水分传感器埋设深度及个数对墒情精度的影响
|
摘要
在灌溉预报过程中,要利用土壤水分传感器监测土壤墒情,同一剖面土壤水分传感器埋设数量越多,测墒精度就越高,在实际应用时,就要求减少土壤水分传感器的埋设数量以降低系统的成本,并保证一定的测墒精度。选取4个试验区,在0～100 cm土层深度内,采用取土烘干法测得5个测试深度土壤水分数据。分析了0～60和0～100 cm土壤剖面平均含水率与监测点含水率的相关关系,并设置了1个监测点和2个监测点不同组合的对比,分别计算了各种情况下土壤剖面平均含水率与监测点含水率的相关系数(R2)、平均相对误差(δR)以及均方根误差(RMSE)。研究结果显示:一个监测点时,40 cm深度的含水率能较好地反映0～60 cm土壤剖面平均含水率,R2达到0.95以上; 0～100 cm土壤剖面平均含水率用60 cm深度含水率反映,R2能达到0.93。两个监测点时,20/50 cm处的含水率与0～60 cm土壤剖面平均含水率的相关性最高,R2为0.994; 0～100 cm土壤剖面平均含水率与40/70 cm处的含水率相关性最高,各试验区平均的R2为0.965。
In the process of irrigation forecasting,the soil moisture sensor should be used to monitor the soil moisture.The more the soil moisture sensor is buried in the same section,the higher the accuracy of the measurement.In practical applications,it is required to reduce the amount of buried soil moisture sensors to reduce the cost of the system and to ensure a certain accuracy.In this paper,four test areas were selected,and the soil moisture data of five test depths measured by soil drying method were used in the depth of 0～100 cm soil layer.The correlation between the average water cut of 0～60 cm and 0～100 cm soil profile and the moisture content of the monitoring point was analyzed,and a comparison of different monitoring points and two monitoring points was set.The correlation coefficient(R2),average relative error(δR) and root mean square error(RMSE) of the average soil moisture content of the soil profile and the moisture content of the monitoring point were calculated.The research result shows that:at a monitoring point,the water content at a depth of 40 cm can better reflect the average water content of the 0～60 cm soil profile,and R2 is above 0.95;the average moisture content of the 0～100 cm soil profile is reflected by the depth of 60 cm,and R2 can reach 0.93.At the two monitoring points,the water content at 20/50 cm has the highest correlation with the average water content of 0～60 cm soil profile,and R2 is 0.994;the average water content of 0～100 cm soil profile is the highest correlation with the water content at 40/70 cm.The average R2 of each test area was 0.965.
In the process of irrigation forecasting,the soil moisture sensor should be used to monitor the soil moisture.The more the soil moisture sensor is buried in the same section,the higher the accuracy of the measurement.In practical applications,it is required to reduce the amount of buried soil moisture sensors to reduce the cost of the system and to ensure a certain accuracy.In this paper,four test areas were selected,and the soil moisture data of five test depths measured by soil drying method were used in the depth of 0～100 cm soil layer.The correlation between the average water cut of 0～60 cm and 0～100 cm soil profile and the moisture content of the monitoring point was analyzed,and a comparison of different monitoring points and two monitoring points was set.The correlation coefficient(R2),average relative error(δR) and root mean square error(RMSE) of the average soil moisture content of the soil profile and the moisture content of the monitoring point were calculated.The research result shows that:at a monitoring point,the water content at a depth of 40 cm can better reflect the average water content of the 0～60 cm soil profile,and R2 is above 0.95;the average moisture content of the 0～100 cm soil profile is reflected by the depth of 60 cm,and R2 can reach 0.93.At the two monitoring points,the water content at 20/50 cm has the highest correlation with the average water content of 0～60 cm soil profile,and R2 is 0.994;the average water content of 0～100 cm soil profile is the highest correlation with the water content at 40/70 cm.The average R2 of each test area was 0.965.
引文
[1]龚元石,李春友,李子忠.农田土壤水分测定三种方法的比较[J].中国农业大学学报,1997,2(3):53-58.
[2]赵宇飞,王长沙.常用土壤含水量测定方法的原理及比较[J].园艺与种苗,2017,(10):70-73.
[3]李加念,洪添胜,冯瑞钰,等.基于真有效值检测的高频电容式土壤水分传感器[J].农业工程学报,2011,27(8):216-221.
[4]Jones S B,Blonquist J J M,Robinson D A,et al.Standardizing characterization of electromagnetic water content sensor(Part 1):Methodology[J].Vadose Zone Journal,2005,4(4):1 048-1 058.
[5]Benghanem M.Low cost management for photovoltaic system in isol11ated sitewith new IV Characterization model proposed[J].Energy Conversion and Management,2009,50(3):748-755.
[6]韩玉国,武亨飞,杨培岭,等.番茄种植地土壤水分传感器最佳埋设深度试验[J].水土保持通报,2013,33(4):260-263.
[7]高阳,刘战东,段爱旺,等.农田土壤剖面水分探头布设及数据处理技术研究[J].灌溉排水学报,2011,30(05):28-32.
[8]王凡,黄磊,吴素萍,等.多路数据采集与处理模型的设计及水分传感器埋设位置优化[J].农业工程学报,2015,31(21):148-153.
[9]李堃,李建设,吴素萍,等.基于实时控制灌溉系统的温室黄瓜土壤水分传感器合理埋设位置研究[J].灌溉排水学报,2015,34(7):18-23.
[10]孙凯.墒情(旱情)监测与预测研究方法研究[D].北京:中国农业大学,2004.
[2]赵宇飞,王长沙.常用土壤含水量测定方法的原理及比较[J].园艺与种苗,2017,(10):70-73.
[3]李加念,洪添胜,冯瑞钰,等.基于真有效值检测的高频电容式土壤水分传感器[J].农业工程学报,2011,27(8):216-221.
[4]Jones S B,Blonquist J J M,Robinson D A,et al.Standardizing characterization of electromagnetic water content sensor(Part 1):Methodology[J].Vadose Zone Journal,2005,4(4):1 048-1 058.
[5]Benghanem M.Low cost management for photovoltaic system in isol11ated sitewith new IV Characterization model proposed[J].Energy Conversion and Management,2009,50(3):748-755.
[6]韩玉国,武亨飞,杨培岭,等.番茄种植地土壤水分传感器最佳埋设深度试验[J].水土保持通报,2013,33(4):260-263.
[7]高阳,刘战东,段爱旺,等.农田土壤剖面水分探头布设及数据处理技术研究[J].灌溉排水学报,2011,30(05):28-32.
[8]王凡,黄磊,吴素萍,等.多路数据采集与处理模型的设计及水分传感器埋设位置优化[J].农业工程学报,2015,31(21):148-153.
[9]李堃,李建设,吴素萍,等.基于实时控制灌溉系统的温室黄瓜土壤水分传感器合理埋设位置研究[J].灌溉排水学报,2015,34(7):18-23.
[10]孙凯.墒情(旱情)监测与预测研究方法研究[D].北京:中国农业大学,2004.