1) It was buried deep under the ground.
它被深埋在地下。
2) groundwater level
地下水埋深
1.
Distribution of dominant plant species and characteristic of its communities on the foreland of Cele Oasis in relation to groundwater level
策勒绿洲外围不同地下水埋深下主要优势植物的分布和群落特征
2.
Based on experimental data from laboratory and field experiments, the relationship between rainfall recharge and groundwater level under farmland drainage is analyzed in this paper.
以室内一维土柱试验和室外水平衡小区观测资料为基础 ,对农田排水条件下降雨入渗补给与地下水埋深关系进行了分析 ,根据降雨、蒸发与地下水埋深关系相似的规律 ,仿照国内外排水计算中较为广泛应用的阿维里扬诺夫经验公式的结构形式 ,建立起降雨入渗补给与地下水埋深的关系 ,并采用室内外试验资料对该关系式进行了验证。
3.
With special equipments of Central Equipment Station in Shanxi province,this model was established on basis of the results of the optimal groundwater level range which was measured by taking full advan.
为建立新型的节水型灌区,科学用水、计划用水,利用山西省中心试验站蒸渗仪,进行了长达10年的试验研究,充分利用马氏瓶调控地下水浅埋区的水位动态变化,得出了最佳地下水埋深范围,建立了动态模拟的作物生育期内潜水蒸发模型。
3) groundwater table
地下水埋深
1.
Effects of reclaimed water irrigation on winter wheat growth under different groundwater tables;
不同地下水埋深条件下再生水灌溉对冬小麦生长的影响
2.
Recent advances in desert vegetation response to groundwater table changes;
荒漠区植被对地下水埋深响应研究进展
3.
Seasonal variation of groundwater table for Pinus sylvestris var. mongolica plantations in southern Keerqin Sandy land
科尔沁沙地南缘樟子松人工林地下水埋深季节变化
4) groundwater embedment depth
地下水埋深
1.
In order to solve above-mentioned problems, this paper took 597 Farm as example, built up the groundwater embedment depth dynamic forecast model of 597 Farm through applying the method of time-series analysis.
为了解决上述问题,以597农场为例,采用时间序列分析方法建立了597农场地下水埋深动态预测模型,对地下水埋深进行模拟和预测;同时,揭示了该区地下水动态变化规律,为三江平原地下水资源的可持续利用提供了科学依据。
2.
In order to solve above-mentioned problems,this paper took 853 Farm as example,built up the groundwater embedment depth dynamic forecast model of 853 Farm through applying the method of time-series analysis.
为解决上述问题,以853农场为例,采用时间序列分析方法建立了853农场地下水埋深动态预测模型,对地下水埋深进行模拟和预测,揭示了该区地下水动态变化规律,为三江平原地下水资源的可持续利用提供了科学依据。
3.
In order to solve above-mentioned problems,this paper took 853 Farm as example,built up the groundwater embedment depth dynamic prediction model of 853 Farm through applying the method of BP neural network.
为解决上述问题,以853农场为例,采用BP神经网络方法建立了853农场地下水埋深动态预测模型,对地下水埋深进行模拟和预测,精度检验结果表明,模型拟合和预测精度均较高。
5) groundwater depth
地下水埋深
1.
The characteristics of the soil seed banks follow different groundwater depth in the lower reaches of Tarim River;
塔里木河下游不同地下水埋深下的土壤种子库特征
2.
Spatiotemporal variation of shallow groundwater depth in intensive agricultural areas;
集约化农业生产区浅层地下水埋深的时空变异规律
3.
Self-memory model for predicting groundwater depth series with periodical fluctuation;
考虑周期性变化的地下水埋深预测自记忆模型
6) basement depth
地下室埋深
补充资料：地下水水资源评价(见水资源评价)
地下水水资源评价(见水资源评价)
d ixiashui shuiziyuan Ping】ia地下水水资源评价见水资源评价。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条