Root Zone Water Research Articles

Predicting the effect of weir management on the discharge of a controlled drainage system in a changing climate

Subsurface drainage in humid areas prevents field waterlogging but also transports nutrients to freshwater systems. Controlled drainage (CD) reduces drainage discharge and nutrient transport from fields. Some regions are expected to experience increased precipitation in the future, requiring CD to be evaluated under a changing climate. The objective of this study was to compare the performance of CD under two weir managements for a future period (2030–2059) and historical period (1992-2021) in southeast Michigan, USA. Climate projections were obtained for the shared socioeconomic pathway 245 emission scenario. Aggressive management involved maintaining the weir height at 40 cm during the growing season and 15 cm during the non-growing season, with a longer period of managed flow compared to common management, which maintained the weir height at 50 cm during the growing season and 30 cm during the non-growing season. It was predicted that the 30-year average annual precipitation would not change significantly in the future. The 30-year average mean monthly temperature would increase by 3.0°C in the future compared to the historical period. We performed simulations using the calibrated Root Zone Water Quality Model 2 (RZWQM2). The average drainage discharge in the future indicated a 20% increase in the 30-year average drainage discharge for a field with free drainage. The CD with common and aggressive managements reduced drainage discharge by 59% and 67% for the historical period, whereas the performance of CD was even better for the future period (63% and 72%, respectively). The improved future performance of CD can be attributed to a shift in precipitation patterns, with reduced precipitation during the growing season and increased precipitation during the non-growing season. As a result, the more aggressive weir management during this period created additional opportunities for reducing drainage discharge. In conclusion, aggressive management resulted in a slightly better flow-reducing performance than common management while indicating that both methods would effectively reduce drainage discharge in the likely future scenario.

Impact of irrigation management on crop water footprint reduction using RZWQM2 in Baghdad, Iraq

Water scarcity becomes a serious global challenge in several world regions and particularly in the Middle East. Appropriate irrigation practice is critical for improving crop yield and alleviating crop water footprint (WF). To alleviate water scarcity, the possibility of reducing wheat and barley water footprint has been examined through alternative surface irrigation practices. The WF was compared under farmers’ irrigation practice and experimental irrigation practice to discover the impact of irrigation practices on the reduction of WF in the west of Baghdad. Weather data and crop management information were collected from 2016 to 2020 for the farmer’s fields in the study area as well as for the experimental field. The Root Zone Water Quality Model (RZWQM2) was used for estimating wheat and barley evapotranspiration. The study results showed that the crop WF was well estimated using the RZWQM2 due to the model capability and accuracy for estimating the impact of field management on crop evapotranspiration and crop water use. Experimental irrigation practice could improve crop yield, water use efficiency, and water profitability by up to 28%, 35%, and 35%, respectively; while the WF was reduced by 35%, compared to the farmers’ irrigation practice. The WF of the wheat crop was lower than the barley WF due to the low barley production.

Exploring the effects of subsoiling tillage under various irrigation regimes on the evapotranspiration and crop water productivity of winter wheat using RZWQM2

Food security is an important pre-requisite for human well-being; however, water shortages and poor quality of arable land threaten food security in the North China Plain (NCP). Subsoiling and proper irrigation can improve soil structure and increase crop yield. This study investigated the effects of two tillage methods (rotary tillage at 15 cm depth, R15; subsoiling at 35 cm depth, S35) combined with three irrigation treatments (no irrigation during the winter wheat growing season, I0; 60 mm irrigation at the jointing stage, I1; 60 mm irrigation at both the jointing and heading stages, I2) on soil moisture dynamics, evapotranspiration, and winter wheat yield. The Root Zone Water Quality Model (RZWQM2) was adopted after calibration and validation base on a field experiment. The results showed that the normalized root mean square errors (calibration and test) between the actual and simulated values of soil water storage (SWS), evapotranspiration (ET), and yield were 7.45–10.87%, 3.80–7.21%, and 5.38–14.15%, respectively. Subsoiling improved winter wheat soil moisture conditions, yield, and crop water productivity (CWP), and irrigation during the winter wheat growing seasons increased crop yield (I2 > I1 > I0) and CWP (I1 > I2 > I0). The best yield treatment during the 2020–2022 winter wheat growing seasons was S35-I2. However, the CWP of S35-I1 was 2.67% higher than that of S35-I2. Tillage methods change the ET structure of winter wheat fields. Compared to rotary tillage, subsoiling reduced actual ET by 16.11% and increased actual transpiration by 10.44%. The results of this study indicate that subsoiling at a depth of 35 cm and 60 mm irrigation at the jointing stage could improve the CWP of winter wheat in the NCP.

Simulating fate and transport of non-steroidal anti-inflammatory drugs using Root Zone Water Quality Model 2.

The fate and transport of non-steroidal anti-inflammatory drugs (NSAIDs) in soil are determined by various processes, and the complexity of the system lends itself to the use of computer simulation models to help understand it. This study demonstrated the first attempt to use empirical data from lab incubation and field studies to parameterize and test a process-based agricultural systems model, Root Zone Water Quality Model 2 (RZWQM2), to simulate the fate and transport of naproxen (NPX), ibuprofen (IBF), and ketoprofen (KTF) in field-based lysimeters amended with alkaline-treated biosolids (ATBs). The model calibrated for the soil-water balance module and contaminant transport module was used to predict water seepage through the soil profile in 2017 and 2018 within a 15% error of the field measured data, with model performance statistics such as Nash-Sutcliffe model efficiency (NSE) and R2 all greater than 0.70. The overall predicted percent recovery of initial spiked NSAIDs in both soil and water samples, after further calibration of the contaminant transport module, was within the same order of magnitude as the measured data. The model underestimated the percent recovery of initial spiked NSAIDs at the 30- to 55-cm soil depth for all treatments on day 3. The calibrated soil subsurface aerobic half-lives of NPX and IBF were found to be considerably lower than their laboratory-measured half-lives obtained from the incubation study. The overall performance of RZWQM2 in simulating the soil hydrology and behavior of NSAIDs in soil profiles receiving various rates of ATB amendments was satisfactory.

Analysis of Hotspots in Subsurface Drip Irrigation Research Using CiteSpace

To investigate the research hotspots and development trends of subsurface drip irrigation (SDI) over the past 20 years, this study analyzed relevant literature from the Web of Science Core Collection spanning from 2002 to 2022. The data were visualized using CiteSpace, showcasing the publication volume trends, countries, keywords, cited references, authors, and affiliated institutions. Based on 1079 articles, the annual publication volume showed an overall upward trend. The United States had the most extensive research coverage and highest publication volume, whereas China had the fastest growing publication rate in recent years. However, relatively little cooperation occurred among research teams and institutions. Over time, research topics became increasingly diverse, with water conservation and yield increases being the primary research objectives. In addition to improving irrigation and fertilizer use efficiency, SDI has also been applied in research on the safe utilization of unconventional water resources (wastewater and salt water) and the optimization of soil conditions. Among these, aerated irrigation technology—aimed at improving root growth in the rhizosphere—may become a new branch of SDI research. Currently, the main research focus in the field of SDI is the diffusion and distribution of water in the crop root zone, for which Hydrus model simulation is a particularly important method.

Empirical equations for estimating field capacity in dryland cropping soils of southeastern Australia

The root zone soil water content at field capacity, θFC, is often crucial for irrigation scheduling and soil-plant-atmosphere modelling. Although θFC is traditionally determined using methodologies based on matric head or when water flux at the bottom of the root-zone equal to a prescribed negligible flux, these approaches can be problematic for some soils and applications. In this study, a novel water storage approach was used to estimate θFC for 11 soil texture classes in southeastern Australia (northwest Victoria) by employing the Soil-Water-Atmosphere-Plant (SWAP) model to simulate gravity drainage from saturation in the active root zone (top 60 cm). Field capacity was specified as the average root zone water content corresponding to a 1% relative change in daily soil water storage. We have also estimated flux-based θFC when prescribed flux at the bottom of the root-zone was 0.1 cm d-1. Three new empirical equations were developed to estimate storage-based θFC as a function of SWAP-simulated drainage flux out of the root zone, the n parameter of the van Genuchten function, and the saturated soil hydraulic conductivity, Ks, or the soil water content at − 100 cm matric head. We have evaluated these three new equations in addition to nine published equations for estimating θFC. The three new equations were found to be better predictors of θFC than most of the nine popular equations reported in the literature when compared to flux-based θFC values. Based on findings from this study the new equations are considered to be effective for irrigation scheduling and crop/climate modelling on the dryland soils of Victoria. Future studies will assess the applicability of the new equations to other parts of Australia.

A modularized parallel distributed High–Performance computing framework for simulating seasonal frost dynamics in Canadian croplands

The winter/spring season in cold climate regions has been recognized as a critical period for cropland nutrient loss and greenhouse gas emissions and has been predicted to be vulnerable to climate change. Agricultural system models serve as essential tools in anticipating potential outcomes. The RZ-SHAW model, combining the Simultaneous Heat and Water Model (SHAW) with the Root Zone Water Quality Model 2 (RZWQM2), comprehensively describes snow and soil freezing dynamics. Showing promising results in simulating winter frost dynamics it, however, remains computationally intensive. High-performance computing has been recognized as a promising approach to reducing simulation runtimes. A modularized parallel distributed high-performance computing (HPC) framework (RS-DPCF) with both multi-threading (MT) and multi-processing (MP) capability was developed for RZ–SHAW calibration and simulation. Two case studies demonstrated that the developed RS-DPCF program could significantly reduce RZ–SHAW calibration time, allow improved computation resource scalability, and perform field-scale simulations of overwintering conditions for multiple croplands across Canada. For the RZ–SHAW model, MT provided a parallel-computing efficiency superior to that of MP.

Forest density and snowpack stability regulate root zone water stress and percolation differently at two sites with contrasting ephemeral vs. stable seasonal snowpacks

Forested, snow-dominated watersheds provide a range of ecosystem services for adjacent and downstream communities including water supply, wildlife habitat, and recreation. While forest-snow-water relations have been well studied in areas with stable seasonal snowpacks, less is known about these interactions in the growing number of areas with ephemeral snowpacks. Here, we evaluate how forest cover and climate variability regulate the seasonality of water inputs, soil moisture, root zone water stress, and percolation at two contrasting seasonal vs. ephemeral snowpack sites, in Arizona, USA. We use a soil moisture model (Hydrus-1D) and three years of continuous soil moisture measurements at two depths (0–10 cm and 0–30 cm) for 6 locations/site distributed across gradients of forest cover. Each soil moisture measurement location has a unique daily moisture input time series previously developed from local snow/rain observations and modeling. Compared to the seasonal snowpack site, the ephemeral site has wetter soils during winters due to frequent mid-winter melt events, leading to greater annual percolation. However, earlier snowmelt at the ephemeral snowpack site also prolongs the duration of root zone water stress. At both sites, dense forest cover is associated with less percolation and longer duration of soil drought, due to increased transpiration. These effects are amplified during an abnormally dry winter. This study examines two sites over three years and develops key steps towards using spatially distributed snowpack and soil moisture measurements to assess how changing climate and forest cover jointly regulate water availability for future ecosystems and downstream use.

Balancing economic benefits and environmental repercussions based on smart irrigation by regulating root zone water and salinity dynamics

As a critical index for irrigation scheduling, plant water deficit index (PWDI) is defined as the ratio of water deficit to water demand to reflect the extent of abiotic stresses such as water and salinity. Recently, smart irrigation scheduling, according to PWDI thresholds to maintain desirable or acceptable stress levels, has been suggested to maximize yields while minimizing negative environmental effects under non-saline conditions. To investigate and quantify the potential for PWDI-driven irrigation on agricultural production under conditions of salinity, a two-year experiment with six specific thresholds was conducted in Shawan of Xinjiang for drip-irrigated cotton under film mulch. Results indicated that, with increasing PWDI threshold, irrigation depth per event increased, while irrigation frequency and total volume decreased. Consequently, the soil water and salt environment deteriorated, resulting in less nutrient uptake, slower growth, and lower yield and net profit. With particularly high PWDI thresholds leading to serious stress conditions, fiber quality was also negatively affected. Within a designed range of PWDI thresholds between 0.39 and 0.62, an elliptic function characterized the processes of water application, yield and net profit (R2 ≥ 0.95), and water productivity could be described by a parabolic function (R2 = 0.77). These quantitative results were used to provide guidelines for smart irrigation scheduling under local conditions considering water management measures and market prices of cotton. For a reference market price of 7.5 CNY kg-1, a PWDI threshold of 0.49 was found to optimize economic benefits while maximizing water productivity. When prices of cotton are prohibitively low, a lower threshold should be considered to obtain an acceptable net profit. Otherwise, a higher threshold would be preferable to use water more efficiently. Further verification and improvement are necessary to deal with more complex scenarios, such as, considering crop sensitivity to water and salinity stresses at different growth stages and optimizing irrigation depth per event.

Optimization of Nitrogen Fertilizer Management in the Yellow River Irrigation Area Based on the Root Zone Water Quality Model

Strategic management of nitrogen fertilizers can not only mitigate agricultural nitrogen pollution but also significantly enhance crop yield and nitrogen use efficiency. This study was designed to determine the optimal nitrogen fertilizer management strategy for the Yellow River irrigation area. Leveraging two years of field data related to soil water nitrogen and summer maize growth indices, parameters for the Root Zone Water Quality Model 2 (RZWQM2) were calibrated and validated. Subsequently, various scenarios were generated to simulate the impacts of different nitrogen application rates and basal chasing ratios on summer maize yield, nitrogen agronomic efficiency, nitrogen physiological efficiency, and nitrogen apparent recovery rate. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was employed for a comprehensive evaluation. RZWQM2 can effectively simulate the dynamic changes in soil moisture and nitrogen in the Yellow River irrigation area, and the results indicated that the mean relative error (MRE) between the simulated and observed values varied from 5.77% to 14.09%, and 4.36% to 33.01%, while the root mean square error (RMSE) ranged from 0.016 to 0.037 cm3/cm3, and 0.111 to 1.995 mg/kg. The normalized root mean square error (NRMSE) varied between 6.20% to 14.42% and 5.24% to 17.84%, respectively. The results validate the model’s effectiveness in simulating summer maize yields and nitrogen metrics under varying nitrogen fertilizer management practices. A nitrogen application rate of 180–200 kg/hm2 (expressed in terms of pure nitrogen) in the Yellow River irrigation area could adequately meet the requirements for summer maize production. The recommended nitrogen fertilizer management strategy in the Yellow River irrigation area involves applying 200 kg/hm2 of nitrogen in a 1:2:1 ratio during the sowing, trumpeting, and anthesis stages.

Harvested winter rye energy cover crop: multiple benefits for North Central US

Cover crops (CCs) can reduce nitrogen (N) loss to subsurface drainage and can be reimagined as bioenergy crops for renewable natural gas production and carbon (C) benefits (fossil fuel substitution and C storage). Little information is available on the large-scale adoption of winter rye for these purposes. To investigate the impacts in the North Central US, we used the Root Zone Water Quality Model to simulate corn-soybean rotations with and without winter rye across 40 sites. The simulations were interpolated across a five-state area (IA, IL, IN, MN, and OH) with counties in the Mississippi River basin, which consists of ∼8 million ha with potential for rye CCs on artificially drained corn-soybean fields (more than 63 million ha total). Harvesting fertilized rye CCs before soybean planting in this area can reduce N loads to the Gulf of Mexico by 27% relative to no CCs, and provide 18 million Mg yr−1 of biomass-equivalent to 0.21 EJ yr−1 of biogas energy content or 3.5 times the 2022 US cellulosic biofuel production. Capturing the CO2 in biogas from digesting rye in the region and sequestering it in underground geologic reservoirs could mitigate 7.5 million Mg CO2 yr−1. Nine clusters of counties (hotspots) were identified as an example of implementing rye as an energy CC on an industrial scale where 400 Gg yr−1 of rye could be sourced within a 121 km radius. Hotspots consisted of roughly 20% of the region’s area and could provide ∼50% of both the N loss reduction and rye biomass. These results suggest that large-scale energy CC adoption would substantially contribute to the goals of reducing N loads to the Gulf of Mexico, increasing bioenergy production, and providing C benefits.

Optimizing relative root-zone water depletion thresholds to maximize yield and water productivity of winter wheat using AquaCrop

Determination of relative root-zone water depletion (RRWD) thresholds to trigger irrigation is crucial to create optimal irrigation schedules targeting maximum yield and/or water productivity with limited water supply for a crop. In this study, a numerical procedure to determine RRWD thresholds was developed through coupling AquaCrop software with genetic-simplex algorithms. Using a two-year field lysimetric experiment for winter wheat conducted in the North China Plain (NCP), AquaCrop adequately simulated canopy cover, final aboveground biomass, grain yield, seasonal evapotranspiration, and soil water storage, with the normalized root mean squared error (NRMSE) smaller than 15 % and determination coefficient (R2) larger than 0.84. The global optimum range of RRWD thresholds was preliminarily determined using the genetic algorithm, and subsequently final RRWD thresholds were optimized by fine tuning using the simplex algorithm. The RRWD threshold combinations (composed of the RRWD thresholds to trigger different sequential irrigation events) for varying number of irrigation events (i.e.1–4) were optimized based on 39 years of historical meteorological data, and the effects of climate change on the optimal crop yield (Ya, opt), water productivity (WPopt), and the combinations of optimized RRWD threshold (RRWDopt) were investigated. The results indicated that both Ya, opt and WPopt generally increased with time showing a tendency of gradually elevated annual CO2 concentration and seasonal average effective temperature. Irrespective of the number of irrigation events during the winter wheat growing season, the differences of RRWDopt for different combinations of irrigation sequence and event in the same kind of hydrological year were relatively small, with a coefficient of variation consistently less than 23 % and a mean of 8 %. When combinations of mean RRWDopt were applied into AquaCrop to trigger irrigation for winter wheat in various hydrological years, the simulated yield (Ya, sim) and water productivity (WPsim) under 1–4 irrigation events were found to be comparable to their respective optimums (Ya, opt and WPopt), with all the values of Ya, sim (WPsim) falling in the range of 92 %Ya, opt (90 %WPopt). Therefore, the mean RRWDopt should be helpful to formulate rational irrigation management strategies of winter wheat under changing climatic conditions in the NCP.

Revisiting the definition of field capacity as a functional parameter in a layered agronomic soil profile beneath irrigated maize

The soil water content at the condition of field capacity (θFC) is a key parameter in irrigation scheduling and has been suggested to be determined by running a synthetic drainage experiment until the flux rate (q) at the bottom of the soil profile achieves a predefined negligible value (qFC). We question the impact of qFC on the assessment of field capacity. Moreover, calculating θFC as the integral mean of the water content profile when q is equal to qFC is strictly valid only for uniform soil profiles. By contrast, this practice is ambiguous and biased for stratified soil profiles due to the soil water content discontinuity at the layer interfaces. In this study, the concept of field capacity was revisited and adapted to practical agronomic heuristics. By resorting to the assessment of root-zone water storage capacity (W), we envision field capacity as a functional hydraulic parameter derived from synthetic irrigation scheduling scenarios to minimize drought stress, drainage, and nitrate leachate below the root zone. A functional analysis was carried out on a 135-cm-thick layered soil profile beneath maize in eastern Nebraska. On-farm irrigation scheduling applications and agricultural practices were recorded for 20 years (2001–2020) at a daily time step. Hydrus-1D was calibrated and validated with direct measurements of the soil water retention curve and soil water content data, respectively, in each soil layer. A set of functional field capacity values was derived from 24 irrigation scheduling scenarios, and the optimal water storage capacity at field capacity (WFC) was approximately 50 cm (corresponding to about 80% saturation in the soil profile). An average irrigation amount of 217.5 mm distributed over 21 events was obtained by using optimal irrigation scheduling, which was initiated when the matric pressure head took on a value of −700 cm and the irrigation rate was set at 1.0 cm d−1. This irrigation practice ensured water storage at approximately the same level (ideally at WFC) by sustaining only evapotranspiration fluxes in the uppermost portion of the root zone and by limiting excessive drainage. This protocol can be transferred to other agricultural fields.

Contrasting ecosystem vegetation response in global drylands under drying and wetting conditions.

Increasing aridity is one major consequence of ongoing global climate change and is expected to cause widespread changes in key ecosystem attributes, functions, and dynamics. This is especially the case in naturally vulnerable ecosystems, such as drylands. While we have an overall understanding of past aridity trends, the linkage between temporal dynamics in aridity and dryland ecosystem responses remain largely unknown. Here, we examined recent trends in aridity over the past two decades within global drylands as a basis for exploring the response of ecosystem state variables associated with land and atmosphere processes (e.g., vegetation cover, vegetation functioning, soil water availability, land cover, burned area, and vapor-pressure deficit) to these trends. We identified five clusters, characterizing spatiotemporal patterns in aridity between 2000 and 2020. Overall, we observe that 44.5% of all areas are getting dryer, 31.6% getting wetter, and 23.8% have no trends in aridity. Our results show strongest correlations between trends in ecosystem state variables and aridity in clusters with increasing aridity, which matches expectations of systemic acclimatization of the ecosystem to a reduction in water availability/water stress. Trends in vegetation (expressed by leaf area index [LAI]) are affected differently by potential driving factors (e.g., environmental, and climatic factors, soil properties, and population density) in areas experiencing water-related stress as compared to areas not exposed to water-related stress. Canopy height for example, has a positive impact on trends in LAI when the system is stressed but does not impact the trends in non-stressed systems. Conversely, opposite relationships were found for soil parameters such as root-zone water storage capacity and organic carbon density. How potential driving factors impact dryland vegetation differently depending on water-related stress (or no stress)is important, for example within management strategies to maintain and restore dryland vegetation.

Review on Drip Irrigation: Impact on Crop Yield, Quality, and Water Productivity in China

The scarcity of freshwater resources is a global concern that is exacerbated by an increasing global population and climate change induced by global warming. To address this issue, the largest water-consuming sector has taken a series of measures termed as drip irrigation schemes. The primary purposes of drip irrigation are to reduce water scarcity near the root zone, reduce evaporation, and decrease water use. The application scope of drip irrigation is getting wider and wider, with the number of papers related to drip irrigation increasing year by year from 1990 to 2022. This study reviews crops planted in China that had been irrigated by drip irrigation equipment. The effects of drip irrigation technology on crop growth, physiology, quality, yield, and water use efficiency are summarized. This paper also provides an overview of drip irrigation technology on crop root development and nitrogen uptake. Through a global meta-analysis, it is found that in the case of water shortage, drip irrigation can save water and ensure crop yield compared to flooding irrigation, border irrigation, furrow irrigation, sprinkler irrigation, and micro-sprinkler irrigation. When the drip irrigation amount is more (100–120%), drip irrigation significantly increases crop yields by 28.92%, 14.55%, 8.03%, 2.32%, and 5.17% relative to flooding irrigation, border irrigation, furrow irrigation, sprinkler irrigation, and micro-sprinkler irrigation, respectively. When water resources are sufficient, increasing the amount of drip irrigation also improves crop yield. Moreover, the researchers found that drip irrigation can reduce fertilizer leaching and soil salinity. However, more studies should be conducted in the future to enrich the research on drip irrigation. In conclusion, drip irrigation technology is effective in improving crop growth, water use efficiency, and reducing water scarcity while decreasing fertilizer leaching and soil salinity, making it an ideal solution to the issue of freshwater resource scarcity globally.

Thickness of a Compost Layer on the Distribution of Water and Nutrients in a Surface-Drip-Irrigated Sandy Soil Column

The management of crop production in a sandy soil “culture” is difficult, mainly due to its low soil-water-holding capacity, organic matter and poor fertilizer efficiency. Options to increase soil water and nutrient retention for these soils include the addition of surface mulch covers, amendment with biochar and the use of layers of a mixture of charcoal and compost material. Our objective was to measure the distribution of water and nutrients for layers of control 1 (CK1), control 2 (CK2) and compost material of different thicknesses (0.02, 0.05 and 0.10 m) buried 0.01 m from the surface in a column (0.2 m radius, 0.5 m height) filled with sand. The experiment was conducted in a greenhouse located at the Agricultural Science Training Base of Ningxia University, China. There were three replicates per treatment and one soil column per replicate. The soil columns were watered with 2 L via a surface drip emitter and 45 days later, soil samples were obtained in 0.01 m increments across the diameter and depth of 0.4 m, with a total of 12 samples per column. In each sample, we measured soil water, pH, electrical conductivity, ammonium and nitrate nitrogen and available P and K. The results showed that the distribution of water content and nutrient contents were centered on the dripper and diffused to its surroundings. Notably, the horizontal diffusion distance was smaller than that of the vertical direction. In the vertical direction, compared with control 1, adding compost changed the spatial distribution of WC and nutrients and had a greater impact on available potassium (AK) than on inorganic nitrogen (IN) and available phosphorus (AP). Compared with control 1, the composting treatment decreased the content of water in the 0–10 cm surface soil, reduced the electrical conductivity (EC) and nitrate nitrogen (NO3-N), C5 and C10 increased the available potassium. Moreover, composting treatments increased the electrical conductivity, available phosphorus, available potassium and nitrate nitrogen of the 10–30 cm substrate by 61–384%, 10–240%, 11–45% and 133–929%, respectively, when compared with control 1.The nutrients increased as the thickness of the compost interlayer increased. A principal component analysis (PCA) of the C5 and C10 treatments significantly distinguished them from control 1. A linear regression fitting analysis showed that the inorganic nitrogen, available potassium and total nutrients positively correlated with the water content and electrical conductivity of the sand. The 5 cm and 10 cm composting interlayers had a high water content and ability to conserve fertilizer for sand culture, but C10 caused an excessive accumulation of nutrients. Thus, it was concluded that a composting interlayer that was less than 5 cm reduced the base fertilizer input by 24–84%. All these results suggest that applying a composting interlayer of 5 cm could retain more suitable root zone water and fertilizer for the next crop season and provide technological support to reduce fertilizer inputs.

Water Age Dynamics in Plant Transpiration: The Effects of Climate Patterns and Rooting Depth

AbstractWater ages in plant transpiration reveal important processes of water dynamics in soil‐plant‐atmosphere continuum, which is regulated by water variability and availability in both precipitation inputs and root zone. However, the impacts of climate patterns and rooting depth on water age dynamics in transpiration are inadequately investigated. In this study, variations in root‐zone water replenishment are estimated based on stable isotope compositions of precipitation and plant xylem water, and a piecewise linear mixing water age model is employed to quantify water ages in plant transpiration under five different climates. The results show that water ages in transpiration are very dynamic in all climates with a range between 1 and 229 days. Water replenishments in the root‐zone reveal whether and how much precipitation enters the root zone. Climate patterns control median (mean) water age in plant transpiration but modified by rooting depth. In wet climates, plants mainly rely on water source that originates from precipitation in the current month (accounting for about 60% on average of their water sources), while plants in dry climates largely rely on water source that originates from precipitation fallen on previous months/seasons. These indicate that climate has profound impacts on plant water source by regulating precipitation inputs, root zone water storage and residence time, and evapotranspiration. Despite the limitations of this study, our study provides an alternative way to reveal the precipitation partitioning in root‐zone and seasonal changes in plant water use of precipitation, which highlights different vegetation responses to water variability between climate types.

Variation in Hydric Response of Two Industrial Hemp Varieties (Cannabis sativa) to Induced Water Stress

Information on industrial hemp (Cannabis sativa) water use and water stress is sparse. We studied water stress impact in two essential-oil hemp cultivars (‘Wife’ and ‘Cherry’) prompted by anecdotal differences in growth and water use. In a greenhouse setting, we measured water relations, water use, growth, and essential oil (CBD-cannabidiol and THC-delta-9 tetrahydrocannabinol) concentrations. Water stress did not significantly affect THC and CBD concentrations, but both cultivars responded to water stress by reducing transpiration through notably different mechanisms. ‘Cherry’ had more anisohydric behavior, maintaining high stomatal conductance (Gs) and more negative leaf water potential until root zone water depletion triggered partial afternoon stomatal closure to moderate stress, resulting in lower flower and CBD yield. By contrast, water-stressed ‘Wife’ rapidly defoliated half its leaf area in balance with less applied water and so maintained high Gs and flower yield on par with well-watered plants, suggesting potential for deficit irrigation to conserve water and reduce post-harvest vegetation management. Differences in water use translated to provisionally suggested crop coefficients of 1 for ‘Cherry’ and 1.3–1.5 for ‘Wife’, but further research is needed. Because hemp is genetically diverse, and cultivar naming conventions are currently lax, further germplasm screening and research are needed to determine the extent to which either conservative ‘Cherry’ or the water-stress defoliation response of ‘Wife’ is found in the larger population of hemp cultivars.

Modeling seasonal vegetation phenology from hydroclimatic drivers for contrasting plant functional groups within drylands of the Southwestern USA

In dryland ecosystems, vegetation within different plant functional groups exhibits distinct seasonal phenologies that are affected by the prevailing hydroclimatic forcing. The seasonal variability of precipitation, atmospheric evaporative demand, and streamflow influences root-zone water availability to plants in water-limited environments. Increasing interannual variations in climate forcing of the local water balance and uncertainty regarding climate change projections have raised the potential for phenological shifts and changes to vegetation dynamics. This poses significant risks to plant functional types across large areas, especially in drylands and within riparian ecosystems. Due to the complex interactions between climate, water availability, and seasonal plant water use, the timing and amplitude of phenological responses to specific hydroclimate forcing cannot be determined a priori, thus limiting efforts to dynamically predict vegetation greenness under future climate change. Here, we analyze two decades (1994–2021) of remote sensing data (soil adjusted vegetation index (SAVI)) as well as contemporaneous hydroclimate data (precipitation, potential evapotranspiration, depth to groundwater, and air temperature), to identify and quantify the key hydroclimatic controls on the timing and amplitude of seasonal greenness. We focus on key phenological events across four different plant functional groups occupying distinct locations and rooting depths in dryland SE Arizona: semi-arid grasses and shrubs, xeric riparian terrace and hydric riparian floodplain trees. We find that key phenological events such as spring and summer greenness peaks in grass and shrubs are strongly driven by contributions from antecedent spring and monsoonal precipitation, respectively. Meanwhile seasonal canopy greenness in floodplain and terrace vegetation showed strong response to groundwater depth as well as antecedent available precipitation (aaP = P − PET) throughout reaches of perennial and intermediate streamflow permanence. The timings of spring green-up and autumn senescence were driven by seasonal changes in air temperature for all plant functional groups. Based on these findings, we develop and test a simple, empirical phenology model, that predicts the timing and amplitude of greenness based on hydroclimate forcing. We demonstrate the feasibility of the model by exploring simple, plausible climate change scenarios, which may inform our understanding of phenological shifts in dryland plant communities and may ultimately improve our predictive capability of investigating and predicting climate-phenology interactions in the future.

Measured and simulated effects of residue removal and amelioration practices in no-till irrigated corn (Zea mays L.)

Reducing nitrous oxide (N2O) emissions to the atmosphere is expected to provide substantial climate mitigation benefits. Herein, we measured soil N2O emission and crop yield responses in a nine-year, no-till continuous corn system under contrasting management practices including irrigation (full; deficit), corn stover retention (100 % retention; maximum mechanical removal), and cover crop use (winter cereal rye, Secale cereale L.; no cover crop). Field-measured data were used to construct a structural equation model (SEMobs) to explore the causal effects of management on soil N2O emissions. We also used the Root Zone Water Quality Model 2 (RZWQM2) to simulate management effects on soil N2O emission. Structural equation modeling was used for the field-measured data (SEMobs) and the RZWQM2 simulated data (SEMsim) to quantify management relationships with soil and determine whether relationships observed in field data were captured by RZWQM2 simulations. Our experimental field results showed that stover removal decreased annual N2O emissions compared to stover retention, only for deficit irrigated soil (2.83 ± 1.31 vs. 4.49 ± 3.65 kg N ha−1 y−1) and that deficit irrigation decreased annual N2O emissions compared to full irrigation, only for soil with cover crops (3.31 ± 3.19 vs. 4.11 ± 3.80 kg N ha−1 y−1). The SEMobs and SEMsim results showed similar direction and magnitude of relationships between daily soil N2O emissions and various management and environmental drivers. Our study improved the mechanistic understanding for the effects of agricultural management on soil N2O emissions and can help reduce N2O emissions from agricultural systems.