基于GIS的地下水及其环境问题分析

以地下水及其环境评价模型体系为支撑的、基于GIS的水文地质空间信息系统（HSIS）,由空间数据管理、应用模型管理、空间分析、数据转换、空间数据查询与检索、系统管理6大模块组成。应用于河西走廊地下水及环境评价,实现了对地下水及其环境信息的动态管理,得到了区域地下水化学成分的形成及分布规律。计算、分析了区域地下水资源量及开采潜力与地下水数值模拟模型集成,实现了计算过程的自动化、计算结果的可视化。利用HSIS提供的综合评价模型评价了黑河流域地质生态环境质量。评价结果显示：黑河中、上游环境质量较好,下游额济纳盆地环境质量较差,基本反映了区内地质生态环境现状。     

Ecohydrological modelling with EcH2O‐iso to quantify forest and grassland effects on water partitioning and flux ages

We used the new process‐based, tracer‐aided ecohydrological model EcH₂O‐iso to assess the effects of vegetation cover on water balance partitioning and associated flux ages under temperate deciduous beech forest (F) and grassland (G) at an intensively monitored site in Northern Germany. Unique, multicriteria calibration, based on measured components of energy balance, hydrological function and biomass accumulation, resulted in good simulations reproducing measured soil surface temperatures, soil water content, transpiration, and biomass production. Model results showed the forest “used” more water than the grassland; of 620 mm average annual precipitation, losses were higher through interception (29% under F, 16% for G) and combined soil evaporation and transpiration (59% F, 47% G). Consequently, groundwater (GW) recharge was enhanced under grassland at 37% (~225 mm) of precipitation compared with 12% (~73 mm) for forest. The model tracked the ages of water in different storage compartments and associated fluxes. In shallow soil horizons, the average ages of soil water fluxes and evaporation were similar in both plots (~1.5 months), though transpiration and GW recharge were older under forest (~6 months compared with ~3 months for transpiration, and ~12 months compared with ~10 months for GW). Flux tracking using measured chloride data as a conservative tracer provided independent support for the modelling results, though highlighted effects of uncertainties in forest partitioning of evaporation and transpiration. By tracking storage—flux—age interactions under different land covers, EcH₂O‐iso could quantify the effects of vegetation on water partitioning and age distributions. Given the likelihood of drier, warmer summers, such models can help assess the implications of land use for water resource availability to inform debates over building landscape resilience to climate change. Better conceptualization of soil water mixing processes and improved calibration data on leaf area index and root distribution appear obvious respective modelling and data needs for improved simulations.     

Impact of dissipation and dispersion terms on simulations of open‐channel confluence flow using two‐dimensional depth‐averaged model

The flow patterns in confluence channel and the simulation of confluence flow are more complex than that in straight channel. Additional terms in the momentum equations, i.e. dissipation terms, denoting the impact of turbulence, and dispersion terms, denoting the vertical non‐uniformity of velocity, show great impacts on the accuracy of numerical simulations. The dissipation terms, i.e. the product of eddy viscosity coefficient and velocity gradient, are much larger than those of the flow in straight channel. In this study, the zero equation model and the depth‐averaged k‐ε model are used to analyse the impact of eddy viscosity. Meanwhile, the dispersion terms in the momentum equation, depending on the vertical non‐uniformity of velocity, are usually neglected in routine simulation. With the use of detailed experimental data for verification, this study presents the distribution of parameters of vertical non‐uniformity and the intimated connection between non‐uniformity parameters and accuracy of numerical simulations of confluence flow with depth‐averaged models. The results present that simulation accuracy of confluence flow is very sensitive to the turbulence modes, which cannot be handled by normal, simple turbulence model. On the contrary, the impact of dispersion terms is both flow‐condition‐dependent and place‐dependent, and such impact is negligible when secondary circulation is weak. The results indicate the key elements in modelling confluence flow and are helpful for selecting suitable numerical model and solving engineering problems encountered in confluence channel. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessment of climate change impacts on the hydrology of the Peruvian Amazon–Andes basin

In this article, we propose an investigation of the modifications of the hydrological response of two Peruvian Amazonas–Andes basins in relationship with the modifications of the precipitation and evapotranspiration rates inferred by the IPCC. These two basins integrate around 10% of the total area of the Amazonian basin. These estimations are based on the application of two monthly hydrological models, GR2M and MWB3, and the climatic projections come from BCM2, CSMK3 and MIHR models for A1B and B1 emission scenarios (SCE A1B and SCE B1). Projections are approximated by two simple scenarios (anomalies and horizon) and annual rainfall rates, evapotranspiration rates and discharge were estimated for the 2020s (2008–2040), 2050s (2041–2070) and 2080s (2071–2099). Annual discharge shows increasing trend over Requena basin (Ucayali river), Puerto Inca basin (Pachitea river), Tambo basin (Tambo river) and Mejorada basin (Mantaro river) while discharge shows decreasing trend over the Chazuta basin (Huallaga river), the Maldonadillo basin (Urubamba river) and the Pisac basin (Vilcanota river). Monthly discharge at the outlet of Puerto Inca, Tambo and Mejorada basins shows increasing trends for all seasons. Trends to decrease are estimated in autumn discharge over the Requena basin and spring discharge over Pisac basin as well as summer and autumn discharges over both the Chazuta and the Maldonadillo basins. Copyright © 2011 John Wiley & Sons, Ltd.     

Effect of digital elevation model spatial resolution on depression storage

Surface water storage—including wetlands and other small waterbodies—has largely been disregarded in traditional hydrological models. In this paper, the grid resampling method is adopted to study the influence of the digital elevation model (DEM) grid resolution on depression storage (DS) considering different rainfall return periods. It is observed that the DEM grid size highly affects DS, and the higher the grid resolution is, the larger the DS value. However, when the grid resolution reaches a certain value, the maximum DS value decreases. This suggests that a critical grid resolution value exists at which the water storage capacity of depressions is maximized, namely, 20 m in this work (except for the overall area simulation under infiltration). This phenomenon is further verified in two test cases with and without the infiltration process, that is, calculations of the local area and without infiltration area, respectively. This research may facilitate the accurate computation of the DS process, which is greatly affected by the grid resolution, thereby improving the reliability of hydrological models.     

Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.     

Comparative probabilistic assessment of the hydrological performance of reconstructed and natural watersheds

The oil sands industry has committed to returning the mine sites to a productive condition. The reconstructed soil covers must have sufficient available water holding capacity (AWHC) to supply enough moisture over the growing season, to promote vegetation. In order to assess the sustainability of various soil cover alternatives, a generic, system dynamic watershed model entitled GSDW was used along with the available historical meteorological records to estimate the maximum soil moisture deficit and annual evapotranspiration fluxes. A probabilistic framework was adopted; consequently, frequency curves of the maximum annual moisture deficit values are constructed and used to assess the probability that various reconstructed and natural watersheds can provide the associated moisture demands. In general, the study showed a tendency for the reconstructed watershed to provide less moisture for evapotranspiration than natural systems. Watersheds of various soil types, layering, thicknesses and topography were studied. The gained knowledge was used to predict the possible performance of a hypothetical reclamation cover. The results indicated that the hypothetical cover performed in a similar manner to the thickest existing soil cover which confirmed a high probability of that cover to survive under the same existing climatic conditions. Moreover, this probabilistic framework was found to be useful for integrating information gained from natural watersheds (e.g. the canopy of mature natural systems and transfer the results to the reconstructed system). The results show that the canopy influenced the moisture deficit regime positively which signifies a greater possibility that reconstructed covers will adapt to vegetation type. In brief, the adopted approach enables better understanding of the response of reconstructed systems via multiple simulations of ‘what‐if’ scenarios using different soil/vegetation alternatives. Copyright © 2010 John Wiley & Sons, Ltd.     

A multimodel comparison for assessing water temperatures under changing climate conditions via the equilibrium temperature concept: case study of the Middle Loire River,France

This paper investigates three categories of models that are derived from the equilibrium temperature concept to estimate water temperatures in the Loire River in France and the sensitivity to changes in hydrology and climate. We test the models' individual performances for simulating water temperatures and assess the variability of the thermal responses under the extreme changing climate scenarios that are projected for 2081–2100. We attempt to identify the most reliable models for studying the impact of climate change on river temperature (T_w). Six models are based on a linear relationship between air temperatures (T_a) and equilibrium temperatures (T_e), six depend on a logistic relationship, and six rely on the closure of heat budgets. For each category, three approaches that account for the river's thermal exchange coefficient are tested. In addition to air temperatures, an index of day length is incorporated to compute equilibrium temperatures. Each model is analysed in terms of its ability to simulate the seasonal patterns of river temperatures and heat peaks. We found that including the day length as a covariate in regression‐based approaches improves the performance in comparison with classical approaches that use only T_a. Moreover, the regression‐based models that rely on the logistic relationship between T_e and T_a exhibit root mean square errors comparable (0.90 °C) with those obtained with a classical five‐term heat budget model (0.82 °C), despite a small number of required forcing variables. In contrast, the regressive models that are based on a linear relationship T_e = f(T_a) fail to simulate the heat peaks and are not advisable for climate change studies. The regression‐based approaches that are based on a logistic relationship and the heat balance approaches generate notably similar responses to the projected climate changes scenarios. This similarity suggests that sophisticated thermal models are not preferable to cruder ones, which are less time‐consuming and require fewer input data. Copyright © 2012 John Wiley & Sons, Ltd.     

Regional regression models for hydro‐climate change impact assessment

Hydro‐climatic impacts in water resources systems are typically assessed by forcing a hydrologic model with outputs from general circulation models (GCMs) or regional climate models. The challenges of this approach include maintaining a consistent energy budget between climate and hydrologic models and also properly calibrating and verifying the hydrologic models. Subjective choices of loss, flow routing, snowmelt and evapotranspiration computation methods also increase watershed modelling uncertainty and thus complicate impact assessment. An alternative approach, particularly appealing for ungauged basins or locations where record lengths are short, is to predict selected streamflow quantiles directly from meteorological variable output from climate models using regional regression models that also include physical basin characteristics. In this study, regional regression models are developed for the western Great Lakes states using ordinary least squares and weighted least squares techniques applied to selected Great Lakes watersheds. Model inputs include readily available downscaled GCM outputs from the Coupled Model Intercomparison Project Phase 3. The model results provide insights to potential model weaknesses, including comparatively low runoff predictions from continuous simulation models that estimate potential evapotranspiration using temperature proxy information and comparatively high runoff projections from regression models that do not include temperature as an explanatory variable. Copyright © 2014 John Wiley & Sons, Ltd.     

多源时相遥感影像数据耦合的水库库容曲线重构

遥感技术为库容曲线的重构带来了新思路,但仍存在多源遥感影像数据难以直接应用、水库批量面积提取效率低等问题,难以形成一套系统化、流程化的方法进行广泛应用。基于此,本文提出了多源时相遥感影像数据耦合的库容曲线重构方法,并重构了深圳市径心水库的水位-库容关系曲线。试验证明,重构后的库容曲线常水位区间的库容曲线偏离率在4.23%~11.5%之间,能够为径心水库的调度管理提供参考,同时对全国库容曲线无法及时重构的水库具有参考意义。