Soil–plant–water relations and water footprint of cover crop–based no‐till cotton and sorghum systems in a humid region

The price of nitrogen (N) fertilizer has increased to the point where it may be cost effective to grow winter legume cover crops as a sole source of nitrogen for a subsequent cotton crop in North Carolina. Establishing these cover crops is critical to the success of this strategy. In order to optimize legume cover crop establishment, cotton producers may have to overseed legumes into cotton that has or will be sprayed with cotton harvest aids, which may interfere with legume germination and growth. A greenhouse experiment was conducted to determine the effects of commonly used cotton harvest aids on legume germination and growth. This was followed by a field study to determine the optimum time to overseed legume cover crops in cotton, to determine the effects of cotton defoliants on legume establishment in the field, and to determine the effects of cover crop species and overseeding timing on cotton growth and yield in a field in which N was not depleted. Cotton defoliants containing thidiazuron plus diuron reduced greenhouse legume germination and growth more than any other cotton harvest aid tested; however, field studies indicate that cover crop germination and cover crop dry weight are not affected by thidiazuron plus diuron. Crimson clover (Trifolium incarnatum L.) and Austrian winter pea (Pisum sativum L.) positively affected cotton yield equally. However, timing of cover crop overseeding played an important role in cover crop germination, accumulated biomass, and lint yield. We observed that overseeding legumes 14 days prior to defoliation resulted in the highest cover crop dry weight and cotton yield.

Petroleum prices impact cotton nitrogen (N) fertilization cost. A field study was conducted from 2005 to 2007 to assess the interactions of cover crop (none, Austrian winter pea (Pisum sativumspp.arvense) or hairy vetch (Vicia villosaRoth)) and N fertilization (0, 67 or 134 kg N/ha applied at planting) on N availability and cotton yield under reduced-tillage management. Nitrogen content in desiccated residues averaged 49, 220, and 183 kg N/ha, in no cover crop, Austrian winter pea, and hairy vetch, respectively. Seventy percent of N in the above ground cover crop was derived from biological N fixation. In 2005, cover crops decreased cotton yield, while fertilizer N had no effect. In 2006, cover crops did not affect yield, but yield was positively correlated with N rate. In 2007, in no N plots, cotton yields were 65% higher in cover crops than in no cover crop. However, yield from N fertilized cover crop plots were similar to N fertilized no cover plots. These results indicate that leguminous cover crops can provide over 150 kg N/ha, but this N may not be as effective as fertilizer N for lack of synchronization between cotton N requirements and N release from residues.

Excessive tillage reduces soil water storage and increases surface runoff. Cover crops can modify the effect of tillage on soil water dynamics, but limited information is available for the Mississippi River Alluvial Basin. This study was conducted to determine whether soil–water dynamics could be manipulated through conservation production systems affecting surface residue management. Effects of tillage (conventional tillage [CT] vs. no‐tillage [NT]) and cover cropping (no cover crop and Austrian pea [ Pisum sativum L.] cover crop [CC]) on soil water balance during the CC season in sorghum ( Sorghum bicolor L.) and cotton ( Gossypium hirsutum L.) crops were modeled using the root zone water quality model for a site near Stoneville, MS, on “Commerce” silty‐loam soil. Capacitance sensors measured soil volumetric water content to 120 cm during CC growth in 2019 and 2020. Field calibration of sensors reduced root mean square error from 0.05 to 0.03 m 3 m −3 . Pooled across years, NT increased volumetric water content in the 0–40 and 40–120 soil layers by 8.5% and 6.8%, respectively, compared to CT. Regardless of the CC treatment and cropping system, NT reduced surface runoff by 24.5% over its conventional counterpart, while soil water storage increased from 2.35 to 5.23 cm within the 1.2‐m profile, resulting in a 17% increase in consumptive use of water (evapotranspiration). CC treatments did not impact soil water storage and consumptive water use. The results demonstrate that NT systems can affect water dynamics by increasing infiltration and soil water storage in the humid subtropical region of the United States.

A water footprint assessment of a pair of jeans: the influence of agricultural policies on the sustainability of consumer products

Simulated effects of cover crops with no-tillage on soil and crop productivity in rainfed semi-arid cotton production systems

Cover crops aid in reducing precipitation runoff, soil erosion, and N losses in highly sloped, mountainous regions. Corn (Zea mays L.) producers in states with late spring warmup and early winters have limited success when planting cover crops following harvest. Studies were conducted from 1992 through 1995 in southern and northern West Virginia to evaluate the groundcover ability of several late‐planted cover crops and their dry weight response to fall N application. In most years, vetch (Viciu villosu Roth cv. Common) and Austrian winter pea (Pisum sutivum var. arvense L. Poir cv. Austrian winter) produced the least groundcover and dry matter of all species evaluated. Rye (Secule cereule L. ‘Abruzzi’ and ‘Wheeler’) was the most reliable and winter‐hardy cover crop, regardless of location. Initial soil nitrate‐N concentrations at planting averaged 12 ppm in soils with continuous corn‐production and no history of manure application (southern experiment) and 40 ppm in soils with similar rotation and a history of manure application (northern experiment). Nitrogen application did not consistently increase the likelihood of cover crop survival, but increased dry matter for some cover crops on soils with low initial N levels. At the southern location, Abruzzi rye planted alone and common rye in combination with common vetch responded positively to additional N application in 3 out of 3 and 2 out of 3 yr, respectively. ‘Pastar’ rye (1992–1993), common rye (1993–1994), wheat (Triticum aestivum L.) (1994–1995), and barley (Hordeum vulgure L. ‘Barsoy’) (1994–1995) also responded positively to N application at the southern location. Cover crops did not respond to additional N application at the northern location on soils high in initial N fertility. Corn producers in mountainous, highly sloped land should consider methods for planting cover crops earlier to ensure plant survival and to protect soil during the winter.Research QuestionCover crops are used in most of the corn‐producing areas of the USA to improve soil conditions and protect the soil during the winter. Producers in highly sloped, mountainous areas with short fall seasons and severe winters have variable success when establishing cover crops following corn harvest.The objectives of this study were to evaluate percentage ground coverage of cover crops planted late following corn harvest and to evaluate the effectiveness of late‐season N application for extending the cover crops planting window.Literature SummaryCover crops planted in the early fall in mountainous regions can provide adequate cover to protect the soil during the winter. Cereal cover crops have been shown to respond to N application. Studies have not been conducted to determine whether N application can effectively extend the window of opportunity to allow successful late planting of cover crops.Study DescriptionTwo experiments (groundcover potential by cover crops and cover crop response to N rates) were conducted in both the southern and northern regions in West Virginia each year from 1992 through 1995. Southern experiments were conducted on a corn producer's field located near Lewisburg, and northern experiments were conducted on a corn producer's field located near Bruceton Mills in 1992–1993 and 1994–1995, and on the West Virginia University Animal Science farm located near Morgantown in 1993–1994. Nine cover crop cultivars and mixtures and four rates of N were evaluated each year.Cover crops: rye, triticale, wheat, barley, common vetch, barley plus vetch, and Austrian winter pea plus triticale.N treatments: 0, 20, 40, and 60 lb/acre N equivalent from ammonium nitrate.Experimental design: randomized complete block (RCB) for the groundcover potential experiment and RCB in a split plot arrangement for the N‐response experiment.Applied QuestionWhat cover crops provide the most consistent groundcover when planted late?The potential for successful late‐season cover crop establishment following corn harvest in mountainous regions is highest with cereal cover crops. Late‐sown legumes have little chance for survival. Ryes survived better and were more reliable as cover crops regardless of the N concentration in the soil. Barley and triticale generally provided good groundcover and yielded well on soils with high initial N concentration. Mixtures of cereal cover crops with vetch did not increase cover or dry matter over the cereal planted alone at a higher rate.Can N applied in the fall at planting increase the dry matter produced the following spring, thus increasing groundcover and extending the planting window?Nitrogen application at the time of planting did not consistently increase dry matter production except for ‘Abruzzi’ rye planted alone (3 out of 3 yr) and common rye planted with and without vetch (2 out of 3 yr) on soils with low initial N (nitrate) concentration in southern West Virginia. Nitrogen application at planting cannot consistently overcome the disadvantages resulting from late‐planting cover crops in harsh winter environments.

工业水足迹评价与应用

A spatially explicit life cycle water analysis framework is proposed, in which a standardized water footprint methodology is coupled with hydrologic modeling to assess blue water, green water (rainfall), and agricultural grey water discharge in the production of biofuel feedstock at county‐level resolution. Grey water is simulated via SWAT, a watershed model. Evapotranspiration (ET) estimates generated with the Penman‐Monteith equation and crop parameters were verified by using remote sensing results, a satellite‐imagery‐derived data set, and other field measurements. Crop irrigation survey data are used to corroborate the estimate of irrigation ET. An application of the concept is presented in a case study for corn‐stover‐based ethanol grown in Iowa (United States) within the Upper Mississippi River basin. Results show vast spatial variations in the water footprint of stover ethanol from county to county. Producing 1 L of ethanol from corn stover growing in the Iowa counties studied requires from 4.6 to 13.1 L of blue water (with an average of 5.4 L), a majority (86%) of which is consumed in the biorefinery. The county‐level green water (rainfall) footprint ranges from 760 to 1000 L L−1. The grey water footprint varies considerably, ranging from 44 to 1579 L, a 35‐fold difference, with a county average of 518 L. This framework can be a useful tool for watershed‐ or county‐level biofuel sustainability metric analysis to address the heterogeneity of the water footprint for biofuels.

Keywords: water footprint; cotton; spatial-temporal dynamics; climate change; xinjiangIntroduction: Cotton stands as a cash crop with high water consumption, yielding necessary benefits for human beings. However, more that 90% of cotton productivity in China are cultivated in Xinjiang, a water scare region, challenged the sustainability of agricultural development. Efforts on supply and demand of water resource for cotton in such region is critical for sustainable water management, but remains unresolved.Material and Methods: Taking cotton cultivated in Xinjiang from 2001 to 2020 over counties as a case, we employed water footprint concept that based on virtual water to depict the spatial-temporal trend of water footprint, spatial clustering patterns of water footprint over county. We further identified the contributions of climate change, planting area, and inputs of fertilizer application to the changes of water footprint over regions.Results: From 2001 to 2020, the average annual water footprint of cotton production in Xinjiang was 9.75 Gm³, with blue, green, and grey water footprints contributes 6.78 Gm³, 1.01 Gm³, and 1.96 Gm³, respectively. The overall water footprint exhibited an initial increase followed by a subsequent decrease, reaching its peak in 2014. Notably, the distribution of water footprints associated with cotton production varied across the study regions, with the average annual water footprints for cotton production in Southern Xinjiang and Northern Xinjiang recorded at 6.91 Gm³ and 2.84 Gm³, respectively. Over the study period, primary concentrations of the total water footprint of cotton were observed in the southern Tianshan Mountains, with no significant shifts in spatial aggregation at the county scale. The expansion of cotton cultivation areas and excessive fertilizer applications emerged as the main factors influencing the long-term dynamics of the cotton water footprint contributing 8.30 Gm³ and 1.26 Gm³ respectively, to the overall water footprint variation. Furthermore, climate change led to a reduction of 0.85 Gm³ in the water footprint of cotton production. The water footprint per unit yield of cotton within the study area exhibited a declining trajectory over the past two decades, with the average annual water footprint per unit yield calculated at 4845.91 m³/t.Conclusions: the expansion of the planting area emerges as the primary driving force behind the dynamic shifts in the water footprint of cotton production in Xinjiang. Despite the overall increase in total cotton production, there is a notable downward trend in the water footprint per unit yield of cotton. This study provides a theoretical basis for balancing the sustainability of water use and the optimization of spatial patterns of cotton.

Organic no-till systems continue to draw interest from organic producers across the upper Midwest in the United States. Fall-planted cover crops, terminated in the spring through the use of a roller-crimper or a mower, are a key component of these systems. In this study, five different cover crops (hairy vetch, Austrian winter peas, winter rye, winter barley, and winter triticale) were planted in the fall and terminated in the spring in preparation for no-till organic row crop production. This study compared the cover crops through measurements of: a) the amount of biomass produced by the cover crops before termination; b) the weed suppression potential of the cover crops terminated with either a roller-crimper or sickle-bar mower; and c) volumetric soil water content throughout the row crop production season. Biomass production of each of the cover crops differed significantly by variety and by year, ranging from 3.67 to 14.56 Mg DM ha−1. Significant differences in weed densities and weed biomass were also found, with almost complete elimination of weed establishment in the rye treatment in 2011. Roll-crimping and sickle-bar mowing treatments demonstrated similar weed suppression and soil moisture from May through October during 2010 and 2011.

Cover crops can reportedly improve soil fertility, suppress weed growth and pest pressure, and contribute to cotton (Gossypium hirsutum L.) yield improvements. To systematically evaluate cover crop effects on cotton yield and weed suppression, we conducted a random‐effects meta‐analysis investigating 10 moderating variables in 104 articles, yielding 1117 independent studies over 48 yr. Globally, cover crops increased cottonseed and lint yield by 6 and 5%, respectively, while decreasing weed biomass by 20%. Overall, leguminous cover crops increased seed cotton yield by 17 to 43% (Vicia spp. and Pisum spp., respectively). Monocots, nonlegume dicots, and legumes were effective at suppressing weed growth (21, 52, and 10%, respectively). Incorporation of cover crops by tillage (rather than chemical burn down) resulted in lint (14%) and seed (42%) yield increases. Cover crops increased cotton yields markedly on loamy soils, whereas there were lesser increases for other textures (p > 0.05). Greater efficacy of cover crops at controlling weeds was proportionate to soil silt content, which was inversely related to sand content. In addition, cover crops were effective at controlling multiple types of weed species; however, weed species with shorter maximum heights were most suppressed by cover crops. Overall, cover crops had a positive effect on cotton yield and weed suppression. Their effectiveness, however, can vary depending on soil texture, management strategy, and cover crop or weed genera. These results are useful in developing recommendations for suppressing weed growth and improving yield via cover crop integration in cotton cropping systems per geographic region and soil texture.

Long-term effect of cover crop on rainwater balance components and use efficiency in the no-tilled and rainfed corn and soybean rotation system

Cover crops in organic cotton systems can offset the carbon loss typically observed in conventional systems. However, their effects on greenhouse gas (GHG) emissions and soil microclimate are poorly understood. Our objective was to investigate the effects of cover crops on soil carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) emissions and soil moisture and temperature dynamics in organic cotton systems. To achieve this, we used static chamber techniques with soil sensors in a field study near College Station, TX, from 2020 to 2022. Cover crops tested were oat (Avena sativa L.), Austrian winter pea (Pisum sativum L.) (AWP), turnip (Brassica rapa subsp. rapa), a mixture of all three, and a fallow control. In the first year of organic transition (2020), mixed species treatment enhanced CO2 emission by 39.6%, 34.4%, and 40% than AWP, turnip, and control, respectively. Compared to the control, N2O emissions were lower in AWP, turnip, and oat treatments by 77%, 57.2%, and 53% in 2020. Weed pressure and drought in 2021 and 2022 neutralized cover crops’ effect on soil GHG emissions. Soils generally acted as net CH4 sinks, but the uptake did not differ among the treatments. Cover crops depleted soil moisture during their growing period, but surface residues helped retain more moisture during the cotton season. Compared to fallow, mixed species and AWP were observed to reduce soil temperature fluctuations. Therefore, in transitioning, organic systems effects of cover crops on soil GHG emissions can vary depending on weather, weed management, and the cover crop types.

<p>Nepal is an agrarian country and almost one-third of Gross Domestic Product (GDP) is dependent on agricultural sector. Koshi river basin is the largest basin in the country and serves large share on agricultural production. Like another country, Nepalese agriculture holds largest water use in agriculture. In this context, it is necessary to reduce water use pressure. In this study, water footprint of different crop (rice, maize, wheat, millet, sugarcane, potato and barley) have been estimated for the year 2005 -2014 to get the average water footprint of crop production during study period. CROPWAT model, developed by Food and Agriculture Organization (FAO 2010b).</p><p>For the computation of the green and blue water footprints, estimated values of ET (the output of CROPWAT model) and yield (derived from statistical data) are utilised. Blue and green water footprint are computed for different districts (16 districts within KRB) / for KRB in different years (10 years from 2005 to 2014) and crops (considered 7 local crops). The water footprint of crops production for any district or basin represents the average of WF production of seven crops in the respective district or basin.</p><p>The study provides a picture of green and blue water use in crop production in the field and reduction in the water footprint of crop production by selecting suitable crops at different places in the field. The Crop, that has lower water footprint, can be intensified at that location and the crops, having higher water footprint, can be discontinued for production or measure for water saving technique needs to be implemented reducing evapotranspiration. The water footprint of agriculture crop production can be reduced by increasing the yield of the crops. Some measures like use of an improved variety of seed, fertilizer, mechanized farming and soil moisture conservation technology may also be used to increase the crop yields.</p><p>The crop harvested areas include both rainfed as well as irrigated land. Agricultural land occupies 22% of the study area, out of which 94% areas are rainfed whereas remaining 6% areas are under irrigation. The study shows 98% of total water use in crop production is due to green water use (received from rainfall) and remaining 2 % is due to blue water use received from irrigation (surface and ground water as source). Potato has 22% blue water proportion and contributes 85% share to the total blue water use in the basin. Maize and rice together hold 77% share of total water use in crops production. The average annual water footprint of crop production in KRB is 1248 cubic meter/ton having the variation of 9% during the period of 2005-2014. Sunsari, Dhankuta districts have lower water footprint of crop production. The coefficient of variation of water footprint of millet crop production is lower as compared to those of other crops considered for study whereas sugarcane has a higher variation of water footprint for its production.</p>

Abstract. Meeting growing food demands while simultaneously shrinking the water footprint (WF) of agricultural production is one of the greatest societal challenges. Benchmarks for the WF of crop production can serve as a reference and be helpful in setting WF reduction targets. The consumptive WF of crops, the consumption of rainwater stored in the soil (green WF), and the consumption of irrigation water (blue WF) over the crop growing period varies spatially and temporally depending on environmental factors like climate and soil. The study explores which environmental factors should be distinguished when determining benchmark levels for the consumptive WF of crops. Hereto we determine benchmark levels for the consumptive WF of winter wheat production in China for all separate years in the period 1961–2008, for rain-fed vs. irrigated croplands, for wet vs. dry years, for warm vs. cold years, for four different soil classes, and for two different climate zones. We simulate consumptive WFs of winter wheat production with the crop water productivity model AquaCrop at a 5 by 5 arcmin resolution, accounting for water stress only. The results show that (i) benchmark levels determined for individual years for the country as a whole remain within a range of ±20 % around long-term mean levels over 1961–2008, (ii) the WF benchmarks for irrigated winter wheat are 8–10 % larger than those for rain-fed winter wheat, (iii) WF benchmarks for wet years are 1–3 % smaller than for dry years, (iv) WF benchmarks for warm years are 7–8 % smaller than for cold years, (v) WF benchmarks differ by about 10–12 % across different soil texture classes, and (vi) WF benchmarks for the humid zone are 26–31 % smaller than for the arid zone, which has relatively higher reference evapotranspiration in general and lower yields in rain-fed fields. We conclude that when determining benchmark levels for the consumptive WF of a crop, it is useful to primarily distinguish between different climate zones. If actual consumptive WFs of winter wheat throughout China were reduced to the benchmark levels set by the best 25 % of Chinese winter wheat production (1224 m3 t−1 for arid areas and 841 m3 t−1 for humid areas), the water saving in an average year would be 53 % of the current water consumption at winter wheat fields in China. The majority of the yield increase and associated improvement in water productivity can be achieved in southern China.