Theory and Application of the Numerical Simulation in the Frozen Soil Problems

The freezing-thawing processes in soils are important components of terrestrial hydrology, which significantly influence energy and water exchanges between land surface and sub-surface. Long-term changes in frost and thaw depths are also an important indicator of climate change. A water-heat coupled movements model is established with frozen soil in this paper, which treats the freezing/thawing front as a moving interface governed by some Stefan problems with two free boundaries. The numerical simulation is conducted by using the modified finite difference method. The model is validated to compare its predictions with GEWEX Asian Monsoon Experiment(GAME)-Tibet observations at D66 site in Tibetan Plateau. The results show that the simulated soil temperature, soil water content and frost/thaw depth are in excellent agreement with the measured values. Finally, optimal error estimation for L^∞ norm is derived on the model problem by using coordinate transformation method. The numerical simulation system is established on the basis of rigorous mathematics and mechanics, which successfully solved the important and difficult problems of environmental science.

A new fully-coupled atmospheric-hydrological model for urban areas: development and testing

<p>Urban areas have distinct features (e.g. impervious surfaces) which modify the energy-water balance at the upper subsurface, lower atmosphere, and over the land surface. Moreover, the atmosphere and groundwater are strongly coupled in places with shallow groundwater. To improve the understanding of urban atmospheric-hydrological processes, their interconnections, and their impacts on other environmental processes, a new fully-coupled urban atmosphere-surface-subsurface hydrometeorological model was developed. The new model brings together WRF-PUCM (Princeton Urban Canopy Model) with ParFlow (a 3D variably saturated groundwater model with an integrated 2D overland flow component) to build WRF-PUCM-PF. The new model and the original non-coupled WRF-PUCM were both applied to a small watershed (10.64 km2) in a heavily urbanized area in the Baltimore metropolitan region as a demonstration test case. To capture atmospheric-hydrological processes at scales closer to urban heterogeneous land cover, models were run at a 90-m horizontal resolution using the LES mode in WRF. The analysis period after the two models were spun up to an identical initial condition spanned 96 hours from July 19 to July 23, 2008. The period was selected as it started with a drydown period for 40 hours followed by several intense rain events. This period allowed evaluation of both models' responses to dry-down and rain events. First the models were run with homogeneous similar hydrogelogic input to isolate the effect of terrestrial hydrology implementations in each model. In response to rain events, the homogeneous WRF-PUCM model output gained and retained a 40% greater amount of soil moisture (area-averaged) compared to the homogeneous WRF-PUCM-PF case. WRF-PUCM performed poorly in lateral distribution of water due to its 1D implementation of subsurface hydrology and lack of overland flow parameterization. The spatial distribution of soil moisture at the end of the simulation in a homogeneous WRF-PUCM model looked similar to the cumulative spatial distribution rain at the end of the simulation with no indication of surface topography impact on soil moisture distribution. On the other hand, lateral movement of water in WRF-PUCM-PF resulted in a more realistic distribution of soil moisture following topography. To further analyze the impact of urban areas, results of WRF-PUCM-PF simulations incorporating heterogeneous subsurface hydrogeology  were compared with WRF-PUCM with its 2D implementation of hydrogeology units for the region. The heterogeneous WRF-PUCM model generated a 10-fold greater area-averaged soil moisture increase compared to the heterogeneous WRF-PUCM-PF case. Influenced by lateral hydrology and impervious surfaces, the heterogeneous WRF-PUCM-PF model output, generated lower latent heat flux, resulting in half of the domain having higher land surface temperatures (2-10 ◦C), compared to the heterogeneous WRF-PUCM model. Overall, the new model provides a tool that can enhance simulation of urban areas by combining ParFlow’s representation of terrestrial hydrology, PUCM’s improved representation of the urban heterogeneous energy and water balance, and incorporation of higher-resolution urban heterogeneous microclimatic variations.</p>

Is large-scale terrestrial hydrological cycling well represented in Earth System Models?

<p>This paper addresses how large-scale terrestrial water cycling is represented in the land surface schemes of Earth System Models (ESMs). Good representation is essential, for example in regional planning for climate change adaptation and in preparation for hydro-climatic extremes that have recently set records world-wide in devastating consequences for societies and deaths of thousands of people. ESMs provide simulations and projections for the climate system and its interactions with the terrestrial hydrological cycle, and are widely used to study and prepare for associated impacts of climate change. However, the reliability of ESMs is unclear with regard to their representation of large-scale terrestrial hydrology and its changes and interactions between its key variables‎. Despite being crucial for model realism, analysis of co-variations among terrestrial hydrology variables is still largely missing in ESM performance evaluations. To bridge this research gap, we have studied and identified large-scale co-variation patterns between soil moisture (SM) and the main freshwater fluxes of runoff (R), precipitation (P), and evapotranspiration (ET) from observational data and across 6405 hydrological catchments in different parts and climates of the world. Furthermore, we have compared the identified observation-based relationships with those emerging from ESMs and reanalysis products. Our results show that the most strongly correlated freshwater variables based on observational data are also the most misrepresented hydrological patterns in ESMs and reanalysis simulations. In particular, we find SM and R to have the generally strongest large-scale correlations according to the observation-based data, across the numerous studied catchments with widely different hydroclimatic characteristics. Compared to the SM-R correlation signals, the observation-based correlations are overall weaker for the commonly expected closer dependencies of: R on P; ET on P; SM on P; and ET on SM. Nevertheless, this strongest SM-R correlation and the P-R correlation are the most misrepresented hydrological patterns in reanalysis products and ESMs. Our results also show that ESM outputs can perform relatively well in simulating individual hydrological variables, while exhibiting essential inconsistencies in simulated co-variations between variables. Such investigations of large-scale terrestrial hydrology representation by ESMs can enhance our understanding of fundamental ESM biases and uncertainties while providing important insights for systematic ESM improvement with regard to the large-scale hydrological cycling over the world’s continents and regional land areas.</p>

Implications of Model Selection: A Comparison of Publicly Available, CONUS-Extent Hydrologic Component Estimates

Spatiotemporally continuous estimates of the hydrologic cycle are often generated through hydrologic modeling, reanalysis, or remote sensing methods, and commonly applied as a supplement to, or a substitute for, in-situ measurements when observational data are sparse or unavailable. Many of these datasets are shared within the public domain, helping to accelerate progress in the fields of hydrology, climatology, and meteorology by (a) reducing the need for technical programming skills and computational power, and (b) providing a wide range of forecast and hindcast estimates of terrestrial hydrology that can be applied within ensemble analyses. Past model inter-comparisons focused on the causes of model disagreement, emphasizing forcing data, model structure, and calibration methods. Despite the relatively recent increased application of publicly available modeled estimates in the scientific community, there is limited discussion or understanding of how selection of one dataset over others can affect study results. This study compares estimates of precipitation (P), actual evapotranspiration (AET), runoff (R), snow water equivalent (SWE), and rootzone soil moisture (RZSM) from 87 unique datasets generated by 47 hydrologic models, reanalysis datasets, and remote sensing products at the monthly timescale across the conterminous United States (CONUS) from 1982 to 2014. To understand the effect of model selection on terrestrial hydrology analyses, 2,925 water budgets were calculated over 2001-2010 for each of eight Environmental Protection Agency ecoregions by iterating through all combinations of 43 hydrologic flux estimates. Variability between hydrologic component estimates was shown to be higher in the western CONUS, with median coefficient of variation (CV) ranging from 11–22 % for P, 14–27 % for AET, 28–153 % for R, 92-102 % for SWE, and 39-92% for RZSM. Variability between estimates was lower in the eastern CONUS, with median CV ranging from 5–15 % for P, 13–23% for AET, 29–96 % for R, 64–70 % for SWE, and 44–81 % for RZSM. Inter-annual trends in estimates from 1982–2010 show more comprehensive agreement for trends in P and AET fluxes but common disagreement for trends in R, SWE, and RZSM. Correlating fluxes and stores against remote sensing-derived products shows poor overall correlation in the western CONUS for AET and RZSM estimates. Iterative budget relative imbalances were shown to range from −50 % to +50 % in major eastern ecoregions and −150 % to +60 % in western ecoregions, depending on models selected. These results demonstrate that disagreement between estimates can be substantial, sometimes exceeding the magnitude of the measurements themselves. The authors conclude that multi-model ensembles are not only useful, but are in fact a necessity, to accurately represent uncertainty in research results. Spatial biases of model disagreement values in the western United States show that targeted research efforts in arid and semi-arid water-limited regions are warranted, with the greatest emphasis on storage and runoff components, to better describe complexities of the terrestrial hydrologic system and reconcile model disagreement.

Implementation of WRF-Hydro at two drainage basins in the region of Attica, Greece

An integrated modeling approach for simulating flood events is presented in the current study. An advanced flood forecasting model, which is based on the coupling of hydrological and atmospheric components, was used for a twofold objective: first to investigate the potential of a coupled hydrometeorological model to be used for flood forecasting at two drainage basins in the area of Attica (Greece) and second to investigate the influence of the use of the coupled hydrometeorological model on the improvement of the precipitation forecast skill. For this reason, we used precipitation and hydrometric in-situ data for 7 events at two selected drainage regions of Attica. The simulations were carried out with WRF-Hydro model, which is an enhanced version of the Weather Research and Forecasting (WRF) model complemented with the feedback of terrestrial hydrology on the atmosphere, where surface and subsurface runoff were computed at a fine resolution grid of 95 m. Results showed that WRF-Hydro is capable to produce the observed discharge after the adequate calibration method at the studied basins. Besides, the WRF-Hydro has the tendency to slightly improve the simulated precipitation in comparison to the simulated precipitation produced the atmospheric only version of the model. These outcomes provide confidence that the model configuration is robust and, thus, can be used for flood research and operational forecasting purposes in the area of Attica.

Optimal Strategy of a GPS Position Time Series Analysis for Post-Glacial Rebound Investigation in Europe

We describe a comprehensive analysis of the 469 European Global Positioning System (GPS) vertical position time series. The assumptions we present should be employed to perform the post-glacial rebound (PGR)-oriented comparison. We prove that the proper treatment of either deterministic or stochastic components of the time series is indispensable to obtain reliable vertical velocities along with their uncertainties. The statistical significance of the vertical velocities is examined; due to their small vertical rates, 172 velocities from central and western Europe are found to fall below their uncertainties and excluded from analyses. The GPS vertical velocities reach the maximum values for Scandinavia with the maximal uplift equal to 11.0 mm/yr. Moreover, a comparison between the GPS-derived rates and the present-day motion predicted by the newest Glacial Isostatic Adjustment (GIA) ICE-6G_C (VM5a) model is provided. We prove that these rates agree at a 0.5 mm/yr level on average; the Sweden area with the most significant uplift observed agrees within 0.2 mm/yr. The largest discrepancies between GIA-predicted uplift and the GPS vertical rates are found for Svalbard; the difference is equal to 6.7 mm/yr and arises mainly from the present-day ice melting. The GPS-derived vertical rates estimated for the southern coast of the Baltic Sea are systematically underestimated by the GIA prediction by up to 2 mm/yr. The northern British Isles vertical rates are overestimated by the GIA model by about 0.5 mm/yr. The area of the Netherlands and the coastal area of Belgium are both subsiding faster than it is predicted by the GIA model of around 1 mm/yr. The inland part of Belgium, Luxemburg and the western part of Germany show strong positive velocities when compared to the GIA model. Most of these stations uplift of more than 1 mm/yr. It may be caused by present-day elastic deformation due to terrestrial hydrology, especially for Rhein basin, or non-tidal atmospheric loading, for Belgium and Luxembourg.

Use of WRF-Hydro over the Northeast of the US to Estimate Water Budget Tendencies in Small Watersheds

In the Northeast of the US, climate change will bring a series of impacts on the terrestrial hydrology. Observations indicate that temperature has steadily increased during the last century, including changes in precipitation. This study implements the Weather Research and Forecasting (WRF)-Hydro framework with the Noah-Multiparameterization (Noah-MP) model that is currently used in the National Water Model to estimate the tendencies of the different variables that compounded the water budget in the Northeast of the US from 1980 to 2016. We use North American Land Data Assimilation System-2 (NLDAS-2) climate data as forcing, and we calibrated the model using 192 US Geological Survey (USGS) Geospatial Attributes of Gages for Evaluating Streamflow II (Gages II) reference stations. We study the tendencies determining the Kendall-Theil slope of streamflow using the maximum three-day average, seven-day minimum flow, and the monotonic five-day mean times series. For the water budget, we determine the Kendall-Theil slope for changes in monthly values of precipitation, surface and subsurface runoff, evapotranspiration, transpiration, soil moisture, and snow accumulation. The results indicate that the changes in precipitation are not being distributed evenly in the components of the water budget. Precipitation is decreasing during winter and increasing during the summer, with the direct impacts being a decrease in snow accumulation and an increase in evapotranspiration. The soil tends to be drier, which does not translate to a rise in infiltration since the surface runoff aggregated tendencies are positive, and the underground runoff aggregated tendencies are negative. The effects of climate change on streamflows are buffered by larger areas, indicating that more attention needs to be given to small catchments to adapt to climate change.