Constraining water table depth simulations in a land surface model using estimated baseflow

Several recent studies have shown the significance of representing groundwater in land surface hydrologic simulations. However, optimal methods for model parameter calibration in order to realistically simulate baseflow and groundwater depth have received little attention. Most studies still use globally constant groundwater parameters due to the lack of available datasets for calibration. Moreover, when models are calibrated, various parameter combinations are found to exhibit equifinality in simulated total runoff due to model parameter interactions. In this study, a simple lumped groundwater model is incorporated into the Community Land Model (CLM), in which the water table is interactively coupled to soil moisture through the groundwater recharge fluxes. The coupled model (CLMGW) is successfully validated in Illinois using a 22-year (1984–2005) monthly observational dataset. Baseflow estimates from the digital recursive filter technique are used to calibrate the CLMGW parameters. The advantage obtained from incorporating baseflow calibration in addition to traditional calibration based on measured streamflow alone is demonstrated by a Monte Carlo-type simulation analysis. Using the optimal parameter sets identified from baseflow calibration, flow partitioning and water table depth simulations using CLMGW are improved, and the equifinality problem is alleviated. For other regions that lack observations of water table depth, the baseflow calibration approach can be used to enhance parameter estimation and constrain water table depth simulations.     

Many roads to Paris: Explaining urban climate action in 885 European cities

Research on urban climate action has identified a broad range of potential factors explaining why and how local governments decide to tackle climate change. However, empirical evidence linking such factors in order to explain actual urban climate action has so far been mixed. To address this roadblock, our paper relies on a novel approach, postulating that different configurations of factors may lead to the same outcome (“equifinality”), through a qualitative comparative analysis (QCA). It is based on an available data set of local climate mitigation plans in 885 European cities. We find that urban climate action is systematically associated with four qualitatively different configurations of factors, each with its own consistent narrative (“networker cities”, “green cities”, “lighthouse cities”, “fundraising cities”). Crucially, some factors play a positive role in some configurations, a negative in others, and no role in further configurations (e.g., whether a city is located in a country with supportive national climate policies). This confirms that there is no single explanation for urban climate action. Achieving greater robustness in empirical research about urban climate action may thus require a shift, both conceptual and methodological, to the interactions between factors, allowing for different explanations in different contexts.     

不同尺度流域月径流模拟对比与敏感性分析——以西江流域为例

通过新安江月径流模型耦合加速遗传算法对西江流域3个不同尺度子流域——新兴江流域(1 790 km2)、罗定江流域(3 164 km2)和贺江流域(8 326 km2)进行了模拟,同时对模型参数进行了敏感性分析.结果表明:1)在模型参数较多的情况下,用加速遗传算法能很快找到最优化参数,通过参数的初始区间的合理设定可以使参数值达到全局最优,并且使其符合参数的实际取值情况;2)在1 000～9 000 km2流域面积内只有1个气象站的情况下,利用新安江月径流模型模拟的Nash-Sutcliffe效率系数为65%以上;3)降雨径流的相关性越强,则模拟精度越高;4)20世纪80年代后,罗定江流域径流的变化主要受降雨的影响,人类活动影响相对其他2个子流域弱;5)新安江月径流模型的敏感参数为蒸发系数K、地下水出流系数KG、地下水消退系数CG和自由水蓄水容量SM(0～10),参数的取值范围会影响到模型参数的敏感性;异参同效仍然是流域水文模型的不确定性的一个重要方面,GLUE方法能够反映这一点.     

Slopes,boundary conditions,and the development of convexo-concave forms—some numerical experiments

Slope profile sequences are as much influenced by their boundary conditions as they are by the processes operating. The development of a simple slope under a single process can adopt a variety of forms depending on initial and boundary conditions, and a given form can be derived from several different processes. For example, convexo-concave forms develop under soil creep with basal accumulation, under wash with an initial step form, and under mixed wash and creep processes.     

A Linking Test to reduce the number of hydraulic parameters necessary to simulate groundwater recharge in unsaturated soils

In environmental studies, numerical simulation models are valuable tools for testing hypothesis about systems functioning and to perform sensitivity studies under scenarios of land use or climate changes. The simulations depend upon parameters which are not always measurable quantities and must be calibrated against observations, using for instance inverse modelling. Due to the scarcity of these observations, it has been found that parameter sets allowing a good matching between simulated and measured quantities are often non-unique, leading to the problem of equifinality. This can lead to non-physical values, erroneous fluxes and misleading sensitivity analysis. Therefore, a simple but robust inverse method coined the Linking Test is presented to determine if the parameters are linked. Linked parameters are then sub-divided into classes according to their impact on water fluxes. The Linking Test establishes the causes of non-uniqueness of parameter sets and the feasibility of the inverse modelling.