A CALIBRATION PROCEDURE USING TOPMODEL TO DETERMINE SUITABILITY FOR EVALUATING POTENTIAL CLIMATE CHANGE EFFECTS ON WATER YIELD1

ABSTRACT: An evaluation was conducted on three forested upland watersheds in the northeastern U.S. to test the suitability of TOPMODEL for predicting water yield over a wide range of climatic scenarios. The analysis provides insight of the usefulness of TOPMODEL as a predictive tool for future assessments of potential long-term changes in water yield as a result of changes in global climate. The evaluation was conducted by developing a calibration procedure to simulate a range of climatic extremes using historical temperature, precipitation, and streamfiow records for years having wet, average, and dry precipitation amounts from the Leading Ridge (Pennsylvania), Fernow (West Virginia), and Hubbard Brook (New Hampshire) Experimental Watersheds. This strategy was chosen to determine whether the model could be successfully calibrated over a broad range of soil moisture conditions with the assumption that this would be representative of the sensitivity necessary to predict changes in streamfiow under a variety of climate change scenarios. The model calibration was limited to a daily time step, yet performed reasonably well for each watershed. Model efficiency, a least squares measure of how well a model performs, averaged between 0.64 and 0.78. A simple test of the model whereby daily temperatures were increased by 1.7°C, resulted in annual water yield decreases of 4 to 15 percent on the three watersheds. Although these results makes the assumption that the model components adequately describe the system, this version of TOPMODEL is capable to predict water yield impacts given subtle changes in the temperature regime. This suggests that adequate representations of the effects of climate change on water yield for regional assessment purposes can be expected using the TOPMODEL concept.     

基于雷达估算降雨的湖北漳河流域径流模拟研究

本文以湖北省漳河流域为研究对象,从2008-2017年中选取了16次洪水过程(10次过程用于率定参数,6次过程用于检验),分别采用了4种方法进行雷达降雨估算,并将估算结果输入到TOPMODEL和新安江模型进行了径流模拟计算。结果表明:4种雷达降雨估算方法中动态Z-I的平均相对误差最小为8.16%,其次是分组Z-I为20.1%,最优Z-I和经典Z-I分别为29.7%和29.02%;从径流模拟结果来看,动态Z-I效果最佳,分组Z-I次之,最优Z-I和经典Z-I模拟效果相对较差,且TOPMODEL模型的洪峰相对误差和峰现时差比新安江模型的模拟结果要小,新安江模型模拟结果的确定性系数与TOPMODEL模型接近。     

DEM栅格分辨率对TOPMODEL模拟不确定性的影响研究

选择南水北调水源区所在的汉江流域的3个不同地貌类型的子流域为试验流域,采用1:5万比例尺DEM为基准数据,基于以地形为基础的半分布式流域水文模型TOPMODEL,研究栅格分辨率对水文模拟不确定性的影响,并利用多目标模糊优化算法,对水文模拟的不确定性进行了综合评价。结果表明,DEM栅格分辨率对地形特征和地形指数都有很大的影响,从而影响水文模拟的不确定性,但由于水文模拟的复杂性在一定程度上掩盖了不同DEM分辨率计算的地形指数的差别,使得这种影响不是很大。对于现有试验流域而言,当分辨率为200 m的时候可以得到相对较优的不确定性预测区间。     

基于栅格产汇流的TOPMODEL

经典的TOPMODEL产汇流演算原是建立在子流域单位基础上的半分布式水文模型。考虑到流域地形、下垫面条件及流域气象条件的空间差异性,将TOPMODEL的产流计算细化到每个栅格,以改进模型的分布式计算,并在考虑地形坡度影响的情况下,根据降水-径流资料优选出的参数率定等流时线、利用率定的等流时线进行流域的汇流计算,以提升TOPMODEL在中、大尺度流域模拟演算的能力。使用改进后的模型在两河口流域（2 818 km2）以精度60 m的数字高程模型栅格网为基础,配合气象数据和水文资料对径流流量进行日模拟,模拟精度达到70%左右,进一步的分析认为该模型仍有较大的改进空间。     

RUNOFF MODELING OF A MOUNTAINOUS CATCHMENT USING TOPMODEL: A CASE STUDY1

ABSTRACT: The rainfall‐runoff response of the Tygarts Creek Catchment in eastern Kentucky is studied using TOPMODEL, a hydrologic model that simulates runoff at the catchment outlet based on the concepts of saturation excess overland flow and subsurface flow. Unlike the traditional application of this model to continuous rainfall‐runoff data, the use of TOPMOEL in single event runoff modeling, specifically floods, is explored here. TOPMODEL utilizes a topographic index as an indicator of the likely spatial distribution of rainfall excess generation in the catchment. The topographic index values within the catchment are determined using the digital terrain analysis procedures in conjunction with digital elevation model (DEM) data. Select parameters in TOPMODEL are calibrated using an iterative procedure to obtain the best‐fit runoff hydrograph. The calibrated parameters are the surface transmissivity, T_O, the transmissivity decay parameter, m, and the initial moisture deficit in the root zone, S_r0. These parameters are calibrated using three storm events and verified using three additional storm events. Overall, the calibration results obtained in this study are in general agreement with the results documented from previous studies using TOPMODEL. However, the parameter values did not perform well during the verification phase of this study.     

基于TOPMODEL径流模拟的黑河水资源探讨

以黑河莺落峡流域的精度30m、地形图比例尺1∶5万的数字高程模型(DEM)栅格网为基础,辅以黑河地区水文站点降水资料,运用PRISM算法内插降水要素,充分考虑高程、地形、距离等因子对降水的影响,在内插结果与实测资料对比精度满意的前提下,使用TOPMODEL对黑河莺落峡流域(10009km2)径流流量进行逐日模拟,模型模拟精度达70%左右。     

Estimating the potential impact of vegetation on the water cycle requires accurate soil water parameter estimation

It is well known that vegetation dynamics at the catchment scale depends on the prevailing weather and soil moisture conditions. Soil moisture, however, is not equally distributed in space due to differences in topography, weather patterns, soil properties and the type and amount of vegetation cover. To elucidate the complex interaction between vegetation and soil moisture, the dynamic vegetation model LPJ-GUESS (Smith et al., 2001), which provides estimations of vegetation dynamics, but does not consider lateral water fluxes was coupled with the hydrological TOPMODEL (cf. Beven, 2001) in order to be able to evaluate the importance of these lateral fluxes. The new model LG-TM was calibrated and validated in two climatically different mountain catchments. The estimations of runoff were good, when monthly and weekly time scales were considered, although the low flow periods at winter time were somewhat underestimated. The uncertainty in the climate induced change vegetation carbon storage caused by the uncertainty in soil parameters was up to 3-5 kg C m⁻² (depending on elevation and catchment), compared to the total change in vegetation carbon storage of 5-9 kg C m⁻². Therefore accurate estimates of the parameters influencing the water holding capacity of the soil, for example depth and porosity, are necessary when estimating future changes in vegetation carbon storage. Similarly, changes in plant transpiration due to climatic changes could be almost double as high (88 mm m⁻²) in the not calibrated model compared to the new model version (ca 50 mm m⁻² transpiration change). The uncertainties in these soil properties were found to be more important than the lateral water exchange between grid cells, even in steep topography at least for the temporal and spatial resolution used here.     

分布式TOPMODEL模型在清江流域降雨径流模拟中的应用

以清江流域上游为研究区域,探讨TOPMODEL模型在大流域的应用;对比了SRTM和地形图两种DEM数据在流域地形指数计算及降雨径流模拟中的差异,结果表明,虽然不同DEM计算得到的地形指数和模型率定参数存在较大差异,但是模拟效率基本相同,SRTM数据作为全球覆盖的免费高分辨率DEM数据将极大促进TOPMODEL模型的应用;分析了TOPMODEL模型在大流域中应用存在的局限性,在此基础上,构建了基于子流域的松散耦合的分布式TOPMODEL模型,提出了利用流域实际下垫面数据进行模型参数率定的方法,探讨了子流域划分详细程度对模拟结果的影响,结果表明,分布式TOPMODEL模型充分考虑了流域降雨和下垫面属性空间不均匀性对水文过程的影响,模拟效率高于传统TOPMODEL模型,随着子流域数目的增加,模型在率定期和校验期的效率均呈上升趋势,但是到达一定程度之后,受降雨等输入参数及模型计算误差所限,增加子流域个数不能继续提高模拟效率.     

EQUIVALENCE BETWEEN TOPMODEL AND THE NRCS CURVE NUMBER METHOD IN PREDICTING VARIABLE RUNOFF SOURCE AREAS1

An equivalence is proposed between two rainfall‐runoff methods with a long history of use in the United States and Europe. In watersheds where variable source areas dominate runoff, the two methods can have comparable probability distribution functions of moisture deficit, and therefore predict similar saturated runoff source areas. A novel approach is introduced to determine the S parameter in the Natural Resources Conservation Service (NRCS) method. This approach constrains S by the physical soil and topography characteristics of the catchment and depth to water table. The NRCS curve number method is at the core of many rainfall‐runoff models in hydrology. As a simple lumped parameter method, it is often scrutinized because it is not obvious how to derive S from catchment hydromorphological characteristics. The novel approach provides a clear physical meaning for S, allowing better estimation of this parameter in humid shallow water table environments where the variable source area can be the dominant runoff mechanism.     

Mechanistic Simulation of Tree Effects in an Urban Water Balance Model1

Abstract: A semidistributed, physical‐based Urban Forest Effects – Hydrology (UFORE‐Hydro) model was created to simulate and study tree effects on urban hydrology and guide management of urban runoff at the catchment scale. The model simulates hydrological processes of precipitation, interception, evaporation, infiltration, and runoff using data inputs of weather, elevation, and land cover along with nine channel, soil, and vegetation parameters. Weather data are pre‐processed by UFORE using Penman‐Monteith equations to provide potential evaporation terms for open water and vegetation. Canopy interception algorithms modified established routines to better account for variable density urban trees, short vegetation, and seasonal growth phenology. Actual evaporation algorithms allocate potential energy between leaf surface storage and transpiration from soil storage. Infiltration algorithms use a variable rain rate Green‐Ampt formulation and handle both infiltration excess and saturation excess ponding and runoff. Stream discharge is the sum of surface runoff and TOPMODEL‐based subsurface flow equations. Automated calibration routines that use observed discharge has been coupled to the model. Once calibrated, the model can examine how alternative tree management schemes impact urban runoff. UFORE‐Hydro model testing in the urban Dead Run catchment of Baltimore, Maryland, illustrated how trees significantly reduce runoff for low intensity and short duration precipitation events.