped with a GPS-based recording system was used for yield monitoring and mapping from 2012 to 2015. Soil samples were taken at depths from 0–15 cm and 15–30 cm from 54 locations in the two watersheds in fall 2015 and analyzed for physical and chemical properties. The ECa was measured using EMI device, EM38-MK2, which provides four dipole readings ECa-H-0.5, ECa-H-1, ECa-V-0.5, and ECa-V-1. Soybean and corn yields at depositional position were 38% and 62% lower than the shoulder position in 2014 and 2015, respectively. Soil pH, total carbon (TC), total nitrogen (TN), Mehlich-3 Phosphorus (P), Bray-1 P and ECa at depositional positions were significantly higher compared to shoulder positions. Corn and soybeans yields were weakly to moderately (<±0.75) correlated with ECa. At the deposition position at the 0–15 cm depth ECa-H-0.5 was weakly correlated (r < ±0.50) with soil pH and was moderately correlated (r = ±0.50–±0.75) with organic matter (OM), calcium (Ca) and sulfur (S). Slope variation from 1%–20% at the research site had a strong influence on soil properties at watershed scale. When data from all topographic positions were combined together in all basins spatial interpolation between Mehlich-3 P and ECa-H-0.5 resulted in a larger cross validation RMSE compared to individual shoulder and backslope positions. Results demonstrated that topographic position should be considered while making correlations of ECa with soil properties. Methods of delineating topography positions presented in this paper can easily be replicated on other fields with similar landscape characteristics and EMI sensor based survey techniques can certainly improve and help in making detailed prediction maps of soil properties.

In the Midwestern United States, cover crops are being promoted as a best management practice for managing nutrient and sediment losses from agricultural fields through surface and subsurface water movement. To date, the water quality benefits of cover crops have been inferred primarily from plot scale studies. This project is one of the first to analyze the impacts of cover crops on stream water quality at the watershed scale. The objective of this research was to evaluate nitrogen, phosphorus, and sediment loss in stream water from a no-till corn-soybean rotation planted with winter cover crops cereal rye (Secale cereale) and hairy vetch (Vicia villosa) in non-tile drained paired watersheds in Illinois, USA. The paired watersheds are under mixed land use (agriculture, forest, and pasture). The control watershed had 27 ha of row-crop agriculture, and the treatment watershed had 42 ha of row crop agriculture with cover crop treatment (CC-treatment). During a 4-year calibration period, 42 storm events were collected and Event Mean Concentrations (EMCs) for each storm event were calculated for total suspended solids (TSS), nitrate-N (NO₃-N), ammonia-N (NH₄-N), dissolved reactive phosphorus (DRP), and total discharge. Predictive regression equations developed from the calibration period were used for calculating TSS, NO₃-N, NH₄-N, and DRP losses of surface runoff for the CC-treatment watershed. The treatment period consisted of total 18 storm events, seven of which were collected during the cereal rye, eight in the hairy vetch cover crop season and three during cash crop season. Cover crops reduced TSS and discharge by 33% and 34%, respectively in the CC-treatment watershed during the treatment period. However, surprisingly, EMCs for NO₃-N, NH₄-N, and DRP did not decrease. Stream discharge from the paired-watersheds will continue to be monitored to determine if the current water quality results hold or new patterns emerge.