三峡库区笋溪河流域面源污染及其与土壤可蚀性k值的关系

研究三峡库区面源污染特征及其与水土流失的关系,可为库区氮磷污染和土壤侵蚀控制提供依据.选择三峡库区库尾笋溪河流域,在流域内分园地、林地和耕地3种土地利用类型共采集126个土壤样品,并在主干和支流采集52个水质样品.根据EPIC模型计算土壤可蚀性k值,分析流域内土壤可蚀性k值对面源污染的影响.结果表明,笋溪河流域面源污染主要是氮污染,总氮均值达1.37 mg/L,氮素的主要形态为硝态氮,占总氮的71.2%;总磷浓度为0.1 mg/L.流域内土壤可蚀性k值均值为0.040,随着土层加深土壤可蚀性k值呈上升趋势;林地土壤可蚀性k值显著低于园地和耕地.笋溪河流域总氮浓度与园地和耕地0-20 cm土壤可蚀性k值有关,硝态氮浓度与耕地0-40 cm土壤可蚀性k值有关.因此,笋溪河流域面源污染严重,主要来源是耕地和园地,应实行免耕、植物篱等措施,同时减少化肥施用,增加有机肥比例,以增加土壤抗侵蚀能力,进而控制流域水土流失和面源污染.(图6参37)     

Carbon sequestration in soils of SW-Germany as affected by agricultural management—Calibration of the EPIC model for regional simulations

Global emissions trading allows for agricultural measures to be accounted for the carbon sequestration in soils. The Environmental Policy Integrated Climate (EPIC) model was tested for central European site conditions by means of agricultural extensification scenarios. Results of soil and management analyses of different management systems (cultivation with mouldboard plough, reduced tillage, and grassland/fallow establishment) on 13 representative sites in the German State Baden-Württemberg were used to calibrate the EPIC model. Calibration results were compared to those of the Intergovernmental Panel on Climate Change (IPCC) prognosis tool. The first calibration step included adjustments in (a) N depositions, (b) N₂-fixation by bacteria during fallow, and (c) nutrient content of organic fertilisers according to regional values. The mixing efficiency of implements used for reduced tillage and four crop parameters were adapted to site conditions as a second step of the iterative calibration process, which should optimise the agreement between measured and simulated humus changes. Thus, general rules were obtained for the calibration of EPIC for different criteria and regions. EPIC simulated an average increase of +0.341 Mg humus-C ha⁻¹ a⁻¹ for on average 11.3 years of reduced tillage compared to land cultivated with mouldboard plough during the same time scale. Field measurements revealed an average increase of +0.343 Mg C ha⁻¹ a⁻¹ and the IPCC prognosis tool +0.345 Mg C ha⁻¹ a⁻¹. EPIC simulated an average increase of +1.253 Mg C ha⁻¹ a⁻¹ for on average 10.6 years of grassland/fallow establishment compared to an average increase of +1.342 Mg humus-C ha⁻¹ a⁻¹ measured by field measurements and +1.254 Mg C ha⁻¹ a⁻¹ according to the IPCC prognosis tool. The comparison of simulated and measured humus C stocks was r² ≥ 0.825 for all treatments. However, on some sites deviations between simulated and measured results were considerable. The result for the simulation of yields was similar. In 49% of the cases the simulated yields differed from the surveyed ones by more than 20%. Some explanations could be found by qualitative cause analyses. Yet, for quantitative analyses the available information from farmers was not sufficient. Altogether EPIC is able to represent the expected changes by reduced tillage or grassland/fallow establishment acceptably under central European site conditions of south-western Germany.     

An Approach for Estimating Soil Carbon Using the National Nutrient Loss Database

Agricultural lands have the potential to contribute to greenhouse gas mitigation by sequestering organic carbon within the soil. Credible and consistent estimates will be necessary to design programs and policies to encourage management practices that increase carbon sequestration. Because a nationwide survey of soil carbon by the wide range of natural resources and management conditions of the United States is prohibitively expensive, a simulation modeling approach must be used. The National Nutrient Loss Database (NNLD) is a modeling and database system designed and built jointly by the USDA– Natural Resources Conservation Service (NRCS) and Texas A&M University to provide science-based inferences on environmental impacts from changes in agricultural management practices and programs at the regional and national level. Currently, the NNLD simulates 16 crops and covers 1.35 × 10⁸ ha. For estimating soil carbon sequestration, the database will be populated with 1.5 × 10⁶ field-level model runs using the EPIC (Environmental Policy Impact Calculator) model, which includes newly incorporated carbon equations consistent with those in the Century model. Each run will represent a unique situation defined by state, crop, climate, soil, irrigation type, conservation practice, tillage system, and nutrient management treatment (nutrient rate, application frequency, application timing, and manure category). Results are to be assigned to specific National Resource Inventory points (NRI) to simulate regional and national baselines. In this article we present the modeling approach and discuss the strengths and limitations. Published online     

WATER QUALITY IMPACTS OF CONSERVATION AGRICULTURAL PRACTICES IN THE MISSISSIPPI DELTA1

ABSTRACT: Nonpoint pollution in the form of runoff generated by conventional agricultural practices is one of the major sources of environmental degradation of surface water bodies. Agricultural conservation practices including no‐tillage operations have been introduced as alternatives to cope with such challenges. This study attempts to examine the economic and environmental impacts of no‐tillage as compared to conventional agricultural practices for cotton, soybeans and corn cultivated in the Mississippi Delta. Impacts in the form of sediment, nutrient and pesticide runoff at farm level are investigated, using the Erosion Productivity Impact Calculator (EPIC).     

黄土高原旱塬地冬小麦水分生产潜力与土壤水分动态的模拟研究

在EPIC模型介绍和模拟精度验证的基础上,利用EPIC模型对黄土高原旱塬地冬小麦水分生产潜力和土壤水分动态进行了中期(12a)和长期(30a)评价定量模拟研究。结果表明:(1)在12a实时气象条件下的模拟时段内,旱塬地小麦水分生产潜力随降水量变化呈现波动性降低趋势,3m土层土壤有效含水量也表现为剧烈波动性和逐渐下降趋势,土壤干燥化趋势明显;(2)在30a模拟气象条件下的模拟时段内,旱塬地小麦水分生产潜力呈现波动性轻微降低趋势,3m土层土壤有效含水量季节性和年际间波动性显著,但土壤干燥化趋势并不明显;(3)综合分析认为,在降水量减少幅度不显著的情况下,旱塬地麦田土壤干燥化只是一种短期现象,不会导致长期性土壤强烈干燥化现象发生,但产量随降水量变化的波动性不可避免。     

黄土高原冬小麦田土壤水分与小麦产量对降水和气温变化响应的模拟研究

明确黄土高原地区降水和气温变化对冬小麦田土壤水分和产量的影响,对探索适应气候变化的冬小麦田间管理措施具有重要的现实意义。论文在验证EPIC模型对冬小麦田土壤水分模拟精度的基础上,以历史气象数据为基础,设置TR1、TR2和TR3三个气候情景,采用作物模型模拟的方法,研究黄土高原冬小麦田土壤水分和冬小麦产量对降水和气温变化的响应。结果显示：1）1961—2010年黄土高原降水呈降低趋势,其年际间变化幅度和频率均有所增加。与1961—1970年相比,洛川、长武、运城和延安的年均降水量在2001—2010年间分别降低了18.1%、13.6%、18.8%和24.9%,其变差系数分别增加了0.029、0.087、0.02和0.057。1961—2010年黄土高原气温呈波动性增加趋势,其中日最低气温增加幅度大于日最高气温增加幅度。与1961—1970年相比,日最高气温在2001—2010年间增加了0.30~0.84 ℃,而日最低气温增加了1.00~1.55 ℃。2）EPIC模型能够较好地模拟黄土高原冬小麦田土壤水分动态变化规律,0~2.0 m土层土壤湿度观测值与模拟值间的相对均方根误差RRMSE值为6.0%~14.0%,R²和模型效率ME值分别为0.824和0.815。3）黄土高原地区降水的减少和最高气温的增加均不利于冬小麦生产,而最低气温的提高对冬小麦生产较为有利。洛川、长武、运城和延安冬小麦产量因年降水量的降低而分别减产了8.5%、7.6%、11.7%和12.3%;因日最高气温的升高分别减产了6.4%、6.8%、7.2%和-3.0%;因日最低气温的提高而分别增加了8.8%、10.2%、1.5%和12.0%。因此,为适应降水减少和日最低气温升高的趋势,黄土高原冬小麦生产区应适当调整冬小麦播期,研究并推广保水节水技术措施,充分利用气候变化对冬小麦生产的有利因素,克服不利因素,确保冬小麦的可持续生产。     

应用EPIC模型计算黄土塬区作物生产潜力的初步尝试

黄土高原地区土壤侵蚀强烈,土地现实生产力水平低,研究该地区作物生产潜力可以为有效提高作物产量及合理进行农业生产规划提供依据。论文介绍了EPIC(侵蚀-生产力影响计算模型)的特点、组成部分及应用步骤,对部分作物参数进行了修订。以黄土塬区冬小麦和春玉米为例,对EPIC模型的适用性进行了分析和验证,表明EPIC在黄土高原地区作物生产潜力模拟研究中具有较好的适用性。结果显示,冬小麦产量模拟值与实测值之间多年平均误差为7.78%;春玉米多年平均误差为9.60%。冬小麦水分胁迫天数多年平均为9.9天,最少为1.7天(1993年),最多为23.1天(1995年);春玉米水分胁迫天数多年平均为13.4天,最少为1.1天(1993年),最多为44.2天(1995年),与各年作物生育期降水情况基本一致。此模型经修正后在正常年份模拟值较为精确,在干旱年份对作物、土壤等参数的修正方法需要进一步探讨。     

秸秆还田对江西农田土壤固碳影响的模拟分析

秸秆还田等农田管理措施能有效地增加土壤碳储量,从而有利于减缓大气CO₂浓度的上升趋势。论文基于环境政策综合气候模型(EPIC),采用千烟洲生态试验站和鹰潭生态试验站农田监测场长期观测数据,验证和优化了EPIC模型参数,同时利用1990-2010年江西省气象资料以及土壤清查资料,模拟分析了4种秸秆还田(CR)比例情景下2010-2030年江西省水稻田土壤的固碳潜力。研究结果表明,无秸秆还田 (CR0%)和秸秆还田25%(CR25%)两种处理下耕作层土壤有机碳储量分别下降21.3%和6.5%,秸秆还田50%(CR50%)和100%(CR100%)处理下土壤有机碳储量分别增加5.4%和11.9%;相对CR0%情景而言,CR25%、CR50%、CR100% 情景下江西省水稻田土壤总固碳潜力分别为6.43、14.92和25.26 TgC(1 Tg = 10⁶ t)。研究结果表明,通过合理的调控措施,采用保护性耕作(秸秆还田)是提高水稻田土壤固碳能力的一种有效途径。     

Modeling soil and plant phosphorus within DSSAT

The crop models in the Decision Support System for Agrotechnology Transfer (DSSAT) have served worldwide as a research tool for improving predictions of relationships between soil and plant nitrogen (N) and crop yield. However, without a phosphorus (P) simulation option, the applicability of the DSSAT crop models in P-deficient environments is limited. In this study, a soil-plant P model integrated to DSSAT was described, and results showing the ability of the model to mimic wide differences in maize responses to P in Ghana are presented as preliminary attempts to testing the model on highly weathered soils. The model simulates P transformations between soil inorganic labile, active and stable pools and soil organic microbial and stable pools. Plant growth is limited by P between two concentration thresholds that are species-specific optimum and minimum concentrations of P defined at different stages of plant growth. Phosphorus stress factors are computed to reduce photosynthesis, dry matter accumulation and dry matter partitioning. Testing on two highly weathered soils from Ghana over a wide range of N and P fertilizer application rates indicated that the P model achieved good predictability skill at one site (Kpeve) with a final grain yield root mean squared error (RMSE) of 535 kg ha⁻¹and a final biomass RMSE of 507 kg ha⁻¹. At the other site (Wa), the RMSE was 474 kg ha⁻¹ for final grain yield and 1675 kg ha⁻¹ for final biomass. A local sensitivity analysis indicated that under P-limiting conditions and no P fertilizer application, crop biomass, grain yield, and P uptake could be increased by over 0.10% due to organic P mineralization resulting from a 1% increase in organic carbon. It was also shown that the modeling philosophy that makes P in a root-free zone unavailable to plants resulted in a better agreement of simulated crop biomass and grain yield with field measurements. Because the complex soil P chemistry makes the availability of P to plants extremely variable, testing under a wider range of agro-ecological conditions is needed to complement the initial evaluation presented here, and extend the use of the DSSAT-P model to other P-deficient environments.     

SIMULATING NITROGEN LOSSES FROM AGRICULTURAL LAND: IMPLICATIONS FOR WATER QUALITY AND PROTECTION POLICY1

ABSTRACT: EPIC, a soil erosion/plant growth simulation model, is used to simulate nitrogen losses for 120 randomly selected and previously surveyed cropland sites. Simulated nitrogen losses occur through volatilization, surface water and soil runoff, subsurface lateral flow, and leaching. Physical and crop management variables explain a moderate but significant proportion of the variation in nitrogen losses. Site slope and tillage have offsetting effects on surface and ground water losses. Nitrogen applications in excess of agronomic recommendations and manure obtained off the farm and applied to the sites are significant contributors to nitrogen losses. Farm characteristics such as production of confined livestock, total manure nitrogen available, and farm income per cropland acre explain a relatively large portion of the variability in manure nitrogen applied to survey sites. The results help to identify farm characteristics that can be used to target nutrient management programs. Simulation modeling provides a useful tool for investigating variables which contribute to agricultural nitrogen losses.