Grain-filling strategies of wheat of contrasting grain sizes under various planting patterns and irrigation levels

In a study comparing grain filling and yield in a large-and a small-grain-size wheat cultivar under two planting patterns and two irrigation regimes,plastic-covered ridge and furrow planting with sprinkler irrigation increased grain filling and yield in both cultivars.The largest contributors to grain yield were an extended active grain-filling period in Shuangda 1 and an increased mean grain-filling rate in XN538.

北方旱区保护性耕作对农田土壤水分的影响

土壤水分是中国北方旱区农业生产的主要限制因子,研究保护性耕作技术体系下土壤水分的动态变化,明确不同耕作模式下的水分平衡规律,对于选择适宜的保护性耕作技术,提高北方旱区土壤水分的利用效率具有重要的指导意义。该文在2a田间试验的基础上采用DSSAT模型对4个不同保护性耕作处理的土壤体积含水量、水分平衡以及水分利用效率进行了模拟和检验。结果表明干旱年份保护性耕作处理土壤体积含水量较传统耕作高,RMSE误差在0.025～0.063;干旱年份传统耕作土壤储水量减少最多,为144.6mm,降水较多年份减少也最多,为46.1mm;干旱年份水分利用效率1.52～1.78kg/m3,免耕覆盖水分利用效率最高,降水较多年份水分利用效率1.70～1.71kg/m3,各处理间差异并不显著。研究结果为保护性耕作技术对农田土壤水分的影响研究提供了理论依据。

DSSAT模型对豫西冬小麦保护性耕作效应模拟效果验证

简要介绍了美国乔治亚大学组织开发的DSSATV4.5模型,并利用洛阳市孟津县2005-2006年冬小麦田间试验结果对模型的模拟结果进行验证及其适用性分析。通过对冬小麦叶面积指数、产量和农田土壤水分、水分利用效率的模拟与实测结果的对比分析,认为DSSAT模型的模拟效果较好。分析结果表明：模型对叶面积指数的模拟误差RMSE在0.034-0.076之间;模拟各处理的产量与水分利用效率也与实测值的关系基本一致;对各处理土壤体积含水量的RMSE误差在0.051-0.151之间。研究结果认为DSSAT模型在豫西应用的适宜性较好,可为该地区研究保护性耕作对冬小麦生长及土壤水分的影响提供理论支持。

Scale Effects of STATSGO and SSURGO on Flow and Water Quality Predictions

Soil information is one of the crucial inputs needed to assess the impacts of existing and alternative agricultural management practices on water quality. Therefore, it is important to understand the effects of spatial scale at which soil databases are developed on water quality evaluations. In the United States, STATSGO (State Soils Geographic) and SSURGO (Soil Survey Geographic) are the most commonly available soil databases. The purpose of this paper was to quantify the effect of scale by employing STATSGO (1:250,000) and SSURGO (1:24,000) soil databases in predicting and comparing flow, sediment, nitrate and phosphorus losses for High Island Creek. This watershed is predominately agricultural and located in south-central Minnesota. The ADAPT (Agricultural Drainage and Pesticide Transport), model was calibrated for flow, sediment, nitrate and phosphorus losses over two years (2001-2002) using STATSGO and SSURGO soil databases. Then the calibrated model was used to evaluate alternative tillage and fertilizer management practices such as adoption of conservation tillage, and rate, timing and method of N- and P-fertilizer applications. Statistical comparison of calibration results with observed data indicated excellent agreement for both soil databases (STATSGO with r2 of 0.95, 0.97, 0.77 and 0.92 and SSURGO with r2 of 0.90, 0.97, 0.82 and 0.99 for flow, sediment, nitrate and phosphorus losses, respectively). However, STATSGO based predictions of annual nitrate-N losses were consistently greater than those with SSURGO database and vice-versa for predicted annual phosphorus losses for the alternative management practice that were evaluated.

Heat units-based potential yield assessment for cotton production in Uzbekistan

Cotton yields in Uzbekistan are significantly lower than those in similar agro-climatic regions,requiring the estimation of crop potential and baseline yield to track progress of production enhancement efforts.The current study estimated potential cotton development and baseline yield(maximum given no production constraints)using total heat units(THU)and potential cotton yield(PCY),respectively.Calculations were based on heat units(HU)for a 30-year(1984-2013)period.Long-term average THU and PCY,as well as PCY at three different exceedance probabilities(p=0.99,p=0.80,and p=0.75),were calculated for 21 selected weather stations across cotton-growing areas of Uzbekistan.After confirmation that the current planting date(April 15)is optimal,a comparison of THU with the accepted cotton production cutoff threshold(1444°C)suggested that areas with lower elevations and latitudes are more appropriate for cotton production.Yield gap analysis(relative difference between long-term average PCY and actual yields)confirmed that Uzbekistan cotton production is below potential,while the spatial distribution of yield gaps outlined where efforts should be targeted.Areas near the stations of Nukus,Kungrad,Chimbay,and Syrdarya should be further investigated as benefit/cost ratio is highest in these areas.A comparison between state-set yield targets and PCY values,taking into account climatic variability,suggested that all areas except Jaslyk,Nurata,and Samarkand have safe,appropriate targets.These results present a starting-point to aid in strategic actions for Uzbekistan cotton production improvement.

Explaining farmers’reluctance to adopt recommendations for sustainable ecosystem management

Introduction:The lower Syr Darya River Basin is an integral part of the Aral Sea Basin that is shared by four riparian countries.In Kazakhstan,the water is mainly used for agricultural purposes.However,the poor quality and insufficient quantity of water and the overall degradation of natural resources due to unsustainable management practices threaten the profitability of the sector.The situation is even worse for downstream users.Three alternative scenarios for sustainable water and land management were developed using the RIOS and SWAT models as decision support tools.The scenario that offered the highest water and land productivity was presented to farmers to assess their willingness to forgo their current practices and adopt proposed management practices.We introduce willingness to forego(WTF)—a qualitative approach and a variant of the concept of opportunity costs to look beyond hypothetical markets to trading current benefits for future returns.We also tap into literature on agricultural risk management to provide additional insight into farmers’rationale behind their choices.Result:Generally,despite their stated preference to conserve ecosystem services,farmers’actions were found to be inconsistent with the proposed sustainable management.WTF analysis revealed that farmers’desire to maximize current benefits and more importantly to minimize future risks override all sustainability considerations.Their WTF current benefits mainly depended on their location along the canal and hence their access to water and land,overall cost of production,market conditions that informed their crop choices,and the cost of adopting recommended packages.While the results remain specific to this case,they are consistent with the literature that links farmers’behaviors to ecological performances.Conclusions:The study highlights the limitations of decision support tools and other valuation approaches including willingness to pay(WTP)and willingness to accept(payment)(WTA),to capture the delicate trade-offs that need to be considered to ensure household food and income security and encourage adoption of sustainable ecosystem management practices.Adequate information on potential effects of proposed conservation measures on yield,markets and hence farm profits,and availability of other alternatives are critical in shaping farmers’decisions.

Effects of Conservation Agriculture on Land and Water Productivity in Yellow River Basin, China

In the dryland regions of North China,water is the limiting factor for rainfed crop production.Conservation agriculture(featuring reduced or zero tillage,mulching,crop rotations and cover crops)has been proposed to improve soil and water conservation and enhance yields in these areas.Conservation agriculture systems typically result in increased crop water availability and agro-ecosystem productivity,and reduced soil erosion.To evaluate the potential of conservation agriculture to improve soil water balance and agricultural productivity,the DSSAT crop model was calibrated using the data of a field experiment in Shouyang County in the semi-arid northeastern part of the Yellow River Basin.The average annual precipitation at the site is 472 mm,75%of which falls during the growing season.The site had a maize-fallow-maize rotation.data from two crop seasons(2005 and 2006)and four treatments for calibration and analysis were used.The treatments were:conventional tillage(CT),no-till with straw mulching(NTSM),all-straw incorporated(ASRT)and one-third residue left on the surface with no-till(RRT).The calibration results gave satisfactory agreement between field observed and model predicted values for crop yield for all treatments except RRT treatment,and for soil water content of different layers in the 150 cm soil profile for all treatments.The difference between observed and predicted values was in the range of 3%-25%for maize yield and RMSE was in the range of 0.03-0.06 cm^(3)/cm^(3) for soil water content measured periodically each cropping season.While these results are encouraging,more rigorous calibration and independent model evaluation are warranted prior to making recommendations based on model simulations.Medium-term simulations(1995-2004)were conducted for three of the treatments using the calibrated model.The NTSM and ASRT treatments had similar or higher yields(by up to 36%),higher crop water productivity by up to 28%and reduced runoff of up to 93%or 43 mm compared to CT treatment.

Evaluation of a GIS-based watershed modeling approach for sediment transport

In order to improve water quality and restore impaired watersheds,managers need to make decisions using data that are able to gather.Data collection can be expensive,tedious and time consuming.Not all watershed managers have sufficient budgets to undertake such exercises.In such situations using modeling approach makes sense.The Sediment Nutrient Assessment Program(SNAP)is a functionally distributed model.It uses Geographic Information System(GIS)-based methodology employing commonly used Revised Universal Soil Loss Equation(RUSLE)to estimate the amount of erosion that can occur in the study area and Flux model for estimating the sediment transport.By adopting this methodology a modeler can estimate fractions of sediment contributions from the three landforms(upland,surface tiled,riparian).An intermediate result is mapping of areas producing erosion at rates above,below and equal to tolerable rates for each soil type.The model works best on smaller watersheds(<4,000 hectare)where staff have time and resources to inventory water quality.A good understanding of the watershed is needed to validate the model outputs.The model implementation is relatively cheap,cost effective and easy.Existing data and freely available information in the public domain are used for computations.It takes a multifaceted and holistic approach by integrating current,localized research literature,field surveys,water quality data,and GIS into one tool for refining watershed management decisions.The SNAP model serves as a first stage of analyzing as to how bad the sedimentation problem is with limited resources.