The Tarrawarra project: high resolution spatial measurement, modelling and analysis of soil moisture and hydrological response
The Tarrawarra project: high resolution spatial measurement, modelling and analysis of soil moisture and hydrological response
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Tarrawarra 项目：土壤湿度和水文响应的高分辨率空间测量、建模和分析
DOI：
10.1002/(sici)1099-1085(19990415)13:5
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发表时间：
1999
影响因子：
3.2
通讯作者：
T. Green
中科院分区：
文献类型：
--
作者：
A. Western;R. Grayson;T. Green
在澳大利亚维多利亚州南部10.5公顷的Tarrawarra流域，对13个日期的土壤水分进行了详细的空间格局测量。总结了对数据的几种分析。其中包括：水文行为，包括优先状态、空间组织和地形指数的表现；土壤水分模式的地质统计特性；以及土壤水分模式的遥感。在论文的第二部分中，结合地表径流和气象资料，在塔拉瓦拉应用了泰利斯模式和VIC模式。Thales是一个基于过程的分布参数水文模型，它显式地模拟了土壤水分的时空格局，而VIC则使用集中统计分布方法来模拟土壤水分储量的空间变异性。这两个模型都模拟饱和超额径流，并受降雨和潜在蒸散的影响。对VIC进行了校准，以观测到汇水口的径流。对泰利斯的径流和土壤水分模式进行了有限的人工校准。内部检验是通过比较Thales模型的预测和观测的土壤水分空间分布以及VIC模型的预测和观测的土壤有效贮水量的累积分布来实现的。在有限的校准工作下，泰利斯能够模拟土壤水分空间模式特征的季节变化。对模拟模式中的错误进行详细检查，可以确定模式中的结构问题，包括模拟秋季集水区潮湿时的横向再分配问题。对于VIC模型，空间平均内部状态变量的时间序列(总存储)与观测值一致。然而，模型中假设的土壤贮水量的统计分布与观测结果不同。土壤水分模式的详细空间数据的收集为测试与每个模型公式相关的内部状态(泰利斯为空间分布，VIC为统计集中)提供了基础，以及改进了对主要径流过程的识别。
Detailed spatial patterns of soil moisture were measured for 13 dates at the 10.5 ha Tarrawarra catchment in southern Victoria, Australia. Several analyses of the data are summarized. These include: hydrological behaviour, including preferred states, spatial organization and the performance of terrain indices; geostatistical properties of the soil moisture patterns; and remote sensing of the soil moisture patterns. In the second part of the paper, the patterns along with surface runoff and meteorological data are used in applications of the Thales and VIC models at Tarrawarra. Thales is a process-based distributed parameter hydrological model which explicitly simulates the spatio-temporal patterns of soil moisture, while VIC uses a lumped statistical distribution approach to model the spatial variability of soil moisture storage. Both models simulate saturation excess runoff and are forced by rainfall and potential evapotranspiration. VIC was calibrated to observed runoff at the catchment outlet. Limited manual calibration of Thales to runoff and the soil moisture patterns was performed. Internal testing was achieved by comparison of predicted and observed spatial soil moisture patterns for the Thales model and of predicted and observed cumulative distributions of active soil moisture storage for the VIC model. With limited calibration effort, Thales was able to to simulate the seasonal changes in characteristics of the spatial soil moisture patterns. Detailed examination of the errors in the simulated patterns allowed identification of structural problems in the model, including problems with simulating lateral redistribution as the catchment wets in autumn. For the VIC model, time-series of spatially averaged internal state variables (total storage) were consistent with observations. However, the statistical distribution of soil moisture storage assumed in the model differed from that observed. The collection of detailed spatial data for soil moisture patterns provided a basis for testing the internal states relevant to each model formulation (spatially distributed for Thales and statistically lumped for VIC), as well as improving the identification of the dominant runoff processes.