Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Other Disciplines of Agriculture, Forestry,Livestock & Aquatic Products Science submitted time 2023-02-17 Cooperative journals: 《智慧农业（中英文）》
Abstract： Dissolved oxygen is an important environmental factor for prawn breeding. In order to improve the prediction accuracy of dissolved oxygen concentration in prawn pond, and solve the problem of low prediction accuracy of different frequency domain modal classification after empirical modal decomposition of nonlinear time series data when there are few training samples, an combination prediction model based on empirical mode decomposition (EMD), random forest (RF) and long short term memory neural network (LSTM) was proposed in this research. Firstly, the time series data of prawn breeding dissolved oxygen concentration were decomposed at multiple scales by EMD to obtain a set of stationary intrinsic mode function (IMF). Secondly, with fewer training samples, poor predicts effects on the low-frequency were verified component by LSTM. Then, IMF1－ IMF4 were divided into high-frequency components through test results and used for LSTM model. IMF5－IMF7, Rn were divided for RF model, the EMD-RF-LSTM combination model was constructed to improve the prediction accuracy. Modeled lowfrequency and high-frequency components IMF using RF and LSTM, then predictions of each component were accumulated and the prediction value of dissolved oxygen of sequence data were got. Finally, the performance of the model was compared with the limit learning machine (ELM), RF, standard LSTM, EMD-ELM and EMD-RF, EMD-LSTM, etc. In the test based on real dataset, the EMD-ELM model contrasted with ELM model, reduced the mean absolute error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) by 30.11%, 29.60% and 32.95%, respectively. The MAPE, RMSE, MAE for the proposed models were 0.0129, 0.1156, 0.0844, respectively. MAPE decreased by 84.07%, 57.57%, and 49.81% compared with EMD-ELM, EMD-RF and EMD-LSTM, respectively, the prediction accuracy was significantly improved. The results show that the proposed model EMD-RF-LSTM has good prediction performance and generalization ability, which is meets the actual demand of accurate prediction of dissolved oxygen concentration in prawn culture, and can provide reference for the prediction and early warning of prawn pond water quality.
Subjects: Environmental Sciences, Resource Sciences >> Basic Disciplines of Environmental Science and Technology submitted time 2021-01-25 Cooperative journals: 《干旱区研究》
Abstract：疏勒河流域位于内陆干旱区，水资源是制约流域植被生长和发展的关键因素，植被耗水量研究对于实现该流域水资源合理配置起着至关重要的作用。本文基于气象数据和GIS技术，使用改进的彭曼公式法，定量分析了疏勒河流域不同植被类型各生长阶段耗水量的时空变化特征。研究结果表明：疏勒河流域植被耗水量在2000—2015年间呈上升趋势，多年平均耗水量为18.24×108 m3。植被耗水量呈明显的空间异质性，南部祁连山区植被耗水最多，北部马鬃山地区最少。荒漠植被耗水量最多（11.25×108 m3），有林地最少（0.10×108 m3）。2000—2015年植被不同生长阶段的耗水量变化存在较大差异，生长初期和发育期的耗水量呈减少趋势，生长中期和生长晚期的耗水量呈增加趋势。相比植被分布变化，参考蒸散发量的变化是疏勒河流域植被耗水变化的主要影响因素。
Subjects: Environmental Sciences, Resource Sciences >> Basic Disciplines of Environmental Science and Technology submitted time 2018-11-08 Cooperative journals: 《干旱区研究》
Abstract：土壤含水率是影响干旱区植物生长的重要因素，获取区域尺度土壤含水率数据，能够为干旱半干旱区生态恢复和脆弱生态系统保护提供科学依据。结合MODIS地表温度和反射率数据及全球陆面数据同化系统（GLDAS）土壤含水率数据，利用表观热惯量法和统计降尺度方法反演疏勒河流域土壤含水率，研究其时空变化及其与植被的相关性，得到以下结论：2016年整个疏勒河流域年均土壤含水率偏低，且季节变化显著，其均值、离散程度存在7月＞10月＞4月＞12月的趋势；流域东部土壤含水率整体高于西部；流域土壤含水率空间分布的季节变化显著，其变异系数的空间分布与年均土壤含水率相似；土壤含水率与归一化植被指数NDVI正相关，但不同区域两者相关程度不同，灌区土壤含水率与植被的相关性最高。
Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Basic Disciplines of Agriculture submitted time 2017-11-08 Cooperative journals: 《中国生态农业学报》
Abstract：为明确秸秆颗粒还田在农业生产中推广应用的可行性, 在山东省冬小麦-夏玉米一年两熟种植区通过田间微区试验,研究了秸秆不还田(CK)、常规粉碎还田(CCSI)和秸秆颗粒还田(GSI)对耕层土壤养分含量、冬小麦群体茎蘖数、旗叶净光合速率、叶绿素含量、干物质积累及分配和小麦产量的影响。结果表明: 与CK 和CCSI 处理相比, GSI 处理显著提高土壤有机质、碱解氮和有效磷的含量; 增加基本苗和分蘖成穗率, 显著提高有效穂数13.23%和16.64%。同时, GSI 处理显著提高灌浆期叶面积指数、旗叶叶绿素含量和净光合速率, 改善开花后旗叶光合性能, 促进地上部干物质积累及其向籽粒的转运。与CK和CCSI 处理相比, GSI 处理的开花后干物质向籽粒的转运量显著提高19.65%和14.75%, 籽粒产量显著提高9.69%和10.71%。 相关分析表明, 穗粒数和千粒重对产量影响不显著, 有效穂数的提高是秸秆颗粒还田增产的主要原因。因此, 秸秆颗粒还田可作为一种安全有效的还田方式, 可在农业生产中推广应用。
Subjects: Biology >> Ecology submitted time 2017-03-22 Cooperative journals: 《生态学报》
Abstract：粮食生产服务是区域生态系统主要的服务功能之一，也是人类福祉和社会发展的基础，受自然环境和社会经济发展而不断变化。然而，目前国内外尚缺乏统一的生态系统服务价值的时空动态评估方法，尤其是在脆弱的山区过渡带区域。以灾害频发的脆弱生态过渡带——甘肃白龙江流域为例，尝试引入自然环境和人文社会要素对区域生态系统生产服务经济价值进行系数调整与修正，构建生态系统服务价值的计量评估模型，测算流域内生态系统生产服务价值并分析其时空差异性。结果表明：（1）1990-2010年间白龙江流域耕地面积波动起伏较大，但流域内生态系统生产服务价值却表现出持续上升的趋势，至2010年平均生产服务价值达186.74万元。生态系统生产服务价值空间格局变化不大，其高产区约占42.4%以上，主要分布在宕昌县西北部的岷江两岸和舟曲城关镇-武都汉王镇的白龙江两岸及其以北区域。（2）方法改进后，白龙江流域生产经济价值相对减小（172.74万元），间接反映了研究区内滑坡、泥石流等自然灾害和区位人文社会要素对生产经济价值的影响，更符合流域的实际情况。
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