满足机械收割农艺条件下稻田排水暗管布局DRAINMOD模型模拟

在长江中下游稻麦轮作区,水稻秋收期阴雨连绵现象时有发生,收割机械因农田土壤过湿而无法及时下田收割。如果建设暗管排水系统,则可及时降低地下水埋深,保证机械收割的顺利进行。该文以江苏省扬州市江都区昭关灌区为例,以地下水埋深降至60~80 cm作为适于一般机械收割的田间排水要求,运用田间水文模型-DRAINMOD模拟了满足1~5 d机械下田条件的暗管排水布局,并分析了相应的田间水文效应以及模型主要输入参数的敏感性。根据研究区1954-2016年逐日气象数据(包含降雨、气温、湿度、风速和日照时数等)的模拟结果显示:考虑大型机械收割要求(地下水埋深大于80 cm),当暗管埋深为90~150 cm时,满足98%、95%和90%保证率的最大暗管间距分别为7.42~18.74 m、13.01~26.20 m和15.27~28.72 m;满足小型机械收割要求(地下水埋深大于60 cm)的暗管布置间距则可更大,满足98%、95%和90%保证率的最大暗管间距分别为10.36~19.59 m、18.17~30.90 m和22.88~33.02 m。多年平均机械收割天数对侧向饱和导水率、不透水层深度、土壤蒸发蒸腾量、潜水上升通量和土壤可排空体积5类参数最为敏感。研究成果可为类似水稻种植区基于机械收割要求的农田暗管排水系统设计提供理论依据。

Drainage layout in paddy fields meeting machinery harvest requirement based on DRAINMOD model

Abstract: In the rice and wheat rotation area in the middle and lower reaches of Yangtze River, consecutive rainfall events occur during the rice harvesting period, leading to poor trafficability for agricultural machinery in the excessively wet soils. This may result in low or no crop yield due to delayed harvest. Subsurface drainage is known for its quick drawdown of water table to enable trafficability of machinery. In order to determine the proper layout of subsurface drainage system for improved trafficability of rice harvesters, this paper presents a simulation study using the field hydrology model-DRAINMOD based on long term weather record in the Zhaoguan Irrigation District in Yangzhou, China. With a simple model testing, DRAINMOD simulations were conducted to examine the probability of achieving different harvesting days by lowering water table to 60-80 cm below soil surface. Two drainage criteria were examined: 1) lowering water table depth to 80 cm below soil surface for at least 1 d to facilitate large rice harvesters; 2) lowering water table depth to 60 cm below soil surface for at least 2 d to facilitate small rice harvesters. According to the long term daily weather data from 1954 to 2016 in the study area, DRAINMOD was applied to simulate subsurface drainage layout meeting required work days of both small and large rice harvesters; Simulation results were presented for probability of 98%, 95% and 90% corresponding to 50-, 20- and 10-year recurrence intervals for predicted harvesting days from 1 to 5 days. The simulation results showed that: 1) DRAINMOD can predict water table depths reasonably well for the study area; the average relative error and RMSE between simulated and measured water table depths for model testing were 3.05% and 3.00 cm, respectively; 2) when the water table control depth ranged from 60 to 80 cm, the subsurface pipe depth should be 20 cm deeper than the required depth to achieve at least 1 harvesting day for probabilities between 96.83% and 85.71%; 3) for the water table control depth above, the predicted subsurface pipe spacing ranged from 10 to 25 m, and the probability for obtaining at least 1 harvesting day ranged from 95.24% to 89.29%; 4) when subsurface pipe depths ranged from 90 to 150 cm, the predicted subsurface pipe spacing was in the ranges of 7.42-18.74 m, 13.01-26.20 m and 15.27-28.72 m, respectively to meet probability of 98%, 95% and 90% for different machinery trafficability. The simulation results also showed that, shallow and narrow layouts of subsurface drainage systems are more effective in removing field water during heavy rainfall events, while the deep and wide systems can lower water table more effectively out of the rainy period. Sensitivity analysis on DRAINMOD input parameters showed that the predicted harvesting days were mostly sensitive to the lateral hydraulic conductivity, depth to impermeable layer, potential evapotranspiration, upward flux and soil volume drained in the drained fields; for subsurface pipe depth at 100 cm and subsurface pipe spacing at 25 m, ±30% variations in lateral saturated hydraulic conductivity and depth from surface to the impermeable layer resulted in variation of the predicted harvesting days in the range of ?41.58%-15.35% and ?59.41%-10.40%, respectively. Findings from this research may provide valuable information for subsurface drainage system design considering variability of rainfall pattern and soil properties in regions similar to our areas.